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

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

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...

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Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: Fakultas Kedokteran dan Ilmu Kesehatan, Universitas Warmadewa 2023-05-01
Series:WMJ (Warmadewa Medical Journal)
Subjects:
covid-19 infection
predicting factors
public health
health-care worker
covid-19 vaccination
comorbidity
Online Access:https://www.ejournal.warmadewa.ac.id/index.php/warmadewa_medical_journal/article/view/5329/4507
Description
Summary: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.
ISSN:2527-4627
2579-9010

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