Socio-spatial Aspects Contributing to the Spread of COVID-19 in Yogyakarta Province (Indonesia)

Pub Date : 2023-01-01 DOI:10.21638/spbu07.2023.209
R. Pramono, Ramadhani N. Putri
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Abstract

In the early pandemic, the positive cases of COVID-19 predominately occurred in the big cities in Indonesia. However, the virus spread rapidly and extensively across the cities and districts. This shows that the COVID-19 pandemic is limited to urban areas and has spread widely to more remote area This study aims to investigate the correlation between socio-economic characteristics against the spread of confirmed COVID-19 cases. In this study, we collected data from residents with confirmed positive for COVID-19 and their socio-economic profiles in 78 subdistricts in the Special Region of Yogyakarta province, Indonesia. The collected data were statistically analyzed in three sequential steps, including a correlation test, classic assumption test (e.g., normality test, homoscedasticity test, and non-multicollinearity test), and multiple regression test to determine the correlation between the COVID-19-infected population and the socio-economic data in each subdistrict (as dependent variables). The results demonstrated that regions with more urban character, particularly socio-economic, were more susceptible to COVID-19 infection during the first year of the pandemic. However, the socio-spatial aspects such as population density as one of the requirements for the "compact cities" and the proportion of built-up land area were not contributing factors to the viral transmission. Socio-spatial aspects may influence the risk of virus transmission, but not as significantly as social factors and human behavior in an area. Therefore, efforts to prevent the spread of the COVID-19 virus must be more focused on social factors and human behavior.
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促进COVID-19在日惹省(印度尼西亚)传播的社会空间因素
在大流行早期,COVID-19阳性病例主要发生在印度尼西亚的大城市。然而,病毒在城市和地区迅速而广泛地传播。这表明COVID-19大流行仅限于城市地区,并已广泛传播到更偏远的地区。本研究旨在探讨社会经济特征与COVID-19确诊病例传播之间的相关性。在这项研究中,我们收集了来自印度尼西亚日惹省特区78个街道的COVID-19确诊阳性居民及其社会经济概况的数据。对收集到的数据进行相关检验、经典假设检验(如正态性检验、均方差检验、非多元共线性检验)和多元回归检验3个步骤的统计分析,确定各街道感染人群与社会经济数据(作为因变量)的相关性。结果表明,在大流行的第一年,城市特征更强的地区,特别是社会经济特征更强的地区,更容易感染COVID-19。然而,社会空间方面,如作为“紧凑型城市”要求之一的人口密度和建成土地面积的比例,并不是病毒传播的促成因素。社会空间因素可能会影响病毒传播的风险,但影响程度不如一个地区的社会因素和人类行为。因此,预防新冠病毒传播必须更加注重社会因素和人的行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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