LAUSR

Epidemiology occupies a very important position in preventive medicine. Its essence is to summarize the etiology and epidemic laws by studying the distribution and possible effects of diseases, so as to promote the formation of scientific epidemic prevention measures. The purpose of this article is to help relevant personnel complete the collection, induction, and analysis of epidemiological survey data by establishing a data collection system model to improve work efficiency. This article focuses on the new coronavirus pneumonia (COVID-19), investigates the development status of epidemiological survey data collection, and analyzes the problems in the current business process, and on this basis, develops a dedicated epidemiological survey System model for data collection. From the experimental data, the optimized correction evaluation index has been increased from 8.384 to 9.067. It can be seen that the combination of data mining algorithms and backpropagation algorithms can better improve the system's ability to process information. Professional information disclosure platforms can have a good positive impression on the prevention and treatment of epidemics. The Internet-based epidemiological survey customized system model established in this article is to integrate various epidemiological data so that people can correctly understand the spread of epidemics and promote the development of preventive medicine.