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乌干达卡塞塞区伤寒的时间、空间和家庭动态。

Temporal, spatial and household dynamics of Typhoid fever in Kasese district, Uganda.

机构信息

Department of Biosecurity Ecosystems and Veterinary Public Health, Makerere University, Kampala, Uganda.

Division of Genetics and Genomics, The Roslin Institute, The Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom.

出版信息

PLoS One. 2019 Apr 22;14(4):e0214650. doi: 10.1371/journal.pone.0214650. eCollection 2019.

Abstract

Typhoid fever affects 21 million people globally, 1% of whom succumb to the disease. The social, economic and public health consequences of this disease disproportionately affect people in Africa and Asia. In order to design context specific prevention strategies, we need to holistically characterise outbreaks in these settings. In this study, we used retrospective data (2013-2016) at national and district level to characterise temporal and spatial dynamics of Typhoid fever outbreaks using time series and spatial analysis. We then selected cases matched with controls to investigate household socio-economic drivers using a conditional logistic regression model, and also developed a Typhoid fever outbreak-forecasting framework. The incidence rate of Typhoid fever at national and district level was ~ 160 and 60 cases per 100,000 persons per year, respectively, predominantly in urban areas. In Kasese district, Bwera sub-county registered the highest incidence rate, followed by Kisinga, Kitholhu and Nyakiyumbu sub-counties. The male-female case ratio at district level was at 1.68 and outbreaks occurred between the 20th and 40th week (May and October) each year following by seven weeks of precipitation. Our forecasting framework predicted outbreaks better at the district level rather than national. We identified a temporal window associated with Typhoid fever outbreaks in Kasese district, which is preceded by precipitation, flooding and displacement of people. We also observed that areas with high incidence of Typhoid fever also had high environmental contamination with limited water treatment. Taken together with the forecasting framework, this knowledge can inform the development of specific control and preparedness strategies at district and national level.

摘要

伤寒病影响全球 2100 万人,其中 1%的人因此病死亡。这种疾病的社会、经济和公共卫生后果不成比例地影响非洲和亚洲的人民。为了设计特定背景的预防策略,我们需要全面描述这些地区的疫情爆发情况。在这项研究中,我们使用国家和地区层面的回顾性数据(2013-2016 年),通过时间序列和空间分析来描述伤寒疫情爆发的时间和空间动态。然后,我们选择与对照相匹配的病例,使用条件逻辑回归模型调查家庭社会经济驱动因素,并开发了一个伤寒疫情爆发预测框架。国家和地区层面的伤寒发病率分别约为 160 和 60 例/10 万人/年,主要发生在城市地区。在卡塞塞区,布韦拉县的发病率最高,其次是基辛加、基特胡和尼亚基永布县。区县级别的男女病例比例为 1.68,疫情每年发生在第 20 周至第 40 周(5 月至 10 月),随后是 7 周的降水。我们的预测框架在区县级别上对疫情爆发的预测效果更好,而不是在国家层面。我们确定了卡塞塞区伤寒疫情爆发的时间窗口,该窗口与降水、洪水和人口流离失所有关。我们还观察到,伤寒发病率高的地区也存在高环境污染,且水处理有限。综合考虑预测框架,这些知识可以为区县级和国家级制定具体的控制和准备策略提供信息。

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