Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/11603
Title: Social Determinants of Covid-19 Morbidity in Indonesia: Observational District Level Analysis
Authors: Heryana, Ade
Adisasmito, Wiku
Ayuningtyas, Dumilah
Keywords: Covid-19;
Pandemic;
Social Determinants;
Morbidity;
Delta Wave;
Issue Date: Mar-2025
Publisher: Published by Public Health Faculty, Hasanuddin University
Abstract: ABSTRACT Since the COVID-19 pandemic globally struggled in late 2019, the global community has become aware that outbreaks of infectious diseases are associated with conditions beyond health factors, such as social, economic, demographic, geographic, and lifestyle. This paper aims to identify the influence of Social Determinants of Health (SDOH) on COVID-19 morbidity rates in Indonesia. The study analyzed morbidity cases during the second wave of the COVID-19 pandemic, namely the Delta variant wave. Multivariate analysis with linear regression was used to determine the predictors that affect COVID-19 morbidity in 128 districts/cities of the Java and Bali isles, which were controlled by the pandemic stages including pre, resurgence, decline, and post. Morbidity data was collected cross-sectionally from the National COVID-19 Task Force dataset and the social determinant of the 2021 Central Statistics Agency report. The number of health facilities is the most influential characteristic of the regency/city to COVID-19 morbidity at the pre-and resurgence-pandemic stages. The ratio of the immune population is the most influential characteristic when the pandemic experiences a decline stage; meanwhile, during the post-pandemic, the second dose of vaccination is the most influential characteristic. We recommended that testing, tracing, quarantine, and isolation intervention should be prioritized in the districts/cities with higher health facilities (preand resurgence-stage), higher herd immunity (decline-stage), and booster vaccination (post-stage). Social determinants of health are suggested to be used as a basis for predicting the risk factors for an outbreak of infectious diseases in a region and contributing to different SDOH factors in different outbreak stages.
URI: http://localhost:8080/xmlui/handle/123456789/11603
ISSN: 2356-4067
Appears in Collections:VOL 21 NO 1 2025

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