{"title":"Environmental and Health Services Factors Associated with New Covid19 Case in Central Java Province: A Spatial Analysis","authors":"Sidiq Purwoko, Yeny Yulistanti, Diyan Ermawan Effendy, Afi Nursafingi, Ina Kusrini","doi":"10.20473/jkl.v15i1.2023.37-45","DOIUrl":null,"url":null,"abstract":"Introduction: At the end of December 2020, there were 93,035 Covid19 cases reported in Central Java. The spatial analysis is useful for assessing the association of environmental and health services factors with new Covid19 cases. Methods: This study was conducted to identify a spatial autocorrelation between environmental conditions and health services on new Covid19 cases in Central Java Province in 2020. The data were obtained from Central Java Profile Published in 2021 with a cross-sectional design. This autocorrelation regression technique was used to determine the relationship between districts/cities for new Covid19 cases. The independent variables in this study were environmental factors such as access to quality drinking water, access to quality sanitation, percentage of Open Defecation Free (ODF) villages, and percentage of healthy food management places. In addition, the independent variables also covered health service factors such as the number of public health centers, hospitals, medical personnel, and population density. Results and Discussion: The findings found that in Central Java province, the factors that influenced new Covid19 cases included population density (p-value 0.0001; Morran I -0.032) and the number of medical personnel (p-value 0.0001; Morrans I 0.021). Conclusion: The new cases of Covid19 in Central Java Province formed a clustered pattern. Factors significantly influencing the regression test are population density and the number of medical personnel. Besides that, spatial autocorrelation was also found in other variables in this study but was not significant.","PeriodicalId":32974,"journal":{"name":"Jurnal Kesehatan Lingkungan","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Kesehatan Lingkungan","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20473/jkl.v15i1.2023.37-45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: At the end of December 2020, there were 93,035 Covid19 cases reported in Central Java. The spatial analysis is useful for assessing the association of environmental and health services factors with new Covid19 cases. Methods: This study was conducted to identify a spatial autocorrelation between environmental conditions and health services on new Covid19 cases in Central Java Province in 2020. The data were obtained from Central Java Profile Published in 2021 with a cross-sectional design. This autocorrelation regression technique was used to determine the relationship between districts/cities for new Covid19 cases. The independent variables in this study were environmental factors such as access to quality drinking water, access to quality sanitation, percentage of Open Defecation Free (ODF) villages, and percentage of healthy food management places. In addition, the independent variables also covered health service factors such as the number of public health centers, hospitals, medical personnel, and population density. Results and Discussion: The findings found that in Central Java province, the factors that influenced new Covid19 cases included population density (p-value 0.0001; Morran I -0.032) and the number of medical personnel (p-value 0.0001; Morrans I 0.021). Conclusion: The new cases of Covid19 in Central Java Province formed a clustered pattern. Factors significantly influencing the regression test are population density and the number of medical personnel. Besides that, spatial autocorrelation was also found in other variables in this study but was not significant.
截至2020年12月底,中爪哇省共报告了93035例covid - 19病例。空间分析有助于评估环境和卫生服务因素与新冠肺炎病例的关联。方法:本研究旨在确定2020年中爪哇省新冠肺炎病例环境条件与卫生服务之间的空间自相关性。数据来自2021年发布的中央Java概况,采用横断面设计。利用自相关回归技术确定新发病例区/市之间的关系。本研究的自变量为环境因素,如获得优质饮用水、获得优质卫生设施、无露天排便(ODF)村的百分比和健康食品管理场所的百分比。此外,自变量还包括公共卫生中心、医院、医务人员和人口密度等卫生服务因素。结果与讨论:结果发现,在中爪哇省,影响新发病例的因素包括人口密度(p值0.0001;Morran I -0.032)和医务人员人数(p值0.0001;莫兰斯(0.021)。结论:中爪哇省新发病例呈聚集性分布。对回归检验有显著影响的因素是人口密度和医务人员数量。除此之外,本研究中其他变量也存在空间自相关,但不显著。