RESUMO
Aim: This study aims to investigate depression, anxiety, stress, and fear of the COVID-19 pandemic and the associated risk factors among Bangladeshi medical students. It also explored qualitative insights on mental health from medical students during the first wave of the pandemic. Methods: This mixed-methods study was conducted online in Bangladesh from June 2020 to September 2020. Participants were Bangladeshi medical students from the first year to the final year. The quantitative part included a structured online survey. One focus group discussion (FGD) was organized using the Zoom platform to collect qualitative insights from the students. To determine levels of stress, anxiety, and depression, the Bangla-validated version of the Depression, Anxiety, and Stress Scale 21 (DASS-21) was used. A 7-item and Bangla-validated Fear of COVID-19 Scale, also known as FCV-19S, was used to explore the COVID-19-specific fear of the students. A semi-structured topic guide was used for exploring the qualitative insights of medical students' perceptions of fear of COVID-19, mental health impacts during COVID-19, overall recommendations to support students, and the impact of the pandemic on the future of the medical curriculum. Results: The study reported that 51.20%, 59.40%, and 64% of the 406 respondents had moderate to severe stress, anxiety, and depressive symptoms, respectively, according to the DASS-21. The mean fear score for the COVID-19 scale was 19.4 (SD 6.4). Respondents with family members aged 50 years or older (B = 2.1; CI: 0.3-3.9) and those who had infected family members (B = 1.9; 95% CI: 0.1-3.7) exhibited a higher level of fear of COVID-19. Moreover, depression was associated with a history of having cancer among family members (AOR = 2.9, CI: 1.1-7.5), anxiety was strongly associated with having symptoms of COVID-19 (AOR = 2, CI: 1.3-3.2), and stress was associated with having symptoms of COVID-19 infection among family members (AOR = 1.9, CI: 1.3-3). Altered sleep was a potential risk factor for developing stress, anxiety, and depression symptoms. Manual thematic analysis of qualitative data generated four major themes, including the perception of fear of COVID-19, the perception of mental health impacts during COVID-19, the change in the medical curriculum along with the pandemic, and recommendations from the medical students to support the mental health concerns of medical students during public health crises like this pandemic. Qualitative findings showed that the participants experienced fear of their parents becoming infected by COVID-19, and this fear was more prominent in those who had their loved ones hospitalized. They were also stressed and anxious, with thoughts of death. Their fear also extended to their thoughts on academic progress and the effectiveness of online classes. Conclusion: A substantial proportion of medical students experienced mental health difficulties in Bangladesh. Appropriate interventions should be designed, and adequate support should be provided to the medical students to protect their mental health and wellbeing, considering their potential impact on the future health system in a low-resource setting like Bangladesh.
RESUMO
Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the effectiveness of interventions. Asymptomatic breakthrough infections have been a major problem during the ongoing surge of Delta variant globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines used in the higher-income regions. Here, we show for the first time how statistical and machine learning (ML) approaches can discriminate SARS-CoV-2 infection from immune response to an inactivated whole virion vaccine (BBV152, Covaxin, India), thereby permitting real-world vaccine effectiveness assessments from cohort-based serosurveys in Asia and Africa where such vaccines are commonly used. Briefly, we accessed serial data on Anti-S and Anti-NC antibody concentration values, along with age, sex, number of doses, and number of days since the last vaccine dose for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine (SVM) model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, 724 were classified as infected. Since the vaccine contains wild-type virus and the antibodies induced will neutralize wild type much better than Delta variant, we determined the relative ability of a random subset of such samples to neutralize Delta versus wild type strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, Delta variant, was neutralized more effectively than the wild type, which cannot happen without infection. The fraction rose to 71.8% (28 of 39) in subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period.
RESUMO
To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India), conducted a sero-survey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS CoV2 anti-nucleocapsid (anti-NC) antibodies; 95% with surrogate neutralization activity. Three-fourth recalled no symptoms. Repeat serology tests at 3 (n=346) and 6 (n=35) months confirmed stability of antibody response and neutralization potential. Local sero-positivity was higher in densely populated cities and was inversely correlated with a 30 day change in regional test positivity rates (TPR). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of sero-positivity were high-exposure work (Odds Ratio, 95% CI, p value; 2{middle dot}23, 1{middle dot}92-2{middle dot}59, 6{middle dot}5E-26), use of public transport (1{middle dot}79, 1{middle dot}43-2{middle dot}24, 2{middle dot}8E-06), not smoking (1{middle dot}52, 1{middle dot}16-1{middle dot}99, 0{middle dot}02), non-vegetarian diet (1{middle dot}67, 1{middle dot}41-1{middle dot}99, 3{middle dot}0E-08), and B blood group (1{middle dot}36,1{middle dot}15-1{middle dot}61, 0{middle dot}001). Impact StatementWidespread asymptomatic and undetected SARS-CoV2 infection affected more than a 100 million Indians by September 2020. Declining new cases thereafter may be due to persisting humoral immunity amongst sub-communities with high exposure. FundingCouncil of Scientific and Industrial Research, India (CSIR)
RESUMO
The aim of this study is to compare accessibility of vision-impaired (VI) patients to other eyecare centres before attending the mobile and stationary hospitals. Under a cross-sectional study design, VI patients were consecutively enrolled if they visited one of the three Impact Foundation Hospitals--one mobile and two stationary hospitals. The cost and service output of all hospitals were also reviewed; 27.7% of patients at the mobile and 36.8% at the two stationary hospitals had sought eyecare at other health facilities in the past. Mobile hospital patients lived closer to the hospital but spent more time in travelling, bore less direct cost, needed less extra support, and had a higher level of satisfaction on the service. They also identified more barriers to access eyecare in the past. The mobile hospital had a higher percentage of patients with accessibility problems and should continue to help the remote population in overcoming these problems.
