Does Ambient Temperature Affect Foodborne Disease?

Background Foodborne illness is a significant public health issue in most countries with an estimated four million cases occurring in Australia annually. There is evidence that the growth and dissemination of micro-organisms may be influenced by the weather and some foodborne illnesses show seasonality, salmonellosis is most commonly reported in summer, while campylobacteriosis peaks in spring. This is a study of the effect of temperature on salmonellosis notifications and a comparison of this effect for five Australian cities. Methods Log-linear models describing monthly salmonellosis notifications over the period 1991 to 2001 in terms of calendar time and monthly average temperatures were fitted, for each city, using a negative binomial regression to allow for over-dispersion in the counts. To prevent occasional extreme values from overwhelming the analysis, we included an indicator variable for each outbreak month as a predictor in the model. Season was entered as a categorical variable in the model, while a cubic polynomial described the smooth long-term time trend. The complete model described the temperature effect in terms of mean temperature of the current month (temp0), mean temperature of the previous month (temp1) plus quadratic and cubic terms of these temperature variables. Log (population size) was included as an offset to make direct comparisons of results from the different cities more meaningful. Results The long-term trend showed an increase in salmonellosis notifications in each of the five cities. A positive association between monthly salmonellosis notifications and mean monthly temperature of the previous month was highly significant in every city. Regression coefficients for temperature were similar for four cities (≫0.05). For Brisbane the coefficient was twice as large (0.097). Seasonal patterns in salmonellosis notifications were no longer significant once temperature was allowed for. For a temperature increase of IoC, the increase in the proportion of salmonellosis cases is 10% in Brisbane, 6% in Sydney, 5% in Melbourne and Adelaide and 4% in Perth. The mean temperature of the current month temp0, is not as good a predictor of the number of notifications in a month as temp1, the mean temperature of the previous month. Discussion The results of this study show a significant positive association between mean temperature of the previous month and the number of salmonellosis notifications in the current month. Our finding was consistent over five major cities of Australia, located very large distances apart, covering a range of latitude from 27 to 38 degrees. The lag of one month suggests that temperature might be more influential earlier in the production process, rather than at the food preparation stage. Understanding this can help to guide policy on food preparation and distribution, possibly serve as an early warning system for increased incidence when climatic conditions suggest this and validate health concerns associated with global warming.