Significance There is still much to be understood about the factors influencing the ecology and epidemiology of COVID-19. In particular, whether environmental variation is likely to drive seasonal changes in SARS-CoV-2 transmission dynamics is largely unknown. We investigate the effects of the environment on SARS-CoV-2 transmission rates across the United States and then incorporate the most important environmental parameters into an epidemiological model. We show that temperature and population density can be important factors in transmission but only in the absence of mobility-restricting policy measures, although particularly strong policy measures may be required to mitigate the highest population densities. Our findings improve our understanding of the drivers of COVID-19 transmission and highlight areas in which policy decisions can be proactive. As COVID-19 continues to spread across the world, it is increasingly important to understand the factors that influence its transmission. Seasonal variation driven by responses to changing environment has been shown to affect the transmission intensity of several coronaviruses. However, the impact of the environment on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains largely unknown, and thus seasonal variation remains a source of uncertainty in forecasts of SARS-CoV-2 transmission. Here we address this issue by assessing the association of temperature, humidity, ultraviolet radiation, and population density with estimates of transmission rate ( R ). Using data from the United States, we explore correlates of transmission across US states using comparative regression and integrative epidemiological modeling. We find that policy intervention (“lockdown”) and reductions in individuals’ mobility are the major predictors of SARS-CoV-2 transmission rates, but, in their absence, lower temperatures and higher population densities are correlated with increased SARS-CoV-2 transmission. Our results show that summer weather cannot be considered a substitute for mitigation policies, but that lower autumn and winter temperatures may lead to an increase in transmission intensity in the absence of policy interventions or behavioral changes. We outline how this information may improve the forecasting of COVID-19, reveal its future seasonal dynamics, and inform intervention policies.
【저자키워드】 SARS-CoV-2, Epidemiology, Transmission, seasonality, Climate, 【초록키워드】 COVID-19, Coronaviruses, coronavirus, Variation, Intervention, Spread, SARS-CoV-2 transmission, Measures, ultraviolet, response, temperature, epidemiological, predictor, estimate, information, association, COVID-19 transmission, seasonal variation, changes, Radiation, intensity, acute respiratory syndrome, Factor, measure, transmission rate, parameter, Effect, The United States, Affect, mitigate, highlight, IMPROVE, highest, shown, the United State, required, changes in, absence, correlated, increase in, reductions in, driven by, increasingly, driver, SARS-CoV-2 transmission rate, SARS-CoV-2 transmission rates, Significance, 【제목키워드】 SARS-CoV-2 transmission, nonpharmaceutical intervention, absence,