Impact of meteorological factors on the COVID-19 transmission: A multi-city study in China

Liu, Jiangtao; Zhou, Ji; Yao, Jinxi; Zhang, Xiuxia; Li, Lanyu; Xu, Xiufang; He, Xiaokai; Wang, Bo; Fu, Shihua; Niu, Tingting; Yan, Jun; Shi, Yanjun; Ren, Xiaowei; Niu, Jingping; Zhu, Weihao; Li, Sheng; Luo, Bin; Zhang, Kai

doi:10.1016/j.scitotenv.2020.138513

Cited by 483 publications

(599 citation statements)

References 23 publications

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“…While some have documented the route of transmission through human-to-human contact, others have examined the role that some environmental factors may play in facilitating the rate of spread of the disease through the analysis of temporal and spatial relationships of these factors with COVID-19 transmission rate. Most of these studies have reported a negative relationship between transmission rate and several proxies of temperature and humidity, suggesting that the disease spread is enhanced in colder and drier climates [5][6][7][8][9] .Other environmental variables have received less attention and results have been inconclusive or differed among countries. For example, one study reported an inverse relationship between COVID-19 transmission and wind speed in Iran 10 , while global studies have found no signi cant association between both variables 11,12 .…”

Section: Introductionmentioning

confidence: 99%

Environmental determinants of COVID-19 transmission across a wide climatic gradient in Chile

Correa‐Araneda

Ulloa-Yañez

Núñez

et al. 2020

Preprint

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Several studies have examined the transmission dynamics of the novel COVID-19 disease in different parts of the world. Some have reported relationships with several environmental variables, suggesting that spread of the disease is enhanced in colder and drier climates. However, evidence is still scarce and mostly limited to a few countries, particularly from Asia. We examined the potential role of multiple environmental variables in COVID-19 transmission rates and patterns from February 23 to April 16 across 121 cities of Chile; this country covers a large climatic gradient (≈ 40º of latitude, ≈ 4,000 m of altitude and 5 climatic regions, from desert to tundra), but all cities share their social behaviour patterns and regulations. Our results indicated that COVID-19 transmission in Chile was mostly related to 3 main climatic factors (mean temperature, relative humidity and wind speed) and population size. Transmission was greater in colder and drier cities (although wind modulated the effect of temperature) and when wind speed was higher; finally, transmission increased with population size. The results of this study support some previous findings about the main environmental and demographic determinants of COVID-19 transmission, which may be useful for decision-making and management of the disease.

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Section: Introductionmentioning

confidence: 99%

Environmental determinants of COVID-19 transmission across a wide climatic gradient in Chile

Correa‐Araneda

Ulloa-Yañez

Núñez

et al. 2020

Preprint

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“…incidence (Liu et al 2020;Prata et al 2020;Qi et al 2020;Şahin 2020). SIR: social isolation rate; UV: ultraviolet radiation; T: temperature; RH: relative humidity; WS: wind speed; 3 : three days previous to case reports; 7 : seven days previous to case reports; 14 : fourteen days previous to case reports.…”

Section: Resultsmentioning

confidence: 99%

“…One recent review has addressed the role of climate change in the emergence and re-emergence of infectious diseases worldwide, indicating that temperature is an important environmental condition determining the success of infectious agents (El-Sayed and Kamel 2020). Furthermore, several studies have investigated the impact of weather on the COVID-19 transmission, with special attention to temperature and humidity (Liu et al 2020;Qi et al 2020;Şahin 2020;Wu et al 2020). Even though conducted in different countries and using distinct approaches, these investigations have indicated that temperature is inversely related to COVID-19 incidence.…”

Section: Introductionmentioning

confidence: 99%

COVID-19 pandemic: environmental and social factors influencing the spread of SARS-CoV-2 in the expanded metropolitan area of São Paulo, Brazil

Nakada

Urban

2020

Preprint

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The new Coronavirus SARS-CoV-2 has infected more than three million people worldwide so far. Brazil is currently the second leading country in number of critical cases and the third in number of new deaths caused by COVID-19, while São Paulo State accounts for more than 33% of total confirmed cases in Brazil. Therefore, understanding the mechanisms of SARS-CoV-2 spread in São Paulo State is an important task. The aim of this study was to assess environmental and social factors influencing the spread of SARS-CoV-2 in the expanded metropolitan area of São Paulo, Brazil. Firstly, a spatial analysis was conducted to provide insights into the spread of COVID-19 within the expanded metropolitan area. Moreover, statistical analyses were performed to assess social indicators and environmental conditions which possibly influence the incidence of COVID-19. Our results reveal that the spread of COVID-19 from the capital city São Paulo – its epicenter in Brazil – is directly associated with the availability of highways within the expanded metropolitan area of São Paulo. As for social aspects, cumulative COVID-19 confirmed cases were found to be both positively correlated with population density, and negatively correlated with social isolation rate, hence, indicating that social distancing has been effective in reducing the COVID-19 transmission. Finally, cumulative COVID-19 confirmed cases were found to be inversely correlated with both temperature and UV radiation. Together with recent literature our study suggests that the UV radiation provided by sunlight might reduce the infectivity of SARS-CoV-2.

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“…Another related work is the work of Liu et al [8], who analyzed the impact of meteorological factors on COVID-19 in China's provinces. The results obtained from this study indicated that the transmission may be affected by factors such as low temperature, low humidity, and mild diurnal temperature range.…”

Section: Related Workmentioning

confidence: 99%

An Exploration and Forecast of COVID-19 in Mexico with Machine Learning

Gomez-Cravioto

Diaz-Ramos

Cantú-Ortiz

et al. 2020

Preprint

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Background: To understand and approach the COVID-19 spread, Machine Learning offers fundamental tools. This study presents the use of machine learning techniques for the projection of COVID-19 infections and deaths in Mexico. The research has three main objectives: first, to identify which function adjusts the best to the infected population growth in Mexico; second, to determine the feature importance of climate and mobility; third, to compare the results of a traditional time series statistical model with a modern approach in machine learning. The motivation for this work is to support health care providers in their preparation and planning. Methods: The methods used are linear, polynomial, and generalized logistic regression models to evaluate the growth of the COVID-19 incidents in the country. Additionally, machine learning and time-series techniques are used to identify feature importance and perform forecasting for daily cases and fatalities. The study uses the publicly available data sets from the John Hopkins University of Medicine in conjunction with mobility rates obtained from Google’s Mobility Reports and climate variables acquired from Weather Online. Results: The results suggest that the logistic growth model fits best the behavior of the pandemic in Mexico, that there is a significant correlation of climate and mobility variables with the disease numbers, and that LSTM is a more suitable approach for the prediction of daily cases. Conclusion: We hope that this study can make some contributions to the world’s response to this epidemic as well as give some references for future research.

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Impact of meteorological factors on the COVID-19 transmission: A multi-city study in China

Cited by 483 publications

References 23 publications

Environmental determinants of COVID-19 transmission across a wide climatic gradient in Chile

Environmental determinants of COVID-19 transmission across a wide climatic gradient in Chile

COVID-19 pandemic: environmental and social factors influencing the spread of SARS-CoV-2 in the expanded metropolitan area of São Paulo, Brazil

An Exploration and Forecast of COVID-19 in Mexico with Machine Learning

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