Abstract
The Corona Virus Disease 2019 (COVID-19) is spreading all over the world. Quantitative analysis of the effects of various factors on the spread of the epidemic will help people better understand the transmission characteristics of SARS-CoV-2, thus providing a theoretical basis for governments to develop epidemic prevention and control strategies. This article uses public data sets from The Center for Systems Science and Engineering at Johns Hopkins University (JHU CSSE), Air Quality Open Data Platform, China Meteorological Data Network, and WorldPop website to construct experimental data. The epidemic situation is predicted by Dual-link BiGRU Network, and the relationship between epidemic spread and various feature factors is quantitatively analyzed by the Gauss-Newton iteration Method. The study found that population density has the greatest positive correlation to the spread of the epidemic among the selected feature factors, followed by the number of landing flights. The number of newly diagnosed daily will increase by 1.08% for every 1% of the population density, the number of newly diagnosed daily will increase by 0.98% for every 1% of the number of landing flights. The results of this study show that the control of social distance and population movement has a high priority in epidemic prevention and control strategies, and it can play a very important role in controlling the spread of the epidemic.
Highlights
In order to further grasp the factors affecting the spread of SARS-CoV-2, better support the decision-making of epidemic prevention and control, timely made targeted countermeasures, and control the further spread of the epidemic, it is very urgent to quantitatively analyze the relationship between various factors and the spread of SARS-CoV-2
This paper carries out quantitative analysis and research on COVID-19 transmission by various factors all over the world and comes to the conclusion that the increase of population density, population flow, and flight times has a positively correlated impact on the epidemic transmission, and the increase of temperature, relative humidity, and dew point temperature has a negative correlation impact on the epidemic transmission
It can be concluded that the positive correlation effect of population density on the epidemic spread is much greater than the negative correlation effect of climate factors on the epidemic spread
Summary
Quantitative analysis of the effects of various factors on the spread of the epidemic will help people better understand the transmission characteristics of SARS-CoV-2, providing a theoretical basis for governments to develop epidemic prevention and control strategies. The study found that population density has the greatest positive correlation to the spread of the epidemic among the selected feature factors, followed by the number of landing flights. Since December 2019, The Corona Virus Disease 2019 (COVID-19) caused by the SARSCoV-2, has spread rapidly around the world. In order to prevent the spread of the epidemic, countries have adopted many measures, such as reducing gathering activities, controlling the movement of people, advocating the use of masks, and regular disinfection in public areas [9]. In order to further grasp the factors affecting the spread of SARS-CoV-2, better support the decision-making of epidemic prevention and control, timely made targeted countermeasures, and control the further spread of the epidemic, it is very urgent to quantitatively analyze the relationship between various factors and the spread of SARS-CoV-2
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