资源介绍
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.
