Faktor yang Mempengaruhi Kejadian Demam Berdarah Dengue Berdasarkan Model Spasial di Kabupaten Sikka Tahun 2019-2021

Jurnal Bidang Ilmu Kesehatan Pub Date : 2023-09-30 DOI:10.52643/jbik.v13i3.2636

Anastasia Sofia Lete Keraf, Pius Weraman, Honey Ivon Ndoen, Yendris Krisno Syamruth

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引用次数: 0

Abstract

Various efforts to control dengue cases in Sikka Regency have been carried out, one of which was by issuing a Regent's Instruction in 2019 but cases increased by 1,816 cases from 620 cases in 2019. In 2020 another Regent's Instruction was issued so that dengue cases decreased to 183 cases. There are many risk factors for increasing dengue cases that have not been detected. One way is to look at the risk factors for dengue fever from a regional (spatial) perspective. Sikka Regency has experienced 4 outbreaks in the period 2010-2021. The study aims to analyze the factors that influence the incidence of DHF studied in the spatial analysis model. Type of research is analytic observational with an ecological study design. The data used in this study is secondary data. The results showed that there was an effect of population density in 2020 on the incidence of DHF, while population density in 2019 and 2021 had no effect. There are 6 sub-districts that become hotspot areas (High-High) in the influence of population density with DHF, namely Nelle, Kewapante, Kangae, Alok, East Alok and Lela Districts, while the coldspot (Low-High) areas are East Alok and Koting Districts. The altitude of the area has no effect on the incidence of DHF in 2019-2021. There are 2 hotspots, namely Nelle and Koting sub-districts, while the coldspot areas are in Kewapante, Alok Timur, Kangae and Lela sub-districts. There is no effect of temperature, humidity and rainfall in 2019, whereas in 2020 humidity has a positive effect and rainfall has a negative effect on the incidence of DHF and in 2021 there is a positive effect of air humidity on the incidence of DHF in Sikka Regency. Suggestions for dengue prevention programs need to be prioritized in hotspot and coldspot areas. There needs to be an alert for DHF in neighboring areas of DHF outbreaks. Keywords : Aedes Aegypti, Moran’s I, LISA, Autocorrelation spatial, Spatial regression

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基于空间模型的 2019-2021 年锡卡区登革热发病率影响因素

在西卡摄政开展了控制登革热病例的各种努力，其中之一是在2019年发布了摄政指令，但病例从2019年的620例增加到1816例。2020年发布了另一项摄政王指令，使登革热病例减少到183例。导致登革热病例增加的许多危险因素尚未被发现。一种方法是从区域(空间)角度看待登革热的危险因素。2010-2021年期间，西卡摄政经历了4次疫情。本研究旨在分析空间分析模型中DHF发病的影响因素。研究类型为生态学研究设计的分析观察。本研究使用的数据为二手数据。结果表明，2020年人口密度对登革出血热发病有影响，2019年和2021年人口密度对登革出血热发病无影响。人口密度受DHF影响的热点区(高-高)有6个街道，分别是Nelle区、Kewapante区、Kangae区、Alok区、East Alok区和Lela区，而冷点区(低-高)是East Alok区和Koting区。该地区海拔对2019-2021年登革出血热发病率无影响。有两个热点地区，即内尔和哥亭街道，而冷点地区则在基瓦潘特、阿洛克铁木尔、Kangae和莱拉街道。2019年气温、湿度和降雨量对登革出血热发病率没有影响，2020年湿度对登革出血热发病率有正影响，而降雨量对登革出血热发病率有负影响，2021年空气湿度对登革出血热发病率有正影响。登革热预防规划的建议需要优先考虑热点和冷点地区。在发生登革出血热疫情的邻近地区，需要对登革出血热发出警报。关键词:埃及伊蚊，Moran’s I, LISA，自相关空间，空间回归

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Jurnal Bidang Ilmu Kesehatan

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