Syndromic Surveillance in Public Health Emergencies: A Systematic Analysis of Cases Related to Exposure to 2023 Floodwaters in Romagna, Italy

公共卫生突发事件中的综合征监测:对意大利罗马涅地区2023年洪水暴露相关病例的系统分析

阅读:1

Abstract

BACKGROUND: In May 2023, Romagna, Italy, faced a devastating flood resulting in 16 fatalities, forced displacement of 26,000 citizens, and significant economic losses. Due to potential water contamination, implementing public health strategies became imperative for the Local Health Authority to mitigate the health consequences, analyze the flood's impact on the local population's health, and detect early anomalies requiring timely public health interventions. METHODS: Between June and July 2023, general practitioners who were part of the RespiVirNet surveillance network completed weekly structured forms. These forms collected data on individuals exposed or not to floodwaters and clinical syndromes. Rates per 1000 resident population aged > 14 were stratified by district, week of observation, and symptomatology. Missing data were addressed by imputation using second-order autoregressive modeling. RESULTS: An incidence of 3.52 syndromes potentially related to flood water exposure per 1000 individuals (95% CI 2.82-4.35) was estimated. Ravenna, the city most affected by the flood, recorded the highest rate (6.05 per 1000, 95% CI 4.59-7.82). Incidence decreased in the weeks post-event. Anxiety, or trauma and stress symptoms, exhibited higher rates among the exposed, diminishing over weeks. The incidence for the non-exposed (12.76 per 1000, 95% CI 10.55-15.29) showed no significant territorial differences compared to the exposed ones. CONCLUSIONS: Syndromic surveillance provided timely information on the flood's health impact, revealing a higher incidence of individual syndromes among the non-exposed. This study contributes to guiding the implementation of future public health preparedness and response strategies for populations facing similar natural disasters.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。