RESUMO
Background: Hydroxychloroquine (HCQ) had generated considerable interest for coronavirus disease 2019 (COVID-19) prophylaxis. We conducted a prospective observational study at a tertiary care hospital in India, with dedicated COVID-19 care facilities. Objectives: Primary objective was incidence of adverse effects, secondary objective being efficacy in preventing COVID-19. Methods: Healthcare workers were recruited and grouped based on voluntary HCQ prophylaxis as per national guidelines. Side effects in HCQ group were graded in accordance with national cancer institute-common terminology criteria for adverse events (NCI-CTCAE) version 5.0. At 3-7-week follow-up, groups were compared for COVID-19 exposure, symptoms development and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RT-PCR results. Results: Among 358 participants recruited, 216 (60.3%) were males and mean age was 31.2 ± 6.6 years. Chemoprophylaxis was initiated by 258 (72%) participants. After loading dose, 7 (2.7%) reported grade 2 and 1 (0.4%) grade 3 adverse effects. Discontinuation of HCQ due to side effects was reported in 11 (4.3%) participants. Electrocardiogram was done by 50 (19.4%) participants on HCQ; no abnormalities were noted. A total of 106 (41%) among those taking and 63 (63%) among those not taking HCQ were tested for SARS-CoV-2 due to influenza-like illness or significant exposure. Among all participants, 25 (6.9%, 95% confidence interval [CI] 4.3-9.6) developed COVID-19 during the study period. In the group taking HCQ, 10 (3.9%) tested positive compared to 15 (15%) in the group not taking HCQ (P < 0.001). Odds ratio with HCQ intake was 0.34 (95% CI 0.13-0.83, P = 0.01) and the number needed to treat was 12. Conclusion: HCQ is safe at the recommended dose for pre-exposure prophylaxis of COVID-19.
RESUMO
OBJECTIVE: The present study aims to predict the likelihood of and likely time required to attain herd immunity against COVID-19 in New Delhi due to natural infection. METHOD: An ODE-based mathematical model was constructed by extending the classical SEIR model to predict the seroprevalence rate. We estimated the parameter values for Delhi using available data (reported cases and the seroprevalence rate) and used them for future prediction. Also, changes in the seroprevalence rate with different possibilities of reinfection were predicted. RESULTS: Maximum seroprevalence rate obtained through our model is 31.65% and also a reduction in the seroprevalence rate was observed for the upcoming one month (month of January, 2021) due to the reduced transmission rate. After increasing the transmission rate to the value same as the third wave in New Delhi, we obtained a maximum value of 54.96%. This maximum value significantly decreased with the reduction in the reinfection possibilities. Also, a little impact of the duration of persistence of antibodies, 180 vs 105 days, was observed on the maximum seroprevalence. CONCLUSION: This modelling study suggests that natural infection alone, as gauged by serial sero-surveys, may not result in attainment of herd immunity in the state of Delhi.
