Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period

There is an urgent need to project how transmission of the novel betacoronavirus SARS-CoV-2 will unfold in coming years. These dynamics will depend on seasonality, the duration of immunity, and the strength of cross-immunity to/from the other human coronaviruses. Using data from the United States, we measured how these factors affect transmission of human betacoronaviruses HCoV-OC43 and HCoV-HKU1. We then built a mathematical model to simulate transmission of SARS-CoV-2 through the year 2025. We project that recurrent wintertime outbreaks of SARS-CoV-2 will probably occur after an initial pandemic wave. We summarize the full range of plausible transmission scenarios and identify key data still needed to distinguish between them, most importantly longitudinal serological studies to determine the duration of immunity to SARS-CoV-2.

[1]  Richard J. Beckman,et al.  A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code , 2000, Technometrics.

[2]  J. Shaman,et al.  Direct Measurement of Rates of Asymptomatic Infection and Clinical Care-Seeking for Seasonal Coronavirus , 2020, medRxiv.

[3]  Marie E Killerby,et al.  Human coronavirus circulation in the United States 2014–2017 , 2018, Journal of Clinical Virology.

[4]  N. Linton,et al.  Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data , 2020, medRxiv.

[5]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[6]  M. Lipsitch,et al.  How generation intervals shape the relationship between growth rates and reproductive numbers , 2007, Proceedings of the Royal Society B: Biological Sciences.

[7]  N. Messonnier,et al.  Transcript for the CDC telebriefing update on COVID-19 : press briefing transcript : Wednesday, March 10, 2020 , 2020 .

[8]  Marc Lipsitch,et al.  Absolute humidity and pandemic versus epidemic influenza. , 2011, American journal of epidemiology.

[9]  C. Dolea,et al.  World Health Organization , 1949, International Organization.

[10]  J. Wallinga,et al.  Different Epidemic Curves for Severe Acute Respiratory Syndrome Reveal Similar Impacts of Control Measures , 2004, American journal of epidemiology.

[11]  C. Tse,et al.  Global Spatio-temporal Patterns of Influenza in the Post-pandemic Era , 2014, Scientific Reports.

[12]  Cécile Viboud,et al.  Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States , 2010, PLoS biology.

[13]  Zunyou Wu,et al.  Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. , 2020, JAMA.

[14]  Herman Tse,et al.  Cross-reactive antibodies in convalescent SARS patients' sera against the emerging novel human coronavirus EMC (2012) by both immunofluorescent and neutralizing antibody tests , 2013, Journal of Infection.

[15]  Jing Zhao,et al.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia , 2020, The New England journal of medicine.

[16]  C. Viboud,et al.  Characterizing the reproduction number of epidemics with early subexponential growth dynamics , 2016, Journal of The Royal Society Interface.

[17]  G. Gao,et al.  Epidemiology, Genetic Recombination, and Pathogenesis of Coronaviruses , 2016, Trends in Microbiology.

[18]  China Cdc Weekly.  The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19) — China, 2020 , 2020, China CDC weekly.

[19]  D. Cummings,et al.  Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictions , 2020, medRxiv.

[20]  P. Lemey,et al.  Complete Genomic Sequence of Human Coronavirus OC43: Molecular Clock Analysis Suggests a Relatively Recent Zoonotic Coronavirus Transmission Event , 2005, Journal of Virology.

[21]  M. Peiris,et al.  SARS legacy: outbreak reporting is expected and respected , 2013, The Lancet.

[22]  Marc Lipsitch,et al.  The US 2009 A(H1N1) Influenza Epidemic: Quantifying the Impact of School Openings on the Reproductive Number , 2014, Epidemiology.

[23]  M. Drebot,et al.  An Outbreak of Human Coronavirus OC43 Infection and Serological Cross-reactivity with SARS Coronavirus. , 2006, The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale.

[24]  J. Robins,et al.  Transmission Dynamics and Control of Severe Acute Respiratory Syndrome , 2003, Science.

[25]  K. Mandl,et al.  The role of absolute humidity on transmission rates of the COVID-19 outbreak , 2020, medRxiv.

[26]  Sarah Cobey,et al.  Predicting the Epidemic Sizes of Influenza A/H1N1, A/H3N2, and B: A Statistical Method , 2011, PLoS medicine.

[27]  Mariëtte Hooiveld,et al.  Driving factors of influenza transmission in the Netherlands. , 2013, American journal of epidemiology.

[28]  D. Tyrrell,et al.  The time course of the immune response to experimental coronavirus infection of man , 1990, Epidemiology and Infection.

[29]  A. Wilder-Smith,et al.  Demonstrating vaccine effectiveness during a waning epidemic: A WHO/NIH meeting report on approaches to development and licensure of Zika vaccine candidates , 2019, Vaccine.

[30]  Paul S. Wikramaratna,et al.  The antigenic evolution of influenza: drift or thrift? , 2013, Philosophical Transactions of the Royal Society B: Biological Sciences.

[31]  Hannah R. Meredith,et al.  The incubation period of 2019-nCoV from publicly reported confirmed cases: estimation and application , 2020 .

[32]  Emre Kıcıman,et al.  Conjunction of factors triggering waves of seasonal influenza , 2017, bioRxiv.

[33]  Karline Soetaert,et al.  Solving Differential Equations in R: Package deSolve , 2010 .

[34]  R. Neher,et al.  Potential impact of seasonal forcing on a SARS-CoV-2 pandemic , 2020, medRxiv.