Dessy Triana, M. Martini, A. Suwondo, Muchlis Achsan Udji Sofro Achsan Udji Sofro, S. Hadisaputro, S. Suhartono
{"title":"Dengue Hemorrhagic Fever (DHF): Vulnerability Model Based on Population and Climate Factors in Bengkulu City","authors":"Dessy Triana, M. Martini, A. Suwondo, Muchlis Achsan Udji Sofro Achsan Udji Sofro, S. Hadisaputro, S. Suhartono","doi":"10.31584/jhsmr.2023982","DOIUrl":null,"url":null,"abstract":"Objective: The causes for the increasing number of dengue cases are complex and multifactorial. The approach taken must combine influencing factors, and comprehensive prevention strategy is needed that includes all the components of factors that influence dengue disease to predict the incidence of the disease. This research aimed to analyze the relationship between population and climate components including population density, population density <15 years old, sanitation, temperature, humidity and rainfall, on the incidence rate of Dengue Hemorrhagic Fever (DHF).Material and Methods: This study used a cross-sectional design, with the research sample being all sub-districts in Bengkulu City, Indonesia (67 sub-districts). Data analysis was conducted using structural equation modeling to create a dengue modeling based on population and climate factors, through the SmartPLS application.Results: Population and climate factors had a significant relationship with the incidence rate of dengue, with p-values of 0.018 and 0.000, respectively. Population and climate factors had a percentage effect on the incidence rate of dengue (36.9%).Conclusion: Population and climate factors had an influence of 36.9% on the incidence of dengue. There were many factors affecting the incidence of dengue, so a more comprehensive modeling of the various influencing factors is needed. Dengue modeling is crucial as an early warning system for the early prevention of dengue outbreaks, so that the control strategies implemented can be more effective.","PeriodicalId":36211,"journal":{"name":"Journal of Health Science and Medical Research","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Health Science and Medical Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31584/jhsmr.2023982","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: The causes for the increasing number of dengue cases are complex and multifactorial. The approach taken must combine influencing factors, and comprehensive prevention strategy is needed that includes all the components of factors that influence dengue disease to predict the incidence of the disease. This research aimed to analyze the relationship between population and climate components including population density, population density <15 years old, sanitation, temperature, humidity and rainfall, on the incidence rate of Dengue Hemorrhagic Fever (DHF).Material and Methods: This study used a cross-sectional design, with the research sample being all sub-districts in Bengkulu City, Indonesia (67 sub-districts). Data analysis was conducted using structural equation modeling to create a dengue modeling based on population and climate factors, through the SmartPLS application.Results: Population and climate factors had a significant relationship with the incidence rate of dengue, with p-values of 0.018 and 0.000, respectively. Population and climate factors had a percentage effect on the incidence rate of dengue (36.9%).Conclusion: Population and climate factors had an influence of 36.9% on the incidence of dengue. There were many factors affecting the incidence of dengue, so a more comprehensive modeling of the various influencing factors is needed. Dengue modeling is crucial as an early warning system for the early prevention of dengue outbreaks, so that the control strategies implemented can be more effective.