A One Health real-time surveillance system for nowcasting Campylobacter gastrointestinal illness outbreaks, Norway, week 30 2010 to week 11 2022.

David Swanson, Clemence Koren, Petter Hopp, Malin E Jonsson, Gunnar Isaksson Rø, Richard A White, Gry Marysol Grøneng
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引用次数: 1

Abstract

BackgroundCampylobacter is a leading cause of food and waterborne illness. Monitoring and modelling Campylobacter 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.AimsTo leverage data on weather and Campylobacter on broiler farms to build a risk model for possible human Campylobacter outbreaks and to communicate risk assessments with health authorities.MethodsWe developed a spatio-temporal random effects model for weekly GI illness consultations in Norwegian municipalities with Campylobacter 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.ResultsLagged temperature and precipitation covariates, as well as 2-week-lagged positive Campylobacter sampling in broilers, were associated with higher levels of GI consultations. Significant inter-municipality variability in outbreak nowcasts were observed.ConclusionsCampylobacter surveillance in broilers can be useful in GI illness outbreak nowcasting. Surveillance of Campylobacter 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 Campylobacter outbreaks and reduces impact on human health.

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一个One Health实时监测系统,用于近预报弯曲杆菌胃肠道疾病暴发,挪威,2010年第30周至2022年第11周。
弯曲杆菌是食物和水传播疾病的主要原因。对肉鸡养殖场的弯曲杆菌进行监测和建模,结合天气模式监测,可以帮助预测人类胃肠道疾病的爆发。与卫生当局近乎实时地共享数据和模型结果有助于提高潜在的疫情应对能力。目的利用肉鸡养殖场的天气和弯曲杆菌数据,为可能的人类弯曲杆菌暴发建立风险模型,并与卫生当局沟通风险评估。方法利用弯曲杆菌监测数据和2010年第30周至2022年11月的天气数据,建立了挪威城市每周胃肠道疾病咨询的时空随机效应模型,给出了1周胃肠道疾病暴发的临近预报。该方法结合了季节性调整胃肠道疾病的城市随机效应基线模型和从该基线的峰值偏差的第二个模型。模型结果通过互动网站Sykdomspulsen One Health传达给国家和地方利益攸关方。结果在肉鸡中,滞后的温度和降水协变量以及滞后2周的弯曲杆菌阳性取样与较高的GI咨询水平相关。在疫情临近预报中观察到显著的城市间差异。结论肉鸡肠道菌群监测可用于肠道疾病暴发预报。沿着从环境到疾病的潜在途径监测弯曲杆菌,例如通过水系统监测,可以改善临近预报。“同一个卫生”系统向卫生专业人员传达近乎实时的监测数据和风险的即时预报变化,有助于预防弯曲杆菌疫情,并减少对人类健康的影响。
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