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Wilson J, Cereno T, Petrik M, Esfandiari N, Davy D, Mahdi A, Aramini J, Gilliam WJ, Hunt T, Rivers J. It's time to apply outbreak response best practices to avian influenza: A national call to action. CANADIAN JOURNAL OF VETERINARY RESEARCH = REVUE CANADIENNE DE RECHERCHE VETERINAIRE 2024; 88:94-98. [PMID: 38988336 PMCID: PMC11232087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Accepted: 06/11/2024] [Indexed: 07/12/2024]
Abstract
Cases of high pathogenicity avian influenza (HPAI) in Canada are upon us again and with reports of infection in US dairy cattle and a dairy farmer in the United States, concern has been raised. Although panic isn't helpful, this heightened level of concern is appropriate, given that reports of human infections with the H5N1 virus often indicate high mortality rates. These can range from 14 to 50%. The current devastating impact of the virus on the poultry industry, as well as its propensity to mutate are also reasons for concern. At the same time, HPAI provides an opportunity for the poultry and livestock industries to align and organize coherently for the management of all zoonotic diseases and other industry issues. To manage HPAI more effectively, it is essential to align all stakeholders under Outbreak Response Best Practices using a formal Quality Management System (QMS). The objective of this article is to describe this approach with examples drawn from management of the Walkerton waterborne disease crisis. We urge the veterinary profession to rise to the challenge of HPAI and use it as a context in which to align more coherently with national stakeholders for the prevention and management of all priority issues within the areas of Agri-food and Public Health.
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Affiliation(s)
- Jeff Wilson
- Novometrix Research Inc., 4564 Nassagaweya-Puslinch TL, Moffat, Ontario L0P 1J0 (Wilson, Esfandiari, Aramini, Hunt); Canadian Food Inspection Agency (CFIA-ACIA), 59 Camelot Drive, Ottawa, Ontario K1A 0Y9 (Cereno); Petrik Veterinary Consultants, Cambridge, Ontario (Petrik); Econse Water Purification Systems Inc., 120 Nebo Road, Unit #4, Hamilton, Ontario L8W 2E4 (Davy); Translational and Molecular Medicine, Faculty of Medicine, University of Ottawa, 75 Laurier Avenue East, Ottawa, Ontario K1N 6N5 (Mahdi); Balsillie School of International Affairs, Wilfrid Laurier University, Waterloo, Ontario N2L 6C2 (Gilliam); Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1 (Rivers)
| | - Teresa Cereno
- Novometrix Research Inc., 4564 Nassagaweya-Puslinch TL, Moffat, Ontario L0P 1J0 (Wilson, Esfandiari, Aramini, Hunt); Canadian Food Inspection Agency (CFIA-ACIA), 59 Camelot Drive, Ottawa, Ontario K1A 0Y9 (Cereno); Petrik Veterinary Consultants, Cambridge, Ontario (Petrik); Econse Water Purification Systems Inc., 120 Nebo Road, Unit #4, Hamilton, Ontario L8W 2E4 (Davy); Translational and Molecular Medicine, Faculty of Medicine, University of Ottawa, 75 Laurier Avenue East, Ottawa, Ontario K1N 6N5 (Mahdi); Balsillie School of International Affairs, Wilfrid Laurier University, Waterloo, Ontario N2L 6C2 (Gilliam); Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1 (Rivers)
| | - Mike Petrik
- Novometrix Research Inc., 4564 Nassagaweya-Puslinch TL, Moffat, Ontario L0P 1J0 (Wilson, Esfandiari, Aramini, Hunt); Canadian Food Inspection Agency (CFIA-ACIA), 59 Camelot Drive, Ottawa, Ontario K1A 0Y9 (Cereno); Petrik Veterinary Consultants, Cambridge, Ontario (Petrik); Econse Water Purification Systems Inc., 120 Nebo Road, Unit #4, Hamilton, Ontario L8W 2E4 (Davy); Translational and Molecular Medicine, Faculty of Medicine, University of Ottawa, 75 Laurier Avenue East, Ottawa, Ontario K1N 6N5 (Mahdi); Balsillie School of International Affairs, Wilfrid Laurier University, Waterloo, Ontario N2L 6C2 (Gilliam); Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1 (Rivers)
| | - Negin Esfandiari
- Novometrix Research Inc., 4564 Nassagaweya-Puslinch TL, Moffat, Ontario L0P 1J0 (Wilson, Esfandiari, Aramini, Hunt); Canadian Food Inspection Agency (CFIA-ACIA), 59 Camelot Drive, Ottawa, Ontario K1A 0Y9 (Cereno); Petrik Veterinary Consultants, Cambridge, Ontario (Petrik); Econse Water Purification Systems Inc., 120 Nebo Road, Unit #4, Hamilton, Ontario L8W 2E4 (Davy); Translational and Molecular Medicine, Faculty of Medicine, University of Ottawa, 75 Laurier Avenue East, Ottawa, Ontario K1N 6N5 (Mahdi); Balsillie School of International Affairs, Wilfrid Laurier University, Waterloo, Ontario N2L 6C2 (Gilliam); Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1 (Rivers)
| | - Derek Davy
- Novometrix Research Inc., 4564 Nassagaweya-Puslinch TL, Moffat, Ontario L0P 1J0 (Wilson, Esfandiari, Aramini, Hunt); Canadian Food Inspection Agency (CFIA-ACIA), 59 Camelot Drive, Ottawa, Ontario K1A 0Y9 (Cereno); Petrik Veterinary Consultants, Cambridge, Ontario (Petrik); Econse Water Purification Systems Inc., 120 Nebo Road, Unit #4, Hamilton, Ontario L8W 2E4 (Davy); Translational and Molecular Medicine, Faculty of Medicine, University of Ottawa, 75 Laurier Avenue East, Ottawa, Ontario K1N 6N5 (Mahdi); Balsillie School of International Affairs, Wilfrid Laurier University, Waterloo, Ontario N2L 6C2 (Gilliam); Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1 (Rivers)
| | - Aaya Mahdi
- Novometrix Research Inc., 4564 Nassagaweya-Puslinch TL, Moffat, Ontario L0P 1J0 (Wilson, Esfandiari, Aramini, Hunt); Canadian Food Inspection Agency (CFIA-ACIA), 59 Camelot Drive, Ottawa, Ontario K1A 0Y9 (Cereno); Petrik Veterinary Consultants, Cambridge, Ontario (Petrik); Econse Water Purification Systems Inc., 120 Nebo Road, Unit #4, Hamilton, Ontario L8W 2E4 (Davy); Translational and Molecular Medicine, Faculty of Medicine, University of Ottawa, 75 Laurier Avenue East, Ottawa, Ontario K1N 6N5 (Mahdi); Balsillie School of International Affairs, Wilfrid Laurier University, Waterloo, Ontario N2L 6C2 (Gilliam); Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1 (Rivers)
| | - Jeff Aramini
- Novometrix Research Inc., 4564 Nassagaweya-Puslinch TL, Moffat, Ontario L0P 1J0 (Wilson, Esfandiari, Aramini, Hunt); Canadian Food Inspection Agency (CFIA-ACIA), 59 Camelot Drive, Ottawa, Ontario K1A 0Y9 (Cereno); Petrik Veterinary Consultants, Cambridge, Ontario (Petrik); Econse Water Purification Systems Inc., 120 Nebo Road, Unit #4, Hamilton, Ontario L8W 2E4 (Davy); Translational and Molecular Medicine, Faculty of Medicine, University of Ottawa, 75 Laurier Avenue East, Ottawa, Ontario K1N 6N5 (Mahdi); Balsillie School of International Affairs, Wilfrid Laurier University, Waterloo, Ontario N2L 6C2 (Gilliam); Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1 (Rivers)
| | - William Joseph Gilliam
- Novometrix Research Inc., 4564 Nassagaweya-Puslinch TL, Moffat, Ontario L0P 1J0 (Wilson, Esfandiari, Aramini, Hunt); Canadian Food Inspection Agency (CFIA-ACIA), 59 Camelot Drive, Ottawa, Ontario K1A 0Y9 (Cereno); Petrik Veterinary Consultants, Cambridge, Ontario (Petrik); Econse Water Purification Systems Inc., 120 Nebo Road, Unit #4, Hamilton, Ontario L8W 2E4 (Davy); Translational and Molecular Medicine, Faculty of Medicine, University of Ottawa, 75 Laurier Avenue East, Ottawa, Ontario K1N 6N5 (Mahdi); Balsillie School of International Affairs, Wilfrid Laurier University, Waterloo, Ontario N2L 6C2 (Gilliam); Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1 (Rivers)
| | - Treasure Hunt
- Novometrix Research Inc., 4564 Nassagaweya-Puslinch TL, Moffat, Ontario L0P 1J0 (Wilson, Esfandiari, Aramini, Hunt); Canadian Food Inspection Agency (CFIA-ACIA), 59 Camelot Drive, Ottawa, Ontario K1A 0Y9 (Cereno); Petrik Veterinary Consultants, Cambridge, Ontario (Petrik); Econse Water Purification Systems Inc., 120 Nebo Road, Unit #4, Hamilton, Ontario L8W 2E4 (Davy); Translational and Molecular Medicine, Faculty of Medicine, University of Ottawa, 75 Laurier Avenue East, Ottawa, Ontario K1N 6N5 (Mahdi); Balsillie School of International Affairs, Wilfrid Laurier University, Waterloo, Ontario N2L 6C2 (Gilliam); Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1 (Rivers)
| | - Jocelyn Rivers
- Novometrix Research Inc., 4564 Nassagaweya-Puslinch TL, Moffat, Ontario L0P 1J0 (Wilson, Esfandiari, Aramini, Hunt); Canadian Food Inspection Agency (CFIA-ACIA), 59 Camelot Drive, Ottawa, Ontario K1A 0Y9 (Cereno); Petrik Veterinary Consultants, Cambridge, Ontario (Petrik); Econse Water Purification Systems Inc., 120 Nebo Road, Unit #4, Hamilton, Ontario L8W 2E4 (Davy); Translational and Molecular Medicine, Faculty of Medicine, University of Ottawa, 75 Laurier Avenue East, Ottawa, Ontario K1N 6N5 (Mahdi); Balsillie School of International Affairs, Wilfrid Laurier University, Waterloo, Ontario N2L 6C2 (Gilliam); Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1 (Rivers)
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Boni MF. Breaking the cycle of malaria treatment failure. FRONTIERS IN EPIDEMIOLOGY 2022; 2:1041896. [PMID: 38455307 PMCID: PMC10910953 DOI: 10.3389/fepid.2022.1041896] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Accepted: 11/28/2022] [Indexed: 03/09/2024]
Abstract
Treatment of symptomatic malaria became a routine component of the clinical and public health response to malaria after the second world war. However, all antimalarial drugs deployed against malaria eventually generated enough drug resistance that they had to be removed from use. Chloroquine, sulfadoxine-pyrimethamine, and mefloquine are well known examples of antimalarial drugs to which resistance did and still does ready evolve. Artemisinin-based combination therapies (ACTs) are currently facing the same challenge as artemisinin resistance is widespread in Southeast Asia and emerging in Africa. Here, I review some aspects of drug-resistance management in malaria that influence the strength of selective pressure on drug-resistant malaria parasites, as well as an approach we can take in the future to avoid repeating the common mistake of deploying a new drug and waiting for drug resistance and treatment failure to arrive. A desirable goal of drug-resistance management is to reduce selection pressure without reducing the overall percentage of patients that are treated. This can be achieved by distributing multiple first-line therapies (MFT) simultaneously in the population for the treatment of uncomplicated falciparum malaria, thereby keeping treatment levels high but the overall selection pressure exerted by each individual therapy low. I review the primary reasons that make MFT a preferred resistance management option in many malaria-endemic settings, and I describe two exceptions where caution and additional analyses may be warranted before deploying MFT. MFT has shown to be feasible in practice in many endemic settings. The continual improvement and increased coverage of genomic surveillance in malaria may allow countries to implement custom MFT strategies based on their current drug-resistance profiles.
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Affiliation(s)
- Maciej F. Boni
- Department of Biology, Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, United States
- Nuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, United Kingdom
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Chebil D, Ben Hassine D, Melki S, Nouira S, Kammoun Rebai W, Hannachi H, Merzougui L, Ben Abdelaziz A. Place of distancing measures in containing epidemics: a scoping review. Libyan J Med 2022; 17:2140473. [PMID: 36325628 PMCID: PMC9639554 DOI: 10.1080/19932820.2022.2140473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 10/22/2022] [Indexed: 11/06/2022] Open
Abstract
Distancing is one of the barrier measures in mitigating epidemics. We aimed to investigate the typology, effectiveness, and side effects of distancing rules during epidemics. Electronic searches were conducted on MEDLINE, PubMed in April 2020, using Mesh-Terms representing various forms of distancing ('social isolation', 'social distancing', 'quarantine') combining with 'epidemics'. PRISMA-ScR statement was consulted to report this review. A total of 314 titles were identified and 93 were finally included. 2009 influenza A and SARS-CoV-2 epidemics were the most studied. Distancing measures were mostly classified as case-based and community-based interventions. The combination of distancing rules, like school closure, home working, isolation and quarantine, has proven to be effective in reducing R0 and flattening the epidemic curve, also when initiated early at a high rate and combined with other non-pharmaceutical interventions. Epidemiological and modeling studies showed that Isolation and quarantine in the 2009 Influenza pandemic were effective measures to decrease attack rate also with high level of compliance but there was an increased risk of household transmission. lockdown was also effective to reduce R0 from 2.6 to 0.6 and to increase doubling time from 2 to 4 days in the covid-19 pandemic. The evidence for school closure and workplace distancing was moderate as single intervention. Psychological disorder, unhealthy behaviors, disruption of economic activities, social discrimination, and stigmatization were the main side effects of distancing measures. Earlier implementation of combined distancing measures leads to greater effectiveness in containing outbreaks. Their indication must be relevant and based on evidence to avoid adverse effects on the community. These results would help decision-makers to develop response plans based on the required experience and strengthen the capacity of countries to fight against future epidemics. Mesh words: Physical Distancing, Quarantine, Epidemics, Public Health, Scoping Review.
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Affiliation(s)
- Dhekra Chebil
- Infection Prevention Control Department, Ibn Al Jazzar University Hospital, Kairouan, Tunisia
- Research Laboratory, LR19SP01, Sousse, Tunisia
- Faculty of medicine of Sousse, University of Sousse, Sousse, Tunisia
| | - Donia Ben Hassine
- Research Laboratory, LR19SP01, Sousse, Tunisia
- Information System Direction (DSI), Sahloul University Hospital, Sousse, Tunisia
| | - Sarra Melki
- Research Laboratory, LR19SP01, Sousse, Tunisia
- Information System Direction (DSI), Sahloul University Hospital, Sousse, Tunisia
| | - Sarra Nouira
- Research Laboratory, LR19SP01, Sousse, Tunisia
- Information System Direction (DSI), Sahloul University Hospital, Sousse, Tunisia
| | - Wafa Kammoun Rebai
- Regional Training Center supported by WHO-TDR for East Mediterranean Region (EMR), Pasteur Institute of Tunis, Tunisia
| | - Hajer Hannachi
- Infection Prevention Control Department, Ibn Al Jazzar University Hospital, Kairouan, Tunisia
- Faculty of medicine of Sousse, University of Sousse, Sousse, Tunisia
| | - Latifa Merzougui
- Infection Prevention Control Department, Ibn Al Jazzar University Hospital, Kairouan, Tunisia
- Faculty of medicine of Sousse, University of Sousse, Sousse, Tunisia
| | - Ahmed Ben Abdelaziz
- Research Laboratory, LR19SP01, Sousse, Tunisia
- Faculty of medicine of Sousse, University of Sousse, Sousse, Tunisia
- Information System Direction (DSI), Sahloul University Hospital, Sousse, Tunisia
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Cooney DB, Mori Y. Long-time behavior of a PDE replicator equation for multilevel selection in group-structured populations. J Math Biol 2022; 85:12. [PMID: 35864421 DOI: 10.1007/s00285-022-01776-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 03/11/2022] [Accepted: 05/04/2022] [Indexed: 11/26/2022]
Abstract
In many biological systems, natural selection acts simultaneously on multiple levels of organization. This scenario typically presents an evolutionary conflict between the incentive of individuals to cheat and the collective incentive to establish cooperation within a group. Generalizing previous work on multilevel selection in evolutionary game theory, we consider a hyperbolic PDE model of a group-structured population, in which members within a single group compete with each other for individual-level replication; while the group also competes against other groups for group-level replication. We derive a threshold level of the relative strength of between-group competition such that defectors take over the population below the threshold while cooperation persists in the long-time population above the threshold. Under stronger assumptions on the initial distribution of group compositions, we further prove that the population converges to a steady state density supporting cooperation for between-group selection strength above the threshold. We further establish long-time bounds on the time-average of the collective payoff of the population, showing that the long-run population cannot outperform the payoff of a full-cooperator group even in the limit of infinitely-strong between-group competition. When the group replication rate is maximized by an intermediate level of within-group cooperation, individual-level selection casts a long shadow on the dynamics of multilevel selection: no level of between-group competition can erase the effects of the individual incentive to defect. We further extend our model to study the case of multiple types of groups, showing how the games that groups play can coevolve with the level of cooperation.
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Affiliation(s)
- Daniel B Cooney
- Department of Mathematics and Center for Mathematical Biology, University of Pennsylvania, Philadelphia, PA, USA.
| | - Yoichiro Mori
- Department of Mathematics, Department of Biology, and Center for Mathematical Biology, University of Pennsylvania, Philadelphia, PA, USA
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Spira B. The Impact of the Highly Virulent SARS-CoV-2 Gamma Variant on Young Adults in the State of São Paulo: Was It Inevitable? Cureus 2022; 14:e26486. [PMID: 35919213 PMCID: PMC9339207 DOI: 10.7759/cureus.26486] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/30/2022] [Indexed: 11/21/2022] Open
Abstract
Background The coronavirus disease 2019 (COVID-19) pandemic had and is still having a tremendous impact on people all over the world, but it has been particularly harsh in South America. Nine out of 13 South American countries are among the 50 countries with the highest COVID-19 death rates. The gamma severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant that emerged by the end of 2020 in the Brazilian Amazon quickly spread throughout the country causing the harsh COVID-19 second wave. This variant displayed high viral loads, high transmissibility, and increased virulence as compared to previous variants. Aims The aim of this retrospective study is to revisit and analyse the epidemiology of the COVID-19 second wave in the state of São Paulo, the most populous Brazilian state. In addition to examining the possible factors that led to the emergence and propagation of the gamma variant, measures that could have prevented its spread and that of other highly virulent variants were also investigated. Materials and methods Data from São Paulo's official sources on morbidity, mortality, age distribution, and testing prior to and during the COVID-19 second wave (February - June 2021) and data regarding the distribution of SARS-CoV-2 variants in the country were parsed, analyzed, and compared to the period that anteceded the eruption of the second COVID-19 wave. Results In the state of São Paulo, the toll of the COVID-19 second wave surpassed that of the first 11 months of the pandemic (from March 2020 to January 2021), as 56% of the deaths occurred in the five months of the second wave between February and June 2021. The mean age of COVID-19 victims, which was already below life expectancy in the state dropped even further in the pandemic's second wave, reaching an average of 60 years of age. The years of life lost per death per month doubled and the case-fatality rate (CFR) of young adults (20-39 years old) more than trebled during this period. A number of hypotheses have been raised that might explain the emergence and spread of the gamma variant and the measures that could have been taken to prevent it and minimise its impact on the population. Conclusions Over 142,000 people died as a result of the SARS-CoV-2 gamma variant sweep in São Paulo in the first semester of 2021. Due to its high viral load, the gamma variant displayed high transmissibility and a high degree of virulence resulting in increased case fatality rates across most age tiers. Notably, this second wave was marked by a very significant increase in deaths among young adults. This increase was at least partially due to a deterioration in general health provoked by non-pharmaceutical interventions. In hindsight, a safer and more effective measure might have been to allow the free spread of the virus among the young and healthy in the first wave, thus conferring immunity against more virulent variants that emerged later on.
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Tran TNA, Wikle NB, Yang F, Inam H, Leighow S, Gentilesco B, Chan P, Albert E, Strong ER, Pritchard JR, Hanage WP, Hanks EM, Crawford FW, Boni MF. SARS-CoV-2 Attack Rate and Population Immunity in Southern New England, March 2020 to May 2021. JAMA Netw Open 2022; 5:e2214171. [PMID: 35616938 PMCID: PMC9136627 DOI: 10.1001/jamanetworkopen.2022.14171] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 04/09/2022] [Indexed: 12/15/2022] Open
Abstract
Importance In emergency epidemic and pandemic settings, public health agencies need to be able to measure the population-level attack rate, defined as the total percentage of the population infected thus far. During vaccination campaigns in such settings, public health agencies need to be able to assess how much the vaccination campaign is contributing to population immunity; specifically, the proportion of vaccines being administered to individuals who are already seropositive must be estimated. Objective To estimate population-level immunity to SARS-CoV-2 through May 31, 2021, in Rhode Island, Massachusetts, and Connecticut. Design, Setting, and Participants This observational case series assessed cases, hospitalizations, intensive care unit occupancy, ventilator occupancy, and deaths from March 1, 2020, to May 31, 2021, in Rhode Island, Massachusetts, and Connecticut. Data were analyzed from July 2021 to November 2021. Exposures COVID-19-positive test result reported to state department of health. Main Outcomes and Measures The main outcomes were statistical estimates, from a bayesian inference framework, of the percentage of individuals as of May 31, 2021, who were (1) previously infected and vaccinated, (2) previously uninfected and vaccinated, and (3) previously infected but not vaccinated. Results At the state level, there were a total of 1 160 435 confirmed COVID-19 cases in Rhode Island, Massachusetts, and Connecticut. The median age among individuals with confirmed COVID-19 was 38 years. In autumn 2020, SARS-CoV-2 population immunity (equal to the attack rate at that point) in these states was less than 15%, setting the stage for a large epidemic wave during winter 2020 to 2021. Population immunity estimates for May 31, 2021, were 73.4% (95% credible interval [CrI], 72.9%-74.1%) for Rhode Island, 64.1% (95% CrI, 64.0%-64.4%) for Connecticut, and 66.3% (95% CrI, 65.9%-66.9%) for Massachusetts, indicating that more than 33% of residents in these states were fully susceptible to infection when the Delta variant began spreading in July 2021. Despite high vaccine coverage in these states, population immunity in summer 2021 was lower than planned owing to an estimated 34.1% (95% CrI, 32.9%-35.2%) of vaccines in Rhode Island, 24.6% (95% CrI, 24.3%-25.1%) of vaccines in Connecticut, and 27.6% (95% CrI, 26.8%-28.6%) of vaccines in Massachusetts being distributed to individuals who were already seropositive. Conclusions and Relevance These findings suggest that future emergency-setting vaccination planning may have to prioritize high vaccine coverage over optimized vaccine distribution to ensure that sufficient levels of population immunity are reached during the course of an ongoing epidemic or pandemic.
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Affiliation(s)
- Thu Nguyen-Anh Tran
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park
| | - Nathan B. Wikle
- Center for Infectious Disease Dynamics, Department of Statistics, Pennsylvania State University, University Park
| | - Fuhan Yang
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park
| | - Haider Inam
- Center for Infectious Disease Dynamics, Department of Bioengineering, Pennsylvania State University, University Park
| | - Scott Leighow
- Center for Infectious Disease Dynamics, Department of Bioengineering, Pennsylvania State University, University Park
| | | | - Philip Chan
- Department of Medicine, Brown University, Providence, Rhode Island
| | - Emmy Albert
- Department of Physics, Pennsylvania State University, University Park
| | - Emily R. Strong
- Center for Infectious Disease Dynamics, Department of Statistics, Pennsylvania State University, University Park
| | - Justin R. Pritchard
- Center for Infectious Disease Dynamics, Department of Bioengineering, Pennsylvania State University, University Park
| | - William P. Hanage
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Ephraim M. Hanks
- Center for Infectious Disease Dynamics, Department of Statistics, Pennsylvania State University, University Park
| | - Forrest W. Crawford
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
- Department of Statistics and Data Science, Yale University, New Haven, Connecticut
| | - Maciej F. Boni
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park
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Tran TNA, Wikle NB, Yang F, Inam H, Leighow S, Gentilesco B, Chan P, Albert E, Strong ER, Pritchard JR, Hanage WP, Hanks EM, Crawford FW, Boni MF. SARS-CoV-2 attack rate and population immunity in southern New England, March 2020 - May 2021. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.12.06.21267375. [PMID: 34909789 PMCID: PMC8669856 DOI: 10.1101/2021.12.06.21267375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Estimating an infectious disease attack rate requires inference on the number of reported symptomatic cases of a disease, the number of unreported symptomatic cases, and the number of asymptomatic infections. Population-level immunity can then be estimated as the attack rate plus the number of vaccine recipients who had not been previously infected; this requires an estimate of the fraction of vaccines that were distributed to seropositive individuals. To estimate attack rates and population immunity in southern New England, we fit a validated dynamic epidemiological model to case, clinical, and death data streams reported by Rhode Island, Massachusetts, and Connecticut for the first 15 months of the COVID-19 pandemic, from March 1 2020 to May 31 2021. This period includes the initial spring 2020 wave, the major winter wave of 2020-2021, and the lagging wave of lineage B.1.1.7(Alpha) infections during March-April 2021. In autumn 2020, SARS-CoV-2 population immunity (equal to the attack rate at that point) in southern New England was still below 15%, setting the stage for a large winter wave. After the roll-out of vaccines in early 2021, population immunity in many states was expected to approach 70% by spring 2021, with more than half of this immune population coming from vaccinations. Our population immunity estimates for May 31 2021 are 73.4% (95% CrI: 72.9% - 74.1%) for Rhode Island, 64.1% (95% CrI: 64.0% - 64.4%) for Connecticut, and 66.3% (95% CrI: 65.9% - 66.9%) for Massachusetts, indicating that >33% of southern Englanders were still susceptible to infection when the Delta variant began spreading in July 2021. Despite high vaccine coverage in these states, population immunity in summer 2021 was lower than planned due to 34% (Rhode Island), 25% (Connecticut), and 28% (Massachusetts) of vaccine distribution going to seropositive individuals. Future emergency-setting vaccination planning will likely have to consider over-vaccination as a strategy to ensure that high levels of population immunity are reached during the course of an ongoing epidemic.
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Affiliation(s)
- Thu Nguyen-Anh Tran
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA
| | - Nathan B Wikle
- Center for Infectious Disease Dynamics, Department of Statistics, Pennsylvania State University, University Park, PA
| | - Fuhan Yang
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA
| | - Haider Inam
- Center for Infectious Disease Dynamics, Department of Bioengineering, Pennsylvania State University, University Park, PA
| | - Scott Leighow
- Center for Infectious Disease Dynamics, Department of Bioengineering, Pennsylvania State University, University Park, PA
| | | | - Philip Chan
- Department of Medicine, Brown University, Providence, RI
| | - Emmy Albert
- Department of Physics, Pennsylvania State University, University Park, PA
| | - Emily R Strong
- Center for Infectious Disease Dynamics, Department of Statistics, Pennsylvania State University, University Park, PA
| | - Justin R Pritchard
- Center for Infectious Disease Dynamics, Department of Bioengineering, Pennsylvania State University, University Park, PA
| | - William P Hanage
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Ephraim M Hanks
- Center for Infectious Disease Dynamics, Department of Statistics, Pennsylvania State University, University Park, PA
| | - Forrest W Crawford
- Department of Biostatistics, Yale Schools of Public Health, Yale University, New Haven, CT
- Department of Biostatistics, Yale Schools of Public Health, Yale University, New Haven, CT
| | - Maciej F Boni
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA
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MacLean OA, Lytras S, Weaver S, Singer JB, Boni MF, Lemey P, Kosakovsky Pond SL, Robertson DL. Natural selection in the evolution of SARS-CoV-2 in bats created a generalist virus and highly capable human pathogen. PLoS Biol 2021; 19:e3001115. [PMID: 33711012 PMCID: PMC7990310 DOI: 10.1371/journal.pbio.3001115] [Citation(s) in RCA: 126] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 03/24/2021] [Accepted: 01/25/2021] [Indexed: 02/08/2023] Open
Abstract
Virus host shifts are generally associated with novel adaptations to exploit the cells of the new host species optimally. Surprisingly, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has apparently required little to no significant adaptation to humans since the start of the Coronavirus Disease 2019 (COVID-19) pandemic and to October 2020. Here we assess the types of natural selection taking place in Sarbecoviruses in horseshoe bats versus the early SARS-CoV-2 evolution in humans. While there is moderate evidence of diversifying positive selection in SARS-CoV-2 in humans, it is limited to the early phase of the pandemic, and purifying selection is much weaker in SARS-CoV-2 than in related bat Sarbecoviruses. In contrast, our analysis detects evidence for significant positive episodic diversifying selection acting at the base of the bat virus lineage SARS-CoV-2 emerged from, accompanied by an adaptive depletion in CpG composition presumed to be linked to the action of antiviral mechanisms in these ancestral bat hosts. The closest bat virus to SARS-CoV-2, RmYN02 (sharing an ancestor about 1976), is a recombinant with a structure that includes differential CpG content in Spike; clear evidence of coinfection and evolution in bats without involvement of other species. While an undiscovered "facilitating" intermediate species cannot be discounted, collectively, our results support the progenitor of SARS-CoV-2 being capable of efficient human-human transmission as a consequence of its adaptive evolutionary history in bats, not humans, which created a relatively generalist virus.
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Affiliation(s)
- Oscar A. MacLean
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Spyros Lytras
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Steven Weaver
- Temple University, Institute for Genomics and Evolutionary Medicine, Philadelphia, Pennsylvania, United States of America
| | - Joshua B. Singer
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Maciej F. Boni
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Sergei L. Kosakovsky Pond
- Temple University, Institute for Genomics and Evolutionary Medicine, Philadelphia, Pennsylvania, United States of America
| | - David L. Robertson
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
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9
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Spanakis N, Kassela K, Dovrolis N, Bampali M, Gatzidou E, Kafasi A, Froukala E, Stavropoulou A, Lilakos K, Veletza S, Tsiodras S, Tsakris A, Karakasiliotis I. A main event and multiple introductions of SARS-CoV-2 initiated the COVID-19 epidemic in Greece. J Med Virol 2021; 93:2899-2907. [PMID: 33410223 DOI: 10.1002/jmv.26778] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 12/23/2020] [Accepted: 12/29/2020] [Indexed: 12/19/2022]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Chains of infections starting from various countries worldwide seeded the outbreak of COVID-19 in Athens, capital city of Greece. A full-genome analysis of isolates from Athens' hospitals and other healthcare providers revealed the variety of SARS-CoV-2 that initiated the pandemic before lockdown and passenger flight restrictions. A dominant variant, encompassing the G614D amino acid substitution, spread through a major virus dispersal event, and sporadic introductions of rare variants characterized the local initiation of the epidemic. Mutations within the genome highlighted the genetic drift of the virus as rare variants emerged. An important variant contained a premature stop codon in orf7a leading to the truncation of a possibly important for viral pathogenesis domain. This study may serve as a reference for resolving future lines of infection in the area, especially after resumption of passenger flight connections to Athens and Greece during summer of 2020.
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Affiliation(s)
- Nikolaos Spanakis
- Laboratory of Microbiology, Medical School, National and Kapodistrian University, Athens, Greece
| | - Katerina Kassela
- Laboratory of Biology, Department of Medicine, Democritus University of Thrace, Alexandroupolis, Greece
| | - Nikolas Dovrolis
- Laboratory of Biology, Department of Medicine, Democritus University of Thrace, Alexandroupolis, Greece
| | - Maria Bampali
- Laboratory of Biology, Department of Medicine, Democritus University of Thrace, Alexandroupolis, Greece
| | - Elisavet Gatzidou
- Laboratory of Biology, Department of Medicine, Democritus University of Thrace, Alexandroupolis, Greece
| | - Athanasia Kafasi
- Laboratory of Microbiology, Medical School, National and Kapodistrian University, Athens, Greece
| | - Elisavet Froukala
- Laboratory of Microbiology, Medical School, National and Kapodistrian University, Athens, Greece
| | - Anastasia Stavropoulou
- Laboratory of Microbiology, Medical School, National and Kapodistrian University, Athens, Greece
| | - Konstantinos Lilakos
- ANTISEL SA and Haematology Clinic, Medical School, National and Kapodistrian University, Athens, Greece
| | - Stavroula Veletza
- Laboratory of Biology, Department of Medicine, Democritus University of Thrace, Alexandroupolis, Greece
| | - Sotirios Tsiodras
- 4th Department of Internal Medicine, Medical School, National and Kapodistrian University, Athens, Greece
| | - Athanasios Tsakris
- Laboratory of Microbiology, Medical School, National and Kapodistrian University, Athens, Greece
| | - Ioannis Karakasiliotis
- Laboratory of Biology, Department of Medicine, Democritus University of Thrace, Alexandroupolis, Greece
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10
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Eccles R. Why is temperature sensitivity important for the success of common respiratory viruses? Rev Med Virol 2020; 31:1-8. [PMID: 32776651 PMCID: PMC7435572 DOI: 10.1002/rmv.2153] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 07/22/2020] [Accepted: 07/22/2020] [Indexed: 01/01/2023]
Abstract
This review explores the idea that temperature sensitivity is an important factor in determining the success of respiratory viruses as human parasites. The review discusses several questions. What is viral temperature sensitivity? At what range of temperatures are common respiratory viruses sensitive? What is the mechanism for their temperature sensitivity? What is the range of temperature along the human airway? What is it that makes respiratory viruses such successful parasites of the human airway? What is the role of temperature sensitivity in respiratory zoonoses? A definition of temperature sensitivity is proposed, as “the property of a virus to replicate poorly or not at all, at the normal body temperature of the host (restrictive temperature), but to replicate well at the lower temperatures found in the upper airway of the host (permissive temperature).” Temperature sensitivity may influence the success of a respiratory virus in several ways. Firstly; by restricting the infection to the upper airways and reducing the chance of systemic infection that may reduce host mobility and increase mortality, and thus limit the spread of the virus. Secondly; by causing a mild upper airway illness with a limited immune response compared to systemic infection, which means that persistent herd immunity does not develop to the same extent as with systemic infections, and re‐infection may occur later. Thirdly; infection of the upper airway triggers local reflex rhinorrhea, coughing and sneezing which aid the exit of the virus from the host and the spread of infection in the community.
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Affiliation(s)
- Ronald Eccles
- Emeritus Professor, Cardiff School of Biosciences, Cardiff University, UK
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11
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MacLean OA, Lytras S, Weaver S, Singer JB, Boni MF, Lemey P, Kosakovsky Pond SL, Robertson DL. Natural selection in the evolution of SARS-CoV-2 in bats, not humans, created a highly capable human pathogen. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020. [PMID: 32577659 DOI: 10.1101/2020.05.28.122366] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
RNA viruses are proficient at switching host species, and evolving adaptations to exploit the new host's cells efficiently. Surprisingly, SARS-CoV-2 has apparently required no significant adaptation to humans since the start of the COVID-19 pandemic, with no observed selective sweeps since genome sampling began. Here we assess the types of natural selection taking place in Sarbecoviruses in horseshoe bats versus SARS-CoV-2 evolution in humans. While there is moderate evidence of diversifying positive selection in SARS-CoV-2 in humans, it is limited to the early phase of the pandemic, and purifying selection is much weaker in SARS-CoV-2 than in related bat Sarbecoviruses . In contrast, our analysis detects significant positive episodic diversifying selection acting on the bat virus lineage SARS-CoV-2 emerged from, accompanied by an adaptive depletion in CpG composition presumed to be linked to the action of antiviral mechanisms in ancestral hosts. The closest bat virus to SARS-CoV-2, RmYN02 (sharing an ancestor ∼1976), is a recombinant with a structure that includes differential CpG content in Spike; clear evidence of coinfection and evolution in bats without involvement of other species. Collectively our results demonstrate the progenitor of SARS-CoV-2 was capable of near immediate human-human transmission as a consequence of its adaptive evolutionary history in bats, not humans.
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12
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Hunter P. The spread of the COVID-19 coronavirus: Health agencies worldwide prepare for the seemingly inevitability of the COVID-19 coronavirus becoming endemic. EMBO Rep 2020; 21:e50334. [PMID: 32181577 PMCID: PMC7132190 DOI: 10.15252/embr.202050334] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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13
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Delabouglise A, Nguyen-Van-Yen B, Thanh NTL, Xuyen HTA, Tuyet PN, Lam HM, Boni MF. Poultry population dynamics and mortality risks in smallholder farms of the Mekong river delta region. BMC Vet Res 2019; 15:205. [PMID: 31208467 PMCID: PMC6580564 DOI: 10.1186/s12917-019-1949-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Accepted: 06/04/2019] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Poultry farming is widely practiced by rural households in Vietnam and the vast majority of domestic birds are kept on small household farms. However, smallholder poultry production is constrained by several issues such as infectious diseases, including avian influenza viruses whose circulation remains a threat to public health. This observational study describes the demographic structure and dynamics of small-scale poultry farms of the Mekong river delta region. METHOD Fifty three farms were monitored over a 20-month period, with farm sizes, species, age, arrival/departure of poultry, and farm management practices recorded monthly. RESULTS Median flock population sizes were 16 for chickens (IQR: 10-40), 32 for ducks (IQR: 18-101) and 11 for Muscovy ducks (IQR: 7-18); farm size distributions for the three species were heavily right-skewed. Muscovy ducks were kept for long periods and outdoors, while chickens and ducks were farmed indoors or in pens. Ducks had a markedly higher removal rate (broilers: 0.14/week; layer/breeders: 0.05/week) than chickens and Muscovy ducks (broilers: 0.07/week; layer/breeders: 0.01-0.02/week) and a higher degree of specialization resulting in a substantially shorter life span. The rate of mortality due to disease did not differ much among species, with birds being less likely to die from disease at older ages, but frequency of disease symptoms differed by species. Time series of disease-associated mortality were correlated with population size for Muscovy ducks (Kendall's coefficient τ = 0.49, p-value < 0.01) and with frequency of outdoor grazing for ducks (τ = 0.33, p-value = 0.05). CONCLUSION The study highlights some challenges to disease control in small-scale multispecies poultry farms. The rate of interspecific contact and overlap between flocks of different ages is high, making small-scale farms a suitable environment for pathogens circulation. Muscovy ducks are farmed outdoors with little investment in biosecurity and few inter-farm movements. Ducks and chickens are more at-risk of introduction of pathogens through movements of birds from one farm to another. Ducks are farmed in large flocks with high turnover and, as a result, are more vulnerable to disease spread and require a higher vaccination coverage to maintain herd immunity.
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Affiliation(s)
- Alexis Delabouglise
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, Millenium Sciences Complex, Pollock road, University Park, PA, 16802, USA.
| | - Benjamin Nguyen-Van-Yen
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam.,École Normale Supérieure, CNRS UMR 8197, 46 rue d'Ulm, Paris, France
| | - Nguyen Thi Le Thanh
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
| | - Huynh Thi Ai Xuyen
- Ca Mau sub-Department of Livestock Production and Animal Health, Ca Mau, Vietnam
| | - Phung Ngoc Tuyet
- Ca Mau sub-Department of Livestock Production and Animal Health, Ca Mau, Vietnam
| | - Ha Minh Lam
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam.,Center for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Maciej F Boni
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, Millenium Sciences Complex, Pollock road, University Park, PA, 16802, USA.,Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam.,Center for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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14
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Wollacott AM, Boni MF, Szretter KJ, Sloan SE, Yousofshahi M, Viswanathan K, Bedard S, Hay CA, Smith PF, Shriver Z, Trevejo JM. Safety and Upper Respiratory Pharmacokinetics of the Hemagglutinin Stalk-Binding Antibody VIS410 Support Treatment and Prophylaxis Based on Population Modeling of Seasonal Influenza A Outbreaks. EBioMedicine 2016; 5:147-55. [PMID: 27077121 PMCID: PMC4816807 DOI: 10.1016/j.ebiom.2016.02.021] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Revised: 02/09/2016] [Accepted: 02/10/2016] [Indexed: 11/18/2022] Open
Abstract
Background Seasonal influenza is a major public health concern in vulnerable populations. Here we investigated the safety, tolerability, and pharmacokinetics of a broadly neutralizing monoclonal antibody (VIS410) against Influenza A in a Phase 1 clinical trial. Based on these results and preclinical data, we implemented a mathematical modeling approach to investigate whether VIS410 could be used prophylactically to lessen the burden of a seasonal influenza epidemic and to protect at-risk groups from associated complications. Methods Using a single-ascending dose study (n = 41) at dose levels from 2 mg/kg–50 mg/kg we evaluated the safety as well as the serum and upper respiratory pharmacokinetics of a broadly-neutralizing antibody (VIS410) against influenza A (ClinicalTrials.gov identifier NCT02045472). Our primary endpoints were safety and tolerability of VIS410 compared to placebo. We developed an epidemic microsimulation model testing the ability of VIS410 to mitigate attack rates and severe disease in at risk-populations. Findings VIS410 was found to be generally safe and well-tolerated at all dose levels, from 2–50 mg/kg. Overall, 27 of 41 subjects (65.9%) reported a total of 67 treatment emergent adverse events (TEAEs). TEAEs were reported by 20 of 30 subjects (66.7%) who received VIS410 and by 7 of 11 subjects (63.6%) who received placebo. 14 of 16 TEAEs related to study drug were considered mild (Grade 1) and 2 were moderate (Grade 2). Two subjects (1 subject who received 30 mg/kg VIS410 and 1 subject who received placebo) experienced serious AEs (Grade 3 or 4 TEAEs) that were not related to study drug. VIS410 exposure was approximately dose-proportional with a mean half-life of 12.9 days. Mean VIS410 Cmax levels in the upper respiratory tract were 20.0 and 25.3 μg/ml at the 30 mg/kg and 50 mg/kg doses, respectively, with corresponding serum Cmax levels of 980.5 and 1316 μg/mL. Using these pharmacokinetic data, a microsimulation model showed that median attack rate reductions ranged from 8.6% (interquartile range (IQR): 4.7%–11.0%) for 2% coverage to 22.6% (IQR: 12.7–30.0%) for 6% coverage. The overall benefits to the elderly, a vulnerable subgroup, are largest when VIS410 is distributed exclusively to elderly individuals, resulting in reductions in hospitalization rates between 11.4% (IQR: 8.2%–13.3%) for 2% coverage and 30.9% (IQR: 24.8%–35.1%) for 6% coverage among those more than 65 years of age. Interpretation VIS410 was generally safe and well tolerated and had good relative exposure in both serum and upper respiratory tract, supporting its use as either a single-dose therapeutic or prophylactic for influenza A. Including VIS410 prophylaxis among the public health interventions for seasonal influenza has the potential to lower attack rates and substantially reduce hospitalizations in individuals over the age of 65. Funding Visterra, Inc. VIS410, a broadly neutralizing monoclonal antibody, neutralizes seasonal strains of influenza A. VIS410 was found to be safe and well tolerated in a phase 1 clinical study. VIS410 drug levels in the upper respiratory tract support treatment and prophylaxis of influenza A. Epidemic modeling of VIS410 as a prophylactic therapy demonstrated substantial reduction of hospitalizations.
Influenza infection results in significant morbidity and mortality especially in high risk groups such as the elderly. VIS410 is a broadly neutralizing antibody engineered to bind the influenza A virus. VIS410 was shown to be safe and well tolerated in a phase 1 clinical trial in healthy adult volunteers. Measurements of drug levels of VIS410 in the upper respiratory tract demonstrated that protective levels were achieved at the site of infection. Epidemic modeling indicate that for an antibody such as VIS410 prophylactic administration to 4–6% of the population would be sufficient to substantially suppress hospitalizations related to severe influenza.
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Affiliation(s)
| | - Maciej F. Boni
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Viet Nam
- Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | | | - Susan E. Sloan
- Visterra Inc., One Kendall Square, Cambridge, MA 02139, USA
| | | | | | - Sylvain Bedard
- Visterra Inc., One Kendall Square, Cambridge, MA 02139, USA
| | | | | | | | - Jose M. Trevejo
- Visterra Inc., One Kendall Square, Cambridge, MA 02139, USA
- Corresponding author at: Visterra, Inc., One Kendall Square, Suite B3301, Building 300, 3rd Floor, Cambridge, MA 02139, USA.Visterra, Inc.One Kendall Square, Suite B3301, Building 300, 3rd FloorCambridgeMA02139USA
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15
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Boni MF, Galvani AP, Wickelgren AL, Malani A. Economic epidemiology of avian influenza on smallholder poultry farms. Theor Popul Biol 2013; 90:135-44. [PMID: 24161559 PMCID: PMC3851691 DOI: 10.1016/j.tpb.2013.10.001] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2013] [Revised: 08/03/2013] [Accepted: 10/08/2013] [Indexed: 11/01/2022]
Abstract
Highly pathogenic avian influenza (HPAI) is often controlled through culling of poultry. Compensating farmers for culled chickens or ducks facilitates effective culling and control of HPAI. However, ensuing price shifts can create incentives that alter the disease dynamics of HPAI. Farmers control certain aspects of the dynamics by setting a farm size, implementing infection control measures, and determining the age at which poultry are sent to market. Their decisions can be influenced by the market price of poultry which can, in turn, be set by policy makers during an HPAI outbreak. Here, we integrate these economic considerations into an epidemiological model in which epidemiological parameters are determined by an outside agent (the farmer) to maximize profit from poultry sales. Our model exhibits a diversity of behaviors which are sensitive to (i) the ability to identify infected poultry, (ii) the average price of infected poultry, (iii) the basic reproductive number of avian influenza, (iv) the effect of culling on the market price of poultry, (v) the effect of market price on farm size, and (vi) the effect of poultry density on disease transmission. We find that under certain market and epidemiological conditions, culling can increase farm size and the total number of HPAI infections. Our model helps to inform the optimization of public health outcomes that best weigh the balance between public health risk and beneficial economic outcomes for farmers.
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Affiliation(s)
- Maciej F Boni
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Viet Nam; Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK.
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16
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Pybus OG, Fraser C, Rambaut A. Evolutionary epidemiology: preparing for an age of genomic plenty. Philos Trans R Soc Lond B Biol Sci 2013; 368:20120193. [PMID: 23382418 DOI: 10.1098/rstb.2012.0193] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Affiliation(s)
- O G Pybus
- Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK.
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