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Associations Between Environmental and Sociodemographic Data and Hepatitis‐A Transmission in Pará State (Brazil)

机译:环境与社会渗透数据与乙型肝炎之间的关联 - 帕拉州(巴西)

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摘要

Hepatitis‐A is a waterborne infectious disease transmitted by the eponymous hepatitis‐A virus (HAV). Due to the disease's sociodemographic and environmental characteristics, this study applied public census and remote sensing data to assess risk factors for hepatitis‐A transmission. Municipality‐level data were obtained for the state of Pará, Brazil. Generalized linear and nonlinear models were evaluated as alternative predictors for hepatitis‐A transmission in Pará. The Histogram Gradient Boost (HGB) regression model was deemed the best choice (RMSE= 2.36, and higher R2 = 0.95) among the tested models. Partial dependence analysis and permutation feature importance analysis were used to investigate the partial dependence and the relative importance values of the independent variables in the disease transmission prediction model. Results indicated a complex relationship between the disease transmission and the sociodemographic and environmental characteristics of the study area. Population size, lack of sanitation, urban clustering, year of notification, insufficient public vaccination programs, household proximity to open‐air dumpsites and storm‐drains, and lack of access to healthcare facilities and hospitals were sociodemographic parameters related to HAV transmission. Turbidity and precipitation were the environmental parameters closest related to disease transmission. Based on HGB model, a hepatitis‐A risk map was built for Pará state. The obtained risk map can be thought of as an auxiliary tool for public health strategies. This study reinforces the need to incorporate remote sensing data in epidemiological modelling and surveillance plans for the development of early prevention strategies for hepatitis‐A.
机译:乙型肝炎是由同名乙型肝炎 - 一种病毒(HAV)传播的水性传染病。由于疾病的社会渗目和环境特征,这项研究应用了公共人口普查和遥感数据,以评估乙型肝炎的风险因素 - 一种传播。为巴西帕拉州获得市政级数据。广义的线性和非线性模型被评估为乙型肝炎的替代预测因子 - 帕拉中的传播。直方图渐变升压(HGB)回归模型被视为测试模型中的最佳选择(RMSE = 2.36,更高的R2 = 0.95)。部分依赖性分析和置换特征重要性分析用于研究疾病传输预测模型中独立变量的部分依赖性和相对重要性值。结果表明,疾病传播与研究区的社会渗目与环境特征之间的复杂关系。人口规模,卫生缺乏,城市聚类,通知年份,公共疫苗接种计划不足,家庭接近露天垃圾场和风暴排水管,以及缺乏医疗保健设施和医院的机会是与HAV传输相关的社会造影参数。浊度和沉淀是与疾病传播最近的环境参数。基于HGB模型,建立了乙型肝炎的风险地图是为了帕拉州。获得的风险地图可以被认为是公共卫生策略的辅助工具。本研究强化了在流行病学建模和监测计划中纳入遥感数据,以开发乙型肝炎的预防策略。

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