Seasonality of endemic COVID-19

Author:

Townsend Jeffrey P.1234ORCID,Hassler Hayley B.1,Lamb April D.5,Sah Pratha6,Alvarez Nishio Aia7,Nguyen Cameron5,Tew Alexandra D.5,Galvani Alison P.6,Dornburg Alex5

Affiliation:

1. Department of Biostatistics, Yale School of Public Health, New Haven, USA

2. Department of Ecology and Evolutionary Biology, Yale University, New Haven, USA

3. Program in Computational Biology and Bioinformatics, Yale University, New Haven, USA

4. Program in Microbiology, Yale University, New Haven, USA

5. Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, USA

6. Center for Infectious Disease Modeling and Analysis, Yale University, New Haven, USA

7. Yale College, New Haven, USA

Abstract

ABSTRACT Successive waves of infection by SARS-CoV-2 have left little doubt that this virus will transition to an endemic disease. Foreknowledge of when to expect seasonal surges is crucial for healthcare and public health decision-making. However, the future seasonality of COVID-19 remains uncertain. Evaluating its seasonality is complicated due to the limited years of SARS-CoV-2 circulation, pandemic dynamics, and varied interventions. In this study, we project the expected endemic seasonality by employing a phylogenetic ancestral and descendant state approach that leverages long-term data on the incidence of circulating HCoV coronaviruses. Our projections indicate asynchronous surges of SARS-CoV-2 across different locations in the northern hemisphere, occurring between October and January in New York and between January and March in Yamagata, Japan. This knowledge of spatiotemporal surges leads to medical preparedness and enables the implementation of targeted public health interventions to mitigate COVID-19 transmission. IMPORTANCE The seasonality of COVID-19 is important for effective healthcare and public health decision-making. Previous waves of SARS-CoV-2 infections have indicated that the virus will likely persist as an endemic pathogen with distinct surges. However, the timing and patterns of potentially seasonal surges remain uncertain, rendering effective public health policies uninformed and in danger of poorly anticipating opportunities for intervention, such as well-timed booster vaccination drives. Applying an evolutionary approach to long-term data on closely related circulating coronaviruses, our research provides projections of seasonal surges that should be expected at major temperate population centers. These projections enable local public health efforts that are tailored to expected surges at specific locales or regions. This knowledge is crucial for enhancing medical preparedness and facilitating the implementation of targeted public health interventions.

Funder

National Science Foundation

UNC | University of North Carolina at Charlotte

Publisher

American Society for Microbiology

Subject

Virology,Microbiology

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