Biostatistical Analysis of the risks of spatial spread during the COVID-19 pandemic

Abstract

: With the spread of the new coronavirus around the world, governments of various countries have
begun to use the mathematical modeling method to construct some virus transmission models assessing the
risks of spatial spread of the new coronavirus COVID-19, while carrying out epidemic prevention work, and
then calculate the inflection point for better prevention and control of epidemic transmission. This work
analyzes the spread of the new coronavirus in China, Italy, Germany, Spain, and France, and explores the
quantitative relationship between the growth rate of the number of new coronavirus infections and time. Background: In December 2019 , the first Chinese patients with pneumonia of unknown cause
is China admitted to hospital in Wuhan, Hubei Jinyintan , since then, COVID-19 in the rapid expansion of
China Wuhan, Hubei, in a few months time, COVID-19 is Soon it spread to a total of 34 provincial-level
administrative regions in China and neighboring countries, and Hubei Province immediately became the
hardest hit by the new coronavirus. In an emergency situation, we strive to establish an accurate infectious
disease retardation growth model to predict the development and propagation of COVID-19, and on this basis, make some short-term effective predictions. The construction of this model has Relevant departments are
helpful for the prevention and monitoring of the new coronavirus, and also strive for more time for the clinical
trials of Chinese researchers and the research on vaccines against the virus to eliminate the new corona virus
as soon as possible. Methods: Collect and compare and integrate the spread of COVID-19 in China, Italy, France, Spain and
Germany, record the virus transmission trend among people in each country and the protest measures of
relevant government departments. According to the original data change law, Establish a Logistic growth
model. Findings: Based on the analysis results of the Logistic model model, the Logistic model has a good fitting
effect on the actual cumulative number of confirmed cases, which can bring a better effect to the prediction of
the epidemic situation and the prevention and control of the epidemic situation. Interpretation: In the early stage of the epidemic, due to inadequate anti-epidemic measures in various
countries, the epidemic situation in various countries spread rapidly. However, with the gradual
understanding of COVI D -19, the epidemic situation began to be gradually controlled, thereby retarding
growth.