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        • Universidad Jorge Tadeo Lozano (Colombia)
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        • Universidad Jorge Tadeo Lozano (Colombia)
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        Effect of weather on COVID-19 spread in the US: A prediction model for India in 2020

        Registro en:
        0048-9697
        https://doi.org/10.1016/j.scitotenv.2020.138860
        http://hdl.handle.net/20.500.12010/10597
        https://doi.org/10.1016/j.scitotenv.2020.138860
        http://repositorioslatinoamericanos.uchile.cl/handle/2250/3503714
        Autor
        Gupta, Sonal
        Singh Raghuwanshi, Gourav
        Chanda, Arnab
        Institución
        • Universidad Jorge Tadeo Lozano (Colombia)
        Resumen
        The effect of weather on COVID-19 spread is poorly understood. Recently, few studies have claimed that warm weather can possibly slowdown the global pandemic, which has already affected over 1.6 million people worldwide. Clarification of such relationships in the worst affected country, the US, can be immensely beneficial to understand the role of weather in transmission of the disease in the highly populated countries, such as India. We collected the daily data of new cases in 50 US states between Jan 1–Apr 9, 2020 and also the corresponding weather information (i.e., temperature (T) and absolute humidity (AH)). Distribution modeling of new cases across AH and T, helped identify the narrow and vulnerable AH range. We validated the results for 10-day intervals against monthly observations, and also worldwide trends. The results were used to predict Indian regions which would be vulnerable to weather based spread in upcoming months of 2020. COVID-19 spread in the US is significant for states with 4 b AH b 6 g/m3 and number of new cases N 10,000, irrespective of the chosen time intervals for study parameters. These trends are consistent with worldwide observations, but do not correlate well with India so far possibly due the total cases reported per interval b 10,000. The results clarify the relationship between weather parameters and COVID-19 spread. The vulnerable weather parameters will help classify the risky geographic areas in different countries. Specifically, with further reporting of new cases in India, prediction of states with high risk of weather based spread will be apparent.
        Materias
        COVID-19
        Weather
        Humidity
        Temperature
        US
        India

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        Red de Repositorios Latinoamericanos
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        Red de Repositorios Latinoamericanos
        + de 8.000.000 publicaciones disponibles
        500 instituciones participantes
        Dirección de Servicios de Información y Bibliotecas (SISIB)
        Universidad de Chile
        Ingreso Administradores
        Colecciones destacadas
        • Tesis latinoamericanas
        • Tesis argentinas
        • Tesis chilenas
        • Tesis peruanas
        Nuevas incorporaciones
        • Argentina
        • Brasil
        • Colombia
        • México
        Dirección de Servicios de Información y Bibliotecas (SISIB)
        Universidad de Chile
        Red de Repositorios Latinoamericanos | 2006-2018