Abstract
As incidences of food poisoning, especially norovirus-induced diarrhea, are associated with climate change, there is a need for an approach that can be used to predict the risks of such illnesses with high accuracy. In this paper, we predict the winter norovirus incidence rate in Korea compared to that of other diarrhea-causing viruses using a model based on B-spline added to logistic regression to estimate the long-term pattern of illness. We also develop a risk index based on the estimated probability of occurrence. Our probabilistic analysis shows that the risk of norovirus-related food poisoning in winter will remain stable or increase in Korea based on various Representative Concentration Pathway (RCP) scenarios. Our approach can be used to obtain an overview of the changes occurring in regional and seasonal norovirus patterns that can help assist in making appropriate policy decisions.
Highlights
IntroductionAs the reproduction of microorganisms is substantially affected by weather-related factors such as temperature and humidity, climate change is extremely likely to cause changes in the seasonal patterns of food poisoning incidents caused by microorganisms
We introduce an index that we developed to quantify the incidence rate of norovirusinduced diarrhea according to Representative Concentration Pathway (RCP) scenarios that explain climate change, and we used this index to calculate the future risk of disease due to climate change
We calculated the probability of norovirus occurrence for different age groups by applying the generalized additive linear model (GALM) model using average daily temperature as an explanatory variable, and we calculated the risk index according to RCP scenarios based on the relative risk index (RRI) index presented in this paper
Summary
As the reproduction of microorganisms is substantially affected by weather-related factors such as temperature and humidity, climate change is extremely likely to cause changes in the seasonal patterns of food poisoning incidents caused by microorganisms. As climate conditions continue to change, it is expected that adjustments to food safety policies related to food will become necessary, and scientific methodologies that can accurately predict long-term fluctuations in food poisoning patterns must be developed to assist administrators in proactively devising reasonable policies to respond to the effects of climate change. The incidence of diarrhea may be reduced by economic development, some reports have found that climate change damages urban infrastructure and reduces overall water availability [2]. As diagnostic technology continues advancing, norovirus has been increasingly identified as a major cause of food poisoning [7].
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