Predicting Factors for COVID-19 Infection: A Cross-Sectional Study in Indonesia

Abstract

COVID-19 cases in Indonesia still remain a concern, particularly for public health. Several factors, such as gender, age, comorbidity, occupation, and vaccination status, might influence COVID-19 infection. Individuals who have many predicting factors have a higher risk of being infected by COVID-19. Other studies have not yet shown the significance of predicting factors for COVID-19 infection in Indonesia. The study explored the association between the predicting factors and COVID-19 infection in Indonesia. The study used a cross-sectional method with a population of all Indonesian communities. It was conducted in August 2021 by distributing a Google Form questionnaire in Indonesia. By a saturated sampling of the population in Jawa, Sumatera, Sulawesi, Kalimantan, and Papua, 776 Indonesians were selected; they were aged > 17 years and voluntarily completed the questionnaires. whereas respondents with incomplete data were excluded from this study. The data were analyzed using a binary logistic regression test in SPSS (version 21.0). The respondents include 134 men (17.3%) and 642 women (82.7%). The binary logistic regression analysis showed that COVID-19 infection was more common among respondents who were non-health-care workers (p 0.001) and less common among those who had been fully vaccinated (p 0.001). The COVID-19 infection was significantly associated with occupation and vaccination status.

Keywords

• covid-19 infection
• predicting factors
• public health
• health-care worker
• covid-19 vaccination
• comorbidity