Abstract

Background: Since the emergence of COVID19, researchers have wondered about its seasonality. This article provides the answer based in the analysis of which climatic variables are the ones that most affect the infection rate and how they affect it.Method: From the SIR epidemiological model applied to the spread of COVID19 throughout the world, it has been calculated how the model’s β parameter depends on climatic factors for each virus strain and for each country. We have established a linear formula for the β parameter, in terms of humidity, UV index and population density in the most representative city of the countries studied for the spread of the COVID19. This has been achieved from a linear regression done by Machine Learning from data from 21 countries and 205 cities or regions of the world.Findings: Two of climate variables have been shown to be relevant in propagation of COVID19: relative humidity and ultraviolet index. When humidity increases the rate of transmission too and when the ultraviolet index increases the rate decreases. Another variable on which it depends proportionally is the population density of the cities.Interpretation: From the result shown in the study we can conclude that containment strategies can also be based on the consideration of humidity and the ultraviolet index in the spaces in which people move, live, stays or work, in cases where the strategy of staying at home cannot be maintained.Funding: Universidad Nacional Autónoma de México.Declaration of Interests: The authors state that there is no conflict of interest.

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