1
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Murphy QM, Lewis GK, Sajadi MM, Forde JE, Ciupe SM. Understanding antibody magnitude and durability following vaccination against SARS-CoV-2. Math Biosci 2024; 376:109274. [PMID: 39218212 DOI: 10.1016/j.mbs.2024.109274] [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: 05/11/2024] [Revised: 07/14/2024] [Accepted: 08/05/2024] [Indexed: 09/04/2024]
Abstract
Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) results in transient antibody response against the spike protein. The individual immune status at the time of vaccination influences the response. Using mathematical models of antibody decay, we determined the dynamics of serum immunoglobulin G (IgG) and serum immunoglobulin A (IgA) over time. Data fitting to longitudinal IgG and IgA titers was used to quantify differences in antibody magnitude and antibody duration among infection-naïve and infection-positive vaccinees. We found that prior infections result in more durable serum IgG and serum IgA responses, with prior symptomatic infections resulting in the most durable serum IgG response and prior asymptomatic infections resulting in the most durable serum IgA response. These findings can guide vaccine boosting schedules.
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Affiliation(s)
- Quiyana M Murphy
- Department of Mathematics, Virginia Polytechnic Institute and State University, 225 Stanger Street, Blacksburg, 24060, VA, USA; Virginia Tech Center for the Mathematics of Biosystems, Virginia Tech, Blacksburg, VA, USA
| | - George K Lewis
- Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mohammad M Sajadi
- Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jonathan E Forde
- Department of Mathematics and Computer Sciences, Hobart and William Smith Colleges, Geneva, NY, USA
| | - Stanca M Ciupe
- Department of Mathematics, Virginia Polytechnic Institute and State University, 225 Stanger Street, Blacksburg, 24060, VA, USA; Virginia Tech Center for the Mathematics of Biosystems, Virginia Tech, Blacksburg, VA, USA.
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2
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Braeye T, Proesmans K, Van Cauteren D, Brondeel R, Hens N, Vermeiren E, Hammami N, Rosas A, Taame A, André E, Cuypers L. Personal characteristics and transmission dynamics associated with SARS-CoV-2 semi-quantitative PCR test results: an observational study from Belgium, 2021-2022. Front Public Health 2024; 12:1429021. [PMID: 39319296 PMCID: PMC11420023 DOI: 10.3389/fpubh.2024.1429021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Accepted: 08/20/2024] [Indexed: 09/26/2024] Open
Abstract
Introduction Following harmonization efforts by the Belgian National Reference Center for SARS-CoV-2, semi-quantitative PCR test (SQ-PCR) results, used as a proxy for viral load, were routinely collected after performing RT-qPCR tests. Methods We investigated both the personal characteristics associated with SQ-PCR results and the transmission dynamics involving these results. We used person-level laboratory test data and contact tracing data collected in Belgium from March 2021 to February 2022. Personal characteristics (age, sex, vaccination, and laboratory-confirmed prior infection) and disease stage by date of symptom onset were analyzed in relation to SQ-PCR results using logistic regression. Vaccine effectiveness (VE) against a high viral load (≥107 copies/mL) was estimated from the adjusted probabilities. Contact tracing involves the mandatory testing of high-risk exposure contacts (HREC) after contact with an index case. Odds ratios for test positivity and high viral load in HREC were calculated based on the SQ-PCR result of the index case using logistic regression models adjusted for age, sex, immunity status (vaccination, laboratory-confirmed prior infection), variant (Alpha, Delta, Omicron), calendar time, and contact tracing covariates. Results We included 909,157 SQ-PCR results of COVID-19 cases, 379,640 PCR results from index cases, and 72,052 SQ-PCR results of HREC. High viral load was observed more frequently among recent cases, symptomatic cases, cases over 25 years of age, and those not recently vaccinated (>90 days). The vaccine effectiveness (VE) of the primary schedule in the first 30 days after vaccination was estimated at 47.3% (95%CI 40.8-53.2) during the Delta variant period. A high viral load in index cases was associated with an increased test positivity in HREC (OR 2.7, 95%CI 2.62-2.79) and, among those testing positive, an increased likelihood of a high viral load (OR 2.84, 95%CI 2.53-3.19).
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Affiliation(s)
- Toon Braeye
- Epidemiology of Infectious Diseases, Sciensano, Brussels, Belgium
- I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Kristiaan Proesmans
- Faculty of Pharmaceutical Sciences, Department of Bio-analysis, Ghent University, Ghent, Belgium
| | | | - Ruben Brondeel
- Epidemiology of Infectious Diseases, Sciensano, Brussels, Belgium
| | - Niel Hens
- I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium
- Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Elias Vermeiren
- Epidemiology of Infectious Diseases, Sciensano, Brussels, Belgium
| | - Naïma Hammami
- Department of Care, Infection Prevention and Control, Flemish Community, Brussels, Belgium
| | - Angel Rosas
- Direction Surveillance des Maladies Infectieuses, Agence out une Vie de Qualité (AVIQ), Charleroi, Belgium
| | - Adrae Taame
- Cellule de médecine préventive- Direction santé et aide aux personnes – Vivalis/Cocom, Brussels, Belgium
| | - Emmanuel André
- Department of Laboratory Medicine, National Reference Centre for Respiratory Pathogens, University Hospitals Leuven, Leuven, Belgium
- Department of Microbiology, Immunology and Transplantation, Laboratory of Clinical Microbiology, KU Leuven, Leuven, Belgium
| | - Lize Cuypers
- Department of Laboratory Medicine, National Reference Centre for Respiratory Pathogens, University Hospitals Leuven, Leuven, Belgium
- Department of Microbiology, Immunology and Transplantation, Laboratory of Clinical Microbiology, KU Leuven, Leuven, Belgium
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3
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Bai H, Zhang X, Gong T, Ma J, Zhang P, Cai Z, Ren D, Zhang C. A systematic mutation analysis of 13 major SARS-CoV-2 variants. Virus Res 2024; 345:199392. [PMID: 38729218 PMCID: PMC11112362 DOI: 10.1016/j.virusres.2024.199392] [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: 12/24/2023] [Revised: 04/22/2024] [Accepted: 05/07/2024] [Indexed: 05/12/2024]
Abstract
SARS-CoV-2 evolves constantly with various novel mutations. Due to their enhanced infectivity, transmissibility and immune evasion, a comprehensive understanding of the association between these mutations and the respective functional changes is crucial. However, previous mutation studies of major SARS-CoV-2 variants remain limited. Here, we performed systematic analyses of full-length amino acids mutation, phylogenetic features, protein physicochemical properties, molecular dynamics and immune escape as well as pseudotype virus infection assays among thirteen major SARS-CoV-2 variants. We found that Omicron exhibited the most abundant and complex mutation sites, higher indices of hydrophobicity and flexibility than other variants. The results of molecular dynamics simulation suggest that Omicron has the highest number of hydrogen bonds and strongest binding free energy between the S protein and ACE2 receptor. Furthermore, we revealed 10 immune escape sites in 13 major variants, some of them were reported previously, but four of which (i.e. 339/373/477/496) are first reported to be specific to Omicron, whereas 462 is specific to Epslion. The infectivity of these variants was confirmed by the pseudotype virus infection assays. Our findings may help us understand the functional consequences of the mutations within various variants and the underlying mechanisms of the immune escapes conferred by the S proteins.
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Affiliation(s)
- Han Bai
- The MED-X Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Building 21, Western China Science and Technology Innovation Harbor, Xi'an 710000, China
| | - Xuan Zhang
- Center for Molecular Diagnosis and Precision Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 Dongyue Dadao, Nanchang 330209, China; Department of Clinical Laboratory, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Zhengjie, Nanchang 330006, China; Jiangxi Provincial Center for Advanced Diagnostic Technology and Precision Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 Dongyue Dadao, Nanchang 330209, China; Department of Medical Genetics, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 DongYue Dadao, Nanchang 330209, China
| | - Tian Gong
- Center for Molecular Diagnosis and Precision Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 Dongyue Dadao, Nanchang 330209, China; Department of Clinical Laboratory, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Zhengjie, Nanchang 330006, China; Jiangxi Provincial Center for Advanced Diagnostic Technology and Precision Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 Dongyue Dadao, Nanchang 330209, China; Department of Medical Genetics, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 DongYue Dadao, Nanchang 330209, China
| | - Junpeng Ma
- Center for Molecular Diagnosis and Precision Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 Dongyue Dadao, Nanchang 330209, China; Department of Clinical Laboratory, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Zhengjie, Nanchang 330006, China; Jiangxi Provincial Center for Advanced Diagnostic Technology and Precision Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 Dongyue Dadao, Nanchang 330209, China; Department of Medical Genetics, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 DongYue Dadao, Nanchang 330209, China
| | - Peng Zhang
- Center for Molecular Diagnosis and Precision Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 Dongyue Dadao, Nanchang 330209, China; Department of Clinical Laboratory, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Zhengjie, Nanchang 330006, China; Jiangxi Provincial Center for Advanced Diagnostic Technology and Precision Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 Dongyue Dadao, Nanchang 330209, China; Department of Medical Genetics, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 DongYue Dadao, Nanchang 330209, China
| | - Zeqiong Cai
- The MED-X Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Building 21, Western China Science and Technology Innovation Harbor, Xi'an 710000, China
| | - Doudou Ren
- The MED-X Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Building 21, Western China Science and Technology Innovation Harbor, Xi'an 710000, China
| | - Chengsheng Zhang
- The MED-X Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Building 21, Western China Science and Technology Innovation Harbor, Xi'an 710000, China; Center for Molecular Diagnosis and Precision Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 Dongyue Dadao, Nanchang 330209, China; Department of Clinical Laboratory, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Zhengjie, Nanchang 330006, China; Jiangxi Provincial Center for Advanced Diagnostic Technology and Precision Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 Dongyue Dadao, Nanchang 330209, China; Department of Medical Genetics, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 1519 DongYue Dadao, Nanchang 330209, China.
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4
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Parag KV, Thompson RN. Host behaviour driven by awareness of infection risk amplifies the chance of superspreading events. J R Soc Interface 2024; 21:20240325. [PMID: 39046766 PMCID: PMC11268441 DOI: 10.1098/rsif.2024.0325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 06/17/2024] [Accepted: 06/18/2024] [Indexed: 07/25/2024] Open
Abstract
We demonstrate that heterogeneity in the perceived risks associated with infection within host populations amplifies chances of superspreading during the crucial early stages of epidemics. Under this behavioural model, individuals less concerned about dangers from infection are more likely to be infected and attend larger sized (riskier) events, where we assume event sizes remain unchanged. For directly transmitted diseases such as COVID-19, this leads to infections being introduced at rates above the population prevalence to those events most conducive to superspreading. We develop an interpretable, computational framework for evaluating within-event risks and derive a small-scale reproduction number measuring how the infections generated at an event depend on transmission heterogeneities and numbers of introductions. This generalizes previous frameworks and quantifies how event-scale patterns and population-level characteristics relate. As event duration and size grow, our reproduction number converges to the basic reproduction number. We illustrate that even moderate levels of heterogeneity in the perceived risks of infection substantially increase the likelihood of disproportionately large clusters of infections occurring at larger events, despite fixed overall disease prevalence. We show why collecting data linking host behaviour and event attendance is essential for accurately assessing the risks posed by invading pathogens in emerging stages of outbreaks.
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Affiliation(s)
- Kris V. Parag
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
- NIHR HPRU in Behavioural Science and Evaluation, University of Bristol, Bristol, UK
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5
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Ciupe SM, Conway JM. Incorporating Intracellular Processes in Virus Dynamics Models. Microorganisms 2024; 12:900. [PMID: 38792730 PMCID: PMC11124127 DOI: 10.3390/microorganisms12050900] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2024] [Revised: 04/25/2024] [Accepted: 04/26/2024] [Indexed: 05/26/2024] Open
Abstract
In-host models have been essential for understanding the dynamics of virus infection inside an infected individual. When used together with biological data, they provide insight into viral life cycle, intracellular and cellular virus-host interactions, and the role, efficacy, and mode of action of therapeutics. In this review, we present the standard model of virus dynamics and highlight situations where added model complexity accounting for intracellular processes is needed. We present several examples from acute and chronic viral infections where such inclusion in explicit and implicit manner has led to improvement in parameter estimates, unification of conclusions, guidance for targeted therapeutics, and crossover among model systems. We also discuss trade-offs between model realism and predictive power and highlight the need of increased data collection at finer scale of resolution to better validate complex models.
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Affiliation(s)
- Stanca M. Ciupe
- Department of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060, USA
| | - Jessica M. Conway
- Department of Mathematics and Center for Infectious Disease Dynamics, Penn State University, State College, PA 16802, USA
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6
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Owens K, Esmaeili S, Schiffer JT. Heterogeneous SARS-CoV-2 kinetics due to variable timing and intensity of immune responses. JCI Insight 2024; 9:e176286. [PMID: 38573774 PMCID: PMC11141931 DOI: 10.1172/jci.insight.176286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 03/27/2024] [Indexed: 04/06/2024] Open
Abstract
The viral kinetics of documented SARS-CoV-2 infections exhibit a high degree of interindividual variability. We identified 6 distinct viral shedding patterns, which differed according to peak viral load, duration, expansion rate, and clearance rate, by clustering data from 768 infections in the National Basketball Association cohort. Omicron variant infections in previously vaccinated individuals generally led to lower cumulative shedding levels of SARS-CoV-2 than other scenarios. We then developed a mechanistic mathematical model that recapitulated 1,510 observed viral trajectories, including viral rebound and cases of reinfection. Lower peak viral loads were explained by a more rapid and sustained transition of susceptible cells to a refractory state during infection as well as by an earlier and more potent late, cytolytic immune response. Our results suggest that viral elimination occurs more rapidly during Omicron infection, following vaccination, and following reinfection due to enhanced innate and acquired immune responses. Because viral load has been linked with COVID-19 severity and transmission risk, our model provides a framework for understanding the wide range of observed SARS-CoV-2 infection outcomes.
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Affiliation(s)
- Katherine Owens
- Fred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA
| | - Shadisadat Esmaeili
- Fred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA
| | - Joshua T. Schiffer
- Fred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA
- University of Washington, Department of Medicine, Seattle, Washington, USA
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7
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Zitzmann C, Ke R, Ribeiro RM, Perelson AS. How robust are estimates of key parameters in standard viral dynamic models? PLoS Comput Biol 2024; 20:e1011437. [PMID: 38626190 PMCID: PMC11051641 DOI: 10.1371/journal.pcbi.1011437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 04/26/2024] [Accepted: 04/01/2024] [Indexed: 04/18/2024] Open
Abstract
Mathematical models of viral infection have been developed, fitted to data, and provide insight into disease pathogenesis for multiple agents that cause chronic infection, including HIV, hepatitis C, and B virus. However, for agents that cause acute infections or during the acute stage of agents that cause chronic infections, viral load data are often collected after symptoms develop, usually around or after the peak viral load. Consequently, we frequently lack data in the initial phase of viral growth, i.e., when pre-symptomatic transmission events occur. Missing data may make estimating the time of infection, the infectious period, and parameters in viral dynamic models, such as the cell infection rate, difficult. However, having extra information, such as the average time to peak viral load, may improve the robustness of the estimation. Here, we evaluated the robustness of estimates of key model parameters when viral load data prior to the viral load peak is missing, when we know the values of some parameters and/or the time from infection to peak viral load. Although estimates of the time of infection are sensitive to the quality and amount of available data, particularly pre-peak, other parameters important in understanding disease pathogenesis, such as the loss rate of infected cells, are less sensitive. Viral infectivity and the viral production rate are key parameters affecting the robustness of data fits. Fixing their values to literature values can help estimate the remaining model parameters when pre-peak data is missing or limited. We find a lack of data in the pre-peak growth phase underestimates the time to peak viral load by several days, leading to a shorter predicted growth phase. On the other hand, knowing the time of infection (e.g., from epidemiological data) and fixing it results in good estimates of dynamical parameters even in the absence of early data. While we provide ways to approximate model parameters in the absence of early viral load data, our results also suggest that these data, when available, are needed to estimate model parameters more precisely.
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Affiliation(s)
- Carolin Zitzmann
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico
| | - Ruian Ke
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico
| | - Ruy M. Ribeiro
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico
| | - Alan S. Perelson
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico
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8
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Yu Q, Ascensao JA, Okada T, Boyd O, Volz E, Hallatschek O. Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England. PLoS Pathog 2024; 20:e1012090. [PMID: 38620033 PMCID: PMC11045146 DOI: 10.1371/journal.ppat.1012090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 04/25/2024] [Accepted: 03/03/2024] [Indexed: 04/17/2024] Open
Abstract
Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don't yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.
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Affiliation(s)
- QinQin Yu
- Department of Physics, University of California, Berkeley, California, United States of America
| | - Joao A. Ascensao
- Department of Bioengineering, University of California, Berkeley, California, United States of America
| | - Takashi Okada
- Department of Physics, University of California, Berkeley, California, United States of America
- Department of Integrative Biology, University of California, Berkeley, California, United States of America
- Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
- RIKEN iTHEMS, Wako, Saitama, Japan
| | | | - Olivia Boyd
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Erik Volz
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Oskar Hallatschek
- Department of Physics, University of California, Berkeley, California, United States of America
- Department of Integrative Biology, University of California, Berkeley, California, United States of America
- Peter Debye Institute for Soft Matter Physics, Leipzig University, Leipzig, Germany
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9
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Xing M, Hu G, Wang X, Wang Y, He F, Dai W, Wang X, Niu Y, Liu J, Liu H, Zhang X, Xu J, Cai Q, Zhou D. An intranasal combination vaccine induces systemic and mucosal immunity against COVID-19 and influenza. NPJ Vaccines 2024; 9:64. [PMID: 38509167 PMCID: PMC10954707 DOI: 10.1038/s41541-024-00857-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 02/26/2024] [Indexed: 03/22/2024] Open
Abstract
Despite prolonged surveillance and interventions, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses continue to pose a severe global health burden. Thus, we developed a chimpanzee adenovirus-based combination vaccine, AdC68-HATRBD, with dual specificity against SARS-CoV-2 and influenza virus. When used as a standalone vaccine, intranasal immunization with AdC68-HATRBD induced comprehensive and potent immune responses consisting of immunoglobin (Ig) G, mucosal IgA, neutralizing antibodies, and memory T cells, which protected the mice from BA.5.2 and pandemic H1N1 infections. When used as a heterologous booster, AdC68-HATRBD markedly improved the protective immune response of the licensed SARS-CoV-2 or influenza vaccine. Therefore, whether administered intranasally as a standalone or booster vaccine, this combination vaccine is a valuable strategy to enhance the overall vaccine efficacy by inducing robust systemic and mucosal immune responses, thereby conferring dual lines of immunological defenses for these two viruses.
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Affiliation(s)
- Man Xing
- Department of Pathogen Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
- Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, China
| | - Gaowei Hu
- MOE&NHC&CAMS Key Laboratory of Medical Molecular, Frontiers Science Center of Pathogenic Microorganisms and Infection, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Xiang Wang
- Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, China
| | - Yihan Wang
- Department of Pathogen Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Furong He
- Department of Pathogen Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Weiqian Dai
- Department of Pathogen Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Xinyu Wang
- MOE&NHC&CAMS Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infections Disease and Biosecurity, Frontiers Science Center of Pathogenic Microorganisms and Infection, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Yixin Niu
- Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, China
| | - Jiaojiao Liu
- Department of Pathogen Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Hui Liu
- Chengdu Kanghua Biological Products Co., Ltd, Chengdu, China
| | - Xiaoyan Zhang
- Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, China
| | - Jianqing Xu
- Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, China.
| | - Qiliang Cai
- MOE&NHC&CAMS Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infections Disease and Biosecurity, Frontiers Science Center of Pathogenic Microorganisms and Infection, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
| | - Dongming Zhou
- Department of Pathogen Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China.
- Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, China.
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10
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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] [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.
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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
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11
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Zhao W, Wang X, Tang B. The impacts of spatial-temporal heterogeneity of human-to-human contacts on the extinction probability of infectious disease from branching process model. J Theor Biol 2024; 579:111703. [PMID: 38096979 DOI: 10.1016/j.jtbi.2023.111703] [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: 09/06/2023] [Revised: 11/26/2023] [Accepted: 12/07/2023] [Indexed: 12/18/2023]
Abstract
In this study, we focus on the impacts of spatial-temporal heterogeneity of human-to-human contacts on the spread of infectious diseases and develop a multi-type branching process model by introducing random human-to-human contact mode into a structured population. We provide the general formulas of the generation size, extinction probability, and basic reproduction number of the proposed branching process model. The result shows that the natural temporal heterogeneity (i.e. random contacts over time) can lead to a higher extinction probability while remains the same basic reproduction number and generation size. This is also numerically verified by choosing the real contact distributions from different circumstances of four countries. In addition, we observe a non-monotonic pattern of the differences, against the transmission probability and the mean contact rate, between the extinction probabilities under the constant and random contact patterns. Given the spatial heterogeneity, we show that it can contribute to the increase of basic reproduction number, but also increase the extinction probability of the infectious disease. This study adds novel insights to the course of the impact of heterogeneity on the transmission dynamics and also provides additional evidence for the limited role of reproduction numbers.
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Affiliation(s)
- Wuqiong Zhao
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, PR China.
| | - Xia Wang
- School of Mathematics and Statistics, Shaanxi Normal University, Xi'an 710119, PR China.
| | - Biao Tang
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, PR China.
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12
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Lau KY, Kang J, Park M, Leung G, Wu JT, Leung K. Estimating the Epidemic Size of Superspreading Coronavirus Outbreaks in Real Time: Quantitative Study. JMIR Public Health Surveill 2024; 10:e46687. [PMID: 38345850 PMCID: PMC10863650 DOI: 10.2196/46687] [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: 02/21/2023] [Revised: 12/01/2023] [Accepted: 01/10/2024] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND Novel coronaviruses have emerged and caused major epidemics and pandemics in the past 2 decades, including SARS-CoV-1, MERS-CoV, and SARS-CoV-2, which led to the current COVID-19 pandemic. These coronaviruses are marked by their potential to produce disproportionally large transmission clusters from superspreading events (SSEs). As prompt action is crucial to contain and mitigate SSEs, real-time epidemic size estimation could characterize the transmission heterogeneity and inform timely implementation of control measures. OBJECTIVE This study aimed to estimate the epidemic size of SSEs to inform effective surveillance and rapid mitigation responses. METHODS We developed a statistical framework based on back-calculation to estimate the epidemic size of ongoing coronavirus SSEs. We first validated the framework in simulated scenarios with the epidemiological characteristics of SARS, MERS, and COVID-19 SSEs. As case studies, we retrospectively applied the framework to the Amoy Gardens SARS outbreak in Hong Kong in 2003, a series of nosocomial MERS outbreaks in South Korea in 2015, and 2 COVID-19 outbreaks originating from restaurants in Hong Kong in 2020. RESULTS The accuracy and precision of the estimation of epidemic size of SSEs improved with longer observation time; larger SSE size; and more accurate prior information about the epidemiological characteristics, such as the distribution of the incubation period and the distribution of the onset-to-confirmation delay. By retrospectively applying the framework, we found that the 95% credible interval of the estimates contained the true epidemic size after 37% of cases were reported in the Amoy Garden SARS SSE in Hong Kong, 41% to 62% of cases were observed in the 3 nosocomial MERS SSEs in South Korea, and 76% to 86% of cases were confirmed in the 2 COVID-19 SSEs in Hong Kong. CONCLUSIONS Our framework can be readily integrated into coronavirus surveillance systems to enhance situation awareness of ongoing SSEs.
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Affiliation(s)
- Kitty Y Lau
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, China (Hong Kong)
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, China (Hong Kong)
| | - Jian Kang
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, China (Hong Kong)
| | - Minah Park
- Department of Health Convergence, Ewha Womans University, Seoul, Republic of Korea
| | - Gabriel Leung
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, China (Hong Kong)
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, China (Hong Kong)
| | - Joseph T Wu
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, China (Hong Kong)
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, China (Hong Kong)
- The University of Hong Kong - Shenzhen Hospital, Shenzhen, China
| | - Kathy Leung
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, China (Hong Kong)
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, China (Hong Kong)
- The University of Hong Kong - Shenzhen Hospital, Shenzhen, China
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13
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Owens K, Esmaeili-Wellman S, Schiffer JT. Heterogeneous SARS-CoV-2 kinetics due to variable timing and intensity of immune responses. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.08.20.23294350. [PMID: 37662228 PMCID: PMC10473815 DOI: 10.1101/2023.08.20.23294350] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
The viral kinetics of documented SARS-CoV-2 infections exhibit a high degree of inter-individual variability. We identified six distinct viral shedding patterns, which differed according to peak viral load, duration, expansion rate and clearance rate, by clustering data from 768 infections in the National Basketball Association cohort. Omicron variant infections in previously vaccinated individuals generally led to lower cumulative shedding levels of SARS-CoV-2 than other scenarios. We then developed a mechanistic mathematical model that recapitulated 1510 observed viral trajectories, including viral rebound and cases of reinfection. Lower peak viral loads were explained by a more rapid and sustained transition of susceptible cells to a refractory state during infection, as well as an earlier and more potent late, cytolytic immune response. Our results suggest that viral elimination occurs more rapidly during omicron infection, following vaccination, and following re-infection due to enhanced innate and acquired immune responses. Because viral load has been linked with COVID-19 severity and transmission risk, our model provides a framework for understanding the wide range of observed SARS-CoV-2 infection outcomes.
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Affiliation(s)
- Katherine Owens
- Fred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division
| | | | - Joshua T Schiffer
- Fred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division
- University of Washington, Department of Medicine
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14
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Gubbins S. Quantifying the relationship between within-host dynamics and transmission for viral diseases of livestock. J R Soc Interface 2024; 21:20230445. [PMID: 38379412 PMCID: PMC10879856 DOI: 10.1098/rsif.2023.0445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 01/18/2024] [Indexed: 02/22/2024] Open
Abstract
Understanding the population dynamics of an infectious disease requires linking within-host dynamics and between-host transmission in a quantitative manner, but this is seldom done in practice. Here a simple phenomenological model for viral dynamics within a host is linked to between-host transmission by assuming that the probability of transmission is related to log viral titre. Data from transmission experiments for two viral diseases of livestock, foot-and-mouth disease virus in cattle and swine influenza virus in pigs, are used to parametrize the model and, importantly, test the underlying assumptions. The model allows the relationship between within-host parameters and transmission to be determined explicitly through their influence on the reproduction number and generation time. Furthermore, these critical within-host parameters (time and level of peak titre, viral growth and clearance rates) can be computed from more complex within-host models, raising the possibility of assessing the impact of within-host processes on between-host transmission in a more detailed quantitative manner.
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Affiliation(s)
- Simon Gubbins
- The Pirbright Institute, Ash Road, Pirbright, Surrey GU24 0NF, UK
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15
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Kuehl PJ, Dearing J, Werts A, Cox J, Irshad H, Barrett EG, Tucker SN, Langel SN. Design and validation of an exposure system for efficient inter-animal SARS-CoV-2 airborne transmission in Syrian hamsters. Microbiol Spectr 2023; 11:e0471722. [PMID: 37882564 PMCID: PMC10714807 DOI: 10.1128/spectrum.04717-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 09/18/2023] [Indexed: 10/27/2023] Open
Abstract
IMPORTANCE The main route of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is airborne. However, there are few experimental systems that can assess the airborne transmission dynamics of SARS-CoV-2 in vivo. Here, we designed, built, and characterized a hamster transmission caging and exposure system that allows for efficient SARS-CoV-2 airborne transmission in Syrian hamsters without contributions from fomite or direct contact transmission. We successfully measured SARS-CoV-2 viral RNA in aerosols and demonstrated that SARS-CoV-2 is transmitted efficiently at either a 1:1 or 1:4 infected index to naïve recipient hamster ratio. This is meaningful as a 1:4 infected index to naïve hamster ratio would allow for simultaneous comparisons of various interventions in naïve animals to determine their susceptibility to infection by aerosol transmission of SARS-CoV-2. Our SARS-CoV-2 exposure system allows for testing viral airborne transmission dynamics and transmission-blocking therapeutic strategies against SARS-CoV-2 in Syrian hamsters.
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Affiliation(s)
- Philip J. Kuehl
- Lovelace Biomedical Research Institute, Albuquerque, New Mexico, USA
| | - Justin Dearing
- Lovelace Biomedical Research Institute, Albuquerque, New Mexico, USA
| | - Adam Werts
- Lovelace Biomedical Research Institute, Albuquerque, New Mexico, USA
| | - Jason Cox
- Lovelace Biomedical Research Institute, Albuquerque, New Mexico, USA
| | - Hammad Irshad
- Lovelace Biomedical Research Institute, Albuquerque, New Mexico, USA
| | - Edward G. Barrett
- Lovelace Biomedical Research Institute, Albuquerque, New Mexico, USA
| | | | - Stephanie N. Langel
- Department of Pathology, Center for Global Health and Diseases, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
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16
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Edelstein GE, Boucau J, Uddin R, Marino C, Liew MY, Barry M, Choudhary MC, Gilbert RF, Reynolds Z, Li Y, Tien D, Sagar S, Vyas TD, Kawano Y, Sparks JA, Hammond SP, Wallace Z, Vyas JM, Barczak AK, Lemieux JE, Li JZ, Siedner MJ. SARS-CoV-2 Virologic Rebound With Nirmatrelvir-Ritonavir Therapy : An Observational Study. Ann Intern Med 2023; 176:1577-1585. [PMID: 37956428 PMCID: PMC10644265 DOI: 10.7326/m23-1756] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND Data are conflicting regarding an association between treatment of acute COVID-19 with nirmatrelvir-ritonavir (N-R) and virologic rebound (VR). OBJECTIVE To compare the frequency of VR in patients with and without N-R treatment for acute COVID-19. DESIGN Observational cohort study. SETTING Multicenter health care system in Boston, Massachusetts. PARTICIPANTS Ambulatory adults with acute COVID-19 with and without use of N-R. INTERVENTION Receipt of 5 days of N-R treatment versus no COVID-19 therapy. MEASUREMENTS The primary outcome was VR, defined as either a positive SARS-CoV-2 viral culture result after a prior negative result or 2 consecutive viral loads above 4.0 log10 copies/mL that were also at least 1.0 log10 copies/mL higher than a prior viral load below 4.0 log10 copies/mL. RESULTS Compared with untreated persons (n = 55), those taking N-R (n = 72) were older, received more COVID-19 vaccinations, and more commonly had immunosuppression. Fifteen participants (20.8%) taking N-R had VR versus 1 (1.8%) who was untreated (absolute difference, 19.0 percentage points [95% CI, 9.0 to 29.0 percentage points]; P = 0.001). All persons with VR had a positive viral culture result after a prior negative result. In multivariable models, only N-R use was associated with VR (adjusted odds ratio, 10.02 [CI, 1.13 to 88.74]; P = 0.038). Virologic rebound was more common among those who started therapy within 2 days of symptom onset (26.3%) than among those who started 2 or more days after symptom onset (0%) (P = 0.030). Among participants receiving N-R, those who had VR had prolonged shedding of replication-competent virus compared with those who did not have VR (median, 14 vs. 3 days). Eight of 16 participants (50% [CI, 25% to 75%]) with VR also reported symptom rebound; 2 were completely asymptomatic. No post-VR resistance mutations were detected. LIMITATIONS Observational study design with differences between the treated and untreated groups; positive viral culture result was used as a surrogate marker for risk for ongoing viral transmission. CONCLUSION Virologic rebound occurred in approximately 1 in 5 people taking N-R, often without symptom rebound, and was associated with shedding of replication-competent virus. PRIMARY FUNDING SOURCE National Institutes of Health.
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Affiliation(s)
| | - Julie Boucau
- Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts (J.B., C.M.)
| | - Rockib Uddin
- Massachusetts General Hospital, Boston, Massachusetts (R.U., M.Y.L., M.B., R.F.G., Z.R., D.T., S.S., T.D.V., S.P.H., Z.W.)
| | - Caitlin Marino
- Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts (J.B., C.M.)
| | - May Y Liew
- Massachusetts General Hospital, Boston, Massachusetts (R.U., M.Y.L., M.B., R.F.G., Z.R., D.T., S.S., T.D.V., S.P.H., Z.W.)
| | - Mamadou Barry
- Massachusetts General Hospital, Boston, Massachusetts (R.U., M.Y.L., M.B., R.F.G., Z.R., D.T., S.S., T.D.V., S.P.H., Z.W.)
| | - Manish C Choudhary
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts (M.C.C., J.Z.L.)
| | - Rebecca F Gilbert
- Massachusetts General Hospital, Boston, Massachusetts (R.U., M.Y.L., M.B., R.F.G., Z.R., D.T., S.S., T.D.V., S.P.H., Z.W.)
| | - Zahra Reynolds
- Massachusetts General Hospital, Boston, Massachusetts (R.U., M.Y.L., M.B., R.F.G., Z.R., D.T., S.S., T.D.V., S.P.H., Z.W.)
| | - Yijia Li
- Brigham and Women's Hospital and Massachusetts General Hospital, Boston, Massachusetts, and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Y.L.)
| | - Dessie Tien
- Massachusetts General Hospital, Boston, Massachusetts (R.U., M.Y.L., M.B., R.F.G., Z.R., D.T., S.S., T.D.V., S.P.H., Z.W.)
| | - Shruti Sagar
- Massachusetts General Hospital, Boston, Massachusetts (R.U., M.Y.L., M.B., R.F.G., Z.R., D.T., S.S., T.D.V., S.P.H., Z.W.)
| | - Tammy D Vyas
- Massachusetts General Hospital, Boston, Massachusetts (R.U., M.Y.L., M.B., R.F.G., Z.R., D.T., S.S., T.D.V., S.P.H., Z.W.)
| | - Yumeko Kawano
- Brigham and Women's Hospital, Boston, Massachusetts (G.E.E., Y.K., J.A.S.)
| | - Jeffrey A Sparks
- Brigham and Women's Hospital, Boston, Massachusetts (G.E.E., Y.K., J.A.S.)
| | - Sarah P Hammond
- Massachusetts General Hospital, Boston, Massachusetts (R.U., M.Y.L., M.B., R.F.G., Z.R., D.T., S.S., T.D.V., S.P.H., Z.W.)
| | - Zachary Wallace
- Massachusetts General Hospital, Boston, Massachusetts (R.U., M.Y.L., M.B., R.F.G., Z.R., D.T., S.S., T.D.V., S.P.H., Z.W.)
| | - Jatin M Vyas
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts (J.M.V.)
| | - Amy K Barczak
- Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, and Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts (A.K.B.)
| | - Jacob E Lemieux
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, and Broad Institute, Cambridge, Massachusetts (J.E.L.)
| | - Jonathan Z Li
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts (M.C.C., J.Z.L.)
| | - Mark J Siedner
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, and Africa Health Research Institute, KwaZulu-Natal, South Africa (M.J.S.)
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17
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Wood SGA, Craske J, Burridge HC. Relating quanta conservation and compartmental epidemiological models of airborne disease outbreaks in buildings. Sci Rep 2023; 13:17335. [PMID: 37833394 PMCID: PMC10575980 DOI: 10.1038/s41598-023-44527-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 10/09/2023] [Indexed: 10/15/2023] Open
Abstract
We investigate the underlying assumptions and limits of applicability of several documented models for outbreaks of airborne disease inside buildings by showing how they may each be regarded as special cases of a system of equations which combines quanta conservation and compartmental epidemiological modelling. We investigate the behaviour of this system analytically, gaining insight to its behaviour at large time. We then investigate the characteristic timescales of an indoor outbreak, showing how the dilution rate of the space, and the quanta generation rate, incubation rate and removal rate associated with the illness may be used to predict the evolution of an outbreak over time, and may also be used to predict the relative performances of other indoor airborne outbreak models. The model is compared to a more commonly used model, in which it is assumed the environmental concentration of infectious aerosols adheres to a quasi-steady-state, so that the the dimensionless quanta concentration is equal to the the infectious fraction. The model presented here is shown to approach this limit exponentially to within an interval defined by the incubation and removal rates. This may be used to predict the maximum extent to which a case will deviate from the quasi steady state condition.
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Affiliation(s)
- Samuel G A Wood
- Department of Civil and Environmental Engineering, Imperial College London, London, SW7 2AZ, UK.
| | - John Craske
- Department of Civil and Environmental Engineering, Imperial College London, London, SW7 2AZ, UK
| | - Henry C Burridge
- Department of Civil and Environmental Engineering, Imperial College London, London, SW7 2AZ, UK
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18
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Hart WS, Park H, Jeong YD, Kim KS, Yoshimura R, Thompson RN, Iwami S. Analysis of the risk and pre-emptive control of viral outbreaks accounting for within-host dynamics: SARS-CoV-2 as a case study. Proc Natl Acad Sci U S A 2023; 120:e2305451120. [PMID: 37788317 PMCID: PMC10576149 DOI: 10.1073/pnas.2305451120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 09/07/2023] [Indexed: 10/05/2023] Open
Abstract
In the era of living with COVID-19, the risk of localised SARS-CoV-2 outbreaks remains. Here, we develop a multiscale modelling framework for estimating the local outbreak risk for a viral disease (the probability that a major outbreak results from a single case introduced into the population), accounting for within-host viral dynamics. Compared to population-level models previously used to estimate outbreak risks, our approach enables more detailed analysis of how the risk can be mitigated through pre-emptive interventions such as antigen testing. Considering SARS-CoV-2 as a case study, we quantify the within-host dynamics using data from individuals with omicron variant infections. We demonstrate that regular antigen testing reduces, but may not eliminate, the outbreak risk, depending on characteristics of local transmission. In our baseline analysis, daily antigen testing reduces the outbreak risk by 45% compared to a scenario without antigen testing. Additionally, we show that accounting for heterogeneity in within-host dynamics between individuals affects outbreak risk estimates and assessments of the impact of antigen testing. Our results therefore highlight important factors to consider when using multiscale models to design pre-emptive interventions against SARS-CoV-2 and other viruses.
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Affiliation(s)
- William S. Hart
- Mathematical Institute, University of Oxford, OxfordOX2 6GG, United Kingdom
- lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya464-8602, Japan
| | - Hyeongki Park
- lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya464-8602, Japan
| | - Yong Dam Jeong
- lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya464-8602, Japan
- Department of Mathematics, Pusan National University, Busan46241, South Korea
| | - Kwang Su Kim
- lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya464-8602, Japan
- Department of Scientific Computing, Pukyong National University, Busan48513, South Korea
| | - Raiki Yoshimura
- lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya464-8602, Japan
| | - Robin N. Thompson
- Mathematical Institute, University of Oxford, OxfordOX2 6GG, United Kingdom
- Mathematics Institute, University of Warwick, CoventryCV4 7AL, United Kingdom
- Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, CoventryCV4 7AL, United Kingdom
| | - Shingo Iwami
- lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya464-8602, Japan
- Institute of Mathematics for Industry, Kyushu University, Fukuoka819-0395, Japan
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto606-8501, Japan
- Interdisciplinary Theoretical and Mathematical Sciences Program, RIKEN, Saitama351-0198, Japan
- NEXT-Ganken Program, Japanese Foundation for Cancer Research, Tokyo135-8550, Japan
- Science Groove Inc., Fukuoka810-0041, Japan
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19
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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 : THE PREPRINT SERVER FOR BIOLOGY 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] [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.
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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
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20
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Li A, Wu J, Moghadas SM. Epidemic dynamics with time-varying transmission risk reveal the role of disease stage-dependent infectiousness. J Theor Biol 2023; 573:111594. [PMID: 37549785 DOI: 10.1016/j.jtbi.2023.111594] [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: 04/25/2023] [Revised: 07/19/2023] [Accepted: 08/02/2023] [Indexed: 08/09/2023]
Abstract
A key characteristic of acute communicable diseases is the infectiousness that varies over time as the infection dynamics evolve within a host, which influences the risk of transmission in different stages of the disease. Despite the evidence of time-varying transmission risk, most dynamic models of epidemics assume a constant transmission rate during the infectious period. Recent work has shown the difference in epidemic dynamics when this assumption is relaxed and different transmission rates are used by discretizing the infectious period into multiple sub-periods. Here, we develop an age-structured model to integrate a continuous time-varying transmission risk, based on an established correlation between the viral dynamics and infectiousness profile. Taking into account the natural history and parameter estimates of COVID-19 caused by the original strain of SARS-CoV-2, we demonstrate the difference in temporal epidemic dynamics when a continuous time-varying transmission probability is used as compared to multiple constant transmission probabilities. Our results show a significant difference between the incidence curves in terms of the magnitude and peak time, even when the reproduction number and total number of infections are the same for continuous and discrete transmission probabilities. Finally, we demonstrate the spurious outcome of preventing an epidemic through the isolation of infectious individuals when constant transmission probabilities are used, highlighting the importance of integrating a continuous time-dependent transmission parameter in dynamic models. These findings suggest a more cautious interpretation of model outcomes, especially those that are intended to evaluate the effectiveness of interventions and inform policy decisions for disease mitigation strategies.
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Affiliation(s)
- Ao Li
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, M3J 1P3, Canada
| | - Jianhong Wu
- Department of Mathematics and Statistics, York University, Toronto, Ontario, M3J 1P3, Canada
| | - Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, M3J 1P3, Canada.
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21
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Larsen SL, Shin I, Joseph J, West H, Anorga R, Mena GE, Mahmud AS, Martinez PP. Quantifying the impact of SARS-CoV-2 temporal vaccination trends and disparities on disease control. SCIENCE ADVANCES 2023; 9:eadh9920. [PMID: 37531439 PMCID: PMC10396293 DOI: 10.1126/sciadv.adh9920] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 06/30/2023] [Indexed: 08/04/2023]
Abstract
SARS-CoV-2 vaccines have been distributed at unprecedented speed. Still, little is known about temporal vaccination trends, their association with socioeconomic inequality, and their consequences for disease control. Using data from 161 countries/territories and 58 states, we examined vaccination rates across high and low socioeconomic status (SES), showing that disparities in coverage exist at national and subnational levels. We also identified two distinct vaccination trends: a rapid initial rollout, quickly reaching a plateau, or sigmoidal and slow to begin. Informed by these patterns, we implemented an SES-stratified mechanistic model, finding profound differences in mortality and incidence across these two vaccination types. Timing of initial rollout affects disease outcomes more substantially than final coverage or degree of SES disparity. Unexpectedly, timing is not associated with wealth inequality or GDP per capita. While socioeconomic disparity should be addressed, accelerating initial rollout for all over focusing on increasing coverage is an accessible intervention that could minimize the burden of disease across socioeconomic groups.
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Affiliation(s)
- Sophie L. Larsen
- Program in Ecology, Evolution, and Conservation Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Ikgyu Shin
- Department of Statistics, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Jefrin Joseph
- Department of Microbiology, School of Molecular and Cellular Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Haylee West
- Department of Microbiology, School of Molecular and Cellular Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Rafael Anorga
- Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois Chicago, Chicago, IL, USA
| | | | - Ayesha S. Mahmud
- Department of Demography, University of California, Berkeley, CA, USA
| | - Pamela P. Martinez
- Department of Statistics, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Department of Microbiology, School of Molecular and Cellular Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA
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22
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Kanté DSI, Jebrane A, Hakim A, Boukamel A. Characterization of superspreaders movement in a bidirectional corridor using a social force model. Front Public Health 2023; 11:1188732. [PMID: 37575110 PMCID: PMC10416642 DOI: 10.3389/fpubh.2023.1188732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 07/11/2023] [Indexed: 08/15/2023] Open
Abstract
During infectious disease outbreaks, some infected individuals may spread the disease widely and amplify risks in the community. People whose daily activities bring them in close proximity to many others can unknowingly become superspreaders. The use of contact tracking based on social networks, GPS, or mobile tracking data can help to identify superspreaders and break the chain of transmission. We propose a model that aims at providing insight into risk factors of superspreading events. Here, we use a social force model to estimate the superspreading potential of individuals walking in a bidirectional corridor. First, we applied the model to identify parameters that favor exposure to an infectious person in scattered crowds. We find that low walking speed and high body mass both increase the expected number of close exposures. Panic events exacerbate the risks while social distancing reduces both the number and duration of close encounters. Further, in dense crowds, pedestrians interact more and cannot easily maintain the social distance between them. The number of exposures increases with the density of person in the corridor. The study of movements reveals that individuals walking toward the center of the corridor tend to rotate and zigzag more than those walking along the edges, and thus have higher risks of superspreading. The corridor model can be applied to designing risk reduction measures for specific high volume venues, including transit stations, stadiums, and schools.
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Affiliation(s)
- Dramane Sam Idris Kanté
- LAMAI, Department of Mathematics, Faculty of Sciences and Technologies, Cadi Ayyad University, Marrakesh, Morocco
- Centrale Casablanca, Complex Systems and Interactions Research Center, Ville Verte, Bouskoura, Morocco
| | - Aissam Jebrane
- Centrale Casablanca, Complex Systems and Interactions Research Center, Ville Verte, Bouskoura, Morocco
| | - Abdelilah Hakim
- LAMAI, Department of Mathematics, Faculty of Sciences and Technologies, Cadi Ayyad University, Marrakesh, Morocco
| | - Adnane Boukamel
- Centrale Casablanca, Complex Systems and Interactions Research Center, Ville Verte, Bouskoura, Morocco
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23
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Edelstein GE, Boucau J, Uddin R, Marino C, Liew MY, Barry M, Choudhary MC, Gilbert RF, Reynolds Z, Li Y, Tien D, Sagar S, Vyas TD, Kawano Y, Sparks JA, Hammond SP, Wallace Z, Vyas JM, Barczak AK, Lemieux JE, Li JZ, Siedner MJ. SARS-CoV-2 virologic rebound with nirmatrelvir-ritonavir therapy. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.23.23288598. [PMID: 37425934 PMCID: PMC10327262 DOI: 10.1101/2023.06.23.23288598] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Objective To compare the frequency of replication-competent virologic rebound with and without nirmatrelvir-ritonavir treatment for acute COVID-19. Secondary aims were to estimate the validity of symptoms to detect rebound and the incidence of emergent nirmatrelvir-resistance mutations after rebound. Design Observational cohort study. Setting Multicenter healthcare system in Boston, Massachusetts. Participants We enrolled ambulatory adults with a positive COVID-19 test and/or a prescription for nirmatrelvir-ritonavir. Exposures Receipt of 5 days of nirmatrelvir-ritonavir treatment versus no COVID-19 therapy. Main Outcome and Measures The primary outcome was COVID-19 virologic rebound, defined as either (1) a positive SARS-CoV-2 viral culture following a prior negative culture or (2) two consecutive viral loads ≥4.0 log10 copies/milliliter after a prior reduction in viral load to <4.0 log10 copies/milliliter. Results Compared with untreated individuals (n=55), those taking nirmatrelvir-ritonavir (n=72) were older, received more COVID-19 vaccinations, and were more commonly immunosuppressed. Fifteen individuals (20.8%) taking nirmatrelvir-ritonavir experienced virologic rebound versus one (1.8%) of the untreated (absolute difference 19.0% [95%CI 9.0-29.0%], P=0.001). In multivariable models, only N-R was associated with VR (AOR 10.02, 95%CI 1.13-88.74). VR occurred more commonly among those with earlier nirmatrelvir-ritonavir initiation (29.0%, 16.7% and 0% when initiated days 0, 1, and ≥2 after diagnosis, respectively, P=0.089). Among participants on N-R, those experiencing rebound had prolonged shedding of replication-competent virus compared to those that did not rebound (median: 14 vs 3 days). Only 8/16 with virologic rebound reported worsening symptoms (50%, 95%CI 25%-75%); 2 were completely asymptomatic. We detected no post-rebound nirmatrelvir-resistance mutations in the NSP5 protease gene. Conclusions and Relevance Virologic rebound occurred in approximately one in five people taking nirmatrelvir-ritonavir and often occurred without worsening symptoms. Because it is associated with replication-competent viral shedding, close monitoring and potential isolation of those who rebound should be considered.
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Affiliation(s)
| | - Julie Boucau
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | | | - Caitlin Marino
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - May Y Liew
- Massachusetts General Hospital, Boston, MA, USA
| | | | - Manish C Choudhary
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | | | | | - Yijia Li
- Brigham and Women's Hospital, Boston, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Dessie Tien
- Massachusetts General Hospital, Boston, MA, USA
| | | | | | | | | | | | | | - Jatin M Vyas
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Amy K Barczak
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jacob E Lemieux
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
| | - Jonathan Z Li
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Mark J Siedner
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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24
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Avadhanula V, Creighton CJ, Ferlic-Stark L, Sucgang R, Zhang Y, Nagaraj D, Nicholson EG, Rajan A, Menon VK, Doddapaneni H, Muzny DM, Metcalf G, Cregeen SJJ, Hoffman KL, Gibbs RA, Petrosino J, Piedra PA. Longitudinal host transcriptional responses to SARS-CoV-2 infection in adults with extremely high viral load. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.24.542181. [PMID: 37292999 PMCID: PMC10245966 DOI: 10.1101/2023.05.24.542181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Current understanding of viral dynamics of SARS-CoV-2 and host responses driving the pathogenic mechanisms in COVID-19 is rapidly evolving. Here, we conducted a longitudinal study to investigate gene expression patterns during acute SARS-CoV-2 illness. Cases included SARS-CoV-2 infected individuals with extremely high viral loads early in their illness, individuals having low SARS-CoV-2 viral loads early in their infection, and individuals testing negative for SARS-CoV-2. We could identify widespread transcriptional host responses to SARS-CoV-2 infection that were initially most strongly manifested in patients with extremely high initial viral loads, then attenuating within the patient over time as viral loads decreased. Genes correlated with SARS-CoV-2 viral load over time were similarly differentially expressed across independent datasets of SARS-CoV-2 infected lung and upper airway cells, from both in vitro systems and patient samples. We also generated expression data on the human nose organoid model during SARS-CoV-2 infection. The human nose organoid-generated host transcriptional response captured many aspects of responses observed in the above patient samples, while suggesting the existence of distinct host responses to SARS-CoV-2 depending on the cellular context, involving both epithelial and cellular immune responses. Our findings provide a catalog of SARS-CoV-2 host response genes changing over time.
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Affiliation(s)
- Vasanthi Avadhanula
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Chad J. Creighton
- Dan L. Duncan Comprehensive Cancer Center Division of Biostatistics, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Laura Ferlic-Stark
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Richard Sucgang
- Center for Health Data Science and Analytics, Houston Methodist Research Institute, Houston, TX 77030, USA
| | - Yiqun Zhang
- Dan L. Duncan Comprehensive Cancer Center Division of Biostatistics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Divya Nagaraj
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Erin G. Nicholson
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Anubama Rajan
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Vipin Kumar Menon
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Harshavardhan Doddapaneni
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Donna Marie Muzny
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Ginger Metcalf
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | | | - Kristi Louise Hoffman
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Richard A Gibbs
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Joseph Petrosino
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Pedro A Piedra
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, 77030, USA
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25
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Newbold SC, Ashworth M, Finnoff D, Shogren JF, Thunström L. Physical distancing versus testing with self-isolation for controlling an emerging epidemic. Sci Rep 2023; 13:8185. [PMID: 37210388 DOI: 10.1038/s41598-023-35083-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 05/12/2023] [Indexed: 05/22/2023] Open
Abstract
Two distinct strategies for controlling an emerging epidemic are physical distancing and regular testing with self-isolation. These strategies are especially important before effective vaccines or treatments become widely available. The testing strategy has been promoted frequently but used less often than physical distancing to mitigate COVID-19. We compared the performance of these strategies in an integrated epidemiological and economic model that includes a simple representation of transmission by "superspreading," wherein a relatively small fraction of infected individuals cause a large share of infections. We examined the economic benefits of distancing and testing over a wide range of conditions, including variations in the transmissibility and lethality of the disease meant to encompass the most prominent variants of COVID-19 encountered so far. In a head-to-head comparison using our primary parameter values, both with and without superspreading and a declining marginal value of mortality risk reductions, an optimized testing strategy outperformed an optimized distancing strategy. In a Monte Carlo uncertainty analysis, an optimized policy that combined the two strategies performed better than either one alone in more than 25% of random parameter draws. Insofar as diagnostic tests are sensitive to viral loads, and individuals with high viral loads are more likely to contribute to superspreading events, superspreading enhances the relative performance of testing over distancing in our model. Both strategies performed best at moderate levels of transmissibility, somewhat lower than the transmissibility of the ancestral strain of SARS-CoV-2.
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Affiliation(s)
- Stephen C Newbold
- Department of Economics, University of Wyoming, Laramie, WY, 82071, USA.
| | - Madison Ashworth
- Department of Economics, University of Wyoming, Laramie, WY, 82071, USA
- Fletcher Group, Inc., London, KY, 40741, USA
| | - David Finnoff
- Department of Economics, University of Wyoming, Laramie, WY, 82071, USA
| | - Jason F Shogren
- Department of Economics, University of Wyoming, Laramie, WY, 82071, USA
| | - Linda Thunström
- Department of Economics, University of Wyoming, Laramie, WY, 82071, USA
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26
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Korosec CS, Betti MI, Dick DW, Ooi HK, Moyles IR, Wahl LM, Heffernan JM. Multiple cohort study of hospitalized SARS-CoV-2 in-host infection dynamics: Parameter estimates, identifiability, sensitivity and the eclipse phase profile. J Theor Biol 2023; 564:111449. [PMID: 36894132 PMCID: PMC9990894 DOI: 10.1016/j.jtbi.2023.111449] [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: 06/22/2022] [Revised: 02/09/2023] [Accepted: 02/22/2023] [Indexed: 03/09/2023]
Abstract
Within-host SARS-CoV-2 modelling studies have been published throughout the COVID-19 pandemic. These studies contain highly variable numbers of individuals and capture varying timescales of pathogen dynamics; some studies capture the time of disease onset, the peak viral load and subsequent heterogeneity in clearance dynamics across individuals, while others capture late-time post-peak dynamics. In this study, we curate multiple previously published SARS-CoV-2 viral load data sets, fit these data with a consistent modelling approach, and estimate the variability of in-host parameters including the basic reproduction number, R0, as well as the best-fit eclipse phase profile. We find that fitted dynamics can be highly variable across data sets, and highly variable within data sets, particularly when key components of the dynamic trajectories (e.g. peak viral load) are not represented in the data. Further, we investigated the role of the eclipse phase time distribution in fitting SARS-CoV-2 viral load data. By varying the shape parameter of an Erlang distribution, we demonstrate that models with either no eclipse phase, or with an exponentially-distributed eclipse phase, offer significantly worse fits to these data, whereas models with less dispersion around the mean eclipse time (shape parameter two or more) offered the best fits to the available data across all data sets used in this work. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".
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Affiliation(s)
- Chapin S Korosec
- Modelling Infection and Immunity Lab, Mathematics and Statistics, York University, 4700 Keele St, Toronto, M3J 1P3, ON, Canada; Centre for Disease Modelling, Mathematics and Statistics, York University, 4700 Keele St, Toronto, M3J 1P3, ON, Canada.
| | - Matthew I Betti
- Department of Mathematics and Computer Science, Mount Allison University, 62 York St, Sackville, E4L 1E2, NB, Canada.
| | - David W Dick
- Modelling Infection and Immunity Lab, Mathematics and Statistics, York University, 4700 Keele St, Toronto, M3J 1P3, ON, Canada; Centre for Disease Modelling, Mathematics and Statistics, York University, 4700 Keele St, Toronto, M3J 1P3, ON, Canada.
| | - Hsu Kiang Ooi
- Digital Technologies Research Centre, National Research Council Canada, 222 College Street, Toronto, M5T 3J1, ON, Canada.
| | - Iain R Moyles
- Modelling Infection and Immunity Lab, Mathematics and Statistics, York University, 4700 Keele St, Toronto, M3J 1P3, ON, Canada; Centre for Disease Modelling, Mathematics and Statistics, York University, 4700 Keele St, Toronto, M3J 1P3, ON, Canada.
| | - Lindi M Wahl
- Mathematics, Western University, 1151 Richmond St, London, N6A 5B7, ON, Canada.
| | - Jane M Heffernan
- Modelling Infection and Immunity Lab, Mathematics and Statistics, York University, 4700 Keele St, Toronto, M3J 1P3, ON, Canada; Centre for Disease Modelling, Mathematics and Statistics, York University, 4700 Keele St, Toronto, M3J 1P3, ON, Canada.
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27
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Lim NWH, Lim JT, Dickens BL. Border Control for Infectious Respiratory Disease Pandemics: A Modelling Study for H1N1 and Four Strains of SARS-CoV-2. Viruses 2023; 15:978. [PMID: 37112958 PMCID: PMC10144227 DOI: 10.3390/v15040978] [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: 03/22/2023] [Revised: 04/11/2023] [Accepted: 04/13/2023] [Indexed: 04/29/2023] Open
Abstract
Post-pandemic economic recovery relies on border control for safe cross-border movement. Following the COVID-19 pandemic, we investigate whether effective strategies generalize across diseases and variants. For four SARS-CoV-2 variants and influenza A-H1N1, we simulated 21 strategy families of varying test types and frequencies, quantifying expected transmission risk, relative to no control, by strategy family and quarantine length. We also determined minimum quarantine lengths to suppress relative risk below given thresholds. SARS-CoV-2 variants showed similar relative risk across strategy families and quarantine lengths, with at most 2 days' between-variant difference in minimum quarantine lengths. ART-based and PCR-based strategies showed comparable effectiveness, with regular testing strategies requiring at most 9 days. For influenza A-H1N1, ART-based strategies were ineffective. Daily ART testing reduced relative risk only 9% faster than without regular testing. PCR-based strategies were moderately effective, with daily PCR (0-day delay) testing requiring 16 days for the second-most stringent threshold. Viruses with high typical viral loads and low transmission risk given low viral loads, such as SARS-CoV-2, are effectively controlled with moderate-sensitivity tests (ARTs) and modest quarantine periods. Viruses with low typical viral loads and substantial transmission risk at low viral loads, such as influenza A-H1N1, require high-sensitivity tests (PCR) and longer quarantine periods.
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Affiliation(s)
- Nigel Wei-Han Lim
- Saw Swee Hock School of Public Health, National University of Singapore 12 Science Drive 2, #10-01, Singapore 117549, Singapore; (N.W.-H.L.); (B.L.D.)
| | - Jue Tao Lim
- Lee Kong Chian School of Medicine, Nanyang Technological University Experimental Medicine Building, 59 Nanyang Drive, Singapore 636921, Singapore
| | - Borame Lee Dickens
- Saw Swee Hock School of Public Health, National University of Singapore 12 Science Drive 2, #10-01, Singapore 117549, Singapore; (N.W.-H.L.); (B.L.D.)
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28
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Rao R, Musante CJ, Allen R. A quantitative systems pharmacology model of the pathophysiology and treatment of COVID-19 predicts optimal timing of pharmacological interventions. NPJ Syst Biol Appl 2023; 9:13. [PMID: 37059734 PMCID: PMC10102696 DOI: 10.1038/s41540-023-00269-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 02/09/2023] [Indexed: 04/16/2023] Open
Abstract
A quantitative systems pharmacology (QSP) model of the pathogenesis and treatment of SARS-CoV-2 infection can streamline and accelerate the development of novel medicines to treat COVID-19. Simulation of clinical trials allows in silico exploration of the uncertainties of clinical trial design and can rapidly inform their protocols. We previously published a preliminary model of the immune response to SARS-CoV-2 infection. To further our understanding of COVID-19 and treatment, we significantly updated the model by matching a curated dataset spanning viral load and immune responses in plasma and lung. We identified a population of parameter sets to generate heterogeneity in pathophysiology and treatment and tested this model against published reports from interventional SARS-CoV-2 targeting mAb and antiviral trials. Upon generation and selection of a virtual population, we match both the placebo and treated responses in viral load in these trials. We extended the model to predict the rate of hospitalization or death within a population. Via comparison of the in silico predictions with clinical data, we hypothesize that the immune response to virus is log-linear over a wide range of viral load. To validate this approach, we show the model matches a published subgroup analysis, sorted by baseline viral load, of patients treated with neutralizing Abs. By simulating intervention at different time points post infection, the model predicts efficacy is not sensitive to interventions within five days of symptom onset, but efficacy is dramatically reduced if more than five days pass post symptom onset prior to treatment.
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Affiliation(s)
- Rohit Rao
- Early Clinical Development, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA.
| | - Cynthia J Musante
- Early Clinical Development, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA
| | - Richard Allen
- Early Clinical Development, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA
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29
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Leyfman Y, Emmanuel N, Menon GP, Joshi M, Wilkerson WB, Cappelli J, Erick TK, Park CH, Sharma P. Cancer and COVID-19: unravelling the immunological interplay with a review of promising therapies against severe SARS-CoV-2 for cancer patients. J Hematol Oncol 2023; 16:39. [PMID: 37055774 PMCID: PMC10100631 DOI: 10.1186/s13045-023-01432-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 03/25/2023] [Indexed: 04/15/2023] Open
Abstract
Cancer patients, due to their immunocompromised status, are at an increased risk for severe SARS-CoV-2 infection. Since severe SARS-CoV-2 infection causes multiple organ damage through IL-6-mediated inflammation while stimulating hypoxia, and malignancy promotes hypoxia-induced cellular metabolic alterations leading to cell death, we propose a mechanistic interplay between both conditions that results in an upregulation of IL-6 secretion resulting in enhanced cytokine production and systemic injury. Hypoxia mediated by both conditions results in cell necrosis, dysregulation of oxidative phosphorylation, and mitochondrial dysfunction. This produces free radicals and cytokines that result in systemic inflammatory injury. Hypoxia also catalyzes the breakdown of COX-1 and 2 resulting in bronchoconstriction and pulmonary edema, which further exacerbates tissue hypoxia. Given this disease model, therapeutic options are currently being studied against severe SARS-COV-2. In this study, we review several promising therapies against severe disease supported by clinical trial evidence-including Allocetra, monoclonal antibodies (Tixagevimab-Cilgavimab), peginterferon lambda, Baricitinib, Remdesivir, Sarilumab, Tocilizumab, Anakinra, Bevacizumab, exosomes, and mesenchymal stem cells. Due to the virus's rapid adaptive evolution and diverse symptomatic manifestation, the use of combination therapies offers a promising approach to decrease systemic injury. By investing in such targeted interventions, cases of severe SARS-CoV-2 should decrease along with its associated long-term sequelae and thereby allow cancer patients to resume their treatments.
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Affiliation(s)
- Yan Leyfman
- Icahn School of Medicine at Mount Sinai South Nassau, Rockville Centre, NY, USA
| | - Nancy Emmanuel
- Hospital das Clínicas of the Faculty of Medicine of the University of São Paulo, São Paulo, Brazil
| | | | - Muskan Joshi
- Tbilisi State Medical University, Tbilisi, Georgia
| | | | | | | | | | - Pushpa Sharma
- Department of Anesthesiology, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD, 20814, USA.
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30
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Schijven JF, Wind M, Todt D, Howes J, Tamele B, Steinmann E. Risk assessment of banknotes as a fomite of SARS-CoV-2 in cash payment transactions. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2023; 43:700-708. [PMID: 35491413 PMCID: PMC9347741 DOI: 10.1111/risa.13935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
The COVID 19 pandemic has triggered concerns and assumptions globally about transmission of the SARS-CoV-2 virus via cash transactions. This paper assesses the risk of contracting COVID-19 through exposure to SARS-CoV-2 via cash acting as a fomite in payment transactions. A quantitative microbial risk assessment was conducted for a scenario assuming an infectious person at the onset of symptoms, when virion concentrations in coughed droplets are at their highest. This person then contaminates a banknote by coughing on it and immediately hands it over to another person, who might then be infected by transferring the virions with a finger from the contaminated banknote to a facial mucous membrane. The scenario considered transfer efficiency of virions on the banknote to fingertips when droplets were still wet and after having dried up and subsequently being touched by finger printing or rubbing the object. Accounting for the likelihood of the scenario to occur by considering (1) a local prevalence of 100 COVID-19 cases/100,000 persons, (2) a maximum of about one-fifth of infected persons transmit high virus loads, and (3) the numbers of cash transactions/person/day, the risk of contracting COVID-19 via person-to-person cash transactions was estimated to be much lower than once per 39,000 days (107 years) for a single person. In the general populace, there will be a maximum of 2.6 expected cases/100,000 persons/day. The risk for a cashier at an average point of sale was estimated to be much less than once per 430 working days (21 months). The depicted scenario is a rare event, therefore, for a single person, the risk of contracting COVID-19 via person-to-person cash transactions is very low. At a point of sale, the risk to the cashier proportionally increases but it is still low.
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Affiliation(s)
- Jack F. Schijven
- Centre for Infectious Disease ControlNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
- Department of Earth SciencesUtrecht UniversityUtrechtThe Netherlands
| | - Mark Wind
- Cash Policy DepartmentDe Nederlandsche BankAmsterdamThe Netherlands
| | - Daniel Todt
- Department of Molecular & Medical VirologyRuhr University BochumBochumGermany
- European Virus Bioinformatics Centre (EVBC)JenaGermany
| | - John Howes
- European Central Bank (ECB)Frankfurt am MainGermany
| | | | - Eike Steinmann
- Department of Molecular & Medical VirologyRuhr University BochumBochumGermany
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Terbot JW, Johri P, Liphardt SW, Soni V, Pfeifer SP, Cooper BS, Good JM, Jensen JD. Developing an appropriate evolutionary baseline model for the study of SARS-CoV-2 patient samples. PLoS Pathog 2023; 19:e1011265. [PMID: 37018331 PMCID: PMC10075409 DOI: 10.1371/journal.ppat.1011265] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2023] Open
Abstract
Over the past 3 years, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread through human populations in several waves, resulting in a global health crisis. In response, genomic surveillance efforts have proliferated in the hopes of tracking and anticipating the evolution of this virus, resulting in millions of patient isolates now being available in public databases. Yet, while there is a tremendous focus on identifying newly emerging adaptive viral variants, this quantification is far from trivial. Specifically, multiple co-occurring and interacting evolutionary processes are constantly in operation and must be jointly considered and modeled in order to perform accurate inference. We here outline critical individual components of such an evolutionary baseline model-mutation rates, recombination rates, the distribution of fitness effects, infection dynamics, and compartmentalization-and describe the current state of knowledge pertaining to the related parameters of each in SARS-CoV-2. We close with a series of recommendations for future clinical sampling, model construction, and statistical analysis.
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Affiliation(s)
- John W Terbot
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| | - Parul Johri
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| | - Schuyler W Liphardt
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Vivak Soni
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| | - Susanne P Pfeifer
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| | - Brandon S Cooper
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Jeffrey M Good
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Jeffrey D Jensen
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
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Viloria Winnett A, Akana R, Shelby N, Davich H, Caldera S, Yamada T, Reyna JRB, Romano AE, Carter AM, Kim MK, Thomson M, Tognazzini C, Feaster M, Goh YY, Chew YC, Ismagilov RF. Extreme differences in SARS-CoV-2 viral loads among respiratory specimen types during presumed pre-infectious and infectious periods. PNAS NEXUS 2023; 2:pgad033. [PMID: 36926220 PMCID: PMC10013338 DOI: 10.1093/pnasnexus/pgad033] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 01/18/2023] [Accepted: 01/24/2023] [Indexed: 03/16/2023]
Abstract
SARS-CoV-2 viral-load measurements from a single-specimen type are used to establish diagnostic strategies, interpret clinical-trial results for vaccines and therapeutics, model viral transmission, and understand virus-host interactions. However, measurements from a single-specimen type are implicitly assumed to be representative of other specimen types. We quantified viral-load timecourses from individuals who began daily self-sampling of saliva, anterior-nares (nasal), and oropharyngeal (throat) swabs before or at the incidence of infection with the Omicron variant. Viral loads in different specimen types from the same person at the same timepoint exhibited extreme differences, up to 109 copies/mL. These differences were not due to variation in sample self-collection, which was consistent. For most individuals, longitudinal viral-load timecourses in different specimen types did not correlate. Throat-swab and saliva viral loads began to rise as many as 7 days earlier than nasal-swab viral loads in most individuals, leading to very low clinical sensitivity of nasal swabs during the first days of infection. Individuals frequently exhibited presumably infectious viral loads in one specimen type while viral loads were low or undetectable in other specimen types. Therefore, defining an individual as infectious based on assessment of a single-specimen type underestimates the infectious period, and overestimates the ability of that specimen type to detect infectious individuals. For diagnostic COVID-19 testing, these three single-specimen types have low clinical sensitivity, whereas a combined throat-nasal swab, and assays with high analytical sensitivity, was inferred to have significantly better clinical sensitivity to detect presumed pre-infectious and infectious individuals.
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Affiliation(s)
| | - Reid Akana
- California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
| | - Natasha Shelby
- California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
| | - Hannah Davich
- California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
| | - Saharai Caldera
- California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
| | - Taikun Yamada
- Pangea Laboratory LLC, 14762 Bentley Cir, Tustin, CA 92780, USA.,Zymo Research Corp., 17062 Murphy Ave, Irvine, CA 92614, USA
| | | | - Anna E Romano
- California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
| | - Alyssa M Carter
- California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
| | - Mi Kyung Kim
- California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
| | - Matt Thomson
- California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
| | - Colten Tognazzini
- Pasadena Public Health Department, 1845 N. Fair Oaks Ave, Pasadena, CA 91103, USA
| | - Matthew Feaster
- Pasadena Public Health Department, 1845 N. Fair Oaks Ave, Pasadena, CA 91103, USA
| | - Ying-Ying Goh
- Pasadena Public Health Department, 1845 N. Fair Oaks Ave, Pasadena, CA 91103, USA
| | - Yap Ching Chew
- Pangea Laboratory LLC, 14762 Bentley Cir, Tustin, CA 92780, USA.,Zymo Research Corp., 17062 Murphy Ave, Irvine, CA 92614, USA
| | - Rustem F Ismagilov
- California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
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33
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Chen A, Wessler T, Gregory Forest M. Antibody protection from SARS-CoV-2 respiratory tract exposure and infection. J Theor Biol 2023; 557:111334. [PMID: 36306828 PMCID: PMC9597531 DOI: 10.1016/j.jtbi.2022.111334] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/12/2022] [Accepted: 10/18/2022] [Indexed: 11/06/2022]
Abstract
The COVID-19 pandemic has underscored the need to understand the dynamics of SARS-CoV-2 respiratory infection and protection provided by the immune response. SARS-CoV-2 infections are characterized by a particularly high viral load, and further by the small number of inhaled virions sufficient to generate a high viral titer in the nasal passage a few days after exposure. SARS-CoV-2 specific antibodies (Ab), induced from vaccines, previous infection, or inhaled monoclonal Ab, have proven effective against SARS-CoV-2 infection. Our goal in this work is to model the protective mechanisms that Ab can provide and to assess the degree of protection from individual and combined mechanisms at different locations in the respiratory tract. Neutralization, in which Ab bind to virion spikes and inhibit them from binding to and infecting target cells, is one widely reported protective mechanism. A second mechanism of Ab protection is muco-trapping, in which Ab crosslink virions to domains on mucin polymers, effectively immobilizing them in the mucus layer. When muco-trapped, the continuous clearance of the mucus barrier by coordinated ciliary propulsion entrains the trapped viral load toward the esophagus to be swallowed. We model and simulate the protection provided by either and both mechanisms at different locations in the respiratory tract, parametrized by the Ab titer and binding-unbinding rates of Ab to viral spikes and mucin domains. Our results illustrate limits in the degree of protection by neutralizing Ab alone, the powerful protection afforded by muco-trapping Ab, and the potential for dual protection by muco-trapping and neutralizing Ab to arrest a SARS-CoV-2 infection. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".
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Affiliation(s)
- Alex Chen
- Department of Mathematics, California State University-Dominguez Hills, Carson, CA 90747, USA.
| | - Timothy Wessler
- Department of Mathematics, University of North Carolina—Chapel Hill, Chapel Hill, NC 27599, USA
| | - M. Gregory Forest
- Department of Mathematics, University of North Carolina—Chapel Hill, Chapel Hill, NC 27599, USA,Department of Applied Physical Sciences, University of North Carolina—Chapel Hill, Chapel Hill, NC 27599, USA,UNC/NCSU Joint Department of Biomedical Engineering, University of North Carolina—Chapel Hill, Chapel Hill, NC 27599 and North Carolina State University, Raleigh, NC 27606, USA
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34
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Whitfield CA, Hall I. Modelling the impact of repeat asymptomatic testing policies for staff on SARS-CoV-2 transmission potential. J Theor Biol 2023; 557:111335. [PMID: 36334850 PMCID: PMC9626407 DOI: 10.1016/j.jtbi.2022.111335] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 10/16/2022] [Accepted: 10/18/2022] [Indexed: 11/06/2022]
Abstract
Repeat asymptomatic testing in order to identify and quarantine infectious individuals has become a widely-used intervention to control SARS-CoV-2 transmission. In some workplaces, and in particular health and social care settings with vulnerable patients, regular asymptomatic testing has been deployed to staff to reduce the likelihood of workplace outbreaks. We have developed a model based on data available in the literature to predict the potential impact of repeat asymptomatic testing on SARS-CoV-2 transmission. The results highlight features that are important to consider when modelling testing interventions, including population heterogeneity of infectiousness and correlation with test-positive probability, as well as adherence behaviours in response to policy. Furthermore, the model based on the reduction in transmission potential presented here can be used to parameterise existing epidemiological models without them having to explicitly simulate the testing process. Overall, we find that even with different model paramterisations, in theory, regular asymptomatic testing is likely to be a highly effective measure to reduce transmission in workplaces, subject to adherence. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".
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Affiliation(s)
- Carl A Whitfield
- Department of Mathematics, University of Manchester, United Kingdom.
| | - Ian Hall
- Department of Mathematics, University of Manchester, United Kingdom
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35
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Zhang Y, Britton T, Zhou X. Monitoring real-time transmission heterogeneity from incidence data. PLoS Comput Biol 2022; 18:e1010078. [PMID: 36455043 PMCID: PMC9746975 DOI: 10.1371/journal.pcbi.1010078] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 12/13/2022] [Accepted: 11/16/2022] [Indexed: 12/03/2022] Open
Abstract
The transmission heterogeneity of an epidemic is associated with a complex mixture of host, pathogen and environmental factors. And it may indicate superspreading events to reduce the efficiency of population-level control measures and to sustain the epidemic over a larger scale and a longer duration. Methods have been proposed to identify significant transmission heterogeneity in historic epidemics based on several data sources, such as contact history, viral genomes and spatial information, which may not be available, and more importantly ignore the temporal trend of transmission heterogeneity. Here we attempted to establish a convenient method to estimate real-time heterogeneity over an epidemic. Within the branching process framework, we introduced an instant-individualheterogenous infectiousness model to jointly characterize the variation in infectiousness both between individuals and among different times. With this model, we could simultaneously estimate the transmission heterogeneity and the reproduction number from incidence time series. We validated the model with data of both simulated and real outbreaks. Our estimates of the overall and real-time heterogeneities of the six epidemics were consistent with those presented in the literature. Additionally, our model is robust to the ubiquitous bias of under-reporting and misspecification of serial interval. By analyzing recent data from South Africa, we found evidence that the Omicron might be of more significant transmission heterogeneity than Delta. Our model based on incidence data was proved to be reliable in estimating the real-time transmission heterogeneity.
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Affiliation(s)
- Yunjun Zhang
- Department of Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Statistical Science, Peking University, Beijing, China
| | - Tom Britton
- Department of Mathematics, Stockholm University, Stockholm, Sweden
| | - Xiaohua Zhou
- Department of Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Statistical Science, Peking University, Beijing, China
- Beijing International Center for Mathematical Research, Peking University, Beijing, China
- School of Mathematical Sciences, Peking University, Beijing, China
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36
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Joseph J, Baby HM, Zhao S, Li X, Cheung K, Swain K, Agus E, Ranganathan S, Gao J, Luo JN, Joshi N. Role of bioaerosol in virus transmission and material-based countermeasures. EXPLORATION (BEIJING, CHINA) 2022; 2:20210038. [PMID: 37324804 PMCID: PMC10190935 DOI: 10.1002/exp.20210038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 04/15/2022] [Indexed: 06/17/2023]
Abstract
Respiratory pathogens transmit primarily through particles such as droplets and aerosols. Although often overlooked, the resuspension of settled droplets is also a key facilitator of disease transmission. In this review, we discuss the three main mechanisms of aerosol generation: direct generation such as coughing and sneezing, indirect generation such as medical procedures, and resuspension of settled droplets and aerosols. The size of particles and environmental factors influence their airborne lifetime and ability to cause infection. Specifically, humidity and temperature are key factors controlling the evaporation of suspended droplets, consequently affecting the duration in which particles remain airborne. We also suggest material-based approaches for effective prevention of disease transmission. These approaches include electrostatically charged virucidal agents and surface coatings, which have been shown to be highly effective in deactivating and reducing resuspension of pathogen-laden aerosols.
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Affiliation(s)
- John Joseph
- Center for Nanomedicine, Department of AnesthesiologyPerioperative and Pain Medicine, Brigham and Women's HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
| | - Helna Mary Baby
- Center for Nanomedicine, Department of AnesthesiologyPerioperative and Pain Medicine, Brigham and Women's HospitalBostonMassachusettsUSA
| | - Spencer Zhao
- Center for Nanomedicine, Department of AnesthesiologyPerioperative and Pain Medicine, Brigham and Women's HospitalBostonMassachusettsUSA
| | - Xiang‐Ling Li
- Center for Nanomedicine, Department of AnesthesiologyPerioperative and Pain Medicine, Brigham and Women's HospitalBostonMassachusettsUSA
| | - Krisco‐Cheuk Cheung
- Center for Nanomedicine, Department of AnesthesiologyPerioperative and Pain Medicine, Brigham and Women's HospitalBostonMassachusettsUSA
| | - Kabir Swain
- Center for Nanomedicine, Department of AnesthesiologyPerioperative and Pain Medicine, Brigham and Women's HospitalBostonMassachusettsUSA
| | - Eli Agus
- Center for Nanomedicine, Department of AnesthesiologyPerioperative and Pain Medicine, Brigham and Women's HospitalBostonMassachusettsUSA
| | - Sruthi Ranganathan
- Center for Nanomedicine, Department of AnesthesiologyPerioperative and Pain Medicine, Brigham and Women's HospitalBostonMassachusettsUSA
| | - Jingjing Gao
- Center for Nanomedicine, Department of AnesthesiologyPerioperative and Pain Medicine, Brigham and Women's HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
| | - James N Luo
- Harvard Medical SchoolBostonMassachusettsUSA
- Department of SurgeryBrigham and Women's HospitalBostonMassachusettsUSA
| | - Nitin Joshi
- Center for Nanomedicine, Department of AnesthesiologyPerioperative and Pain Medicine, Brigham and Women's HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
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37
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Rife Magalis B, Rich S, Tagliamonte MS, Mavian C, Cash MN, Riva A, Marini S, Amador DM, Zhang Y, Shapiro J, Horine A, Starostik P, Pieretti M, Vega S, Paula Lacombe A, Salinas J, Stevenson M, Myers P, Glenn Morris J, Lauzardo M, Prosperi M, Salemi M. Severe Acute Respiratory Syndrome Coronavirus 2 Delta Vaccine Breakthrough Transmissibility in Alachua County, Florida. Clin Infect Dis 2022; 75:1618-1627. [PMID: 35271704 PMCID: PMC9617581 DOI: 10.1093/cid/ciac197] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant has caused a dramatic resurgence in infections in the United Sates, raising questions regarding potential transmissibility among vaccinated individuals. METHODS Between October 2020 and July 2021, we sequenced 4439 SARS-CoV-2 full genomes, 23% of all known infections in Alachua County, Florida, including 109 vaccine breakthrough cases. Univariate and multivariate regression analyses were conducted to evaluate associations between viral RNA burden and patient characteristics. Contact tracing and phylogenetic analysis were used to investigate direct transmissions involving vaccinated individuals. RESULTS The majority of breakthrough sequences with lineage assignment were classified as Delta variants (74.6%) and occurred, on average, about 3 months (104 ± 57.5 days) after full vaccination, at the same time (June-July 2021) of Delta variant exponential spread within the county. Six Delta variant transmission pairs between fully vaccinated individuals were identified through contact tracing, 3 of which were confirmed by phylogenetic analysis. Delta breakthroughs exhibited broad viral RNA copy number values during acute infection (interquartile range, 1.2-8.64 Log copies/mL), on average 38% lower than matched unvaccinated patients (3.29-10.81 Log copies/mL, P < .00001). Nevertheless, 49% to 50% of all breakthroughs, and 56% to 60% of Delta-infected breakthroughs exhibited viral RNA levels above the transmissibility threshold (4 Log copies/mL) irrespective of time after vaccination. CONCLUSIONS Delta infection transmissibility and general viral RNA quantification patterns in vaccinated individuals suggest limited levels of sterilizing immunity that need to be considered by public health policies. In particular, ongoing evaluation of vaccine boosters should specifically address whether extra vaccine doses curb breakthrough contribution to epidemic spread.
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Affiliation(s)
- Brittany Rife Magalis
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Pathology, University of Florida, Gainesville, Florida, USA
| | - Shannan Rich
- Department of Epidemiology, University of Florida, Gainesville, Florida, USA
- Florida Department of Health, Alachua County, Gainesville, Florida, USA
| | - Massimiliano S Tagliamonte
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Pathology, University of Florida, Gainesville, Florida, USA
| | - Carla Mavian
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Pathology, University of Florida, Gainesville, Florida, USA
| | - Melanie N Cash
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Pathology, University of Florida, Gainesville, Florida, USA
| | - Alberto Riva
- Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, Florida, USA
| | - Simone Marini
- Department of Pathology, University of Florida, Gainesville, Florida, USA
- Department of Epidemiology, University of Florida, Gainesville, Florida, USA
| | - David Moraga Amador
- Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, Florida, USA
| | - Yanping Zhang
- Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, Florida, USA
| | - Jerne Shapiro
- Department of Epidemiology, University of Florida, Gainesville, Florida, USA
- Florida Department of Health, Alachua County, Gainesville, Florida, USA
| | - Amelia Horine
- Florida Department of Health, Alachua County, Gainesville, Florida, USA
| | - Petr Starostik
- Department of Pathology, University of Florida, Gainesville, Florida, USA
| | | | | | | | - Jessica Salinas
- University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Mario Stevenson
- University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Paul Myers
- Florida Department of Health, Alachua County, Gainesville, Florida, USA
| | - J Glenn Morris
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida
| | - Michael Lauzardo
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Florida Department of Health, Alachua County, Gainesville, Florida, USA
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida
| | - Mattia Prosperi
- Department of Epidemiology, University of Florida, Gainesville, Florida, USA
| | - Marco Salemi
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Pathology, University of Florida, Gainesville, Florida, USA
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38
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Salvagno GL, Henry BM, de NS, Pighi L, Lippi G. Association between viral load and positivization time of a SARS-CoV-2 rapid antigen test in routine nasopharyngeal specimens. J Med Biochem 2022; 41:513-517. [PMID: 36381068 PMCID: PMC9618342 DOI: 10.5937/jomb0-35482] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 01/25/2022] [Indexed: 10/29/2023] Open
Abstract
BACKGROUND Rapid SARS-CoV-2 antigen tests are potentially useful tools for screening carriers with high viral load. This study was aimed to assess the potential association between viral load and positivization time of a manual SARS-CoV-2 commercial antigen test in routine nasopharyngeal specimens. METHODS In a sample of subjects undergoing routine diagnostic testing, SARS-CoV-2 positivity of nasopharyngeal samples was assayed with both molecular (Altona Diagnostics RealStar SARS-CoV-2 RT-PCR Kit) and antigenic (Roche SARS-CoV-2 Rapid Antigen Test) tests. Positivization time of rapid antigen test was correlated and compared with viral load expressed as mean of SARS-CoV2 E/S genes cycle threshold (Ct) values. RESULTS The study sample consisted of 106 patients (median age 48 years, 55 women) with positive results of rapid SARS-CoV-2 antigen testing. A highly significant Spearman's correlation was found between mean SARSCoV-2 E/S genes Ct values and positivization time of manual antigen test (r= 0.70; p<0.001). The positivization time of rapid SARS-CoV-2 antigen test displayed an area under the curve of 0.82 (95%CI, 0.74-0.89) for predicting nasopharyngeal samples with high viral load (i.e., mean Ct <20). A positivization time cut-off of 32 SEC had 94.9% sensitivity and 58.2% specificity for detecting specimens with high viral load. The overall agreement between mean Ct value <20 and positivization time <32 SEC was 70.8%. CONCLUSIONS Positivization time of rapid SARS-CoV-2 antigen tests may provide easy and rapid information on viral load, thus making this type of manual assay potentially suitable for quick and reliable detection and isolation of supercarriers.
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Affiliation(s)
| | - Brandon M. Henry
- Cincinnati Children's Hospital Medical Center, Division of Nephrology and Hypertension, Clinical Laboratory, Cincinnati, United States of America
| | - Nitto Simone de
- University of Verona, Section of Clinical Biochemistry, Verona, Italy
| | - Laura Pighi
- University of Verona, Section of Clinical Biochemistry, Verona, Italy
| | - Giuseppe Lippi
- University of Verona, Section of Clinical Biochemistry, Verona, Italy
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Prioritizing interventions for preventing COVID-19 outbreaks in military basic training. PLoS Comput Biol 2022; 18:e1010489. [PMID: 36206315 PMCID: PMC9581358 DOI: 10.1371/journal.pcbi.1010489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 10/19/2022] [Accepted: 08/12/2022] [Indexed: 11/05/2022] Open
Abstract
Like other congregate living settings, military basic training has been subject to outbreaks of COVID-19. We sought to identify improved strategies for preventing outbreaks in this setting using an agent-based model of a hypothetical cohort of trainees on a U.S. Army post. Our analysis revealed unique aspects of basic training that require customized approaches to outbreak prevention, which draws attention to the possibility that customized approaches may be necessary in other settings, too. In particular, we showed that introductions by trainers and support staff may be a major vulnerability, given that those individuals remain at risk of community exposure throughout the training period. We also found that increased testing of trainees upon arrival could actually increase the risk of outbreaks, given the potential for false-positive test results to lead to susceptible individuals becoming infected in group isolation and seeding outbreaks in training units upon release. Until an effective transmission-blocking vaccine is adopted at high coverage by individuals involved with basic training, need will persist for non-pharmaceutical interventions to prevent outbreaks in military basic training. Ongoing uncertainties about virus variants and breakthrough infections necessitate continued vigilance in this setting, even as vaccination coverage increases.
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40
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Waites W, Cavaliere M, Danos V, Datta R, Eggo RM, Hallett TB, Manheim D, Panovska-Griffiths J, Russell TW, Zarnitsyna VI. Compositional modelling of immune response and virus transmission dynamics. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2022; 380:20210307. [PMID: 35965463 PMCID: PMC9376723 DOI: 10.1098/rsta.2021.0307] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Transmission models for infectious diseases are typically formulated in terms of dynamics between individuals or groups with processes such as disease progression or recovery for each individual captured phenomenologically, without reference to underlying biological processes. Furthermore, the construction of these models is often monolithic: they do not allow one to readily modify the processes involved or include the new ones, or to combine models at different scales. We show how to construct a simple model of immune response to a respiratory virus and a model of transmission using an easily modifiable set of rules allowing further refining and merging the two models together. The immune response model reproduces the expected response curve of PCR testing for COVID-19 and implies a long-tailed distribution of infectiousness reflective of individual heterogeneity. This immune response model, when combined with a transmission model, reproduces the previously reported shift in the population distribution of viral loads along an epidemic trajectory. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.
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Affiliation(s)
- W. Waites
- Department of Computer and Information Sciences, University of Strathclyde, Glasgow, UK
- Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, UK
| | - M. Cavaliere
- Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, UK
| | - V. Danos
- Département d’Informatique, École Normale Supérieure, Paris, France
| | - R. Datta
- Datta Enterprises LLC, San Francisco, CA, USA
| | - R. M. Eggo
- Department of Computer and Information Sciences, University of Strathclyde, Glasgow, UK
| | - T. B. Hallett
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - D. Manheim
- Technion, Israel Institute of Technology, Haifa, Israel
| | - J. Panovska-Griffiths
- The Big Data Institute and the Pandemic Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- The Queen’s College, University of Oxford, Oxford, UK
| | - T. W. Russell
- Department of Computer and Information Sciences, University of Strathclyde, Glasgow, UK
| | - V. I. Zarnitsyna
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA, USA
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41
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Costa GS, Cota W, Ferreira SC. Data-driven approach in a compartmental epidemic model to assess undocumented infections. CHAOS, SOLITONS, AND FRACTALS 2022; 163:112520. [PMID: 35996714 PMCID: PMC9385215 DOI: 10.1016/j.chaos.2022.112520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 07/27/2022] [Accepted: 07/29/2022] [Indexed: 06/15/2023]
Abstract
Nowcasting and forecasting of epidemic spreading rely on incidence series of reported cases to derive the fundamental epidemiological parameters for a given pathogen. Two relevant drawbacks for predictions are the unknown fractions of undocumented cases and levels of nonpharmacological interventions, which span highly heterogeneously across different places and times. We describe a simple data-driven approach using a compartmental model including asymptomatic and pre-symptomatic contagions that allows to estimate both the level of undocumented infections and the value of effective reproductive number R t from time series of reported cases, deaths, and epidemiological parameters. The method was applied to epidemic series for COVID-19 across different municipalities in Brazil allowing to estimate the heterogeneity level of under-reporting across different places. The reproductive number derived within the current framework is little sensitive to both diagnosis and infection rates during the asymptomatic states. The methods described here can be extended to more general cases if data is available and adapted to other epidemiological approaches and surveillance data.
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Affiliation(s)
- Guilherme S Costa
- Departamento de Física, Universidade Federal de Viçosa, 36570-900, Viçosa, MG, Brazil
| | - Wesley Cota
- Departamento de Física, Universidade Federal de Viçosa, 36570-900, Viçosa, MG, Brazil
| | - Silvio C Ferreira
- Departamento de Física, Universidade Federal de Viçosa, 36570-900, Viçosa, MG, Brazil
- National Institute of Science and technology for Complex Systems, Centro Brasileiro de Pesquisas Físicas, Rua Xavier Sigaud 150, 22290-180, Rio de Janeiro, Brazil
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42
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Bashor L, Gagne RB, Bosco-Lauth A, Stenglein M, VandeWoude S. Rapid evolution of SARS-CoV-2 in domestic cats. Virus Evol 2022; 8:veac092. [PMID: 36398096 PMCID: PMC9619536 DOI: 10.1093/ve/veac092] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 09/05/2022] [Accepted: 09/29/2022] [Indexed: 11/26/2023] Open
Abstract
SARS-CoV-2 (SARS2) infection of a novel permissive host species can result in rapid viral evolution. Data suggest that felids are highly susceptible to SARS2 infection, and species-specific adaptation following human-to-felid transmission may occur. We employed experimental infection and analysis of publicly available SARS2 sequences to observe variant emergence and selection in domestic cats. Three cohorts of cats (N = 23) were inoculated with SARS-CoV-2 USA-WA1/2020 or infected via cat-to-cat contact transmission. Full viral genomes were recovered from RNA obtained from nasal washes 1-3 days post-infection and analyzed for within-host viral variants. We detected 118 unique variants at ≥3 per cent allele frequency in two technical replicates. Seventy of these (59 per cent) were nonsynonymous single nucleotide variants (SNVs); the remainder were synonymous SNVs or structural variants. On average, we observed twelve variants per cat, nearly 10-fold higher than what is commonly reported in human patients. We observed signatures of positive selection in the spike protein and the emergence of eleven within-host variants located at the same genomic positions as mutations in SARS2 variant lineages that have emerged during the pandemic. Fewer variants were noted in cats infected from contact with other cats and in cats exposed to lower doses of cultured inoculum. An analysis of ninety-three publicly available SARS2 consensus genomes recovered from naturally infected domestic cats reflected variant lineages circulating in the local human population at the time of sampling, illustrating that cats are susceptible to SARS2 variants that have emerged in humans, and suggesting human-to-felid transmission occurring in domestic settings is typically unidirectional. These experimental results underscore the rapidity of SARS2 adaptation in felid hosts, representing a theoretical potential origin for variant lineages in human populations. Further, cats should be considered susceptible hosts capable of shedding virus during infections occurring within households.
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Affiliation(s)
- Laura Bashor
- College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Roderick B Gagne
- Department of Pathobiology, Wildlife Futures Program, University of Pennsylvania School of Veterinary Medicine, New Bolton Center, Kenneth Square, Pennsylvania, USA
| | - Angela Bosco-Lauth
- College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Mark Stenglein
- College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Sue VandeWoude
- College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, Colorado, USA
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43
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Pharmacometric Modeling of the Impact of Azelastine Nasal Spray on SARS-CoV-2 Viral Load and Related Symptoms in COVID-19 Patients. Pharmaceutics 2022; 14:pharmaceutics14102059. [PMID: 36297492 PMCID: PMC9609097 DOI: 10.3390/pharmaceutics14102059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 09/19/2022] [Accepted: 09/20/2022] [Indexed: 11/17/2022] Open
Abstract
The histamine-1 receptor antagonist azelastine was recently found to impact SARS-CoV-2 viral kinetics in a Phase 2 clinical trial (CARVIN). Thus, we investigated the relationship between intranasal azelastine administrations and viral load, as well as symptom severity in COVID-19 patients and analyzed the impact of covariates using non-linear mixed-effects modeling. For this, we developed a pharmacokinetic (PK) model for the oral and intranasal administration of azelastine. A one-compartment model with parallel absorption after intranasal administration described the PK best, covering both the intranasal and the gastro-intestinal absorption pathways. For virus kinetic and symptoms modeling, viral load and symptom records were gathered from the CARVIN study that included data of 82 COVID-19 patients receiving placebo or intranasal azelastine. The effect of azelastine on viral load was described by a dose–effect model targeting the virus elimination rate. An extension of the model revealed a relationship between COVID-19 symptoms severity and the number of infected cells. The analysis revealed that the intranasal administration of azelastine led to a faster decline in viral load and symptoms severity compared to placebo. Moreover, older patients showed a slower decline in viral load compared to younger patients and male patients experienced higher peak viral loads than females.
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44
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A single-administration therapeutic interfering particle reduces SARS-CoV-2 viral shedding and pathogenesis in hamsters. Proc Natl Acad Sci U S A 2022; 119:e2204624119. [PMID: 36074824 PMCID: PMC9522362 DOI: 10.1073/pnas.2204624119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The high transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a primary driver of the COVID-19 pandemic. While existing interventions prevent severe disease, they exhibit mixed efficacy in preventing transmission, presumably due to their limited antiviral effects in the respiratory mucosa, whereas interventions targeting the sites of viral replication might more effectively limit respiratory virus transmission. Recently, intranasally administered RNA-based therapeutic interfering particles (TIPs) were reported to suppress SARS-CoV-2 replication, exhibit a high barrier to resistance, and prevent serious disease in hamsters. Since TIPs intrinsically target the tissues with the highest viral replication burden (i.e., respiratory tissues for SARS-CoV-2), we tested the potential of TIP intervention to reduce SARS-CoV-2 shedding. Here, we report that a single, postexposure TIP dose lowers SARS-CoV-2 nasal shedding, and at 5 days postinfection, infectious virus shed is below detection limits in 4 out of 5 infected animals. Furthermore, TIPs reduce shedding of Delta variant or WA-1 from infected to uninfected hamsters. Cohoused "contact" animals exposed to infected, TIP-treated animals exhibited significantly lower viral loads, reduced inflammatory cytokines, no severe lung pathology, and shortened shedding duration compared to animals cohoused with untreated infected animals. TIPs may represent an effective countermeasure to limit SARS-CoV-2 transmission.
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45
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Lamarca AP, de Almeida LGP, Francisco RDS, Cavalcante L, Brustolini O, Gerber AL, Guimarães APDC, de Oliveira TH, dos Santos Nascimento ÉR, Policarpo C, de Souza IV, de Carvalho EM, Ribeiro MS, Carvalho S, Dias da Silva F, de Oliveira Garcia MH, de Souza LM, Da Silva CG, Ribeiro CLP, Cavalcanti AC, de Mello CMB, Tanuri A, Vasconcelos ATRD. Phylodynamic analysis of SARS-CoV-2 spread in Rio de Janeiro, Brazil, highlights how metropolitan areas act as dispersal hubs for new variants. Microb Genom 2022; 8. [DOI: 10.1099/mgen.0.000859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
During the first semester of 2021, all of Brazil has suffered an intense wave of COVID-19 associated with the Gamma variant. In July, the first cases of Delta variant were detected in the state of Rio de Janeiro. In this work, we have employed phylodynamic methods to analyse more than 1 600 genomic sequences of Delta variant collected until September in Rio de Janeiro to reconstruct how this variant has surpassed Gamma and dispersed throughout the state. After the introduction of Delta, it has initially spread mostly in the homonymous city of Rio de Janeiro, the most populous of the state. In a second stage, dispersal occurred to mid- and long-range cities, which acted as new close-range hubs for spread. We observed that the substitution of Gamma by Delta was possibly caused by its higher viral load, a proxy for transmissibility. This variant turnover prompted a new surge in cases, but with lower lethality than was observed during the peak caused by Gamma. We reason that high vaccination rates in the state of Rio de Janeiro were possibly what prevented a higher number of deaths.
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Affiliation(s)
- Alessandra Pavan Lamarca
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Luiz G. P. de Almeida
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | | | - Liliane Cavalcante
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Otávio Brustolini
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Alexandra L. Gerber
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | | | - Thiago Henrique de Oliveira
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Cintia Policarpo
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | | | | | - Silvia Carvalho
- Secretaria Estadual de Saúde do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | | | | | | | | | - Andréa Cony Cavalcanti
- Departamento de Virologia, Instituto de Microbiologia Paulo de Góes, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
- Laboratório Central de Saúde Pública Noel Nutels, Rio de Janeiro, Brazil
| | | | - Amilcar Tanuri
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
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46
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Ciupe SM, Tuncer N. Identifiability of parameters in mathematical models of SARS-CoV-2 infections in humans. Sci Rep 2022; 12:14637. [PMID: 36030320 PMCID: PMC9418662 DOI: 10.1038/s41598-022-18683-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 08/16/2022] [Indexed: 12/12/2022] Open
Abstract
Determining accurate estimates for the characteristics of the severe acute respiratory syndrome coronavirus 2 in the upper and lower respiratory tracts, by fitting mathematical models to data, is made difficult by the lack of measurements early in the infection. To determine the sensitivity of the parameter estimates to the noise in the data, we developed a novel two-patch within-host mathematical model that considered the infection of both respiratory tracts and assumed that the viral load in the lower respiratory tract decays in a density dependent manner and investigated its ability to match population level data. We proposed several approaches that can improve practical identifiability of parameters, including an optimal experimental approach, and found that availability of viral data early in the infection is of essence for improving the accuracy of the estimates. Our findings can be useful for designing interventions.
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Affiliation(s)
- Stanca M Ciupe
- Department of Mathematics, Virginia Polytechnic Institute and State University, 225 Stanger Street, Blacksburg, VA, 24060, USA.
| | - Necibe Tuncer
- Department of Mathematics, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
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47
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A single-administration therapeutic interfering particle reduces SARS-CoV-2 viral shedding and pathogenesis in hamsters. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2022. [PMID: 35982679 DOI: 10.1101/2022.08.10.503534] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The high transmissibility of SARS-CoV-2 is a primary driver of the COVID-19 pandemic. While existing interventions prevent severe disease, they exhibit mixed efficacy in preventing transmission, presumably due to their limited antiviral effects in the respiratory mucosa, whereas interventions targeting the sites of viral replication might more effectively limit respiratory virus transmission. Recently, intranasally administered RNA-based therapeutic interfering particles (TIPs) were reported to suppress SARS-CoV-2 replication, exhibit a high barrier to resistance, and prevent serious disease in hamsters. Since TIPs intrinsically target the tissues with the highest viral replication burden (i.e., respiratory tissues for SARS-CoV-2), we tested the potential of TIP intervention to reduce SARS-CoV-2 shedding. Here, we report that a single, post-exposure TIP dose lowers SARS-CoV-2 nasal shedding and at 5 days post-infection infectious virus shed is below detection limits in 4 out of 5 infected animals. Furthermore, TIPs reduce shedding of Delta variant or WA-1 from infected to uninfected hamsters. Co-housed 'contact' animals exposed to infected, TIP-treated, animals exhibited significantly lower viral loads, reduced inflammatory cytokines, no severe lung pathology, and shortened shedding duration compared to animals co-housed with untreated infected animals. TIPs may represent an effective countermeasure to limit SARS-CoV-2 transmission. Significance COVID-19 vaccines are exceptionally effective in preventing severe disease and death, but they have mixed efficacy in preventing virus transmission, consistent with established literature that parenteral vaccines for other viruses fail to prevent mucosal virus shedding or transmission. Likewise, small-molecule antivirals, while effective in reducing viral-disease pathogenesis, also appear to have inconsistent efficacy in preventing respiratory virus transmission including for SARS-CoV-2. Recently, we reported the discovery of a single-administration antiviral Therapeutic Interfering Particle (TIP) against SARS-CoV-2 that prevents severe disease in hamsters and exhibits a high genetic barrier to the evolution of resistance. Here, we report that TIP intervention also reduces SARS-CoV-2 transmission between hamsters.
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48
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Hu Y, Buehler MJ. Nanomechanical analysis of SARS-CoV-2 variants and predictions of infectiousness and lethality. SOFT MATTER 2022; 18:5833-5842. [PMID: 35899933 PMCID: PMC9364333 DOI: 10.1039/d1sm01181b] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 07/20/2022] [Indexed: 06/15/2023]
Abstract
As variants of the pathogen that causes COVID-19 spread around the world, estimates of infectiousness and lethality of newly emerging strains are important. Here we report a predictive model that associates molecular motions and vibrational patterns of the virus spike protein with infectiousness and lethality. The key finding is that most SARS-CoV-2 variants are predicted to be more infectious and less lethal compared to the original spike protein. However, lineage B.1.351 (Beta variant) is predicted to be less infectious and more lethal, and lineage B.1.1.7 (Alpha variant) is predicted to have both higher infectivity and lethality, showing the potential of the virus to mutate towards different performance regimes. The relatively more recent lineage B.1.617.2 (Delta variant), although contains a few key spike mutations other than D614G, behaves quite similar to the single D614G mutation in both vibrational and predicted epidemiological aspects, which might explain its rapid circulation given the prevalence of D614G. This work may provide a tool to estimate the epidemiological effects of new variants, and offer a pathway to screen mutations against high threat levels. Moreover, the nanomechanical approach, as a novel tool to predict virus-cell interactions, may further open up the door towards better understanding other viruses.
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Affiliation(s)
- Yiwen Hu
- Laboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA.
- Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA
| | - Markus J Buehler
- Laboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA.
- Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA
- Center for Computational Science and Engineering, Schwarzman College of Computing, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA
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49
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Heitzman-Breen N, Ciupe SM. Modeling within-host and aerosol dynamics of SARS-CoV-2: The relationship with infectiousness. PLoS Comput Biol 2022; 18:e1009997. [PMID: 35913988 PMCID: PMC9371288 DOI: 10.1371/journal.pcbi.1009997] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 08/11/2022] [Accepted: 07/09/2022] [Indexed: 12/19/2022] Open
Abstract
The relationship between transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the amount of virus present in the proximity of a susceptible host is not understood. Here, we developed a within-host and aerosol mathematical model and used it to determine the relationship between viral kinetics in the upper respiratory track, viral kinetics in the aerosols, and new transmissions in golden hamsters challenged with SARS-CoV-2. We determined that infectious virus shedding early in infection correlates with transmission events, shedding of infectious virus diminishes late in the infection, and high viral RNA levels late in the infection are a poor indicator of transmission. We further showed that viral infectiousness increases in a density dependent manner with viral RNA and that their relative ratio is time-dependent. Such information is useful for designing interventions. Quantifying the relationship between SARS-CoV-2 dynamics in upper respiratory tract and in aerosols is key to understanding SARS-CoV-2 transmission and evaluating intervention strategies. Of particular interest is the link between the viral RNA measured by PCR and a subject’s infectiousness. Here, we developed a mechanistic model of viral transmission in golden hamsters and used data in upper respiratory tract and aerosols to evaluate key within-host and environment based viral parameters. The significance of our research is in identifying the timing and duration of viral shedding, how long it stays infectious, and the link between infectious virus and total viral RNA. Such knowledge enhances our understanding of the SARS-CoV-2 transmission window.
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Affiliation(s)
- Nora Heitzman-Breen
- Department of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America
| | - Stanca M. Ciupe
- Department of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America
- * E-mail:
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50
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Kuylen EJ, Torneri A, Willem L, Libin PJK, Abrams S, Coletti P, Franco N, Verelst F, Beutels P, Liesenborgs J, Hens N. Different forms of superspreading lead to different outcomes: Heterogeneity in infectiousness and contact behavior relevant for the case of SARS-CoV-2. PLoS Comput Biol 2022; 18:e1009980. [PMID: 35994497 PMCID: PMC9436127 DOI: 10.1371/journal.pcbi.1009980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 09/01/2022] [Accepted: 06/29/2022] [Indexed: 11/18/2022] Open
Abstract
Superspreading events play an important role in the spread of several pathogens, such as SARS-CoV-2. While the basic reproduction number of the original Wuhan SARS-CoV-2 is estimated to be about 3 for Belgium, there is substantial inter-individual variation in the number of secondary cases each infected individual causes-with most infectious individuals generating no or only a few secondary cases, while about 20% of infectious individuals is responsible for 80% of new infections. Multiple factors contribute to the occurrence of superspreading events: heterogeneity in infectiousness, individual variations in susceptibility, differences in contact behavior, and the environment in which transmission takes place. While superspreading has been included in several infectious disease transmission models, research into the effects of different forms of superspreading on the spread of pathogens remains limited. To disentangle the effects of infectiousness-related heterogeneity on the one hand and contact-related heterogeneity on the other, we implemented both forms of superspreading in an individual-based model describing the transmission and spread of SARS-CoV-2 in a synthetic Belgian population. We considered its impact on viral spread as well as on epidemic resurgence after a period of social distancing. We found that the effects of superspreading driven by heterogeneity in infectiousness are different from the effects of superspreading driven by heterogeneity in contact behavior. On the one hand, a higher level of infectiousness-related heterogeneity results in a lower risk of an outbreak persisting following the introduction of one infected individual into the population. Outbreaks that did persist led to fewer total cases and were slower, with a lower peak which occurred at a later point in time, and a lower herd immunity threshold. Finally, the risk of resurgence of an outbreak following a period of lockdown decreased. On the other hand, when contact-related heterogeneity was high, this also led to fewer cases in total during persistent outbreaks, but caused outbreaks to be more explosive in regard to other aspects (such as higher peaks which occurred earlier, and a higher herd immunity threshold). Finally, the risk of resurgence of an outbreak following a period of lockdown increased. We found that these effects were conserved when testing combinations of infectiousness-related and contact-related heterogeneity.
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Affiliation(s)
- Elise J. Kuylen
- Centre for Health Economic Research and Modeling Infectious Diseases, University of Antwerp, Antwerp, Belgium
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Andrea Torneri
- Centre for Health Economic Research and Modeling Infectious Diseases, University of Antwerp, Antwerp, Belgium
| | - Lander Willem
- Centre for Health Economic Research and Modeling Infectious Diseases, University of Antwerp, Antwerp, Belgium
| | - Pieter J. K. Libin
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
- Artificial Intelligence Lab, Vrije Universiteit Brussel, Brussels, Belgium
- Rega Institute for Medical Research, Clinical and Epidemiological Virology, University of Leuven, Leuven, Belgium
| | - Steven Abrams
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
- Global Health Institute, University of Antwerp, Antwerp, Belgium
| | - Pietro Coletti
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Nicolas Franco
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
- Namur Institute for Complex Systems, Department of Mathematics, University of Namur, Namur, Belgium
| | - Frederik Verelst
- Centre for Health Economic Research and Modeling Infectious Diseases, University of Antwerp, Antwerp, Belgium
| | - Philippe Beutels
- Centre for Health Economic Research and Modeling Infectious Diseases, University of Antwerp, Antwerp, Belgium
- School of Public Health and Community Medicine, The University of New South Wales, Sydney, NSW, Australia
| | - Jori Liesenborgs
- Expertise Centre for Digital Media, Hasselt University - transnational University Limburg, Hasselt, Belgium
| | - Niel Hens
- Centre for Health Economic Research and Modeling Infectious Diseases, University of Antwerp, Antwerp, Belgium
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
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