Center for Public Health Innovation, Faculty of Medicine, Udayana University, Bali, Indonesia.
Discipline of Public Health, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia.
Front Public Health. 2021 Feb 1;9:605290. doi: 10.3389/fpubh.2021.605290. eCollection 2021.
To analyze the correlation between demographic and healthcare availability indicators with COVID-19 outcome among Indonesian provinces. We employed an ecological study design to study the correlation between demographics, healthcare availability, and COVID-19 indicators. Demographic and healthcare indicators were obtained from the Indonesian Health Profile of 2019 by the Ministry of Health while COVID-19 indicators were obtained from the Indonesian COVID-19 website in August 31st 2020. Non-parametric correlation and multivariate regression analyses were conducted with IBM SPSS 23.0. We found the number of confirmed cases and case growth to be significantly correlated with demographic indicators, especially with distribution of age groups. Confirmed cases and case growth was significantly correlated ( < 0.05) with population density (correlation coefficient of 0.461 and 0.491) and proportion of young people (-0.377; -0.394). Incidence and incidence growth were correlated with ratios of GPs (0.426; 0.534), hospitals (0.376; 0.431), primary care clinics (0.423; 0.424), and hospital beds (0.472; 0.599) per capita. For mortality, case fatality rate (CFR) was correlated with population density (0.390) whereas mortality rate was correlated with ratio of hospital beds (0.387). Multivariate analyses found confirmed case independently associated with population density (β of 0.638) and demographic structure (-0.289). Case growth was independently associated with density (0.763). Incidence growth was independently associated with hospital bed ratio (0.486). Pre-existing inequality of healthcare availability correlates with current reported incidence and mortality rate of COVID-19. Lack of healthcare availability in some provinces may have resulted in artificially low numbers of cases being diagnosed, lower demands for COVID-19 tests, and eventually lower case-findings.
分析印度尼西亚各省人口统计学和医疗保健可及性指标与 COVID-19 结局之间的相关性。我们采用生态研究设计来研究人口统计学、医疗保健可及性和 COVID-19 指标之间的相关性。人口统计学和医疗保健指标来自卫生部 2019 年的印度尼西亚健康状况，而 COVID-19 指标则来自 2020 年 8 月 31 日的印度尼西亚 COVID-19 网站。使用 IBM SPSS 23.0 进行非参数相关性和多元回归分析。我们发现确诊病例数和病例增长率与人口统计学指标显著相关，尤其是与年龄组分布相关。确诊病例数和病例增长率与人口密度（相关系数为 0.461 和 0.491）和年轻人比例（-0.377；-0.394）显著相关。发病率和发病率增长率与全科医生比例（0.426；0.534）、医院比例（0.376；0.431）、初级保健诊所比例（0.423；0.424）和每千人的病床比例（0.472；0.599）相关。死亡率方面，病例死亡率（CFR）与人口密度（0.390）相关，而死亡率与病床比例（0.387）相关。多变量分析发现，确诊病例数独立与人口密度（β为 0.638）和人口统计学结构（-0.289）相关。病例增长率独立与密度（0.763）相关。发病率增长率独立与病床比例（0.486）相关。医疗保健可及性的先前不平等与当前报告的 COVID-19 发病率和死亡率相关。一些省份医疗保健的缺乏可能导致诊断出的病例数量人为减少，对 COVID-19 检测的需求降低，最终发现的病例数量减少。
