Social determinants of Covid-19 infection and death in a rural Indonesia: A rapid healthcare assessment

Understanding the social determinants of Covid-19 infection and death is vital for effective Covid-19 early detection and mitigation strategies. This study aims to examine social determinants of Covid-19 infection and death in the context of rural Indonesia. We used Malang district government Covid-19 contact tracing data from 14,264 individuals, spanning the period from March 1, 2020 to July 29, 2020. The contact tracing data was merged with administrative data from 390 villages to determine whether village characteristics (i.e., the number of health workers, number of community-based healthcare interventions, access to Covid-19 referred hospitals, number of indigenous socio-cultural activities, poverty level and distance to a Covid-19 epicentre city) are associated with Covid-19 infection and death. We used multilevel logistic regression to take advantage of the nested structure of data at the village level. We found among the 14,264 samples, 551 individuals were confirmed infected with Covid-19, and 62 died of Covid-19. Individuals aged 18 and older, civil servants (non-health workers), and those having close contact with people with confirmed cases had a higher likelihood of infection with Covid-19. Greater numbers of community-based healthcare interventions and a lesser distance to a pandemic epicentre reduced the likelihood of infection with the virus. Males, older people, individuals with hypertension, individuals diagnosed with pneumonia, and those diagnosed with respiratory failure had a higher likelihood of death due to Covid-19. A greater number of community-based healthcare interventions seems to reduce the likelihood of Covid-19 infection, while better access to a Covid-19 referred hospital seems to reduce the risk of death among Covid-19 patients. The findings suggest the government to prioritise strategies to control the pandemic in rural area through empowering rural community in health education to prevent Covid-19 and in monitoring people mobility, while providing Covid-19 emergency services for rural areas for reducing mortality.

明确新冠病毒感染与死亡的社会决定因素，对于制定高效的新冠早期检测及疫情缓解策略至关重要。本研究旨在以印度尼西亚农村地区为研究场景，探讨新冠感染与死亡的社会决定因素。我们使用了2020年3月1日至2020年7月29日期间、来自玛琅（Malang）区政府的14264名个体的新冠接触者追踪（contact tracing）数据。本研究将该接触者追踪数据与覆盖390个村庄的行政数据进行合并，以分析村庄特征——包括卫生工作者数量、社区医疗干预项目数量、新冠转诊医院可及性、本土社会文化活动频次、贫困水平以及至新冠疫情震中城市的距离——是否与新冠感染及死亡存在关联。我们采用多层逻辑回归（multilevel logistic regression）模型，以利用村庄层面的嵌套数据结构。在14264份研究样本中，共确认551名个体感染新冠，62名个体因新冠死亡。18岁及以上人群、公务员（非卫生工作者）以及与确诊病例有密切接触者，其新冠感染风险更高。更多的社区医疗干预项目以及与疫情震中更短的距离，可降低病毒感染风险。男性、老年人群、高血压患者、肺炎确诊患者以及呼吸衰竭确诊患者，其因新冠死亡的风险更高。更多的社区医疗干预项目似乎可降低新冠感染风险，而更好的新冠转诊医院可及性则可降低新冠患者的死亡风险。本研究结果提示，政府应优先制定农村地区疫情防控策略：通过赋能农村社区开展新冠防控健康教育与人员流动监测，并为农村地区提供新冠应急医疗服务，以降低新冠死亡率。