Leal Philipe Riskalla, Guimarães Ricardo José de Paula Souza E, Kampel Milton
National Institute for Space Research (INPE, Instituto Nacional de Pesquisas Espaciais) São Paulo Brazil.
Evandro Chagas Institute Belém State of Pará Brazil.
Geohealth. 2021 May 1;5(5):e2020GH000327. doi: 10.1029/2020GH000327. eCollection 2021 May.
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 ( = 2.36, and higher = 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.
甲型肝炎是一种通过同名甲型肝炎病毒(HAV)传播的水传播传染病。鉴于该疾病的社会人口统计学和环境特征,本研究应用人口普查和遥感数据来评估甲型肝炎传播的风险因素。获取了巴西帕拉州市级层面的数据。对广义线性和非线性模型进行了评估,作为帕拉州甲型肝炎传播的替代预测指标。在测试的模型中,直方图梯度提升(HGB)回归模型被认为是最佳选择( = 2.36,更高的 = 0.95)。使用偏依赖分析和排列特征重要性分析来研究疾病传播预测模型中自变量的偏依赖和相对重要性值。结果表明疾病传播与研究区域的社会人口统计学和环境特征之间存在复杂关系。人口规模、卫生设施缺乏、城市聚集、报告年份、公共疫苗接种计划不足、家庭靠近露天垃圾场和雨水排放口以及缺乏医疗设施和医院是与甲型肝炎病毒传播相关的社会人口统计学参数。浊度和降水量是与疾病传播最密切相关的环境参数。基于HGB模型,为帕拉州绘制了甲型肝炎风险地图。所获得的风险地图可被视为公共卫生策略的辅助工具。本研究强调了在流行病学建模和监测计划中纳入遥感数据以制定甲型肝炎早期预防策略的必要性。