Climatic factors can affect the incidence of foodborne diseases (FBDs). Moreover, microbial network inference is useful for predicting the interrelationships between the incidence of FBDs and climatic factors. However, the interrelationships between FBD pathogens and most climatic factors are unknown. Using principal component analysis (PCA) and partial correlation coefficient matrices (PCCMs), we determined the intra-ecosystem interrelationship network of the multiple combined effects of 5 climatic factors (temperature, relative humidity, rainfall, insolation, and cloudiness) and the monthly incidences of 12 bacterial FBDs. Many FBD pathogens are interrelated with multiple combined factors. Salmonellosis has strong positive interrelationships with Vibrio parahaemolyticus and enterohemorrhagic Escherichia coli, and the interrelationships between Staphylococcus aureus/enteropathogenic E. coli/enterotoxigenic E. coli exhibits a typical triangular pattern with the combined effects of all 5 climatic factors. Meanwhile, campylobacteriosis and Clostridium perfringens infections are negatively interrelated with insolation and cloudiness. Enteroinvasive E. coli, Bacillus cereus, Listeria spp., and Yersinia enterocolitica are significantly interrelated with any climatic factor combination. The interrelationships or higher-order interrelationships among these climatic factors play an important role in the incidence of FBDs, although the underlying mechanisms remain unclear. Our results will serve as a foundation for more sophisticated models of future FBD patterns with regard to climate change.

This study aimed to investigate the prevalence of foodborne viruses in reservoirs (an important resource of irrigation water) and its correlation with environmental and weather factors. From May 2017 to November 2018, we visited ten reservoirs and a river in the Anseong region of South Korea and collected a total of 192 samples in accordance with the environment protection agency guidelines. We recorded the weather factors (temperature, humidity, and accumulated precipitation) and investigated the surrounding environment factors (livestock, fishing site, the catchment area of reservoirs, etc.). Our research results show that from the river and reservoirs, the detection rates of human norovirus GII, adenovirus, rotavirus, human norovirus GI, and astrovirus were 27.1, 10.4, 10.4, 4.16, and 3.1%, respectively. Their viral load ranged from −1.48 to 1.55 log₁₀ genome copies/l. However, hepatitis A virus was not detected in any irrigation water sample. Although no sampling was performed in winter, foodborne viruses and male-specific coliphages were frequently found during spring (40.78%) and autumn (39.47%). Interestingly, the significant correlation between the accumulative precipitation and the number of detected norovirus and adenovirus was confirmed by linear regression analysis. Furthermore, when the accumulative precipitation ranged from 20 to 60 mm, it significantly affected the viral load and prevalence. Among the environmental factors, recreational facilities such as fishing sites and bungalow fishing spots were identified as contamination sources by correlation analysis. Our research results confirmed the correlations between environmental contamination factors in the reservoir and weather factors with the prevalence of foodborne viruses in the reservoir. These facilitates the assessment of potential foodborne virus contamination during crop irrigation. In addition, predictive models including environmental and weather factors should be developed for monitoring and controlling the safety of irrigation waters in reservoirs.