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. 2019 Jan:147:e190.
doi: 10.1017/S0950268819000797.

Seasonality and zoonotic foodborne pathogens in Canada: relationships between climate and Campylobacter, E. coli and Salmonella in meat products

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Seasonality and zoonotic foodborne pathogens in Canada: relationships between climate and Campylobacter, E. coli and Salmonella in meat products

B A Smith et al. Epidemiol Infect. 2019 Jan.

Abstract

Infections due to Campylobacter, Escherichia coli and Salmonella pose a significant health burden in Canada, resulting in major costs to the health care system and economic impacts due to lost productivity resulting from illness. Recent literature suggests that climate may play a role in the prevalence of these pathogens along the food chain. This study used integrated surveillance data to examine associations between weather variables, serving as a proxy for climate, in agricultural areas and Campylobacter, generic E. coli and Salmonella contamination on samples of beef, poultry and swine meat products in Canada. Various temperature metrics (average, maximum and variability) were correlated with Campylobacter prevalence along the food chain. The prevalence of E. coli and Salmonella was correlated with both precipitation and temperatures metrics; however, analysis for E. coli was limited to beef and swine meats at retail settings, because prevalence in other combinations approached 100%, which obviated further analysis. Campylobacter contamination in poultry and swine at abattoir and retail settings demonstrated a seasonal trend, with increased prevalence generally from June or July through November, compared to the baseline month of December. Based on these analyses, Campylobacter is the most likely foodborne bacteria studied whose occurrence in meat products is affected by climatic changes in Canada. An exploratory analysis of data at the provincial scale, using Ontario as an example, revealed similar directional relationships between climate and bacterial prevalence.

Keywords: Campylobacter; Escherichia coli (E. coli); climate; food-borne zoonoses; impact of; salmonella.

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Conflict of interest statement

None.

Figures

Fig. 1.
Fig. 1.
Point weather station data conversion to a raster surface.
Fig. 2.
Fig. 2.
Agricultural zones considered for the weather data analysis per livestock type.
Fig. 3.
Fig. 3.
Model coefficients for Campylobacter by month for select analyses. December was selected as the baseline month to which other months were compared.
Fig. 4.
Fig. 4.
Odds ratios for Campylobacter occurrence in chicken at abattoir and retail by month in Ontario. Average temperatures in production areas are shown for comparison. December was selected as the baseline month to which all other months were compared.

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