A time-motion study of the COVID-19 vaccination process in an urban primary health center of Odisha, India

Vaccination is a critical tool in protecting against COVID-19. It is essential to know the time for each activity in a COVID-19 vaccination process for better management, especially during a pandemic. Thus, we conducted a time-motion study to identify activities that led to delayed/increased waiting time in an urban primary health center in Bhubaneswar, India. We observed 196 COVID-19 vaccine beneficiaries over one month (June 2021) from when they arrived at the vaccination center until they left the center. A data collection form and a Stopwatch were used to estimate the time taken for various activities involved in COVID-19 vaccine delivery. The time taken was expressed in mean and median. We also compared the time taken during the first and second doses using the Mann-Whitney U test. The total mean time spent at the vaccination center was 40:56 ± 20:52 minutes. The activity that took the longest was ‘waiting time in queue before vaccination’, which was 34:22 ± 20:56 min constituting 82% of the total time. The activity that took longer for the second dose than the first was the beneficiary verification in the Co-WIN portal with a median of 27 seconds and 36 seconds, respectively (p < .001). This study will help program managers formulate better strategies to improve the vaccination process making it more efficient

Challenges of objective structured clinical examination as a tool in medical assessment

Medical education is witnessing changes across the globe to produce more competent and responsive medical graduates to meet patients' growing needs. Medical educators are aspiring for more objective and relevant assessment methods for the evaluation of medical graduates. Objective structured clinical examination (OSCE) introduced in the year 1975 for clinical evaluation has gone through many changes over the past 45 years and matured over time. The article describes the challenges of OSCE as a tool in medical assessment from students' and organizers' perspectives. We have also suggested a feasible solution to address the challenges while conducting OSCE to assess medical students

Characteristics and predictors of Long COVID among diagnosed cases of COVID-19.

BackgroundLong COVID or long-term symptoms after COVID-19 has the ability to affect health and quality of life. Knowledge about the burden and predictors could aid in their prevention and management. Most of the studies are from high-income countries and focus on severe acute COVID-19 cases. We did this study to estimate the incidence and identify the characteristics and predictors of Long COVID among our patients.MethodologyWe recruited adult (≥18 years) patients who were diagnosed as Reverse Transcription Polymerase Chain Reaction (RTPCR) confirmed SARS-COV-2 infection and were either hospitalized or tested on outpatient basis. Eligible participants were followed up telephonically after four weeks and six months of diagnosis of SARS-COV-2 infection to collect data on sociodemographic, clinical history, vaccination history, Cycle threshold (Ct) values during diagnosis and other variables. Characteristics of Long COVID were elicited, and multivariable logistic regression was done to find the predictors of Long COVID.ResultsWe have analyzed 487 and 371 individual data with a median follow-up of 44 days (Inter quartile range (IQR): 39,47) and 223 days (IQR:195,251), respectively. Overall, Long COVID was reported by 29.2% (95% Confidence interval (CI): 25.3%,33.4%) and 9.4% (95% CI: 6.7%,12.9%) of participants at four weeks and six months of follow-up, respectively. Incidence of Long COVID among patients with mild/moderate disease (n = 415) was 23.4% (95% CI: 19.5%,27.7%) as compared to 62.5% (95% CI: 50.7%,73%) in severe/critical cases(n = 72) at four weeks of follow-up. At six months, the incidence among mild/moderate (n = 319) was 7.2% (95% CI:4.6%,10.6%) as compared to 23.1% (95% CI:12.5%,36.8%) in severe/critical (n = 52). The most common Long COVID symptom was fatigue. Statistically significant predictors of Long COVID at four weeks of follow-up were-Pre-existing medical conditions (Adjusted Odds ratio (aOR) = 2.00, 95% CI: 1.16,3.44), having a higher number of symptoms during acute phase of COVID-19 disease (aOR = 11.24, 95% CI: 4.00,31.51), two doses of COVID-19 vaccination (aOR = 2.32, 95% CI: 1.17,4.58), the severity of illness (aOR = 5.71, 95% CI: 3.00,10.89) and being admitted to hospital (Odds ratio (OR) = 3.89, 95% CI: 2.49,6.08).ConclusionA considerable proportion of COVID-19 cases reported Long COVID symptoms. More research is needed in Long COVID to objectively assess the symptoms and find the biological and radiological markers

Effectiveness of COVID-19 vaccine (Covaxin) against breakthrough SARS-CoV-2 infection in India

India approved COVID-19 vaccine called Covaxin, developed by the Indian Council of Medical Research and Bharat Biotech Ltd. The primary objective of the study was to estimate the effectiveness of Covaxin in preventing breakthrough SARS-CoV-2 infection in healthcare workers (HCWs). A test-negative matched case-control study was conducted among HCWs of tertiary care hospital in Eastern India. Any HCW who tested positive for COVID-19 using RT-PCR during April and May 2021 was taken as the case. The HCWs who tested negative for COVID-19 by RT-PCR were considered as controls after matching with the date of testing and profession of the cases. Vaccination data were collected from the institution’s vaccine database and recall. In case of discrepancy, it was confirmed from the CoWIN portal (cowin.gov.in). The sample size was 670 participants (335 pairs). Conditional logistic regression models were used to calculate the adjusted odds ratio for breakthrough SARS-CoV-2 infection. Vaccine effectiveness was calculated using the following formula: VE = (1-aOR) × 100%. Sensitivity analysis was done for effectiveness of Covaxin, excluding Covishield vaccination. The mean age of participants was 29.1 years (SD = 7.1), and the majority were males (55.2%). Among the study participants, 60% were completely vaccinated, 18.51% were partially vaccinated, and 21.49% were unvaccinated. After adjusting for age, gender, type of household and past history of COVID-19 disease in conditional logistic models, the vaccine effectiveness was 22% (aOR 0.78, 95% CI: 0.52–1.17; p = .233). Sensitivity analysis with Covaxin showed an effectiveness of 29% (aOR 0.71, 95% CI: 0.47–1.08; p = .114) for preventing breakthrough SARS-CoV-2 infection

Characteristics and predictors of Long COVID among diagnosed cases of COVID-19

A cohort study from a tertiary care hospital of Eastern India, which captures the incidence, characteristics and predictor of Long COVID among diagnosed cases of COVID-19, during four weeks and six months of follow-up.</p

Percentage of self-reported Long COVID symptoms at four weeks and six months of follow-up.

Percentage of self-reported Long COVID symptoms at four weeks and six months of follow-up.</p