Association of Meteorological Factors with Contact-transmitted Diseases and Mushroom Poisoning in Loei Province
Keywords:
Temperature, rainfall, diseases related to temperature and rain, relationship, risk ratesAbstract
Specific research to develop a geospatial predictive risk model is currently lacking in Loei Province. This study aimed to analyze the relationship and risk rates of meteorological factors with the number of patients suffering from contact-transmitted diseases and mushroom poisoning. It is a correlational study using monthly time series data from Loei Province data between January 2021 and August 2024. It included meteorological data collected from the Upper Northeast Meteorological Center, and the numbers of patients with contact-transmitted diseases and mushroom poisoning which were collected from the Disease Surveillance Reporting System 506, Bureau of Epidemiology, Department of Disease Control. Data were analyzed using Pearson’s correlation and the generalized linear model. The results showed that the optimal generalized linear models for monthly patient counts were: a Quasi-Poisson regression model for hand-foot-mouth disease, a negative binomial regression model for leptospirosis, and a Quasi-Poisson regression model for mushroom poisoning. Average daily humidity was identified as a statistically significant independent variable (p < 0.05) across all three diseases, with Pearson correlation coefficients of 0.343, 0.276, and 0.507, respectively. The models indicated that each 1% increase in daily average relative humidity was associated with risk rate increases of 1.16 for hand-foot-mouth disease, 1.04 for leptospirosis, and 1.30 for mushroom poisoning. Early relative humidity forecast data can be used as a guide to estimate the number of cases of infectious diseases and mushroom poisoning for appropriate public health measures.
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