1
|
Russell CA, Fouchier RAM, Ghaswalla P, Park Y, Vicic N, Ananworanich J, Nachbagauer R, Rudin D. Seasonal influenza vaccine performance and the potential benefits of mRNA vaccines. Hum Vaccin Immunother 2024; 20:2336357. [PMID: 38619079 PMCID: PMC11020595 DOI: 10.1080/21645515.2024.2336357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 03/26/2024] [Indexed: 04/16/2024] Open
Abstract
Influenza remains a public health threat, partly due to suboptimal effectiveness of vaccines. One factor impacting vaccine effectiveness is strain mismatch, occurring when vaccines no longer match circulating strains due to antigenic drift or the incorporation of inadvertent (eg, egg-adaptive) mutations during vaccine manufacturing. In this review, we summarize the evidence for antigenic drift of circulating viruses and/or egg-adaptive mutations occurring in vaccine strains during the 2011-2020 influenza seasons. Evidence suggests that antigenic drift led to vaccine mismatch during four seasons and that egg-adaptive mutations caused vaccine mismatch during six seasons. These findings highlight the need for alternative vaccine development platforms. Recently, vaccines based on mRNA technology have demonstrated efficacy against SARS-CoV-2 and respiratory syncytial virus and are under clinical evaluation for seasonal influenza. We discuss the potential for mRNA vaccines to address strain mismatch, as well as new multi-component strategies using the mRNA platform to improve vaccine effectiveness.
Collapse
Affiliation(s)
- Colin A. Russell
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Ron A. M. Fouchier
- Department of Viroscience, Erasmus Medical Center, Rotterdam, the Netherlands
| | | | | | | | | | | | | |
Collapse
|
2
|
Reperant L, Russell CA, Osterhaus A. Scientific highlights of the 9th ESWI Influenza Conference. One Health Outlook 2024; 6:5. [PMID: 38561784 PMCID: PMC10986029 DOI: 10.1186/s42522-024-00099-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The European Scientific Working Group on Influenza (ESWI) held the 9th ESWI Influenza Conference in Valencia from 17-20 September 2023. Here we provide a summary of twelve key presentations, covering major topics on influenza virus, respiratory syncytial virus (RSV) and SARS coronavirus 2 (SARS-CoV-2) including: infection processes beyond acute respiratory disease, long COVID, vaccines against influenza and RSV, the implications of the potential extinction of influenza B virus Yamagata lineage, and the threats posed by zoonotic highly pathogenic avian influenza viruses.
Collapse
Affiliation(s)
| | - Colin A Russell
- Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Albert Osterhaus
- Center of Infection Medicine and Zoonosis Research and the University of Veterinary Medicine Hannover, Hannover, Germany.
| |
Collapse
|
3
|
Port JR, Morris DH, Riopelle JC, Yinda CK, Avanzato VA, Holbrook MG, Bushmaker T, Schulz JE, Saturday TA, Barbian K, Russell CA, Perry-Gottschalk R, Shaia C, Martens C, Lloyd-Smith JO, Fischer RJ, Munster VJ. Host and viral determinants of airborne transmission of SARS-CoV-2 in the Syrian hamster. eLife 2024; 12:RP87094. [PMID: 38416804 PMCID: PMC10942639 DOI: 10.7554/elife.87094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2024] Open
Abstract
It remains poorly understood how SARS-CoV-2 infection influences the physiological host factors important for aerosol transmission. We assessed breathing pattern, exhaled droplets, and infectious virus after infection with Alpha and Delta variants of concern (VOC) in the Syrian hamster. Both VOCs displayed a confined window of detectable airborne virus (24-48 hr), shorter than compared to oropharyngeal swabs. The loss of airborne shedding was linked to airway constriction resulting in a decrease of fine aerosols (1-10 µm) produced, which are suspected to be the major driver of airborne transmission. Male sex was associated with increased viral replication and virus shedding in the air. Next, we compared the transmission efficiency of both variants and found no significant differences. Transmission efficiency varied mostly among donors, 0-100% (including a superspreading event), and aerosol transmission over multiple chain links was representative of natural heterogeneity of exposure dose and downstream viral kinetics. Co-infection with VOCs only occurred when both viruses were shed by the same donor during an increased exposure timeframe (24-48 hr). This highlights that assessment of host and virus factors resulting in a differential exhaled particle profile is critical for understanding airborne transmission.
Collapse
Affiliation(s)
- Julia R Port
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - Dylan H Morris
- Department of Ecology and Evolutionary Biology, University of California, Los AngelesLos AngelesUnited States
| | - Jade C Riopelle
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - Claude Kwe Yinda
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - Victoria A Avanzato
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - Myndi G Holbrook
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - Trenton Bushmaker
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - Jonathan E Schulz
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - Taylor A Saturday
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - Kent Barbian
- Rocky Mountain Research and Technologies Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - Colin A Russell
- Department of Medical Microbiology | Amsterdam University Medical Center, University of AmsterdamAmsterdamNetherlands
| | - Rose Perry-Gottschalk
- Rocky Mountain Visual and Medical Arts Unit, Research Technologies Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - Carl Shaia
- Rocky Mountain Veterinary Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - Craig Martens
- Rocky Mountain Research and Technologies Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - James O Lloyd-Smith
- Department of Ecology and Evolutionary Biology, University of California, Los AngelesLos AngelesUnited States
| | - Robert J Fischer
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| | - Vincent J Munster
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthHamiltonUnited States
| |
Collapse
|
4
|
Chevalier JM, Han AX, Hansen MA, Klock E, Pandithakoralage H, Ockhuisen T, Girdwood SJ, Lekodeba NA, de Nooy A, Khan S, Johnson CC, Sacks JA, Jenkins HE, Russell CA, Nichols BE. Impact and cost-effectiveness of SARS-CoV-2 self-testing strategies in schools: a multicountry modelling analysis. BMJ Open 2024; 14:e078674. [PMID: 38417953 PMCID: PMC10900377 DOI: 10.1136/bmjopen-2023-078674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 02/13/2024] [Indexed: 03/01/2024] Open
Abstract
OBJECTIVES To determine the most epidemiologically effective and cost-effective school-based SARS-CoV-2 antigen-detection rapid diagnostic test (Ag-RDT) self-testing strategies among teachers and students. DESIGN Mathematical modelling and economic evaluation. SETTING AND PARTICIPANTS Simulated school and community populations were parameterised to Brazil, Georgia and Zambia, with SARS-CoV-2 self-testing strategies targeted to teachers and students in primary and secondary schools under varying epidemic conditions. INTERVENTIONS SARS-CoV-2 Ag-RDT self-testing strategies for only teachers or teachers and students-only symptomatically or symptomatically and asymptomatically at 5%, 10%, 40% or 100% of schools at varying frequencies. OUTCOME MEASURES Outcomes were assessed in terms of total infections and symptomatic days among teachers and students, as well as total infections and deaths within the community under the intervention compared with baseline. The incremental cost-effectiveness ratios (ICERs) were calculated for infections prevented among teachers and students. RESULTS With respect to both the reduction in infections and total cost, symptomatic testing of all teachers and students appears to be the most cost-effective strategy. Symptomatic testing can prevent up to 69·3%, 64·5% and 75·5% of school infections in Brazil, Georgia and Zambia, respectively, depending on the epidemic conditions, with additional reductions in community infections. ICERs for symptomatic testing range from US$2 to US$19 per additional school infection averted as compared with symptomatic testing of teachers alone. CONCLUSIONS Symptomatic testing of teachers and students has the potential to cost-effectively reduce a substantial number of school and community infections.
Collapse
Affiliation(s)
- Joshua M Chevalier
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Alvin X Han
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Megan A Hansen
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Ethan Klock
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Hiromi Pandithakoralage
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Tom Ockhuisen
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | | | - Nkgomeleng A Lekodeba
- Department of Internal Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Alexandra de Nooy
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | | | | | - Jilian A Sacks
- Department of Epidemic and Pandemic Preparedness and Prevention, World Health Organization, Geneva, Switzerland
| | - Helen E Jenkins
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Colin A Russell
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Brooke E Nichols
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, USA
- FIND, Geneva, Switzerland
- Amsterdam Institute for Global Health and Development, Amsterdam, Netherlands
| |
Collapse
|
5
|
de Jong SPJ, Felix Garza ZC, Gibson JC, van Leeuwen S, de Vries RP, Boons GJ, van Hoesel M, de Haan K, van Groeningen LE, Hulme KD, van Willigen HDG, Wynberg E, de Bree GJ, Matser A, Bakker M, van der Hoek L, Prins M, Kootstra NA, Eggink D, Nichols BE, Han AX, de Jong MD, Russell CA. Determinants of epidemic size and the impacts of lulls in seasonal influenza virus circulation. Nat Commun 2024; 15:591. [PMID: 38238318 PMCID: PMC10796432 DOI: 10.1038/s41467-023-44668-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 12/21/2023] [Indexed: 01/22/2024] Open
Abstract
During the COVID-19 pandemic, levels of seasonal influenza virus circulation were unprecedentedly low, leading to concerns that a lack of exposure to influenza viruses, combined with waning antibody titres, could result in larger and/or more severe post-pandemic seasonal influenza epidemics. However, in most countries the first post-pandemic influenza season was not unusually large and/or severe. Here, based on an analysis of historical influenza virus epidemic patterns from 2002 to 2019, we show that historic lulls in influenza virus circulation had relatively minor impacts on subsequent epidemic size and that epidemic size was more substantially impacted by season-specific effects unrelated to the magnitude of circulation in prior seasons. From measurements of antibody levels from serum samples collected each year from 2017 to 2021, we show that the rate of waning of antibody titres against influenza virus during the pandemic was smaller than assumed in predictive models. Taken together, these results partially explain why the re-emergence of seasonal influenza virus epidemics was less dramatic than anticipated and suggest that influenza virus epidemic dynamics are not currently amenable to multi-season prediction.
Collapse
Affiliation(s)
- Simon P J de Jong
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Zandra C Felix Garza
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Joseph C Gibson
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Sarah van Leeuwen
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Robert P de Vries
- Department of Chemical Biology and Drug Discovery, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Geert-Jan Boons
- Department of Chemical Biology and Drug Discovery, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, USA
- Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, The Netherlands
- Department of Chemistry, University of Georgia, Athens, GA, USA
| | - Marliek van Hoesel
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Karen de Haan
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Laura E van Groeningen
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Katina D Hulme
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Hugo D G van Willigen
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Elke Wynberg
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, The Netherlands
| | - Godelieve J de Bree
- Department of Infectious Diseases, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Amy Matser
- Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, The Netherlands
| | - Margreet Bakker
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Lia van der Hoek
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Maria Prins
- Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, The Netherlands
- Department of Infectious Diseases, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Neeltje A Kootstra
- Department of Experimental Immunology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Dirk Eggink
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Brooke E Nichols
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Department of Global Health, School of Public Health, Boston University, Boston, MA, USA
| | - Alvin X Han
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Menno D de Jong
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Colin A Russell
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.
- Department of Global Health, School of Public Health, Boston University, Boston, MA, USA.
| |
Collapse
|
6
|
van Linge CCA, Hulme KD, Peters-Sengers H, Sirard JC, Goessens WHF, de Jong MD, Russell CA, de Vos AF, van der Poll T. Immunostimulatory Effect of Flagellin on MDR- Klebsiella-Infected Human Airway Epithelial Cells. Int J Mol Sci 2023; 25:309. [PMID: 38203480 PMCID: PMC10778885 DOI: 10.3390/ijms25010309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 12/22/2023] [Accepted: 12/23/2023] [Indexed: 01/12/2024] Open
Abstract
Pneumonia caused by multi-drug-resistant Klebsiella pneumoniae (MDR-Kpneu) poses a major public health threat, especially to immunocompromised or hospitalized patients. This study aimed to determine the immunostimulatory effect of the Toll-like receptor 5 ligand flagellin on primary human lung epithelial cells during infection with MDR-Kpneu. Human bronchial epithelial (HBE) cells, grown on an air-liquid interface, were inoculated with MDR-Kpneu on the apical side and treated during ongoing infection with antibiotics (meropenem) and/or flagellin on the basolateral and apical side, respectively; the antimicrobial and inflammatory effects of flagellin were determined in the presence or absence of meropenem. In the absence of meropenem, flagellin treatment of MDR-Kpneu-infected HBE cells increased the expression of antibacterial defense genes and the secretion of chemokines; moreover, supernatants of flagellin-exposed HBE cells activated blood neutrophils and monocytes. However, in the presence of meropenem, flagellin did not augment these responses compared to meropenem alone. Flagellin did not impact the outgrowth of MDR-Kpneu. Flagellin enhances antimicrobial gene expression and chemokine release by the MDR-Kpneu-infected primary human bronchial epithelium, which is associated with the release of mediators that activate neutrophils and monocytes. Topical flagellin therapy may have potential to boost immune responses in the lung during pneumonia.
Collapse
Affiliation(s)
- Christine C. A. van Linge
- Center for Experimental and Molecular Medicine, Amsterdam University Medical Centers, University of Amsterdam, 1012 WP Amsterdam, The Netherlands (A.F.d.V.); (T.v.d.P.)
- Amsterdam Infection & Immunity Institute, 1105 AZ Amsterdam, The Netherlands
| | - Katina D. Hulme
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, 1012 WP Amsterdam, The Netherlands
| | - Hessel Peters-Sengers
- Center for Experimental and Molecular Medicine, Amsterdam University Medical Centers, University of Amsterdam, 1012 WP Amsterdam, The Netherlands (A.F.d.V.); (T.v.d.P.)
- Amsterdam Infection & Immunity Institute, 1105 AZ Amsterdam, The Netherlands
| | - Jean-Claude Sirard
- Center for Infection and Immunity of Lille, Institut Pasteur de Lille, INSERM U1019, CNRS UMR9017, CHU Lille, University Lille, 59000 Lille, France
| | - Wil H. F. Goessens
- Department of Medical Microbiology and Infectious Diseases, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
| | - Menno D. de Jong
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, 1012 WP Amsterdam, The Netherlands
| | - Colin A. Russell
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, 1012 WP Amsterdam, The Netherlands
- Department of Global Health, School of Public Health, Boston University, Boston, MA 02215, USA
| | - Alex F. de Vos
- Center for Experimental and Molecular Medicine, Amsterdam University Medical Centers, University of Amsterdam, 1012 WP Amsterdam, The Netherlands (A.F.d.V.); (T.v.d.P.)
- Amsterdam Infection & Immunity Institute, 1105 AZ Amsterdam, The Netherlands
| | - Tom van der Poll
- Center for Experimental and Molecular Medicine, Amsterdam University Medical Centers, University of Amsterdam, 1012 WP Amsterdam, The Netherlands (A.F.d.V.); (T.v.d.P.)
- Amsterdam Infection & Immunity Institute, 1105 AZ Amsterdam, The Netherlands
- Division of Infectious Diseases, Amsterdam University Medical Centers, University of Amsterdam, 1012 WP Amsterdam, The Netherlands
| |
Collapse
|
7
|
Han AX, Hannay E, Carmona S, Rodriguez B, Nichols BE, Russell CA. Estimating the potential impact and diagnostic requirements for SARS-CoV-2 test-and-treat programs. Nat Commun 2023; 14:7981. [PMID: 38042923 PMCID: PMC10693634 DOI: 10.1038/s41467-023-43769-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 11/20/2023] [Indexed: 12/04/2023] Open
Abstract
Oral antivirals have the potential to reduce the public health burden of COVID-19. However, now that we have exited the emergency-phase of the COVID-19 pandemic, declining SARS-CoV-2 clinical testing rates (average testing rates = [Formula: see text]10 tests/100,000 people/day in low-and-middle income countries; <100 tests/100,000 people/day in high-income countries; September 2023) make the development of effective test-and-treat programs challenging. We used an agent-based model to investigate how testing rates and strategies affect the use and effectiveness of oral antiviral test-to-treat programs in four country archetypes of different income levels and demographies. We find that in the post-emergency-phase of the pandemic, in countries where low testing rates are driven by limited testing capacity, significant population-level impact of test-and-treat programs can only be achieved by both increasing testing rates and prioritizing individuals with greater risk of severe disease. However, for all countries, significant reductions in severe cases with antivirals are only possible if testing rates were substantially increased with high willingness of people to seek testing. Comparing the potential population-level reductions in severe disease outcomes of test-to-treat programs and vaccination shows that test-and-treat strategies are likely substantially more resource intensive requiring very high levels of testing (≫100 tests/100,000 people/day) and antiviral use suggesting that vaccination should be a higher priority.
Collapse
Affiliation(s)
- Alvin X Han
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
| | - Emma Hannay
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Sergio Carmona
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Bill Rodriguez
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Brooke E Nichols
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
- Department of Global Health, School of Public Health, Boston University, Boston, MA, USA
| | - Colin A Russell
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
- Department of Global Health, School of Public Health, Boston University, Boston, MA, USA.
| |
Collapse
|
8
|
Abstract
Seasonal influenza viruses cause recurring global epidemics by continually evolving to escape host immunity. The viral constraints and host immune responses that limit and drive the evolution of these viruses are increasingly well understood. However, it remains unclear how most of these advances improve the capacity to reduce the impact of seasonal influenza viruses on human health. In this Review, we synthesize recent progress made in understanding the interplay between the evolution of immunity induced by previous infections or vaccination and the evolution of seasonal influenza viruses driven by the heterogeneous accumulation of antibody-mediated immunity in humans. We discuss the functional constraints that limit the evolution of the viruses, the within-host evolutionary processes that drive the emergence of new virus variants, as well as current and prospective options for influenza virus control, including the viral and immunological barriers that must be overcome to improve the effectiveness of vaccines and antiviral drugs.
Collapse
Affiliation(s)
- Alvin X Han
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Simon P J de Jong
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Colin A Russell
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
- Department of Global Health, School of Public Health, Boston University, Boston, MA, USA.
| |
Collapse
|
9
|
Han AX, Hannay E, Carmona S, Rodriguez B, Nichols BE, Russell CA. Estimating the potential impact and diagnostic requirements for SARS-CoV-2 test-and-treat programs. medRxiv 2023:2022.10.05.22280727. [PMID: 36238715 PMCID: PMC9558441 DOI: 10.1101/2022.10.05.22280727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Oral antivirals have the potential to reduce the public health burden of COVID-19. However, now that we have exited the emergency phase of the COVID-19 pandemic, declining SARS-CoV-2 clinical testing rates (average testing rates = ≪10 tests/100,000 people/day in low- and-middle income countries; <100 tests/100,000 people/day in high-income countries; September 2023) make the development of effective test-and-treat programs challenging. We used an agent-based model to investigate how testing rates and strategies affect the use and effectiveness of oral antiviral test-to-treat programs in four country archetypes of different income levels and demographies. We find that in the post-emergency phase of the pandemic, in countries where low testing rates are driven by limited testing capacity, significant population-level impact of test-and-treat programs can only be achieved by both increasing testing rates and prioritizing individuals with greater risk of severe disease. However, for all countries, significant reductions in severe cases with antivirals are only possible if testing rates were substantially increased with high willingness of people to seek testing. Comparing the potential population-level reductions in severe disease outcomes of test-to-treat programs and vaccination shows that test-and-treat strategies are likely substantially more resource intensive requiring very high levels of testing (>>100 tests/100,000 people/day) and antiviral use suggesting that vaccination should be a higher priority.
Collapse
Affiliation(s)
- Alvin X. Han
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Emma Hannay
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Sergio Carmona
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Bill Rodriguez
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Brooke E. Nichols
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
- Department of Global Health, School of Public Health, Boston University, Boston, MA, USA
| | - Colin A. Russell
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
- Department of Global Health, School of Public Health, Boston University, Boston, MA, USA
| |
Collapse
|
10
|
Port JR, Morris DH, Riopelle JC, Yinda CK, Avanzato VA, Holbrook MG, Bushmaker T, Schulz JE, Saturday TA, Barbian K, Russell CA, Perry-Gottschalk R, Shaia CI, Martens C, Lloyd-Smith JO, Fischer RJ, Munster VJ. Host and viral determinants of airborne transmission of SARS-CoV-2 in the Syrian hamster. bioRxiv 2023:2022.08.15.504010. [PMID: 36032963 PMCID: PMC9413705 DOI: 10.1101/2022.08.15.504010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
It remains poorly understood how SARS-CoV-2 infection influences the physiological host factors important for aerosol transmission. We assessed breathing pattern, exhaled droplets, and infectious virus after infection with Alpha and Delta variants of concern (VOC) in the Syrian hamster. Both VOCs displayed a confined window of detectable airborne virus (24-48 h), shorter than compared to oropharyngeal swabs. The loss of airborne shedding was linked to airway constriction resulting in a decrease of fine aerosols (1-10μm) produced, which are suspected to be the major driver of airborne transmission. Male sex was associated with increased viral replication and virus shedding in the air. Next, we compared the transmission efficiency of both variants and found no significant differences. Transmission efficiency varied mostly among donors, 0-100% (including a superspreading event), and aerosol transmission over multiple chain links was representative of natural heterogeneity of exposure dose and downstream viral kinetics. Co-infection with VOCs only occurred when both viruses were shed by the same donor during an increased exposure timeframe (24-48 h). This highlights that assessment of host and virus factors resulting in a differential exhaled particle profile is critical for understanding airborne transmission.
Collapse
Affiliation(s)
- Julia R. Port
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Dylan H. Morris
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA
| | - Jade C. Riopelle
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Claude Kwe Yinda
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Victoria A. Avanzato
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Myndi G. Holbrook
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Trenton Bushmaker
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Jonathan E. Schulz
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Taylor A. Saturday
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Kent Barbian
- Rocky Mountain Research and Technologies Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Colin A. Russell
- Department of Medical Microbiology | Amsterdam University Medical Center, University of Amsterdam
| | - Rose Perry-Gottschalk
- Rocky Mountain Visual and Medical Arts Unit, Research Technologies Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Carl I. Shaia
- Rocky Mountain Veterinary Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Craig Martens
- Rocky Mountain Research and Technologies Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - James O. Lloyd-Smith
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA
| | - Robert J. Fischer
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Vincent J. Munster
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| |
Collapse
|
11
|
Govathson C, Long LC, Russell CA, Moolla A, Pascoe S, Nichols BE. A modelling framework for translating discrete choice experiment results into cost-effectiveness estimates: an application to designing tailored and scalable HIV and contraceptive services for adolescents in Gauteng, South Africa. J Int AIDS Soc 2023; 26:e26124. [PMID: 37463870 PMCID: PMC10354002 DOI: 10.1002/jia2.26124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 05/17/2023] [Indexed: 07/20/2023] Open
Abstract
INTRODUCTION South African youth and adolescents face a high burden of (Sexually Transmitted Infections) STIs, HIV and unintended pregnancies, but uptake of services remains low. To address this, tailored and scalable interventions are urgently needed. We developed a framework to fill the gap and translate the impact of facility-level attributes into a cost-effectiveness analysis for increasing HIV/contraceptive service uptake in adolescents using a discrete choice experiment (DCE). METHODS We used a DCE (n = 805) conducted in Gauteng, South Africa, which found that staff attitude, confidentiality, Wi-Fi, subsidized food, afternoon hours and youth-only services were preferred attributes of health services. Based on this, we simulated the uptake of services adapted for these preferences. We divided preferences into modifiable attributes that could readily be adapted (e.g. Wi-Fi), and challenging to modify (more nuanced attributes that are more challenging to cost and evaluate): staff attitude and estimated the incremental change in the uptake of services using adapted services. Costs for modifiable preferences were estimated using data from two clinics in South Africa (2019 US$). We determined the incremental cost-effectiveness ratio (ICER) for additional adolescents using services of 15 intervention combinations, and report the results of interventions on the cost-effectiveness frontier. RESULTS Greatest projected impact on uptake was from friendly and confidential services, both of which were considered challenging to modify (18.5% 95% CI: 13.0%-24.0%; 8.4% 95% CI: 3.0%-14.0%, respectively). Modifiable factors on their own resulted in only small increases in expected uptake. (Food: 2.3% 95% CI: 4.0%-9.00%; Wi-Fi: 3.0% 95% CI: -4.0% to 10.0%; Youth-only services: 0.3% 95% CI: -6.0% to 7.0%; Afternoon services: 0.8% 95% CI: -6.0% to 7.0%). The order of interventions on the cost-effectiveness frontier are Wi-Fi and youth-only services (ICER US$7.01-US$9.78 per additional adolescent utilizing HIV and contraceptive services), Wi-Fi, youth-only services and food (ICER US$9.32-US$10.45), followed by Wi-Fi, youth-only services and extended afternoon hours (ICER US$14.46-US$43.63). CONCLUSIONS Combining DCE results and costing analyses within a modelling framework provides an innovative way to inform decisions on effective resource utilization. Modifiable preferences, such as Wi-Fi provision, youth-only services and subsidized food, have the potential to cost-effectively increase the proportion of adolescents accessing HIV and contraceptive services.
Collapse
Affiliation(s)
- Caroline Govathson
- Health Economics and Epidemiology Research Office, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Lawrence C Long
- Health Economics and Epidemiology Research Office, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, 02118, USA
| | - Colin A Russell
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, 02118, USA
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Aneesa Moolla
- Health Economics and Epidemiology Research Office, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Sophie Pascoe
- Health Economics and Epidemiology Research Office, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Brooke E Nichols
- Health Economics and Epidemiology Research Office, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, 02118, USA
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| |
Collapse
|
12
|
Arcos S, Han AX, te Velthuis AJW, Russell CA, Lauring AS. Mutual information networks reveal evolutionary relationships within the influenza A virus polymerase. Virus Evol 2023; 9:vead037. [PMID: 37325086 PMCID: PMC10263469 DOI: 10.1093/ve/vead037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 03/27/2023] [Accepted: 05/24/2023] [Indexed: 06/17/2023] Open
Abstract
The influenza A virus (IAV) RNA polymerase is an essential driver of IAV evolution. Mutations that the polymerase introduces into viral genome segments during replication are the ultimate source of genetic variation, including within the three subunits of the IAV polymerase (polymerase basic protein 2, polymerase basic protein 1, and polymerase acidic protein). Evolutionary analysis of the IAV polymerase is complicated, because changes in mutation rate, replication speed, and drug resistance involve epistatic interactions among its subunits. In order to study the evolution of the human seasonal H3N2 polymerase since the 1968 pandemic, we identified pairwise evolutionary relationships among ∼7000 H3N2 polymerase sequences using mutual information (MI), which measures the information gained about the identity of one residue when a second residue is known. To account for uneven sampling of viral sequences over time, we developed a weighted MI (wMI) metric and demonstrate that wMI outperforms raw MI through simulations using a well-sampled severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dataset. We then constructed wMI networks of the H3N2 polymerase to extend the inherently pairwise wMI statistic to encompass relationships among larger groups of residues. We included hemagglutinin (HA) in the wMI network to distinguish between functional wMI relationships within the polymerase and those potentially due to hitch-hiking on antigenic changes in HA. The wMI networks reveal coevolutionary relationships among residues with roles in replication and encapsidation. Inclusion of HA highlighted polymerase-only subgraphs containing residues with roles in the enzymatic functions of the polymerase and host adaptability. This work provides insight into the factors that drive and constrain the rapid evolution of influenza viruses.
Collapse
|
13
|
Han AX, Girdwood SJ, Khan S, Sacks JA, Toporowski A, Huq N, Hannay E, Russell CA, Nichols BE. Strategies for Using Antigen Rapid Diagnostic Tests to Reduce Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 in Low- and Middle-Income Countries: A Mathematical Modelling Study Applied to Zambia. Clin Infect Dis 2023; 76:620-630. [PMID: 36208211 PMCID: PMC9619661 DOI: 10.1093/cid/ciac814] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 09/17/2022] [Accepted: 10/05/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Increasing the availability of antigen rapid diagnostic tests (Ag-RDTs) in low- and middle-income countries (LMICs) is key to alleviating global SARS-CoV-2 testing inequity (median testing rate in December 2021-March 2022 when the Omicron variant was spreading in multiple countries: high-income countries = 600 tests/100 000 people/day; LMICs = 14 tests/100 000 people/day). However, target testing levels and effectiveness of asymptomatic community screening to impact SARS-CoV-2 transmission in LMICs are unclear. METHODS We used Propelling Action for Testing and Treating (PATAT), an LMIC-focused agent-based model to simulate coronavirus disease 2019 (COVID-19) epidemics, varying the amount of Ag-RDTs available for symptomatic testing at healthcare facilities and asymptomatic community testing in different social settings. We assumed that testing was a function of access to healthcare facilities and availability of Ag-RDTs. We explicitly modelled symptomatic testing demand from individuals without SARS-CoV-2 and measured impact based on the number of infections averted due to test-and-isolate. RESULTS Testing symptomatic individuals yields greater benefits than any asymptomatic community testing strategy until most symptomatic individuals who sought testing have been tested. Meeting symptomatic testing demand likely requires at least 200-400 tests/100 000 people/day, on average, as symptomatic testing demand is highly influenced by individuals without SARS-CoV-2. After symptomatic testing demand is satisfied, excess tests to proactively screen for asymptomatic infections among household members yield the largest additional infections averted. CONCLUSIONS Testing strategies aimed at reducing transmission should prioritize symptomatic testing and incentivizing test-positive individuals to adhere to isolation to maximize effectiveness.
Collapse
Affiliation(s)
- Alvin X Han
- Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Sarah J Girdwood
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Shaukat Khan
- Clinton Health Access Initiative, Boston, Massachusetts, USA
| | - Jilian A Sacks
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Amy Toporowski
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Naushin Huq
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Emma Hannay
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Colin A Russell
- Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
- Department of Global Health, School of Public Health, Boston University, Boston, Massachusetts, USA
| | - Brooke E Nichols
- Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
- Department of Global Health, School of Public Health, Boston University, Boston, Massachusetts, USA
| |
Collapse
|
14
|
Arcos S, Han AX, Te Velthuis AJW, Russell CA, Lauring AS. Mutual information networks reveal evolutionary relationships within the influenza A virus polymerase. bioRxiv 2023:2023.02.16.528850. [PMID: 36824962 PMCID: PMC9949103 DOI: 10.1101/2023.02.16.528850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
The influenza A (IAV) RNA polymerase is an essential driver of IAV evolution. Mutations that the polymerase introduces into viral genome segments during replication are the ultimate source of genetic variation, including within the three subunits of the IAV polymerase (PB2, PB1, and PA). Evolutionary analysis of the IAV polymerase is complicated, because changes in mutation rate, replication speed, and drug resistance involve epistatic interactions among its subunits. In order to study the evolution of the human seasonal H3N2 polymerase since the 1968 pandemic, we identified pairwise evolutionary relationships among ∼7000 H3N2 polymerase sequences using mutual information (MI), which measures the information gained about the identity of one residue when a second residue is known. To account for uneven sampling of viral sequences over time, we developed a weighted MI metric (wMI) and demonstrate that wMI outperforms raw MI through simulations using a well-sampled SARS-CoV-2 dataset. We then constructed wMI networks of the H3N2 polymerase to extend the inherently pairwise wMI statistic to encompass relationships among larger groups of residues. We included HA in the wMI network to distinguish between functional wMI relationships within the polymerase and those potentially due to hitchhiking on antigenic changes in HA. The wMI networks reveal coevolutionary relationships among residues with roles in replication and encapsidation. Inclusion of HA highlighted polymerase-only subgraphs containing residues with roles in the enzymatic functions of the polymerase and host adaptability. This work provides insight into the factors that drive and constrain the rapid evolution of influenza viruses.
Collapse
|
15
|
Horsburgh CR, Jo Y, Nichols B, Jenkins HE, Russell CA, White LF. Contribution of Reinfection to Annual Rate of Tuberculosis Infection (ARI) and Incidence of Tuberculosis Disease. Clin Infect Dis 2023; 76:e965-e972. [PMID: 35666515 PMCID: PMC10169390 DOI: 10.1093/cid/ciac451] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/24/2022] [Accepted: 06/01/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Modeling studies have concluded that 60-80% of tuberculosis (TB) infections result from reinfection of previously infected persons. The annual rate of infection (ARI), a standard measure of the risk of TB infection in a community, may not accurately reflect the true risk of infection among previously infected persons. We constructed a model of infection and reinfection with Mycobacterium tuberculosis to explore the predictive accuracy of ARI and its effect on disease incidence. METHODS We created a deterministic simulation of the progression from TB infection to disease and simulated the prevalence of TB infection at the beginning and end of a theoretical year of infection. We considered 10 disease prevalence scenarios ranging from 100/100 000 to 1000/100 000 in simulations where TB exposure probability was homogeneous across the whole simulated population or heterogeneously stratified into high-risk and low-risk groups. ARI values, rates of progression from infection to disease, and the effect of multiple reinfections were obtained from published studies. RESULTS With homogeneous exposure risk, observed ARI values produced expected numbers of infections. However, when heterogeneous risk was introduced, observed ARI was seen to underestimate true ARI by 25-58%. Of the cases of TB disease that occurred, 36% were among previously infected persons when prevalence was 100/100 000, increasing to 79% of cases when prevalence was 1000/100 000. CONCLUSIONS Measured ARI underestimates true ARI as a result of heterogeneous population mixing. The true force of infection in a community may be greater than previously appreciated. Hyperendemic communities likely contribute disproportionally to the global TB disease burden.
Collapse
Affiliation(s)
- C Robert Horsburgh
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Youngji Jo
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Brooke Nichols
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Helen E Jenkins
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Colin A Russell
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, USA
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Laura F White
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| |
Collapse
|
16
|
de Jong SPJ, Felix Garza ZC, Gibson JC, Han AX, van Leeuwen S, de Vries RP, Boons GJ, van Hoesel M, de Haan K, van Groeningen LE, Hulme KD, van Willigen HDG, Wynberg E, de Bree GJ, Matser A, Bakker M, van der Hoek L, Prins M, Kootstra NA, Eggink D, Nichols BE, de Jong MD, Russell CA. Potential impacts of prolonged absence of influenza virus circulation on subsequent epidemics. medRxiv 2022:2022.02.05.22270494. [PMID: 36415458 PMCID: PMC9681055 DOI: 10.1101/2022.02.05.22270494] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Background During the first two years of the COVID-19 pandemic, the circulation of seasonal influenza viruses was unprecedentedly low. This led to concerns that the lack of immune stimulation to influenza viruses combined with waning antibody titres could lead to increased susceptibility to influenza in subsequent seasons, resulting in larger and more severe epidemics. Methods We analyzed historical influenza virus epidemiological data from 2003-2019 to assess the historical frequency of near-absence of seasonal influenza virus circulation and its impact on the size and severity of subsequent epidemics. Additionally, we measured haemagglutination inhibition-based antibody titres against seasonal influenza viruses using longitudinal serum samples from 165 healthy adults, collected before and during the COVID-19 pandemic, and estimated how antibody titres against seasonal influenza waned during the first two years of the pandemic. Findings Low country-level prevalence of influenza virus (sub)types over one or more years occurred frequently before the COVID-19 pandemic and had relatively small impacts on subsequent epidemic size and severity. Additionally, antibody titres against seasonal influenza viruses waned negligibly during the first two years of the pandemic. Interpretation The commonly held notion that lulls in influenza virus circulation, as observed during the COVID-19 pandemic, will lead to larger and/or more severe subsequent epidemics might not be fully warranted, and it is likely that post-lull seasons will be similar in size and severity to pre-lull seasons. Funding European Research Council, Netherlands Organization for Scientific Research, Royal Dutch Academy of Sciences, Public Health Service of Amsterdam. Research in context Evidence before this study: During the first years of the COVID-19 pandemic, the incidence of seasonal influenza was unusually low, leading to widespread concerns of exceptionally large and/or severe influenza epidemics in the coming years. We searched PubMed and Google Scholar using a combination of search terms (i.e., "seasonal influenza", "SARS-CoV-2", "COVID-19", "low incidence", "waning rates", "immune protection") and critically considered published articles and preprints that studied or reviewed the low incidence of seasonal influenza viruses since the start of the COVID-19 pandemic and its potential impact on future seasonal influenza epidemics. We found a substantial body of work describing how influenza virus circulation was reduced during the COVID-19 pandemic, and a number of studies projecting the size of future epidemics, each positing that post-pandemic epidemics are likely to be larger than those observed pre-pandemic. However, it remains unclear to what extent the assumed relationship between accumulated susceptibility and subsequent epidemic size holds, and it remains unknown to what extent antibody levels have waned during the COVID-19 pandemic. Both are potentially crucial for accurate prediction of post-pandemic epidemic sizes.Added value of this study: We find that the relationship between epidemic size and severity and the magnitude of circulation in the preceding season(s) is decidedly more complex than assumed, with the magnitude of influenza circulation in preceding seasons having only limited effects on subsequent epidemic size and severity. Rather, epidemic size and severity are dominated by season-specific effects unrelated to the magnitude of circulation in the preceding season(s). Similarly, we find that antibody levels waned only modestly during the COVID-19 pandemic.Implications of all the available evidence: The lack of changes observed in the patterns of measured antibody titres against seasonal influenza viruses in adults and nearly two decades of epidemiological data suggest that post-pandemic epidemic sizes will likely be similar to those observed pre-pandemic, and challenge the commonly held notion that the widespread concern that the near-absence of seasonal influenza virus circulation during the COVID-19 pandemic, or potential future lulls, are likely to result in larger influenza epidemics in subsequent years.
Collapse
|
17
|
Nichols BE, de Nooy A, Benade M, Balakasi K, Mphande M, Rao G, Claassen CW, Khan S, Stillson C, Russell CA, Doi N, Dovel K. Facility-based HIV self-testing strategies may substantially and cost-effectively increase the number of men and youth tested for HIV in Malawi: results from an individual-based mathematical model. J Int AIDS Soc 2022; 25:e26020. [PMID: 36251161 PMCID: PMC9575938 DOI: 10.1002/jia2.26020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 09/15/2022] [Indexed: 11/10/2022] Open
Abstract
INTRODUCTION Malawi is rapidly closing the gap in achieving the UNAIDS 95-95-95 targets, with 90% of people living with HIV in Malawi aware of their status. As we approach epidemic control, interventions to improve coverage will become more costly. There is, therefore, an urgent need to identify innovative and low-cost strategies to maintain and increase testing coverage without diverting resources from other HIV services. The objective of this study is to model different combinations of facility-based HIV testing modalities and determine the most cost-effective strategy to increase the proportion of men and youth testing for HIV. METHODS A data-driven individual-based model was parameterized with data from a community-representative survey (socio-demographic, health service utilization and HIV testing history) of men and youth in Malawi (data collected August 2019). In total, 79 different strategies for the implementation of HIV self-testing (HIVST) and provider-initiated-testing-and-counselling at the outpatient department (OPD) were evaluated. Outcomes included percent of men/youth tested for HIV in a 12-month period, cost-effectiveness and human resource requirements. The testing yield was assumed to be constant across the scenarios. RESULTS Facility-based HIVST offered year-round resulted in the greatest increase in the proportion of men and youth tested in the OPD (from 45% to 72%-83%), was considered cost-saving for HIVST kit priced at $1.00, and generally reduced required personnel as compared to the status quo. At higher HIVST kit prices, and more relaxed eligibility criteria, all scenarios that considered year-round HIVST in the OPD remained on the cost-effectiveness frontier. CONCLUSIONS Facility-based HIVST is a cost-effective strategy to increase the proportion of men/youth tested for HIV in Malawi and decreases the human resource requirements for HIV testing in the OPD-providing additional healthcare worker time for other priority healthcare activities.
Collapse
Affiliation(s)
- Brooke E. Nichols
- Department of Global Health, School of Public HealthBoston UniversityBostonMassachusettsUSA,Health Economics and Epidemiology Research Office, Department of Internal Medicine, Faculty of Health Sciences, School of Clinical Medicine, University of the WitwatersrandJohannesburgSouth Africa,Department of Medical MicrobiologyAmsterdam University Medical CentreAmsterdamthe Netherlands,Foundation for Innovative New DiagnosticsGenevaSwitzerland
| | - Alexandra de Nooy
- Department of Medical MicrobiologyAmsterdam University Medical CentreAmsterdamthe Netherlands,Right to CareJohannesburgSouth Africa
| | - Mariet Benade
- Department of Global Health, School of Public HealthBoston UniversityBostonMassachusettsUSA
| | | | | | | | - Cassidy W. Claassen
- Center for International Health, Education, and BiosecurityUniversity of Maryland School of MedicineBaltimoreMarylandUSA,Division of Infectious Diseases, Department of MedicineUniversity of Zambia School of MedicineLusakaZambia
| | - Shaukat Khan
- Clinton Health Access InitiativeBostonMarylandUSA
| | | | - Colin A. Russell
- Department of Global Health, School of Public HealthBoston UniversityBostonMassachusettsUSA,Department of Medical MicrobiologyAmsterdam University Medical CentreAmsterdamthe Netherlands
| | - Naoko Doi
- Clinton Health Access InitiativeBostonMarylandUSA
| | - Kathryn Dovel
- Right to CareJohannesburgSouth Africa,Division of Infectious Diseases, Department of MedicineUniversity of California Los Angeles David Geffen School of MedicineLos AngelesCaliforniaUSA
| |
Collapse
|
18
|
Han AX, Toporowski A, Sacks JA, Perkins MD, Briand S, van Kerkhove M, Hannay E, Carmona S, Rodriguez B, Parker E, Nichols BE, Russell CA. SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs. medRxiv 2022:2022.05.20.22275319. [PMID: 35664998 PMCID: PMC9164450 DOI: 10.1101/2022.05.20.22275319] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
The first step in SARS-CoV-2 genomic surveillance is testing to identify infected people. However, global testing rates are falling as we emerge from the acute health emergency and remain low in many low- and middle-income countries (LMICs) (mean = 27 tests/100,000 people/day). We simulated COVID-19 epidemics in a prototypical LMIC to investigate how testing rates, sampling strategies, and sequencing proportions jointly impact surveillance outcomes and showed that low testing rates and spatiotemporal biases delay time-to-detection of new variants by weeks-to-months and can lead to unreliable estimates of variant prevalence even when the proportion of samples sequenced is increased. Accordingly, investments in wider access to diagnostics to support testing rates of ~100 tests/100,000 people/day could enable more timely detection of new variants and reliable estimates of variant prevalence. The performance of global SARS-CoV-2 genomic surveillance programs is fundamentally limited by access to diagnostic testing.
Collapse
Affiliation(s)
- Alvin X. Han
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands,Corresponding authors. and
| | - Amy Toporowski
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Jilian A. Sacks
- Department of Epidemic and Pandemic Preparedness and Prevention, Emergency Preparedness Programme, World Health Organization, Geneva, Switzerland
| | - Mark D. Perkins
- Department of Epidemic and Pandemic Preparedness and Prevention, Emergency Preparedness Programme, World Health Organization, Geneva, Switzerland
| | - Sylvie Briand
- Department of Epidemic and Pandemic Preparedness and Prevention, Emergency Preparedness Programme, World Health Organization, Geneva, Switzerland
| | - Maria van Kerkhove
- Department of Epidemic and Pandemic Preparedness and Prevention, Emergency Preparedness Programme, World Health Organization, Geneva, Switzerland
| | - Emma Hannay
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Sergio Carmona
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Bill Rodriguez
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Edyth Parker
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Brooke E. Nichols
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands,Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland,Department of Global Health, School of Public Health, Boston University, Boston, MA, USA
| | - Colin A. Russell
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands,Department of Global Health, School of Public Health, Boston University, Boston, MA, USA,Corresponding authors. and
| |
Collapse
|
19
|
van der Straten K, Guerra D, van Gils MJ, Bontjer I, Caniels TG, van Willigen HDG, Wynberg E, Poniman M, Burger JA, Bouhuijs JH, van Rijswijk J, Olijhoek W, Liesdek MH, Lavell AHA, Appelman B, Sikkens JJ, Bomers MK, Han AX, Nichols BE, Prins M, Vennema H, Reusken C, de Jong MD, de Bree GJ, Russell CA, Eggink D, Sanders RW. Antigenic cartography using sera from sequence-confirmed SARS-CoV-2 variants of concern infections reveals antigenic divergence of Omicron. Immunity 2022; 55:1725-1731.e4. [PMID: 35973428 PMCID: PMC9353602 DOI: 10.1016/j.immuni.2022.07.018] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 05/26/2022] [Accepted: 07/26/2022] [Indexed: 11/26/2022]
Abstract
Large-scale vaccination campaigns have prevented countless hospitalizations and deaths due to COVID-19. However, the emergence of SARS-CoV-2 variants that escape from immunity challenges the effectiveness of current vaccines. Given this continuing evolution, an important question is when and how to update SARS-CoV-2 vaccines to antigenically match circulating variants, similarly to seasonal influenza viruses where antigenic drift necessitates periodic vaccine updates. Here, we studied SARS-CoV-2 antigenic drift by assessing neutralizing activity against variants of concern (VOCs) in a set of sera from patients infected with viral sequence-confirmed VOCs. Infections with D614G or Alpha strains induced the broadest immunity, whereas individuals infected with other VOCs had more strain-specific responses. Omicron BA.1 and BA.2 were substantially resistant to neutralization by sera elicited by all other variants. Antigenic cartography revealed that Omicron BA.1 and BA.2 were antigenically most distinct from D614G, associated with immune escape, and possibly will require vaccine updates to ensure vaccine effectiveness.
Collapse
Affiliation(s)
- Karlijn van der Straten
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands; Amsterdam UMC Location University of Amsterdam, Department of Internal Medicine, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands
| | - Denise Guerra
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Marit J van Gils
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Ilja Bontjer
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Tom G Caniels
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Hugo D G van Willigen
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Elke Wynberg
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands; Department of Infectious Diseases, Public Health Service of Amsterdam, GGD, 1018 WT Amsterdam, the Netherlands
| | - Meliawati Poniman
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Judith A Burger
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Joey H Bouhuijs
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Jacqueline van Rijswijk
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Wouter Olijhoek
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Marinus H Liesdek
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands; Amsterdam UMC Location University of Amsterdam, Department of Internal Medicine, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands
| | - A H Ayesha Lavell
- Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands; Amsterdam UMC Location VU University Amsterdam, Department of Internal Medicine, Boelelaan 1117, 1081 HV Amsterdam, the Netherlands
| | - Brent Appelman
- Amsterdam UMC Location University of Amsterdam, Center for Experimental and Molecular Medicine, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands
| | - Jonne J Sikkens
- Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands; Amsterdam UMC Location VU University Amsterdam, Department of Internal Medicine, Boelelaan 1117, 1081 HV Amsterdam, the Netherlands
| | - Marije K Bomers
- Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands; Amsterdam UMC Location VU University Amsterdam, Department of Internal Medicine, Boelelaan 1117, 1081 HV Amsterdam, the Netherlands
| | - Alvin X Han
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Brooke E Nichols
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands; Department of Global Health, Boston University School of Public Health, Boston, MA, USA
| | - Maria Prins
- Amsterdam UMC Location University of Amsterdam, Department of Internal Medicine, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Department of Infectious Diseases, Public Health Service of Amsterdam, GGD, 1018 WT Amsterdam, the Netherlands
| | - Harry Vennema
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, 3721 MA Bilthoven, the Netherlands
| | - Chantal Reusken
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, 3721 MA Bilthoven, the Netherlands
| | - Menno D de Jong
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Godelieve J de Bree
- Amsterdam UMC Location University of Amsterdam, Department of Internal Medicine, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands
| | - Colin A Russell
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands.
| | - Dirk Eggink
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands; Centre for Infectious Disease Control, National Institute for Public Health and the Environment, 3721 MA Bilthoven, the Netherlands.
| | - Rogier W Sanders
- Amsterdam UMC Location University of Amsterdam, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands; Department of Microbiology and Immunology, Weill Medical College of Cornell University, New York, NY 10065, USA.
| |
Collapse
|
20
|
Han AX, Kozanli E, Koopsen J, Vennema H, Hajji K, Kroneman A, van Walle I, Klinkenberg D, Wallinga J, Russell CA, Eggink D, Reusken C. Regional importation and asymmetric within-country spread of SARS-CoV-2 variants of concern in the Netherlands. eLife 2022; 11:78770. [PMID: 36097810 PMCID: PMC9470152 DOI: 10.7554/elife.78770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 08/14/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Variants of concern (VOCs) of SARS-CoV-2 have caused resurging waves of infections worldwide. In the Netherlands, the Alpha, Beta, Gamma, and Delta VOCs circulated widely between September 2020 and August 2021. We sought to elucidate how various control measures, including targeted flight restrictions, had impacted the introduction and spread of these VOCs in the Netherlands. Methods: We performed phylogenetic analyses on 39,844 SARS-CoV-2 genomes collected under the Dutch national surveillance program. Results: We found that all four VOCs were introduced before targeted flight restrictions were imposed on countries where the VOCs first emerged. Importantly, foreign introductions, predominantly from other European countries, continued during these restrictions. After their respective introductions into the Netherlands, the Alpha and Delta VOCs largely circulated within more populous regions of the country with international connections before asymmetric bidirectional transmissions occurred with the rest of the country and the VOC became the dominant circulating lineage. Conclusions: Our findings show that flight restrictions had limited effectiveness in deterring VOC introductions due to the strength of regional land travel importation risks. As countries consider scaling down SARS-CoV-2 surveillance efforts in the post-crisis phase of the pandemic, our results highlight that robust surveillance in regions of early spread is important for providing timely information for variant detection and outbreak control. Funding: None.
Collapse
Affiliation(s)
- Alvin X Han
- Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers
| | - Eva Kozanli
- Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers
| | - Jelle Koopsen
- Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers
| | - Harry Vennema
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment
| | - Karim Hajji
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment
| | - Annelies Kroneman
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment
| | - Ivo van Walle
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment
| | - Don Klinkenberg
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment
| | - Jacco Wallinga
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment
| | - Colin A Russell
- Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers
| | - Dirk Eggink
- Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment
| | - Chantal Reusken
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment
| | | |
Collapse
|
21
|
Han AX, Kozanli E, Koopsen J, Vennema H, Hajji K, Kroneman A, van Walle I, Klinkenberg D, Wallinga J, Russell CA, Eggink D, Reusken CB, RIVM COVID-19 molecular epidemiology group. Regional importation and asymmetric within-country spread of SARS-CoV-2 variants of concern in the Netherlands.. [PMID: 35350194 PMCID: PMC8963694 DOI: 10.1101/2022.03.21.22272611] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Variants of concern (VOCs) of SARS-CoV-2 have caused resurging waves of infections worldwide. In the Netherlands, Alpha, Beta, Gamma and Delta variants circulated widely between September 2020 and August 2021. To understand how various control measures had impacted the spread of these VOCs, we analyzed 39,844 SARS-CoV-2 genomes collected under the Dutch national surveillance program. We found that all four VOCs were introduced before targeted flight restrictions were imposed on countries where the VOCs first emerged. Importantly, foreign introductions, predominantly from other European countries, continued during these restrictions. Our findings show that flight restrictions had limited effectiveness in deterring VOC introductions due to the strength of regional land travel importation risks. We also found that the Alpha and Delta variants largely circulated more populous regions with international connections after their respective introduction before asymmetric bidirectional transmissions occurred with the rest of the country and the variant dominated infections in the Netherlands. As countries consider scaling down SARS-CoV-2 surveillance efforts in the post-crisis phase of the pandemic, our results highlight that robust surveillance in regions of early spread is important for providing timely information for variant detection and outbreak control.
Collapse
|
22
|
Koopsen J, van Ewijk CE, Bavalia R, Cornelissen A, Bruisten SM, de Gee F, Han AX, de Jong M, de Jong MD, Jonges M, Khawaja N, Koene FM, van der Lubben M, Mikulic I, Rebers SP, Russell CA, Schinkel J, Schreijer AJ, den Uil JA, Welkers MR, Leenstra T. Epidemiologic and Genomic Analysis of SARS-CoV-2 Delta Variant Superspreading Event in Nightclub, the Netherlands, June 2021. Emerg Infect Dis 2022; 28:1012-1016. [PMID: 35271792 PMCID: PMC9045423 DOI: 10.3201/eid2805.212019] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
We report a severe acute respiratory syndrome coronavirus 2 superspreading event in the Netherlands after distancing rules were lifted in nightclubs, despite requiring a negative test or vaccination. This occurrence illustrates the potential for rapid dissemination of variants in largely unvaccinated populations under such conditions. We detected subsequent community transmission of this strain.
Collapse
|
23
|
van Gils MJ, van Willigen HD, Wynberg E, Han AX, van der Straten K, Burger JA, Poniman M, Oomen M, Tejjani K, Bouhuijs JH, Verveen A, Lebbink R, Dijkstra M, Appelman B, Lavell AA, Caniels TG, Bontjer I, van Vught LA, Vlaar AP, Sikkens JJ, Bomers MK, Russell CA, Kootstra NA, Sanders RW, Prins M, de Bree GJ, de Jong MD. A single mRNA vaccine dose in COVID-19 patients boosts neutralizing antibodies against SARS-CoV-2 and variants of concern. Cell Rep Med 2022; 3:100486. [PMID: 35103254 PMCID: PMC8668345 DOI: 10.1016/j.xcrm.2021.100486] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 09/28/2021] [Accepted: 11/26/2021] [Indexed: 12/20/2022]
Abstract
The urgent need for, but limited availability of, SARS-CoV-2 vaccines worldwide has led to widespread consideration of dose-sparing strategies. Here, we evaluate the SARS-CoV-2-specific antibody responses following BNT162b2 vaccination in 150 previously SARS-CoV-2-infected individuals from a population-based cohort. One week after first vaccine dose, spike protein antibody levels are 27-fold higher and neutralizing antibody titers 12-fold higher, exceeding titers of fully vaccinated SARS-CoV-2-naive controls, with minimal additional boosting after the second dose. Neutralizing antibody titers against four variants of concern increase after vaccination; however, overall neutralization breadth does not improve. Pre-vaccination neutralizing antibody titers and time since infection have the largest positive effect on titers following vaccination. COVID-19 severity and the presence of comorbidities have no discernible impact on vaccine response. In conclusion, a single dose of BNT162b2 vaccine up to 15 months after SARS-CoV-2 infection offers higher neutralizing antibody titers than 2 vaccine doses in SARS-CoV-2-naive individuals.
Collapse
Affiliation(s)
- Marit J. van Gils
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Hugo D.G. van Willigen
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Elke Wynberg
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
- Department of Infectious Diseases, Public Health Service of Amsterdam, GGD, Amsterdam, the Netherlands
| | - Alvin X. Han
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Karlijn van der Straten
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
- Department of Internal Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Judith A. Burger
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Meliawati Poniman
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Melissa Oomen
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Khadija Tejjani
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Joey H. Bouhuijs
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Anouk Verveen
- Department of Medical Psychology, Amsterdam UMC, University of Amsterdam, Amsterdam School of Public Health, Amsterdam, the Netherlands
| | - Romy Lebbink
- Department of Infectious Diseases, Public Health Service of Amsterdam, GGD, Amsterdam, the Netherlands
| | - Maartje Dijkstra
- Department of Infectious Diseases, Public Health Service of Amsterdam, GGD, Amsterdam, the Netherlands
- Department of Internal Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Brent Appelman
- Center for Experimental and Molecular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - A.H. Ayesha Lavell
- Department of Internal Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Tom G. Caniels
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Ilja Bontjer
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Lonneke A. van Vught
- Center for Experimental and Molecular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
- Department of Intensive Care Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Alexander P.J. Vlaar
- Department of Intensive Care Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Jonne J. Sikkens
- Department of Internal Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Marije K. Bomers
- Department of Internal Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Colin A. Russell
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Neeltje A. Kootstra
- Department of Experimental Immunology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Rogier W. Sanders
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
- Department of Microbiology and Immunology, Weill Medical College of Cornell University, New York, NY, USA
| | - Maria Prins
- Department of Infectious Diseases, Public Health Service of Amsterdam, GGD, Amsterdam, the Netherlands
- Department of Internal Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Godelieve J. de Bree
- Department of Internal Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| | - Menno D. de Jong
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands
| |
Collapse
|
24
|
Schorcht A, Cottrell CA, Pugach P, Ringe RP, Han AX, Allen JD, van den Kerkhof TLGM, Seabright GE, Schermer EE, Ketas TJ, Burger JA, van Schooten J, LaBranche CC, Ozorowski G, de Val N, Bader DLV, Schuitemaker H, Russell CA, Montefiori DC, van Gils MJ, Crispin M, Klasse PJ, Ward AB, Moore JP, Sanders RW. The Glycan Hole Area of HIV-1 Envelope Trimers Contributes Prominently to the Induction of Autologous Neutralization. J Virol 2022; 96:e0155221. [PMID: 34669426 PMCID: PMC8754230 DOI: 10.1128/jvi.01552-21] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 10/14/2021] [Indexed: 01/15/2023] Open
Abstract
The human immunodeficiency virus type 1 (HIV-1) trimeric envelope glycoprotein (Env) is heavily glycosylated, creating a dense glycan shield that protects the underlying peptidic surface from antibody recognition. The absence of conserved glycans, due to missing potential N-linked glycosylation sites (PNGS), can result in strain-specific, autologous neutralizing antibody (NAb) responses. Here, we sought to gain a deeper understanding of the autologous neutralization by introducing holes in the otherwise dense glycan shields of the AMC011 and AMC016 SOSIP trimers. Specifically, when we knocked out the N130 and N289 glycans, which are absent from the well-characterized B41 SOSIP trimer, we observed stronger autologous NAb responses. We also analyzed the highly variable NAb responses induced in rabbits by diverse SOSIP trimers from subtypes A, B, and C. Statistical analysis, using linear regression, revealed that the cumulative area exposed on a trimer by glycan holes correlates with the magnitude of the autologous NAb response. IMPORTANCE Forty years after the first description of HIV-1, the search for a protective vaccine is still ongoing. The sole target for antibodies that can neutralize the virus are the trimeric envelope glycoproteins (Envs) located on the viral surface. The glycoprotein surface is covered with glycans that shield off the underlying protein components from recognition by the immune system. However, the Env trimers of some viral strains have holes in the glycan shield. Immunized animals developed antibodies against such glycan holes. These antibodies are generally strain specific. Here, we sought to gain a deeper understanding of what drives these specific immune responses. First, we show that strain-specific neutralizing antibody responses can be increased by creating artificial holes in the glycan shield. Second, when studying a diverse set of Env trimers with different characteristics, we found that the surface area of the glycan holes contributes prominently to the induction of strain-specific neutralizing antibodies.
Collapse
Affiliation(s)
- Anna Schorcht
- Department of Medical Microbiology and Infection Prevention, Amsterdam Infection & Immunity Institute (AI&AII), Amsterdam UMC, Location Meibergdreef, University of Amsterdam, Amsterdam, The Netherlands
| | - Christopher A. Cottrell
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, USA
| | - Pavel Pugach
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, New York, USA
| | - Rajesh P. Ringe
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, New York, USA
| | - Alvin X. Han
- Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology and Infection Prevention, Amsterdam Infection & Immunity Institute (AI&AII), Amsterdam UMC, Location Meibergdreef, University of Amsterdam, Amsterdam, The Netherlands
| | - Joel D. Allen
- Centre for Biological Sciences and Institute for Life Sciences, University of Southampton, Southampton, England, United Kingdom
| | - Tom L. G. M. van den Kerkhof
- Department of Medical Microbiology and Infection Prevention, Amsterdam Infection & Immunity Institute (AI&AII), Amsterdam UMC, Location Meibergdreef, University of Amsterdam, Amsterdam, The Netherlands
- Department of Experimental Immunology, Amsterdam Infection & Immunity Institute (AI&AII), Amsterdam UMC, Location Meibergdreef, University of Amsterdam, Amsterdam, The Netherlands
| | - Gemma E. Seabright
- Centre for Biological Sciences and Institute for Life Sciences, University of Southampton, Southampton, England, United Kingdom
| | - Edith E. Schermer
- Department of Medical Microbiology and Infection Prevention, Amsterdam Infection & Immunity Institute (AI&AII), Amsterdam UMC, Location Meibergdreef, University of Amsterdam, Amsterdam, The Netherlands
| | - Thomas J. Ketas
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, New York, USA
| | - Judith A. Burger
- Department of Medical Microbiology and Infection Prevention, Amsterdam Infection & Immunity Institute (AI&AII), Amsterdam UMC, Location Meibergdreef, University of Amsterdam, Amsterdam, The Netherlands
| | - Jelle van Schooten
- Department of Medical Microbiology and Infection Prevention, Amsterdam Infection & Immunity Institute (AI&AII), Amsterdam UMC, Location Meibergdreef, University of Amsterdam, Amsterdam, The Netherlands
| | - Celia C. LaBranche
- Department of Surgery, Duke University Medical Center, Durham, North Carolina, USA
| | - Gabriel Ozorowski
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, USA
| | - Natalia de Val
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, USA
| | - Daniel L. V. Bader
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, USA
| | - Hanneke Schuitemaker
- Department of Experimental Immunology, Amsterdam Infection & Immunity Institute (AI&AII), Amsterdam UMC, Location Meibergdreef, University of Amsterdam, Amsterdam, The Netherlands
| | - Colin A. Russell
- Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology and Infection Prevention, Amsterdam Infection & Immunity Institute (AI&AII), Amsterdam UMC, Location Meibergdreef, University of Amsterdam, Amsterdam, The Netherlands
| | - David C. Montefiori
- Department of Surgery, Duke University Medical Center, Durham, North Carolina, USA
| | - Marit J. van Gils
- Department of Medical Microbiology and Infection Prevention, Amsterdam Infection & Immunity Institute (AI&AII), Amsterdam UMC, Location Meibergdreef, University of Amsterdam, Amsterdam, The Netherlands
| | - Max Crispin
- Centre for Biological Sciences and Institute for Life Sciences, University of Southampton, Southampton, England, United Kingdom
| | - P. J. Klasse
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, New York, USA
| | - Andrew B. Ward
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, USA
| | - John P. Moore
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, New York, USA
| | - Rogier W. Sanders
- Department of Medical Microbiology and Infection Prevention, Amsterdam Infection & Immunity Institute (AI&AII), Amsterdam UMC, Location Meibergdreef, University of Amsterdam, Amsterdam, The Netherlands
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, New York, USA
| |
Collapse
|
25
|
Hendrickson C, Long LC, van Rensburg C, Claassen CW, Njelesani M, Moyo C, Mulenga L, O'Bra H, Russell CA, Nichols BE. The early-stage comprehensive costs of routine PrEP implementation and scale-up in Zambia. PLOS Glob Public Health 2022; 2:e0001246. [PMID: 36962684 PMCID: PMC10021804 DOI: 10.1371/journal.pgph.0001246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 10/10/2022] [Indexed: 11/07/2022]
Abstract
Pre-exposure prophylaxis (PrEP) is an effective HIV prevention option, but cost-effectiveness is sensitive to implementation and program costs. Studies indicate that, in addition to direct delivery cost, PrEP provision requires substantial demand creation and client support to encourage PrEP initiation and persistence. We estimated the cost of providing PrEP in Zambia through different PrEP delivery models. Taking a guidelines-based approach for visits, labs and drugs, we estimated the annual cost of providing PrEP per client for five delivery models: one focused on key populations (men-who-have-sex-with-men (MSM) and female sex workers (FSW), one on adolescent girls and young women (AGYW), and three integrated programs (operated within HIV counselling and testing services at primary healthcare centres). Program start-up and support costs were based on program expenditure data and number of PrEP sites and clients in 2018. PrEP clinic visit costs were based on micro-costing at two PrEP delivery sites (2018 USD). Costs are presented in 2018 prices and inflated to 2021 prices. The annual cost/PrEP client varied by service delivery model, from $394 (AGYW) to $655 (integrated model). Cost differences were driven largely by client volume, which impacted the relative costs of program support and technical assistance assigned to each PrEP client. Direct service delivery costs ranged narrowly from $205-212/PrEP-client and were a key component in the cost of PrEP, representing 35-65% of total costs. The results show that, even when integrated into full service delivery models, accessing vulnerable, marginalised populations at substantial risk of HIV infection is likely to cost more than previously estimated due to the programmatic costs involved in community sensitization and client support. Improved data on individual client resource usage and outcomes is required to get a better understanding of the true resource utilization, expected outcomes and annual costs of different PrEP service delivery programs in Zambia.
Collapse
Affiliation(s)
- Cheryl Hendrickson
- Health Economics and Epidemiology Research Office, Johannesburg, South Africa
- Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Lawrence C Long
- Health Economics and Epidemiology Research Office, Johannesburg, South Africa
- Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Global Health, School of Public Health, Boston University, Boston, Massachusetts, United States of America
| | - Craig van Rensburg
- Health Economics and Epidemiology Research Office, Johannesburg, South Africa
- Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Cassidy W Claassen
- Center for International Health, Education, and Biosecurity (CIHEB), Institute of Human Virology, University of Maryland School of Medicine, Lusaka, Zambia
| | | | | | | | - Heidi O'Bra
- United States Agency for International Development, Lusaka, Zambia
| | - Colin A Russell
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Brooke E Nichols
- Health Economics and Epidemiology Research Office, Johannesburg, South Africa
- Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
- Department of Global Health, School of Public Health, Boston University, Boston, Massachusetts, United States of America
| |
Collapse
|
26
|
Han AX, Felix Garza ZC, Welkers MRA, Vigeveno RM, Tran ND, Le TQM, Pham Quang T, Dang DT, Tran TNA, Ha MT, Nguyen TH, Le QT, Le TH, Hoang TBN, Chokephaibulkit K, Puthavathana P, Nguyen VVC, Nghiem MN, Nguyen VK, Dao TT, Tran TH, Wertheim HFL, Horby PW, Fox A, van Doorn HR, Eggink D, de Jong MD, Russell CA. Within-host evolutionary dynamics of seasonal and pandemic human influenza A viruses in young children. eLife 2021; 10:e68917. [PMID: 34342576 PMCID: PMC8382297 DOI: 10.7554/elife.68917] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 08/02/2021] [Indexed: 01/14/2023] Open
Abstract
The evolution of influenza viruses is fundamentally shaped by within-host processes. However, the within-host evolutionary dynamics of influenza viruses remain incompletely understood, in part because most studies have focused on infections in healthy adults based on single timepoint data. Here, we analyzed the within-host evolution of 82 longitudinally sampled individuals, mostly young children, infected with A/H1N1pdm09 or A/H3N2 viruses between 2007 and 2009. For A/H1N1pdm09 infections during the 2009 pandemic, nonsynonymous minority variants were more prevalent than synonymous ones. For A/H3N2 viruses in young children, early infection was dominated by purifying selection. As these infections progressed, nonsynonymous variants typically increased in frequency even when within-host virus titers decreased. Unlike the short-lived infections of adults where de novo within-host variants are rare, longer infections in young children allow for the maintenance of virus diversity via mutation-selection balance creating potentially important opportunities for within-host virus evolution.
Collapse
Affiliation(s)
- Alvin X Han
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical CenterAmsterdamNetherlands
| | - Zandra C Felix Garza
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical CenterAmsterdamNetherlands
| | - Matthijs RA Welkers
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical CenterAmsterdamNetherlands
| | - René M Vigeveno
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical CenterAmsterdamNetherlands
| | - Nhu Duong Tran
- National Institute of Hygiene and EpidemiologyHanoiViet Nam
| | | | | | | | | | | | | | | | - Thanh Hai Le
- Vietnam National Children's HospitalHanoiViet Nam
| | | | | | | | | | | | | | | | - Tinh Hien Tran
- Siriraj Hospital, Mahidol UniversityBangkokThailand
- Oxford University Clinical Research UnitHo Chi Minh cityViet Nam
| | - Heiman FL Wertheim
- Oxford University Clinical Research UnitHo Chi Minh cityViet Nam
- Radboud Medical Centre, Radboud UniversityNijmegenNetherlands
- Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
| | - Peter W Horby
- Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
- Oxford University Clinical Research UnitHanoiViet Nam
| | - Annette Fox
- Oxford University Clinical Research UnitHanoiViet Nam
- Peter Doherty Institute for Infection and Immunity, University of MelbourneMelbourneAustralia
- WHO Collaborating Centre for Reference and Research on InfluenzaMelbourneAustralia
| | - H Rogier van Doorn
- Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
- Oxford University Clinical Research UnitHanoiViet Nam
| | - Dirk Eggink
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical CenterAmsterdamNetherlands
- Centre for Infectious Disease Control, National Institute for Public Health and the EnvironmentBilthovenNetherlands
| | - Menno D de Jong
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical CenterAmsterdamNetherlands
| | - Colin A Russell
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical CenterAmsterdamNetherlands
| |
Collapse
|
27
|
Sikkens JJ, Buis DTP, Peters EJG, Dekker M, Schinkel M, Reijnders TDY, Schuurman AR, de Brabander J, Lavell AHA, Maas JJ, Koopsen J, Han AX, Russell CA, Schinkel J, Jonges M, Matamoros S, Jurriaans S, van Mansfeld R, Wiersinga WJ, Smulders YM, de Jong MD, Bomers MK. Serologic Surveillance and Phylogenetic Analysis of SARS-CoV-2 Infection Among Hospital Health Care Workers. JAMA Netw Open 2021; 4:e2118554. [PMID: 34319354 PMCID: PMC9437910 DOI: 10.1001/jamanetworkopen.2021.18554] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
IMPORTANCE It is unclear when, where, and by whom health care workers (HCWs) working in hospitals are infected with SARS-CoV-2. OBJECTIVE To determine how often and in what manner nosocomial SARS-CoV-2 infection occurs in HCW groups with varying exposure to patients with COVID-19. DESIGN, SETTING, AND PARTICIPANTS This cohort study comprised 4 weekly measurements of SARS-CoV-2-specific antibodies and collection of questionnaires from March 23 to June 25, 2020, combined with phylogenetic and epidemiologic transmission analyses at 2 university hospitals in the Netherlands. Included individuals were HCWs working in patient care for those with COVID-19, HCWs working in patient care for those without COVID-19, and HCWs not working in patient care. Data were analyzed from August through December 2020. EXPOSURES Varying work-related exposure to patients infected with SARS-CoV-2. MAIN OUTCOMES AND MEASURES The cumulative incidence of and time to SARS-CoV-2 infection, defined as the presence of SARS-CoV-2-specific antibodies in blood samples, were measured. RESULTS Among 801 HCWs, there were 439 HCWs working in patient care for those with COVID-19, 164 HCWs working in patient care for those without COVID-19, and 198 HCWs not working in patient care. There were 580 (72.4%) women, and the median (interquartile range) age was 36 (29-50) years. The incidence of SARS-CoV-2 was increased among HCWs working in patient care for those with COVID-19 (54 HCWs [13.2%; 95% CI, 9.9%-16.4%]) compared with HCWs working in patient care for those without COVID-19 (11 HCWs [6.7%; 95% CI, 2.8%-10.5%]; hazard ratio [HR], 2.25; 95% CI, 1.17-4.30) and HCWs not working in patient care (7 HCWs [3.6%; 95% CI, 0.9%-6.1%]; HR, 3.92; 95% CI, 1.79-8.62). Among HCWs caring for patients with COVID-19, SARS-CoV-2 cumulative incidence was increased among HCWs working on COVID-19 wards (32 of 134 HCWs [25.7%; 95% CI, 17.6%-33.1%]) compared with HCWs working on intensive care units (13 of 186 HCWs [7.1%; 95% CI, 3.3%-10.7%]; HR, 3.64; 95% CI, 1.91-6.94), and HCWs working in emergency departments (7 of 102 HCWs [8.0%; 95% CI, 2.5%-13.1%]; HR, 3.29; 95% CI, 1.52-7.14). Epidemiologic data combined with phylogenetic analyses on COVID-19 wards identified 3 potential HCW-to-HCW transmission clusters. No patient-to-HCW transmission clusters could be identified in transmission analyses. CONCLUSIONS AND RELEVANCE This study found that HCWs working on COVID-19 wards were at increased risk for nosocomial SARS-CoV-2 infection with an important role for HCW-to-HCW transmission. These findings suggest that infection among HCWs deserves more consideration in infection prevention practice.
Collapse
Affiliation(s)
- Jonne J. Sikkens
- Department of Internal Medicine, Amsterdam
Infection and Immunity Institute, Amsterdam University Medical Centers, Vrije
Universiteit Amsterdam, Amsterdam, the Netherlands
| | - David T. P. Buis
- Department of Internal Medicine, Amsterdam
Infection and Immunity Institute, Amsterdam University Medical Centers, Vrije
Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Edgar J. G. Peters
- Section Infectious Diseases, Department of
Internal Medicine, Amsterdam Infection and Immunity Institute, Amsterdam University
Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Mireille Dekker
- Department of Medical Microbiology and Infection
Prevention, Amsterdam Infection and Immunity Institute, Amsterdam University Medical
Centers, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Michiel Schinkel
- Center for Experimental Molecular Medicine,
Amsterdam Infection and Immunity Institute, Amsterdam University Medical Centers,
University of Amsterdam, Amsterdam, the Netherlands
| | - Tom D. Y. Reijnders
- Center for Experimental Molecular Medicine,
Amsterdam Infection and Immunity Institute, Amsterdam University Medical Centers,
University of Amsterdam, Amsterdam, the Netherlands
| | - Alex. R. Schuurman
- Center for Experimental Molecular Medicine,
Amsterdam Infection and Immunity Institute, Amsterdam University Medical Centers,
University of Amsterdam, Amsterdam, the Netherlands
| | - Justin de Brabander
- Center for Experimental Molecular Medicine,
Amsterdam Infection and Immunity Institute, Amsterdam University Medical Centers,
University of Amsterdam, Amsterdam, the Netherlands
| | - A. H. Ayesha Lavell
- Department of Internal Medicine, Amsterdam
Infection and Immunity Institute, Amsterdam University Medical Centers, Vrije
Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Jaap J. Maas
- Department of Occupational Health and Safety,
Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the
Netherlands
| | - Jelle Koopsen
- Department of Medical Microbiology and Infection
Prevention, Amsterdam University Medical Centers, University of Amsterdam,
Amsterdam, the Netherlands
| | - Alvin X. Han
- Department of Medical Microbiology and Infection
Prevention, Amsterdam University Medical Centers, University of Amsterdam,
Amsterdam, the Netherlands
| | - Colin A. Russell
- Department of Medical Microbiology and Infection
Prevention, Amsterdam University Medical Centers, University of Amsterdam,
Amsterdam, the Netherlands
| | - Janke Schinkel
- Department of Medical Microbiology and Infection
Prevention, Amsterdam University Medical Centers, University of Amsterdam,
Amsterdam, the Netherlands
| | - Marcel Jonges
- Department of Medical Microbiology and Infection
Prevention, Amsterdam University Medical Centers, University of Amsterdam,
Amsterdam, the Netherlands
| | - Sébastien Matamoros
- Department of Medical Microbiology and Infection
Prevention, Amsterdam University Medical Centers, University of Amsterdam,
Amsterdam, the Netherlands
| | - Suzanne Jurriaans
- Department of Medical Microbiology and Infection
Prevention, Amsterdam University Medical Centers, University of Amsterdam,
Amsterdam, the Netherlands
| | - Rosa van Mansfeld
- Department of Medical Microbiology and Infection
Prevention, Amsterdam University Medical Centers, University of Amsterdam,
Amsterdam, the Netherlands
| | - W. Joost Wiersinga
- Division of Infectious Diseases, Department of
Internal Medicine, Amsterdam Infection and Immunity Institute, Amsterdam University
Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Yvo M. Smulders
- Department of Internal Medicine, Amsterdam
Infection and Immunity Institute, Amsterdam University Medical Centers, Vrije
Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Menno D. de Jong
- Department of Medical Microbiology and Infection
Prevention, Amsterdam University Medical Centers, University of Amsterdam,
Amsterdam, the Netherlands
| | - Marije K. Bomers
- Section Infectious Diseases, Department of
Internal Medicine, Amsterdam Infection and Immunity Institute, Amsterdam University
Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| |
Collapse
|
28
|
Affiliation(s)
- William P Hanage
- Department of Epidemiology, Harvard University T. H. Chan School of Public Health, Boston, MA 02115, USA.
| | - Colin A Russell
- Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, Netherlands.
| |
Collapse
|
29
|
Yan AWC, Zhou J, Beauchemin CAA, Russell CA, Barclay WS, Riley S. Quantifying mechanistic traits of influenza viral dynamics using in vitro data. Epidemics 2020; 33:100406. [PMID: 33096342 DOI: 10.1016/j.epidem.2020.100406] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Revised: 07/10/2020] [Accepted: 09/04/2020] [Indexed: 11/28/2022] Open
Abstract
When analysing in vitro data, growth kinetics of influenza virus strains are often compared by computing their growth rates, which are sometimes used as proxies for fitness. However, analogous to mathematical models for epidemics, the growth rate can be defined as a function of mechanistic traits: the basic reproduction number (the average number of cells each infected cell infects) and the mean generation time (the average length of a replication cycle). Fitting a model to previously published and newly generated data from experiments in human lung cells, we compared estimates of growth rate, reproduction number and generation time for six influenza A strains. Of four strains in previously published data, A/Canada/RV733/2003 (seasonal H1N1) had the lowest basic reproduction number, followed by A/Mexico/INDRE4487/2009 (pandemic H1N1), then A/Indonesia/05/2005 (spill-over H5N1) and A/Anhui/1/2013 (spill-over H7N9). This ordering of strains was preserved for both generation time and growth rate, suggesting a positive biological correlation between these quantities which have not been previously observed. We further investigated these potential correlations using data from reassortant viruses with different internal proteins (from A/England/195/2009 (pandemic H1N1) and A/Turkey/05/2005 (H5N1)), and the same surface proteins (from A/Puerto Rico/8/34 (lab-adapted H1N1)). Similar correlations between traits were observed for these viruses, confirming our initial findings and suggesting that these patterns were related to the degree of human adaptation of internal genes. Also, the model predicted that strains with a smaller basic reproduction number, shorter generation time and slower growth rate underwent more replication cycles by the time of peak viral load, potentially accumulating mutations more quickly. These results illustrate the utility of mathematical models in inferring traits driving observed differences in in vitro growth of influenza strains.
Collapse
Affiliation(s)
- Ada W C Yan
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, United Kingdom
| | - Jie Zhou
- Section of Virology, Department of Medicine, Imperial College London, London W2 1PG, United Kingdom
| | - Catherine A A Beauchemin
- Department of Physics, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3, Canada; Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS), RIKEN, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan
| | - Colin A Russell
- Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam, 1105 AZ, The Netherlands
| | - Wendy S Barclay
- Section of Virology, Department of Medicine, Imperial College London, London W2 1PG, United Kingdom
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, United Kingdom.
| |
Collapse
|
30
|
Puylaert CAJ, Scheijmans JCG, Borgstein ABJ, Andeweg CS, Bartels-Rutten A, Beets GL, van Berge Henegouwen MI, Braak SJ, Couvreur R, Daams F, van Es HW, Franken LC, Grotenhuis BA, Hendriks ER, de Hingh IHJT, Hoeijmakers F, Ten Holder JT, Huisman PM, Kazemier G, van Kesteren F, van Kesteren J, Keywani K, Kuiper SZ, Lange MDJ, Lobatto ME, du Mée AWF, Poeze M, van Praag EM, van Rossen J, van Santvoort HC, Sedee WJA, Seelen LWF, Sharabiany S, Sosef NL, Quanjel MJR, Veltman J, Verhagen T, van de Vlasakker VCJ, Weeder PD, van Werven JR, Wesdorp NJ, van Dieren S, Han AX, Russell CA, de Jong MD, Bossuyt PMM, Quarles van Ufford JME, Prokop MW, Gisbertz SS, Prins JM, Besselink MG, Boermeester MA, Gietema HA, Stoker J. Yield of Screening for COVID-19 in Asymptomatic Patients Before Elective or Emergency Surgery Using Chest CT and RT-PCR (SCOUT): Multicenter Study. Ann Surg 2020; 272:919-924. [PMID: 33021367 PMCID: PMC7668335 DOI: 10.1097/sla.0000000000004218] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
OBJECTIVE To determine the yield of preoperative screening for COVID-19 with chest CT and RT-PCR in patients without COVID-19 symptoms. SUMMARY OF BACKGROUND DATA Many centers are currently screening surgical patients for COVID-19 using either chest CT, RT-PCR or both, due to the risk for worsened surgical outcomes and nosocomial spread. The optimal design and yield of such a strategy are currently unknown. METHODS This multicenter study included consecutive adult patients without COVID-19 symptoms who underwent preoperative screening using chest CT and RT-PCR before elective or emergency surgery under general anesthesia. RESULTS A total of 2093 patients without COVID-19 symptoms were included in 14 participating centers; 1224 were screened by CT and RT-PCR and 869 by chest CT only. The positive yield of screening using a combination of chest CT and RT-PCR was 1.5% [95% confidence interval (CI): 0.8-2.1]. Individual yields were 0.7% (95% CI: 0.2-1.1) for chest CT and 1.1% (95% CI: 0.6-1.7) for RT-PCR; the incremental yield of chest CT was 0.4%. In relation to COVID-19 community prevalence, up to ∼6% positive RT-PCR was found for a daily hospital admission rate >1.5 per 100,000 inhabitants, and around 1.0% for lower prevalence. CONCLUSIONS One in every 100 patients without COVID-19 symptoms tested positive for SARS-CoV-2 with RT-PCR; this yield increased in conjunction with community prevalence. The added value of chest CT was limited. Preoperative screening allowed us to take adequate precautions for SARS-CoV-2 positive patients in a surgical population, whereas negative patients needed only routine procedures.
Collapse
Affiliation(s)
- Carl A J Puylaert
- Department of Radiology and Nuclear Medicine, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Jochem C G Scheijmans
- Department of Surgery, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Alexander B J Borgstein
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | | | | | - Geerard L Beets
- Department of Surgical Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Mark I van Berge Henegouwen
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Sicco J Braak
- Department of Radiology, Hospital Group Twente, Almelo, the Netherlands
| | - Roy Couvreur
- Department of Surgery, Haaglanden Medical Center, Den Haag, the Netherlands
| | - Freek Daams
- Department of Surgery, Cancer Center Amsterdam UMC, VU University Amsterdam, Amsterdam, the Netherlands
| | - Hendrik W van Es
- Department of Radiology, Sint Antonius Hospital, Nieuwegein, the Netherlands
| | - Lotte C Franken
- Department of Surgery, Flevo Hospital, Almere, the Netherlands
| | - Brechtje A Grotenhuis
- Department of Surgical Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Eduard R Hendriks
- Department of Surgery, Tergooi Hospitals, Hilversum, the Netherlands
| | | | | | - Joris T Ten Holder
- Department of Pulmonary Medicine, Haaglanden Medical Center, Den Haag, the Netherlands
| | - Peter M Huisman
- Department of Radiology, Tergooi Hospitals, Hilversum, the Netherlands
| | - Geert Kazemier
- Department of Surgery, Cancer Center Amsterdam UMC, VU University Amsterdam, Amsterdam, the Netherlands
| | - Floortje van Kesteren
- Department of Radiology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | | | - Kammy Keywani
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Sara Z Kuiper
- Department of Surgery, Maastricht UMC+, Maastricht, the Netherlands
| | - Maurits D J Lange
- Department of Surgical Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Mark E Lobatto
- Department of Radiology, Spaarne Gasthuis, Haarlem and Hoofddorp, the Netherlands
| | | | - Martijn Poeze
- Department of Surgery, Maastricht UMC+, Maastricht, the Netherlands
| | - Elise M van Praag
- Department of Surgery, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Jorit van Rossen
- Department of Radiology, Hospital Group Twente, Almelo, the Netherlands
| | - Hjalmar C van Santvoort
- Department of Surgery, Sint Antonius Hospital, Nieuwegein, the Netherlands
- Department of Surgery, UMC Utrecht Cancer Center, UMC Utrecht, Utrecht, the Netherlands
| | - Wouter J A Sedee
- Department of Emergency Medicine, St Jansdal Hospital, Harderwijk, the Netherlands
| | - Leonard W F Seelen
- Department of Surgery, Sint Antonius Hospital, Nieuwegein, the Netherlands
| | - Sarah Sharabiany
- Department of Surgery, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Nico L Sosef
- Department of Surgery, Spaarne Gasthuis, Haarlem and Hoofddorp, the Netherlands
| | - Marian J R Quanjel
- Department of Pulmonary Medicine, Sint Antonius Hospital, Nieuwegein, the Netherlands
| | - Jeroen Veltman
- Department of Radiology, Hospital Group Twente, Almelo, the Netherlands
| | - Tim Verhagen
- Department of Surgery, Hospital Group Twente, Almelo, the Netherlands
| | | | - Pepijn D Weeder
- Department of Surgery, Spaarne Gasthuis, Haarlem and Hoofddorp, the Netherlands
| | | | - Nina J Wesdorp
- Department of Surgery, Cancer Center Amsterdam UMC, VU University Amsterdam, Amsterdam, the Netherlands
| | - Susan van Dieren
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Alvin X Han
- Laboratory of Applied Evolutionary Biology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Colin A Russell
- Laboratory of Applied Evolutionary Biology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Menno D de Jong
- Department of Medical Microbiology and Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Patrick M M Bossuyt
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | | | | | - Suzanne S Gisbertz
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Jan M Prins
- Department of Internal Medicine, Division of Infectious Diseases, Amsterdam Institute for Infection and Immunity (AI&II), Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Marc G Besselink
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Marja A Boermeester
- Department of Surgery, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Hester A Gietema
- Department of Radiology, Maastricht UMC+, Maastricht, the Netherlands
| | - Jaap Stoker
- Department of Radiology and Nuclear Medicine, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| |
Collapse
|
31
|
Morris DH, Petrova VN, Rossine FW, Parker E, Grenfell BT, Neher RA, Levin SA, Russell CA. Asynchrony between virus diversity and antibody selection limits influenza virus evolution. eLife 2020; 9:e62105. [PMID: 33174838 PMCID: PMC7748417 DOI: 10.7554/elife.62105] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 11/04/2020] [Indexed: 12/14/2022] Open
Abstract
Seasonal influenza viruses create a persistent global disease burden by evolving to escape immunity induced by prior infections and vaccinations. New antigenic variants have a substantial selective advantage at the population level, but these variants are rarely selected within-host, even in previously immune individuals. Using a mathematical model, we show that the temporal asynchrony between within-host virus exponential growth and antibody-mediated selection could limit within-host antigenic evolution. If selection for new antigenic variants acts principally at the point of initial virus inoculation, where small virus populations encounter well-matched mucosal antibodies in previously-infected individuals, there can exist protection against reinfection that does not regularly produce observable new antigenic variants within individual infected hosts. Our results provide a theoretical explanation for how virus antigenic evolution can be highly selective at the global level but nearly neutral within-host. They also suggest new avenues for improving influenza control.
Collapse
MESH Headings
- Antibodies, Neutralizing/genetics
- Antibodies, Neutralizing/immunology
- Antibodies, Viral/immunology
- Biological Evolution
- Genetic Variation/genetics
- Humans
- Influenza A Virus, H3N2 Subtype/genetics
- Influenza A Virus, H3N2 Subtype/immunology
- Influenza A virus/genetics
- Influenza A virus/immunology
- Influenza, Human/immunology
- Influenza, Human/transmission
- Influenza, Human/virology
- Models, Statistical
- Selection, Genetic/genetics
- Selection, Genetic/immunology
- Virion/genetics
- Virion/immunology
Collapse
Affiliation(s)
- Dylan H Morris
- Department of Ecology & Evolutionary Biology, Princeton UniversityPrincetonUnited States
| | - Velislava N Petrova
- Department of Human Genetics, Wellcome Trust Sanger InstituteCambridgeUnited Kingdom
| | - Fernando W Rossine
- Department of Ecology & Evolutionary Biology, Princeton UniversityPrincetonUnited States
| | - Edyth Parker
- Department of Veterinary Medicine, University of CambridgeCambridgeUnited Kingdom
- Department of Medical Microbiology, Academic Medical Center, University of AmsterdamAmsterdamNetherlands
| | - Bryan T Grenfell
- Department of Ecology & Evolutionary Biology, Princeton UniversityPrincetonUnited States
- Fogarty International Center, National Institutes of HealthBethesdaUnited States
| | | | - Simon A Levin
- Department of Ecology & Evolutionary Biology, Princeton UniversityPrincetonUnited States
| | - Colin A Russell
- Department of Medical Microbiology, Academic Medical Center, University of AmsterdamAmsterdamNetherlands
| |
Collapse
|
32
|
Petrova VN, Sawatsky B, Han AX, Laksono BM, Walz L, Parker E, Pieper K, Anderson CA, de Vries RD, Lanzavecchia A, Kellam P, von Messling V, de Swart RL, Russell CA. Incomplete genetic reconstitution of B cell pools contributes to prolonged immunosuppression after measles. Sci Immunol 2020; 4:4/41/eaay6125. [PMID: 31672862 DOI: 10.1126/sciimmunol.aay6125] [Citation(s) in RCA: 68] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 10/01/2019] [Indexed: 12/24/2022]
Abstract
Measles is a disease caused by the highly infectious measles virus (MeV) that results in both viremia and lymphopenia. Lymphocyte counts recover shortly after the disappearance of measles-associated rash, but immunosuppression can persist for months to years after infection, resulting in increased incidence of secondary infections. Animal models and in vitro studies have proposed various immunological factors underlying this prolonged immune impairment, but the precise mechanisms operating in humans are unknown. Using B cell receptor (BCR) sequencing of human peripheral blood lymphocytes before and after MeV infection, we identified two immunological consequences from measles underlying immunosuppression: (i) incomplete reconstitution of the naïve B cell pool leading to immunological immaturity and (ii) compromised immune memory to previously encountered pathogens due to depletion of previously expanded B memory clones. Using a surrogate model of measles in ferrets, we investigated the clinical consequences of morbillivirus infection and demonstrated a depletion of vaccine-acquired immunity to influenza virus, leading to a compromised immune recall response and increased disease severity after secondary influenza virus challenge. Our results show that MeV infection causes changes in naïve and memory B lymphocyte diversity that persist after the resolution of clinical disease and thus contribute to compromised immunity to previous infections or vaccinations. This work highlights the importance of MeV vaccination not only for the control of measles but also for the maintenance of herd immunity to other pathogens, which can be compromised after MeV infection.
Collapse
Affiliation(s)
| | - Bevan Sawatsky
- Veterinary Medicine Division, Paul-Ehrlich-Institut, Federal Institute for Vaccines and Biomedicines and DZIF TTU Emerging Infections, Langen, Germany
| | - Alvin X Han
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.,Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Brigitta M Laksono
- Department of Viroscience, Postgraduate School of Molecular Medicine, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Lisa Walz
- Veterinary Medicine Division, Paul-Ehrlich-Institut, Federal Institute for Vaccines and Biomedicines and DZIF TTU Emerging Infections, Langen, Germany
| | - Edyth Parker
- Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Kathrin Pieper
- Institute for Research in Biomedicine, Università della Svizzera Italiana, Bellinzona, Switzerland
| | - Carl A Anderson
- Department of Human Genetics, Wellcome Sanger Institute, Cambridge, UK
| | - Rory D de Vries
- Department of Viroscience, Postgraduate School of Molecular Medicine, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Antonio Lanzavecchia
- Institute for Research in Biomedicine, Università della Svizzera Italiana, Bellinzona, Switzerland
| | - Paul Kellam
- Department of Medicine, Division of Infectious Diseases, Imperial College Faculty of Medicine, Wright Fleming Institute, St Mary's Campus, London, UK.,Kymab Ltd., The Bennet Building, Babraham Research Campus, Cambridge, UK
| | - Veronika von Messling
- Veterinary Medicine Division, Paul-Ehrlich-Institut, Federal Institute for Vaccines and Biomedicines and DZIF TTU Emerging Infections, Langen, Germany
| | - Rik L de Swart
- Department of Viroscience, Postgraduate School of Molecular Medicine, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Colin A Russell
- Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands.
| |
Collapse
|
33
|
Lam EKS, Morris DH, Hurt AC, Barr IG, Russell CA. The impact of climate and antigenic evolution on seasonal influenza virus epidemics in Australia. Nat Commun 2020; 11:2741. [PMID: 32488106 PMCID: PMC7265451 DOI: 10.1038/s41467-020-16545-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 05/09/2020] [Indexed: 11/08/2022] Open
Abstract
Although seasonal influenza viruses circulate globally, prevention and treatment occur at the level of regions, cities, and communities. At these scales, the timing, duration and magnitude of epidemics vary substantially, but the underlying causes of this variation are poorly understood. Here, based on analyses of a 15-year city-level dataset of 18,250 laboratory-confirmed and antigenically-characterised influenza virus infections from Australia, we investigate the effects of previously hypothesised environmental and virological drivers of influenza epidemics. We find that anomalous fluctuations in temperature and humidity do not predict local epidemic onset timings. We also find that virus antigenic change has no consistent effect on epidemic size. In contrast, epidemic onset time and heterosubtypic competition have substantial effects on epidemic size and composition. Our findings suggest that the relationship between influenza population immunity and epidemiology is more complex than previously supposed and that the strong influence of short-term processes may hinder long-term epidemiological forecasts.
Collapse
Affiliation(s)
- Edward K S Lam
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Dylan H Morris
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Aeron C Hurt
- WHO Collaborating Centre for Reference and Research on Influenza, VIDRL, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
- Department of Microbiology and Immunology, University of Melbourne, Parkville, VIC, Australia
| | - Ian G Barr
- WHO Collaborating Centre for Reference and Research on Influenza, VIDRL, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
- Department of Microbiology and Immunology, University of Melbourne, Parkville, VIC, Australia
- School of Applied Biomedical Sciences, Federation University, Churchill, VIC, Australia
| | - Colin A Russell
- Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
| |
Collapse
|
34
|
Abstract
Subspecies nomenclature systems of pathogens are increasingly based on sequence data. The use of phylogenetics to identify and differentiate between clusters of genetically similar pathogens is particularly prevalent in virology from the nomenclature of human papillomaviruses to highly pathogenic avian influenza (HPAI) H5Nx viruses. These nomenclature systems rely on absolute genetic distance thresholds to define the maximum genetic divergence tolerated between viruses designated as closely related. However, the phylogenetic clustering methods used in these nomenclature systems are limited by the arbitrariness of setting intra and intercluster diversity thresholds. The lack of a consensus ground truth to define well-delineated, meaningful phylogenetic subpopulations amplifies the difficulties in identifying an informative distance threshold. Consequently, phylogenetic clustering often becomes an exploratory, ad hoc exercise. Phylogenetic Clustering by Linear Integer Programming (PhyCLIP) was developed to provide a statistically principled phylogenetic clustering framework that negates the need for an arbitrarily defined distance threshold. Using the pairwise patristic distance distributions of an input phylogeny, PhyCLIP parameterizes the intra and intercluster divergence limits as statistical bounds in an integer linear programming model which is subsequently optimized to cluster as many sequences as possible. When applied to the hemagglutinin phylogeny of HPAI H5Nx viruses, PhyCLIP was not only able to recapitulate the current WHO/OIE/FAO H5 nomenclature system but also further delineated informative higher resolution clusters that capture geographically distinct subpopulations of viruses. PhyCLIP is pathogen-agnostic and can be generalized to a wide variety of research questions concerning the identification of biologically informative clusters in pathogen phylogenies. PhyCLIP is freely available at http://github.com/alvinxhan/PhyCLIP, last accessed March 15, 2019.
Collapse
Affiliation(s)
- Alvin X Han
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore.,NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore (NUS), Singapore.,Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| | - Edyth Parker
- Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.,Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Frits Scholer
- Department of Medical Microbiology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| | - Sebastian Maurer-Stroh
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore.,NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore (NUS), Singapore.,Department of Biological Sciences, National University of Singapore, Singapore
| | - Colin A Russell
- Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| |
Collapse
|
35
|
Abstract
Current phylogenetic clustering approaches for identifying pathogen transmission clusters are limited by their dependency on arbitrarily defined genetic distance thresholds for within-cluster divergence. Incomplete knowledge of a pathogen’s underlying dynamics often reduces the choice of distance threshold to an exploratory, ad hoc exercise that is difficult to standardise across studies. Phydelity is a new tool for the identification of transmission clusters in pathogen phylogenies. It identifies groups of sequences that are more closely related than the ensemble distribution of the phylogeny under a statistically principled and phylogeny-informed framework, without the introduction of arbitrary distance thresholds. Relative to other distance threshold- and model-based methods, Phydelity outputs clusters with higher purity and lower probability of misclassification in simulated phylogenies. Applying Phydelity to empirical datasets of hepatitis B and C virus infections showed that Phydelity identified clusters with better correspondence to individuals that are more likely to be linked by transmission events relative to other widely used non-parametric phylogenetic clustering methods without the need for parameter calibration. Phydelity is generalisable to any pathogen and can be used to identify putative direct transmission events. Phydelity is freely available at https://github.com/alvinxhan/Phydelity.
Collapse
Affiliation(s)
- Alvin X Han
- Protein Sequence Analysis Group, Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), 30 Biopolis Street, 138671 Singapore.,NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore (NUS), 21 Lower Kent Ridge, 119077 Singapore.,Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Centre, Meibergdreef 9, 1105 AZ Amsterdam-Zuidoost, The Netherlands
| | - Edyth Parker
- Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Centre, Meibergdreef 9, 1105 AZ Amsterdam-Zuidoost, The Netherlands.,Department of Veterinary Medicine, University of Cambridge, Madingley Rd, Cambridge CB3 0ES, UK
| | - Sebastian Maurer-Stroh
- Protein Sequence Analysis Group, Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), 30 Biopolis Street, 138671 Singapore.,Department of Biological Sciences, National University of Singapore, 16 Science Drive 4, 117558 Singapore
| | - Colin A Russell
- Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Centre, Meibergdreef 9, 1105 AZ Amsterdam-Zuidoost, The Netherlands
| |
Collapse
|
36
|
Lee RTC, Chang HH, Russell CA, Lipsitch M, Maurer-Stroh S. Influenza A Hemagglutinin Passage Bias Sites and Host Specificity Mutations. Cells 2019; 8:E958. [PMID: 31443542 PMCID: PMC6770435 DOI: 10.3390/cells8090958] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 08/03/2019] [Accepted: 08/20/2019] [Indexed: 11/17/2022] Open
Abstract
Animal studies aimed at understanding influenza virus mutations that change host specificity to adapt to replication in mammalian hosts are necessarily limited in sample numbers due to high cost and safety requirements. As a safe, higher-throughput alternative, we explore the possibility of using readily available passage bias data obtained mostly from seasonal H1 and H3 influenza strains that were differentially grown in mammalian (MDCK) and avian cells (eggs). Using a statistical approach over 80,000 influenza hemagglutinin sequences with passage information, we found that passage bias sites are most commonly found in three regions: (i) the globular head domain around the receptor binding site, (ii) the region that undergoes pH-dependent structural changes and (iii) the unstructured N-terminal region harbouring the signal peptide. Passage bias sites were consistent among different passage cell types as well as between influenza A subtypes. We also find epistatic interactions of site pairs supporting the notion of host-specific dependency of mutations on virus genomic background. The sites identified from our large-scale sequence analysis substantially overlap with known host adaptation sites in the WHO H5N1 genetic changes inventory suggesting information from passage bias can provide candidate sites for host specificity changes to aid in risk assessment for emerging strains.
Collapse
Affiliation(s)
- Raphael T C Lee
- Bioinformatics Institute, Agency for Science Technology and Research, Singapore 138671, Singapore
| | - Hsiao-Han Chang
- Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, Boston, MA 02115, USA
| | - Colin A Russell
- Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
| | - Marc Lipsitch
- Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, Boston, MA 02115, USA
| | - Sebastian Maurer-Stroh
- Bioinformatics Institute, Agency for Science Technology and Research, Singapore 138671, Singapore.
- Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore.
- National Public Health Laboratory, National Centre for Infectious Diseases, Ministry of Health, Singapore 308442, Singapore.
| |
Collapse
|
37
|
Welkers MRA, Pawestri HA, Fonville JM, Sampurno OD, Pater M, Holwerda M, Han AX, Russell CA, Jeeninga RE, Setiawaty V, de Jong MD, Eggink D. Genetic diversity and host adaptation of avian H5N1 influenza viruses during human infection. Emerg Microbes Infect 2019; 8:262-271. [PMID: 30866780 PMCID: PMC6455201 DOI: 10.1080/22221751.2019.1575700] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The continuing pandemic threat posed by avian influenza A/H5N1 viruses calls for improved insights into their evolution during human infection. We performed whole genome deep sequencing of respiratory specimens from 44 H5N1-infected individuals from Indonesia and found substantial within-host viral diversity. At nearly 30% of genome positions multiple amino acids were observed within or across samples, including positions implicated in aerosol transmission between ferrets. Amino acid variants detected our cohort were often found more frequently in available H5N1 sequences of human than avian isolates. We additionally identified previously unreported amino acid variants and multiple variants that increased in proportion over time in available sequential samples. Given the importance of the polymerase complex for host adaptation, we tested 121 amino acid variants found in the PB2, PB1 and PA subunits for their effects on polymerase activity in human cells. We identified multiple single amino acid variants in all three polymerase subunits that substantially increase polymerase activity including some with effects comparable to that of the widely recognized adaption and virulence marker PB2-E627 K. These results indicate highly dynamic evolutionary processes during human H5N1 virus infection and the potential existence of previously undocumented adaptive pathways.
Collapse
Affiliation(s)
- Matthijs R A Welkers
- a Department of Medical Microbiology , Academic Medical Center , Amsterdam , Netherlands
| | - Hana A Pawestri
- b National Institute of Health Research and Development, Ministry of Health , Jakarta , Indonesia
| | - Judy M Fonville
- a Department of Medical Microbiology , Academic Medical Center , Amsterdam , Netherlands.,c Department of Zoology , University of Cambridge , Cambridge , UK.,e Department of Medical Microbiology , PAMM , Veldhoven , Netherlands
| | - Ondri D Sampurno
- b National Institute of Health Research and Development, Ministry of Health , Jakarta , Indonesia
| | - Maarten Pater
- a Department of Medical Microbiology , Academic Medical Center , Amsterdam , Netherlands
| | - Melle Holwerda
- a Department of Medical Microbiology , Academic Medical Center , Amsterdam , Netherlands
| | - Alvin X Han
- a Department of Medical Microbiology , Academic Medical Center , Amsterdam , Netherlands.,d Bioinformatics Institute, A*STAR , Singapore , Singapore
| | - Colin A Russell
- a Department of Medical Microbiology , Academic Medical Center , Amsterdam , Netherlands
| | - Rienk E Jeeninga
- a Department of Medical Microbiology , Academic Medical Center , Amsterdam , Netherlands
| | - Vivi Setiawaty
- b National Institute of Health Research and Development, Ministry of Health , Jakarta , Indonesia
| | - Menno D de Jong
- a Department of Medical Microbiology , Academic Medical Center , Amsterdam , Netherlands
| | - Dirk Eggink
- a Department of Medical Microbiology , Academic Medical Center , Amsterdam , Netherlands
| |
Collapse
|
38
|
Han AX, Maurer-Stroh S, Russell CA. Individual immune selection pressure has limited impact on seasonal influenza virus evolution. Nat Ecol Evol 2018; 3:302-311. [DOI: 10.1038/s41559-018-0741-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Accepted: 11/01/2018] [Indexed: 01/10/2023]
|
39
|
Berger KA, Pigott DM, Tomlinson F, Godding D, Maurer-Stroh S, Taye B, Sirota FL, Han A, Lee RTC, Gunalan V, Eisenhaber F, Hay SI, Russell CA. The Geographic Variation of Surveillance and Zoonotic Spillover Potential of Influenza Viruses in Domestic Poultry and Swine. Open Forum Infect Dis 2018; 5:ofy318. [PMID: 30619908 PMCID: PMC6309522 DOI: 10.1093/ofid/ofy318] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Accepted: 11/23/2018] [Indexed: 12/14/2022] Open
Abstract
Background Avian and swine influenza viruses circulate worldwide and pose threats to both animal and human health. The design of global surveillance strategies is hindered by information gaps on the geospatial variation in virus emergence potential and existing surveillance efforts. Methods We developed a spatial framework to quantify the geographic variation in outbreak emergence potential based on indices of potential for animal-to-human and secondary human-to-human transmission. We then compared our resultant raster model of variation in emergence potential with the global distribution of recent surveillance efforts from 359105 reports of surveillance activities. Results Our framework identified regions of Southeast Asia, Eastern Europe, Central America, and sub-Saharan Africa with high potential for influenza virus spillover. In the last 15 years, however, we found that 78.43% and 49.01% of high-risk areas lacked evidence of influenza virus surveillance in swine and domestic poultry, respectively. Conclusions Our work highlights priority areas where improved surveillance and outbreak mitigation could enhance pandemic preparedness strategies.
Collapse
Affiliation(s)
- Kathryn A Berger
- Department of Veterinary Medicine, University of Cambridge, United Kingdom.,Agrimetrics Ltd., Harpenden, United Kingdom
| | - David M Pigott
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | | | - David Godding
- Department of Veterinary Medicine, University of Cambridge, United Kingdom
| | | | - Biruhalem Taye
- Bioinformatics Institute, ASTAR, Singapore.,European Molecular Biology Laboratory, Deutsches Elektronen-Synchrotron, Hamburg, Germany
| | | | - Alvin Han
- Bioinformatics Institute, ASTAR, Singapore.,National University of Singapore
| | | | | | - Frank Eisenhaber
- Bioinformatics Institute, ASTAR, Singapore.,National University of Singapore
| | - Simon I Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Colin A Russell
- Academic Medical Center, University of Amsterdam, The Netherlands
| |
Collapse
|
40
|
Petrova VN, Muir L, McKay PF, Vassiliou GS, Smith KGC, Lyons PA, Russell CA, Anderson CA, Kellam P, Bashford-Rogers RJM. Combined Influence of B-Cell Receptor Rearrangement and Somatic Hypermutation on B-Cell Class-Switch Fate in Health and in Chronic Lymphocytic Leukemia. Front Immunol 2018; 9:1784. [PMID: 30147686 PMCID: PMC6095981 DOI: 10.3389/fimmu.2018.01784] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Accepted: 07/19/2018] [Indexed: 01/21/2023] Open
Abstract
A diverse B-cell receptor (BCR) repertoire is required to bind a wide range of antigens. BCRs are generated through genetic recombination and can be diversified through somatic hypermutation (SHM) or class-switch recombination (CSR). Patterns of repertoire diversity can vary substantially between different health conditions. We use isotype-resolved BCR sequencing to compare B-cell evolution and class-switch fate in healthy individuals and in patients with chronic lymphocytic leukemia (CLL). We show that the patterns of SHM and CSR in B-cells from healthy individuals are distinct from CLL. We identify distinct properties of clonal expansion that lead to the generation of antibodies of different classes in healthy, malignant, and non-malignant CLL BCR repertoires. We further demonstrate that BCR diversity is affected by relationships between antibody variable and constant regions leading to isotype-specific signatures of variable gene usage. This study provides powerful insights into the mechanisms underlying the evolution of the adaptive immune responses in health and their aberration during disease.
Collapse
MESH Headings
- B-Lymphocytes/immunology
- B-Lymphocytes/metabolism
- B-Lymphocytes/pathology
- Gene Rearrangement, B-Lymphocyte
- Humans
- Immunoglobulin Class Switching/genetics
- Immunoglobulin Isotypes/genetics
- Immunoglobulin Joining Region/genetics
- Immunoglobulin Variable Region/genetics
- Leukemia, Lymphocytic, Chronic, B-Cell/genetics
- Leukemia, Lymphocytic, Chronic, B-Cell/immunology
- Leukemia, Lymphocytic, Chronic, B-Cell/metabolism
- Leukocytes, Mononuclear/immunology
- Leukocytes, Mononuclear/metabolism
- Leukocytes, Mononuclear/pathology
- Multigene Family
- Receptors, Antigen, B-Cell/genetics
- Somatic Hypermutation, Immunoglobulin
Collapse
Affiliation(s)
| | - Luke Muir
- Department of Medicine, Division of Infectious Diseases, Imperial College London, London, United Kingdom
| | - Paul F. McKay
- Department of Medicine, Division of Infectious Diseases, Imperial College London, London, United Kingdom
| | | | | | - Paul A. Lyons
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Colin A. Russell
- Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | | | - Paul Kellam
- Department of Medicine, Division of Infectious Diseases, Imperial College London, London, United Kingdom
| | | |
Collapse
|
41
|
Bryant NA, Wilkie GS, Russell CA, Compston L, Grafham D, Clissold L, McLay K, Medcalf L, Newton R, Davison AJ, Elton DM. Genetic diversity of equine herpesvirus 1 isolated from neurological, abortigenic and respiratory disease outbreaks. Transbound Emerg Dis 2018; 65:817-832. [PMID: 29423949 PMCID: PMC5947664 DOI: 10.1111/tbed.12809] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2017] [Indexed: 12/14/2022]
Abstract
Equine herpesvirus 1 (EHV‐1) causes respiratory disease, abortion, neonatal death and neurological disease in equines and is endemic in most countries. The viral factors that influence EHV‐1 disease severity are poorly understood, and this has hampered vaccine development. However, the N752D substitution in the viral DNA polymerase catalytic subunit has been shown statistically to be associated with neurological disease. This has given rise to the term “neuropathic strain,” even though strains lacking the polymorphism have been recovered from cases of neurological disease. To broaden understanding of EHV‐1 diversity in the field, 78 EHV‐1 strains isolated over a period of 35 years were sequenced. The great majority of isolates originated from the United Kingdom and included in the collection were low passage isolates from respiratory, abortigenic and neurological outbreaks. Phylogenetic analysis of regions spanning 80% of the genome showed that up to 13 viral clades have been circulating in the United Kingdom and that most of these are continuing to circulate. Abortion isolates grouped into nine clades, and neurological isolates grouped into five. Most neurological isolates had the N752D substitution, whereas most abortion isolates did not, although three of the neurological isolates from linked outbreaks had a different polymorphism. Finally, bioinformatic analysis suggested that recombination has occurred between EHV‐1 clades, between EHV‐1 and equine herpesvirus 4, and between EHV‐1 and equine herpesvirus 8.
Collapse
Affiliation(s)
- N A Bryant
- Animal Health Trust, Kentford, Newmarket, Suffolk, UK
| | - G S Wilkie
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - C A Russell
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - L Compston
- Animal Health Trust, Kentford, Newmarket, Suffolk, UK
| | - D Grafham
- Sheffield Children's NHS Foundation Trust, Sheffield, South Yorkshire, UK
| | - L Clissold
- Earlham Institute, Norwich Research Park, Norwich, Norfolk, UK
| | - K McLay
- Earlham Institute, Norwich Research Park, Norwich, Norfolk, UK
| | - L Medcalf
- Animal Health Trust, Kentford, Newmarket, Suffolk, UK
| | - R Newton
- Animal Health Trust, Kentford, Newmarket, Suffolk, UK
| | - A J Davison
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - D M Elton
- Animal Health Trust, Kentford, Newmarket, Suffolk, UK
| |
Collapse
|
42
|
Langat P, Raghwani J, Dudas G, Bowden TA, Edwards S, Gall A, Bedford T, Rambaut A, Daniels RS, Russell CA, Pybus OG, McCauley J, Kellam P, Watson SJ. Genome-wide evolutionary dynamics of influenza B viruses on a global scale. PLoS Pathog 2017; 13:e1006749. [PMID: 29284042 PMCID: PMC5790164 DOI: 10.1371/journal.ppat.1006749] [Citation(s) in RCA: 65] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Revised: 01/10/2018] [Accepted: 11/13/2017] [Indexed: 12/14/2022] Open
Abstract
The global-scale epidemiology and genome-wide evolutionary dynamics of influenza B remain poorly understood compared with influenza A viruses. We compiled a spatio-temporally comprehensive dataset of influenza B viruses, comprising over 2,500 genomes sampled worldwide between 1987 and 2015, including 382 newly-sequenced genomes that fill substantial gaps in previous molecular surveillance studies. Our contributed data increase the number of available influenza B virus genomes in Europe, Africa and Central Asia, improving the global context to study influenza B viruses. We reveal Yamagata-lineage diversity results from co-circulation of two antigenically-distinct groups that also segregate genetically across the entire genome, without evidence of intra-lineage reassortment. In contrast, Victoria-lineage diversity stems from geographic segregation of different genetic clades, with variability in the degree of geographic spread among clades. Differences between the lineages are reflected in their antigenic dynamics, as Yamagata-lineage viruses show alternating dominance between antigenic groups, while Victoria-lineage viruses show antigenic drift of a single lineage. Structural mapping of amino acid substitutions on trunk branches of influenza B gene phylogenies further supports these antigenic differences and highlights two potential mechanisms of adaptation for polymerase activity. Our study provides new insights into the epidemiological and molecular processes shaping influenza B virus evolution globally.
Collapse
Affiliation(s)
- Pinky Langat
- Wellcome Trust Sanger Institute, Hinxton, United
Kingdom
| | - Jayna Raghwani
- Department of Zoology, University of Oxford, Oxford, United
Kingdom
| | - Gytis Dudas
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh,
United Kingdom
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research
Center, Seattle, Washington, United States of America
| | - Thomas A. Bowden
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics,
University of Oxford, Oxford, United Kingdom
| | | | - Astrid Gall
- Wellcome Trust Sanger Institute, Hinxton, United
Kingdom
| | - Trevor Bedford
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research
Center, Seattle, Washington, United States of America
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh,
United Kingdom
- Fogarty International Center, National Institutes of Health, Bethesda,
Maryland, United States of America
| | - Rodney S. Daniels
- Worldwide Influenza Centre, The Francis Crick Institute, London, United
Kingdom
| | - Colin A. Russell
- Department of Veterinary Medicine, University of Cambridge, Cambridge,
United Kingdom
| | - Oliver G. Pybus
- Department of Zoology, University of Oxford, Oxford, United
Kingdom
| | - John McCauley
- Worldwide Influenza Centre, The Francis Crick Institute, London, United
Kingdom
| | - Paul Kellam
- Wellcome Trust Sanger Institute, Hinxton, United
Kingdom
| | | |
Collapse
|
43
|
Abstract
This corrects the article DOI: 10.1038/nrmicro.2017.118.
Collapse
|
44
|
Lipsitch M, Barclay W, Raman R, Russell CJ, Belser JA, Cobey S, Kasson PM, Lloyd-Smith JO, Maurer-Stroh S, Riley S, Beauchemin CA, Bedford T, Friedrich TC, Handel A, Herfst S, Murcia PR, Roche B, Wilke CO, Russell CA. Viral factors in influenza pandemic risk assessment. eLife 2016; 5. [PMID: 27834632 PMCID: PMC5156527 DOI: 10.7554/elife.18491] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Accepted: 11/03/2016] [Indexed: 12/13/2022] Open
Abstract
The threat of an influenza A virus pandemic stems from continual virus spillovers from reservoir species, a tiny fraction of which spark sustained transmission in humans. To date, no pandemic emergence of a new influenza strain has been preceded by detection of a closely related precursor in an animal or human. Nonetheless, influenza surveillance efforts are expanding, prompting a need for tools to assess the pandemic risk posed by a detected virus. The goal would be to use genetic sequence and/or biological assays of viral traits to identify those non-human influenza viruses with the greatest risk of evolving into pandemic threats, and/or to understand drivers of such evolution, to prioritize pandemic prevention or response measures. We describe such efforts, identify progress and ongoing challenges, and discuss three specific traits of influenza viruses (hemagglutinin receptor binding specificity, hemagglutinin pH of activation, and polymerase complex efficiency) that contribute to pandemic risk.
Collapse
Affiliation(s)
- Marc Lipsitch
- Center for Communicable Disease Dynamics, Harvard T. H Chan School of Public Health, Boston, United States.,Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, United States.,Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, United States
| | - Wendy Barclay
- Division of Infectious Disease, Faculty of Medicine, Imperial College, London, United Kingdom
| | - Rahul Raman
- Department of Biological Engineering, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
| | - Charles J Russell
- Department of Infectious Diseases, St. Jude Children's Research Hospital, Memphis, United States
| | - Jessica A Belser
- Centers for Disease Control and Prevention, Atlanta, United States
| | - Sarah Cobey
- Department of Ecology and Evolutionary Biology, University of Chicago, Chicago, United States
| | - Peter M Kasson
- Department of Biomedical Engineering, University of Virginia, Charlottesville, United States.,Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, United States
| | - James O Lloyd-Smith
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, United States.,Fogarty International Center, National Institutes of Health, Bethesda, United States
| | - Sebastian Maurer-Stroh
- Bioinformatics Institute, Agency for Science Technology and Research, Singapore, Singapore.,National Public Health Laboratory, Communicable Diseases Division, Ministry of Health, Singapore, Singapore.,School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Steven Riley
- MRC Centre for Outbreak Analysis and Modelling, School of Public Health, Imperial College London, London, United Kingdom.,Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | | | - Trevor Bedford
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States
| | - Thomas C Friedrich
- Department of Pathobiological Sciences, University of Wisconsin School of Veterinary Medicine, Madison, United States
| | - Andreas Handel
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, United States
| | - Sander Herfst
- Department of Viroscience, Erasmus Medical Center, Rotterdam, Netherlands
| | - Pablo R Murcia
- MRC-University of Glasgow Centre For Virus Research, Glasgow, United Kingdom
| | | | - Claus O Wilke
- Center for Computational Biology and Bioinformatics, Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, United States.,Department of Integrative Biology, The University of Texas at Austin, Austin, United States
| | - Colin A Russell
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| |
Collapse
|
45
|
Affiliation(s)
- Colin A. Russell
- Department of Veterinary Medicine, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK
| |
Collapse
|
46
|
Li C, Hatta M, Burke DF, Ping J, Zhang Y, Ozawa M, Taft AS, Das SC, Hanson AP, Song J, Imai M, Wilker PR, Watanabe T, Watanabe S, Ito M, Iwatsuki-Horimoto K, Russell CA, James SL, Skepner E, Maher EA, Neumann G, Klimov AI, Kelso A, McCauley J, Wang D, Shu Y, Odagiri T, Tashiro M, Xu X, Wentworth DE, Katz JM, Cox NJ, Smith DJ, Kawaoka Y. Selection of antigenically advanced variants of seasonal influenza viruses. Nat Microbiol 2016; 1:16058. [PMID: 27572841 PMCID: PMC5087998 DOI: 10.1038/nmicrobiol.2016.58] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2016] [Accepted: 03/30/2016] [Indexed: 11/21/2022]
Abstract
Influenza viruses mutate frequently, necessitating constant updates of vaccine viruses. To establish experimental approaches that may complement the current vaccine strain selection process, we selected antigenic variants from human H1N1 and H3N2 influenza virus libraries possessing random mutations in the globular head of the haemagglutinin protein (which includes the antigenic sites) by incubating them with human and/or ferret convalescent sera to human H1N1 and H3N2 viruses. We also selected antigenic escape variants from human viruses treated with convalescent sera and from mice that had been previously immunized against human influenza viruses. Our pilot studies with past influenza viruses identified escape mutants that were antigenically similar to variants that emerged in nature, establishing the feasibility of our approach. Our studies with contemporary human influenza viruses identified escape mutants before they caused an epidemic in 2014-2015. This approach may aid in the prediction of potential antigenic escape variants and the selection of future vaccine candidates before they become widespread in nature.
Collapse
MESH Headings
- Amino Acid Substitution
- Animals
- Antigenic Variation
- Antigens, Viral/genetics
- Antigens, Viral/immunology
- Evolution, Molecular
- Ferrets/immunology
- Hemagglutinin Glycoproteins, Influenza Virus/chemistry
- Hemagglutinin Glycoproteins, Influenza Virus/genetics
- Hemagglutinin Glycoproteins, Influenza Virus/immunology
- Humans
- Immune Evasion
- Influenza A Virus, H1N1 Subtype/genetics
- Influenza A Virus, H1N1 Subtype/immunology
- Influenza A Virus, H3N2 Subtype/genetics
- Influenza A Virus, H3N2 Subtype/immunology
- Influenza Vaccines/genetics
- Influenza Vaccines/immunology
- Influenza, Human/epidemiology
- Influenza, Human/prevention & control
- Mice
- Orthomyxoviridae Infections/prevention & control
- Seasons
Collapse
Affiliation(s)
- Chengjun Li
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
| | - Masato Hatta
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
| | - David F. Burke
- Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
- World Health Organization Collaborating Centre for Modelling, Evolution, and Control of Emerging Infectious Diseases, Cambridge CB2 3EJ, UK
| | - Jihui Ping
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
| | - Ying Zhang
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
| | - Makoto Ozawa
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
- Department of Special Pathogens, International Research Center for Infectious Diseases, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan
| | - Andrew S. Taft
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
| | - Subash C. Das
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
| | - Anthony P. Hanson
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
| | - Jiasheng Song
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
| | - Masaki Imai
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
- Department of Veterinary Medicine, Faculty of Agriculture, Iwate University, Iwate 020-8550, Japan
| | - Peter R. Wilker
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
| | - Tokiko Watanabe
- ERATO Infection-Induced Host Responses Project, Saitama 332-0012, Japan
| | - Shinji Watanabe
- ERATO Infection-Induced Host Responses Project, Saitama 332-0012, Japan
| | - Mutsumi Ito
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan
| | - Kiyoko Iwatsuki-Horimoto
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan
| | - Colin A. Russell
- World Health Organization Collaborating Centre for Modelling, Evolution, and Control of Emerging Infectious Diseases, Cambridge CB2 3EJ, UK
- Fogarty International Center, National Institutes of Health, Bethesda, 20892 Maryland USA
- Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK
| | - Sarah L. James
- Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
- World Health Organization Collaborating Centre for Modelling, Evolution, and Control of Emerging Infectious Diseases, Cambridge CB2 3EJ, UK
| | - Eugene Skepner
- Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
- World Health Organization Collaborating Centre for Modelling, Evolution, and Control of Emerging Infectious Diseases, Cambridge CB2 3EJ, UK
| | - Eileen A. Maher
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
| | - Gabriele Neumann
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
| | - Alexander I. Klimov
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, 30033 Georgia USA
| | - Anne Kelso
- WHO Collaborating Centre for Reference and Research on Influenza (VIDRL) at the Peter Doherty Institute for Infection and Immunity, Melbourne, 3000 Victoria Australia
| | - John McCauley
- Division of Virology, MRC National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, UK
| | - Dayan Wang
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Yuelong Shu
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Takato Odagiri
- Influenza Virus Research Center, National Institute of Infectious Diseases, Musashi-Murayama, 208-0011 Tokyo Japan
| | - Masato Tashiro
- Influenza Virus Research Center, National Institute of Infectious Diseases, Musashi-Murayama, 208-0011 Tokyo Japan
| | - Xiyan Xu
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, 30033 Georgia USA
| | - David E. Wentworth
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, 30033 Georgia USA
| | - Jacqueline M. Katz
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, 30033 Georgia USA
| | - Nancy J. Cox
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, 30033 Georgia USA
| | - Derek J. Smith
- Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
- World Health Organization Collaborating Centre for Modelling, Evolution, and Control of Emerging Infectious Diseases, Cambridge CB2 3EJ, UK
- Department of Virology, Erasmus Medical Center, Rotterdam 3000 CA, Netherlands
| | - Yoshihiro Kawaoka
- Department of Pathobiological Sciences, Influenza Research Institute, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, 53711 Wisconsin USA
- Department of Special Pathogens, International Research Center for Infectious Diseases, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan
- ERATO Infection-Induced Host Responses Project, Saitama 332-0012, Japan
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan
| |
Collapse
|
47
|
Lewis NS, Russell CA, Langat P, Anderson TK, Berger K, Bielejec F, Burke DF, Dudas G, Fonville JM, Fouchier RA, Kellam P, Koel BF, Lemey P, Nguyen T, Nuansrichy B, Peiris JM, Saito T, Simon G, Skepner E, Takemae N, Webby RJ, Van Reeth K, Brookes SM, Larsen L, Watson SJ, Brown IH, Vincent AL. The global antigenic diversity of swine influenza A viruses. eLife 2016; 5:e12217. [PMID: 27113719 PMCID: PMC4846380 DOI: 10.7554/elife.12217] [Citation(s) in RCA: 124] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2015] [Accepted: 03/23/2016] [Indexed: 12/11/2022] Open
Abstract
Swine influenza presents a substantial disease burden for pig populations worldwide and poses a potential pandemic threat to humans. There is considerable diversity in both H1 and H3 influenza viruses circulating in swine due to the frequent introductions of viruses from humans and birds coupled with geographic segregation of global swine populations. Much of this diversity is characterized genetically but the antigenic diversity of these viruses is poorly understood. Critically, the antigenic diversity shapes the risk profile of swine influenza viruses in terms of their epizootic and pandemic potential. Here, using the most comprehensive set of swine influenza virus antigenic data compiled to date, we quantify the antigenic diversity of swine influenza viruses on a multi-continental scale. The substantial antigenic diversity of recently circulating viruses in different parts of the world adds complexity to the risk profiles for the movement of swine and the potential for swine-derived infections in humans. DOI:http://dx.doi.org/10.7554/eLife.12217.001 Influenza viruses, commonly called flu, infect millions of people and animals every year and occasionally causes pandemics in humans. The immune system can neutralise flu viruses by recognising the proteins on the virus surface, generically referred to as antigens. These antigens change as flu viruses evolve to escape detection by the immune system. These changes tend to be relatively small such that exposure to one flu virus generates immunity that is still effective against other related flu viruses. However, over time, the accumulation of these small changes can result in larger differences such that prior infections no longer provide protection against the new virus. Influenza A viruses infect a wide variety of birds and mammals. Viruses can also transmit from one species to another, which may result in the introduction of viruses with antigens that are new to the recipient species and which have the potential to cause substantial outbreaks. Pig flu viruses have long been considered to be a potential risk for human pandemic viruses and were the source of the 2009 pandemic H1N1 virus. Importantly, humans often transmit flu viruses to pigs. Understanding the dynamics and consequences of this two-way transmission is important for designing effective strategies to detect and respond to new strains of flu. Influenza A viruses of the H1 and H3 subtypes circulate widely in pigs. However, it was poorly understood how closely related swine and human viruses circulating in different regions were to one another and how much the antigens varied between the different viruses. Lewis, Russell et al. have now analysed the antigenic variation of hundreds of H1 and H3 viruses from pigs on multiple continents. The antigenic diversity of recent swine flu viruses resembles the diversity of H1 and H3 viruses observed in humans over the last 40 years. A key factor driving the diversity of the H1 and H3 viruses in pigs is the frequent introduction of human viruses to pigs. In contrast, only one flu virus from a bird had contributed to the observed antigenic diversity in pigs in a substantial way. Once in pigs, human-derived flu viruses continue to evolve their antigens. This results in a tremendous diversity of flu viruses that can be transmitted to other pigs and also to humans. These flu viruses could pose a serious risk to public health because they are no longer similar to the current human flu strains. These findings have important implications not only for developing flu vaccines for pigs but also for informing the development of more-effective surveillance and disease-control strategies to prevent the spread of new flu variants. DOI:http://dx.doi.org/10.7554/eLife.12217.002
Collapse
Affiliation(s)
- Nicola S Lewis
- Department of Zoology, University of Cambridge, Cambridge, United Kingdom
| | - Colin A Russell
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Pinky Langat
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
| | - Tavis K Anderson
- Virus and Prion Research Unit, National Animal Disease Center, USDA-ARS, Ames, United States
| | - Kathryn Berger
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Filip Bielejec
- Clinical and Epidemiological Virology, Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Belgium
| | - David F Burke
- Department of Zoology, University of Cambridge, Cambridge, United Kingdom
| | - Gytis Dudas
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
| | - Judith M Fonville
- Department of Zoology, University of Cambridge, Cambridge, United Kingdom
| | - Ron Am Fouchier
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
| | - Paul Kellam
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
| | - Bjorn F Koel
- Department of Viroscience, Erasmus Medical Center, Rotterdam, Netherlands
| | - Philippe Lemey
- Clinical and Epidemiological Virology, Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Belgium
| | - Tung Nguyen
- Department of Animal Health, National Centre for Veterinary Diagnostics, Hanoi, Vietnam
| | | | - Js Malik Peiris
- School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | | | - Gaelle Simon
- Swine Virology Immunology Unit, Anses, Ploufragan-Plouzané Laboratory, Ploufragan, France
| | - Eugene Skepner
- Department of Zoology, University of Cambridge, Cambridge, United Kingdom
| | | | | | - Richard J Webby
- St Jude Children's Research Hospital, Memphis, United States
| | - Kristien Van Reeth
- Laboratory of Virology, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium
| | | | - Lars Larsen
- National Veterinary Institute, Technical University of Denmark, Frederiksberg, Denmark
| | - Simon J Watson
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
| | - Ian H Brown
- Animal Health and Plant Agency, Weybridge, United Kingdom
| | - Amy L Vincent
- Virus and Prion Research Unit, National Animal Disease Center, USDA-ARS, Ames, United States
| |
Collapse
|
48
|
Neher RA, Bedford T, Daniels RS, Russell CA, Shraiman BI. Prediction, dynamics, and visualization of antigenic phenotypes of seasonal influenza viruses. Proc Natl Acad Sci U S A 2016; 113:E1701-9. [PMID: 26951657 PMCID: PMC4812706 DOI: 10.1073/pnas.1525578113] [Citation(s) in RCA: 134] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Human seasonal influenza viruses evolve rapidly, enabling the virus population to evade immunity and reinfect previously infected individuals. Antigenic properties are largely determined by the surface glycoprotein hemagglutinin (HA), and amino acid substitutions at exposed epitope sites in HA mediate loss of recognition by antibodies. Here, we show that antigenic differences measured through serological assay data are well described by a sum of antigenic changes along the path connecting viruses in a phylogenetic tree. This mapping onto the tree allows prediction of antigenicity from HA sequence data alone. The mapping can further be used to make predictions about the makeup of the future A(H3N2) seasonal influenza virus population, and we compare predictions between models with serological and sequence data. To make timely model output readily available, we developed a web browser-based application that visualizes antigenic data on a continuously updated phylogeny.
Collapse
MESH Headings
- Amino Acid Sequence
- Antigenic Variation/genetics
- Antigens, Viral/genetics
- Antigens, Viral/immunology
- Computer Graphics
- Computer Simulation
- Evolution, Molecular
- Forecasting
- Hemagglutinin Glycoproteins, Influenza Virus/genetics
- Hemagglutinin Glycoproteins, Influenza Virus/immunology
- Humans
- Influenza A Virus, H1N1 Subtype/genetics
- Influenza A Virus, H1N1 Subtype/immunology
- Influenza A Virus, H3N2 Subtype/genetics
- Influenza A Virus, H3N2 Subtype/immunology
- Influenza Vaccines
- Influenza, Human/epidemiology
- Influenza, Human/prevention & control
- Betainfluenzavirus/genetics
- Betainfluenzavirus/immunology
- Models, Immunological
- Molecular Sequence Data
- Phenotype
- Phylogeny
- Seasons
- Software
Collapse
Affiliation(s)
- Richard A Neher
- Evolutionary Dynamics and Biophysics, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany
| | - Trevor Bedford
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109
| | - Rodney S Daniels
- Worldwide Influenza Centre, The Francis Crick Institute, London NW7 1AA, United Kingdom
| | - Colin A Russell
- Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, United Kingdom
| | - Boris I Shraiman
- Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106
| |
Collapse
|
49
|
Mosterín Höpping A, Fonville JM, Russell CA, James S, Smith DJ. Influenza B vaccine lineage selection--an optimized trivalent vaccine. Vaccine 2016; 34:1617-1622. [PMID: 26896685 PMCID: PMC4793086 DOI: 10.1016/j.vaccine.2016.01.042] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2015] [Accepted: 01/20/2016] [Indexed: 11/27/2022]
Abstract
Epidemics of seasonal influenza viruses cause considerable morbidity and mortality each year. Various types and subtypes of influenza circulate in humans and evolve continuously such that individuals at risk of serious complications need to be vaccinated annually to keep protection up to date with circulating viruses. The influenza vaccine in most parts of the world is a trivalent vaccine, including an antigenically representative virus of recently circulating influenza A/H3N2, A/H1N1, and influenza B viruses. However, since the 1970s influenza B has split into two antigenically distinct lineages, only one of which is represented in the annual trivalent vaccine at any time. We describe a lineage selection strategy that optimizes protection against influenza B using the standard trivalent vaccine as a potentially cost effective alternative to quadrivalent vaccines.
Collapse
Affiliation(s)
| | - Judith M Fonville
- Department of Zoology, University of Cambridge, Cambridge, United Kingdom; Department of Virology, Erasmus MC, Rotterdam, The Netherlands
| | - Colin A Russell
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Sarah James
- Department of Zoology, University of Cambridge, Cambridge, United Kingdom
| | - Derek J Smith
- Department of Zoology, University of Cambridge, Cambridge, United Kingdom; Department of Virology, Erasmus MC, Rotterdam, The Netherlands.
| |
Collapse
|
50
|
Wecsler JS, Raghavendra A, Mack WJ, Tripathy D, Yamashita M, Sheth P, Hovanessian-Larsen L, Sener SF, Russell CA, MacDonald H, Lang JE. Abstract P4-02-05: Predictors of MRI detection of occult lesions in newly diagnosed breast cancer. Cancer Res 2016. [DOI: 10.1158/1538-7445.sabcs15-p4-02-05] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
BACKGROUND: The appropriate use of preoperative magnetic resonance imaging (MRI) in patients with newly diagnosed breast cancer remains a topic of debate. We aimed to determine the usefulness of MRI in the detection of occult multicentric, multifocal and contralateral lesions not seen by ultrasound or mammography.
METHODS: We performed a retrospective analysis of consecutive patients who underwent preoperative MRI for newly diagnosed biopsy-proven stage 0-III breast cancer who were treated surgically from January 2006-March 2013. All newly diagnosed breast cancer patients at our two affiliated institutions were evaluated with pre-operative MRI. Patients who received neoadjuvant systemic therapy or surgery at an outside institution were excluded from our study. Demographic, radiographic and pathologic data points including age, race, body mass index (BMI), lesion size, mammographic density, biopsy histology, and biomarkers were assessed for each patient with respect to the findings of multifocality, multicentricity, and the presence of contralateral lesions on all three imaging modalities. We performed univariate analysis associating factors separately in each of three models with multicentric, multifocal and contralateral disease on surgical pathology followed by multivariable analysis using logistic regression to calculate odds ratios.
RESULTS: Of 857 patients undergoing breast MRI within this time period, 770 patients were identified who met inclusion criteria. All patients underwent diagnostic mammogram and ultrasound followed by MRI. The patient population was 44.2% Hispanic, reflective of the population of our two institutions. Mean age was 54.7 years. MRI identified 86 patients with biopsy-proven multicentricity compared to 66 on conventional imaging. MRI identified 170 patients with biopsy-proven multifocality compared to 132 on conventional imaging. Finally, MRI identified 24 patients with biopsy-proven contralateral cancers compared to 7 on conventional imaging. Biopsy histology of invasive lobular carcinoma was predictive of the presence of multifocality on MRI (p=0.038, OR=1.95, 95% CI 1.09-3.48). Mammographic density was found to be a predictor of multicentricity (p=0.015, OR=2.22, 95% CI 1.13-3.33). Lesion size trended towards statistical significance on multivariate analysis of the multicentric lesions (p=0.057, OR=1.88, 95% CI 1.00-3.51). For contralateral cancers seen on MRI the presence of invasive lobular carcinoma on biopsy (p=0.027, OR=4.83, 95% CI 1.25-16.21) was predictive of finding a contralateral cancer.
CONCLUSIONS: Predictive factors including breast density, biopsy histology, and lesion size should be taken into account as clinical predictors of utility of pre-operative breast MRI. This data is being used to construct nomograms to predict multicentric, multifocal and contralateral disease to aid clinicians in evaluating the potential clinical utility of preoperative breast MRI.
Citation Format: Wecsler JS, Raghavendra A, Mack WJ, Tripathy D, Yamashita M, Sheth P, Hovanessian-Larsen L, Sener SF, Russell CA, MacDonald H, Lang JE. Predictors of MRI detection of occult lesions in newly diagnosed breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-02-05.
Collapse
Affiliation(s)
- JS Wecsler
- Division of Breast and Soft Tissue Surgery, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; University of Southern California, Los Angeles, CA; Division of Breast Imaging, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA
| | - A Raghavendra
- Division of Breast and Soft Tissue Surgery, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; University of Southern California, Los Angeles, CA; Division of Breast Imaging, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA
| | - WJ Mack
- Division of Breast and Soft Tissue Surgery, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; University of Southern California, Los Angeles, CA; Division of Breast Imaging, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA
| | - D Tripathy
- Division of Breast and Soft Tissue Surgery, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; University of Southern California, Los Angeles, CA; Division of Breast Imaging, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA
| | - M Yamashita
- Division of Breast and Soft Tissue Surgery, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; University of Southern California, Los Angeles, CA; Division of Breast Imaging, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA
| | - P Sheth
- Division of Breast and Soft Tissue Surgery, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; University of Southern California, Los Angeles, CA; Division of Breast Imaging, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA
| | - L Hovanessian-Larsen
- Division of Breast and Soft Tissue Surgery, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; University of Southern California, Los Angeles, CA; Division of Breast Imaging, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA
| | - SF Sener
- Division of Breast and Soft Tissue Surgery, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; University of Southern California, Los Angeles, CA; Division of Breast Imaging, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA
| | - CA Russell
- Division of Breast and Soft Tissue Surgery, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; University of Southern California, Los Angeles, CA; Division of Breast Imaging, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA
| | - H MacDonald
- Division of Breast and Soft Tissue Surgery, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; University of Southern California, Los Angeles, CA; Division of Breast Imaging, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA
| | - JE Lang
- Division of Breast and Soft Tissue Surgery, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; University of Southern California, Los Angeles, CA; Division of Breast Imaging, USC Norris Comprehensive Cancer Center and Los Angeles County Medical Center, Los Angeles, CA
| |
Collapse
|