Knowledge, attitude, and practice related to the COVID-19 pandemic among undergraduate medical students in Indonesia: a nationwide cross-sectional study (preprint)

IntroductionThe potential role of medical students in raising awareness during public health emergencies has been acknowledged. To further explore their potentials as public educators and role models for the communities during the coronavirus disease 2019 (COVID-19) pandemic, a study is conducted to assess the knowledge, attitude, and practice of these students toward COVID-19. MethodsAn online cross-sectional survey was conducted among undergraduate medical students in Indonesia. Socio-demographical characteristics, social interaction history, information-seeking behavior, as well as knowledge, attitude, and practice toward COVID-19 were collected through a self-reported questionnaire. A p-value of <0.05 indicated statistical significance. ResultsOut of 4870 respondents, 64.9% and 51.5% had positive attitude and practice toward COVID-19 while only 29.8% had adequate knowledge. Knowledge was slightly positively correlated with attitude and practice ({rho}=0.074 and {rho}=0.054, respectively; both p<0.001), while attitude was weakly correlated with practice ({rho}=0.234, p<0.001). Several factors including age, sex, place of residence, institution type, academic level, family income, history of chronic illness, prior volunteering experience, and perceptual awareness on COVID-19 were significantly associated with either knowledge, attitude, and/or practice toward COVID-19. Furthermore, health institutions and the governments press releases, as well as health expert opinions were deemed as the most reliable sources of COVID-19-related information - yet trivially none of these sources were associated with knowledge, attitude, and practice in the study population. ConclusionMany undergraduate medical students in Indonesia had positive attitude and practice against COVID-19, yet only a few had adequate knowledge. This warrants further interventions to keep them updated with COVID-19 evidence to maximize their potentials in raising public awareness on COVID-19.

The emergence of COVID-19 in Indonesia: analysis of predictors of infection and mortality using independent and clustered data approaches (preprint)

Background: Analyses of correlates of SARS-CoV-2 infection or mortality have usually assessed individual predictors. This study aimed to determine if patterns of combined predictors may better identify risk of infection and mortality. Methods: For the period of March 2nd to 10th 2020, the first 9 days of the COVID-19 pandemic in Indonesia, we selected all 18 confirmed cases, of which 6 died, and all 60 suspected cases, of which 1 died; and 28 putatively negative patients with pneumonia and no travel history. We recorded data for travel, contact history, symptoms, haematology, comorbidities, and chest x-ray. Hierarchical cluster analyses (HCA) and principal component analyses (PCA) identified cluster and covariance patterns for symptoms or haematology which were analysed with other predictors of infection or mortality using logistic regression. Results: For univariate analyses, no significant association with infection was seen for fever, cough, dyspnoea, headache, runny nose, sore throat, gastrointestinal complaints (GIC), or haematology. A PCA symptom component for fever, cough, and GIC tended to increase risk of infection (OR 3.41; 95% CI 1.06 - 14; p=0.06), and a haematology component with elevated monocytes decreased risk (OR 0.26; 0.07 - 0.79; 0.027). Multivariate analysis revealed that an HCA cluster of 3-5 symptoms, typically fever, cough, headache, runny nose, sore throat but little dyspnoea and no GIC tended to reduce risk (aOR 0.048; <0.001 - 0.52; 0.056). In univariate analyses for death, an HCA cluster of cough, fever and dyspnoea had increased risk (OR 5.75; 1.06 - 31.3, 0.043), but no other individual predictor, cluster or component was associated. Other significant predictors of infection were age >= 45, international travel, contact with COVID-19 patient, and pneumonia. Diabetes and history of contact were associated with higher mortality. Conclusions: Cluster groups and co-variance patterns may be stronger correlates of SARS-CoV-2 infection than individual predictors. Comorbidities may warrant careful attention as would COVID-19 exposure levels.