Correlation Analysis between Meteorological Influencing Factors and Incidence Features of OIDDs in Guangzhou from 2006 to 2020

Abstract

Objectives. This study is to analyze the epidemiological characteristics of other infectious diarrhea diseases (OIDDs) reported in Guangzhou in the past 15 years and the meteorological data of the city in the same period, to explore the correlation between meteorological factors and the incidence. Methodology. This study starts with using quartiles to test the normal distribution of case data. This study has selected five meteorological factors with the highest correlation coefficients and case data from 2006 to 2018 were used to establish a multiple linear regression equation, and the regression equation was tested with case data from 2019 to 2020. Results. Regression modeling based on the statistics for OIDDs during 2006 to 2018 obtained a correlation coefficient R (multiple R) value of about 0.50. The R square value, also known as the coefficient of determination or goodness of fit, was about 0.25. The adjusted R square value was about 0.25. The overall significance test value (significance F) in the regression equation was much lower than the F statistic, thereby indicating that the dependent variable and independent variable were significant. Conclusion. The results indicated that factors other than meteorological or social factors should be considered to understand the outbreak of OIDDs in Guangzhou.