학술논문
Predicting Factors for COVID-19 Infection: A Cross-Sectional Study in Indonesia
Document Type
article
Author
Pharmasinta Putri Hapsari; Lily Aina; Nanda Ardianto; Eunice Marlene Sicilia Kundiman; Fatimatuz Zahra Oviary Satryo; Melinda Putri Amelia Rachman; Fauzul Meiliani; Farah Meutia; Arina Dery Puspitasari; Bambang Subakti Zulkarnain; Alfian Nur Rosyid; Tamara Nur Budiarti; Brigitta Dhyah Kunthi Wardhani; Dhieo Kurniawan
Source
WMJ (Warmadewa Medical Journal), Vol 8, Iss 1, Pp 34-40 (2023)
Subject
Language
English
ISSN
2527-4627
2579-9010
2579-9010
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.