建立登革出血热传播预测模型以加强中爪哇克拉丹区格古农村预警系统

T. Satoto, Alfin Harjuno Dwiputro, Rifa Nadhifa Risdwiyanto, A. Hakim, Nur Alvira Pascawati, Ajib Diptyanusa
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引用次数: 4

摘要

原则上,引起登革出血热的登革热病毒是通过伊蚊叮咬传播给人类的。在印度尼西亚,该病在大多数省份流行,包括中爪哇克laten区的Gergunung村。该村在过去5年中出现了最高的登革出血热发病率。人口状况、环境和气候条件的变化是登革热的预测因素。本研究旨在通过对潜在预测因子的分析,揭示人类行为变量、自然环境因素和气候因素与登革出血热传播的关系,建立登革出血热疫情主动监测模型。本研究采用病例对照设计的观察性分析研究。研究人群选自2016 - 2017年发生登革出血热病例的家庭和对照,比例为1:2。共有34个家庭被标记为病例,68个家庭被标记为对照。数据收集通过观察、直接测量和访谈进行。对资料进行统计学分析,概率值为p 0.05)。房屋间距离越近,DHF发病越多(p<0.05;OR: 2.96;95% ci: 1.01-8.67)。在本研究中,物理环境因素和气候因素与登革出血热病例的发生没有显著的关联。人类行为变量、自然环境因素和气候因素可能是登革出血热暴发的潜在预测因子,应纳入模型,加强预警系统。
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Prediction model of dengue hemorrhagic fever transmission to enhance early warning system in Gergunung Village, Klaten District, Central Java
The dengue virus that causes dengue hemorrhagic fever (DHF) in principle is transmitted to humans through the bites of Aedes sp. In Indonesia, the disease is endemic in most provinces, including in Gergunung Village in Klaten District, Central Java. The village has shown the highest incidence of DHF for the last 5 years. Changes in demographical conditions, environment, and climate condition are predictors of dengue fever. This study aimed to demonstrate the association among human behavioral variables, physical environmental factors, and climate elements with DHF transmission to develop active surveillance model of DHF outbreak by the analysis of potential predictors. The research was an observational analytic study with case control design. Study population was selected from households with DHF case in 2016 through 2017 and the controls with ratio of 1:2. In total, 34 households were labeled as case and 68 households were labeled as control. Data collection was performed by observations, direct measurements, and interviews. Data were analyzed using appropriate statistical analysis with probability value of p 0.05). In contrast, houses closer to each other tended to have more DHF cases (p<0.05; OR: 2.96; 95% CI: 1.01–8.67). Physical environmental factors and climate elements did not demonstrate significant associations with DHF case occurrence in this study. Human behavioral variables, physical environmental factors, and climate elements may serve as potential predictors of DHF outbreak, hence should be put into the model to enhance early warning system.
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