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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/8297| Containment measures limit environmental effects on COVID-19 early outbreak dynamics | |
| Gentile Francesco Ficetola DIEGO RUBOLINI | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| https://doi.org/10.1101/2020.03.23.20040501 | |
| https://www.medrxiv.org/content/10.1101/2020.03.23.20040501v4 | |
| Environmental factors are well known to affect spatio-temporal patterns of infectious disease outbreaks, but whether the recent rapid spread of COVID-19 across the globe is related to local environmental conditions is highly debated. We assessed the impact of environmental factors (temperature, humidity and air pollution) on the global patterns of COVID-19 early outbreak dynamics during January-May 2020, controlling for several key socio-economic factors and airport connections. We showed that during the earliest phase of the global outbreak (January-March), COVID-19 growth rates were non-linearly related to climate, with fastest spread in regions with a mean temperature of ca. 5°C, and in the most polluted regions. However, environmental effects faded almost completely when considering later outbreaks, in keeping with the progressive enforcement of containment actions. Accordingly, COVID-19 growth rates consistently decreased with stringent containment actions during both early and late outbreaks. Our findings indicate that environmental drivers may have played a role in explaining the early variation among regions in disease spread. With limited policy interventions, seasonal patterns of disease spread might emerge, with temperate regions of both hemispheres being most at risk of severe outbreaks during colder months. Nevertheless, containment measures play a much stronger role and overwhelm impacts of environmental variation, highlighting the key role for policy interventions in curbing COVID-19 diffusion within a given region. If the disease will become seasonal in the next years, information on environmental drivers of COVID-19 can be integrated with epidemiological models to inform forecasting of future outbreak risks and improve management plans. | |
| bioRxiv | |
| 08-12-2020 | |
| Preimpreso | |
| Inglés | |
| Público en general | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Materiales de Consulta y Comunicados Técnicos |
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