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Abstract

Background

is a leading cause of food and waterborne illness. Monitoring and modelling at chicken broiler farms, combined with weather pattern surveillance, can aid nowcasting of human gastrointestinal (GI) illness outbreaks. Near real-time sharing of data and model results with health authorities can help increase potential outbreak responsiveness.

Aims

To leverage data on weather and on broiler farms to build a risk model for possible human outbreaks and to communicate risk assessments with health authorities.

Methods

We developed a spatio-temporal random effects model for weekly GI illness consultations in Norwegian municipalities with monitoring and weather data from week 30 2010 to 11 2022 to give 1-week nowcasts of GI illness outbreaks. The approach combined a municipality random effects baseline model for seasonally-adjusted GI illness with a second model for peak deviations from that baseline. Model results are communicated to national and local stakeholders through an interactive website: Sykdomspulsen One Health.

Results

Lagged temperature and precipitation covariates, as well as 2-week-lagged positive sampling in broilers, were associated with higher levels of GI consultations. Significant inter-municipality variability in outbreak nowcasts were observed.

Conclusions

surveillance in broilers can be useful in GI illness outbreak nowcasting. Surveillance of along potential pathways from the environment to illness such as via water system monitoring may improve nowcasting. A One Health system that communicates near real-time surveillance data and nowcast changes in risk to health professionals facilitates the prevention of outbreaks and reduces impact on human health.

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/content/10.2807/1560-7917.ES.2022.27.43.2101121
2022-10-27
2022-11-30
http://instance.metastore.ingenta.com/content/10.2807/1560-7917.ES.2022.27.43.2101121
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