Project description:ObjectiveTo investigate the presence of white hat bias in Covid-19 treatment research by evaluating the effects of citation and reporting bias.Study design and settingCitation bias was investigated by assessing the degree of agreement between evidence provided by a remdesivir randomized controlled trial and its citing articles. The dissimilarity of outcomes derived from nonrandomized and randomized studies was tested by a meta-analysis of hydroxychloroquine effects on mortality. The differential influence of studies with beneficial over those with neutral results was evaluated by a bibliometric analysis.ResultsThe articles citing the ACTT-1 remdesivir trial preferentially presented its positive outcomes in 55.83% and its negative outcomes in 6.43% of cases. The hydroxychloroquine indicated no significant effect by randomized studies, but a significant survival benefit by nonrandomized ones. Citation mapping revealed that the study reporting survival benefit from the hydroxychloroquine-azithromycin combination was the most influential, despite subsequent studies reporting potential harmful effects.ConclusionThe present study raises concerns about citation bias and a predilection of reporting beneficial over harmful effects in the Covid-19 treatment research, potentially in the context of white hat bias. Preregistration, data sharing and avoidance of selective reporting are crucial to ensure the credibility of future research.
Project description:PurposeConflicting information on potential benefits of drugs as well as reports on hypothetical harm of commonly used drugs in COVID-19 treatment have challenged clinicians and healthcare systems. We analyzed the change in ambulatory drug utilization before, during, and after the first wave of the pandemic in 2020.MethodsWe explored dispensing data of nearly 19 000 pharmacies at the expense of the statutory health insurance funds covering 88% of Germany's population. We analyzed utilization of publicly discussed drugs with conflicting information. Drug utilization as number of packages dispensed per week from January to June 2020, reflecting 314 million claims, was compared with 2019.ResultsUtilization of hydroxychloroquine increased +110% during March 2020 and then slightly decreased until week April 13-19. Renin-angiotensin-aldosterone system inhibitors and simvastatin/atorvastatin increased, +78% and +74%, respectively, and subsequently decreased below 2019 levels. Utilization of azithromycin and all systemic antibiotics decreased continuously from March 2-8 until June to levels considerably lower compared to 2019 (June 22-28: azithromycin: -55%, all systemic antibiotics: -27%). Pneumococcal vaccines utilization initially increased +373%, followed by supply shortages. Paracetamol utilization showed an initial increase of +111%, mainly caused by an increase of over-the-counter dispensings.ConclusionsApart from the pandemic itself, the data suggest that dissemination of misinformation and unsound speculations as well as supply shortages influenced drug prescribing, utilization, and purchasing behavior. The findings can inform post-pandemic policy to prevent unfounded over- and underprescribing and off-label use as well as drug shortages during a public health crisis.
Project description:Stay-at-home-orders, online learning, and work from home policies are some of the responses governments, universities, and other institutions adopted to slow the spread of COVID-19. However, research shows these measures have increased pre-existing gender disparities in the workplace. The working conditions for women during the pandemic worsened due to increased family care responsibilities and unequal distribution of domestic labor. In the academy, working from home has resulted in reduced research time and increased teaching and family care responsibilities, with a larger proportion of that burden falling to women. We investigate the persistence of gender inequity among academic scientists resulting from university COVID-19 responses over time. We draw on two surveys administered in May 2020 and May 2021 to university-based biologists, biochemists, and civil and environmental engineers, to analyze how the pandemic response has disproportionately impacted women in academia and the endurance of those inequities. Results show significantly greater negative impacts from the pandemic on women's research activities and work-life balance, compared to men. We conclude by discussing the implications of our results, and the need for the academy to better predict and adjust to the gender disparities its policies create.
Project description:We aimed to do a systematic review and meta-analysis of studies describing suicidal ideation, suicide attempts and suicide and associated risk factors during COVID-19 pandemic. We searched following electronic databases using relevant search terms: Medline, Embase, PsycInfo and CINAHL and systematically reviewed the evidence following PRISMA guidelines. The meta-analysis of prevalence of suicidal ideation was done using random effect model. The search returned 972 records, we examined 106 in full text and included 38 studies describing 120,076 participants. Nineteen studies described suicide or attempted self-harm, mostly in case reports. Out of 19 studies describing suicidal ideations, 12 provided appropriate data for meta-analysis. The pooled prevalence of suicidal ideation in these studies was 12.1% (CI 9.3-15.2). Main risk factors for suicidal ideations were: low social support, high physical and mental exhaustion and poorer self-reported physical health in frontline medical workers, sleep disturbances, quarantine and exhaustion, loneliness, and mental health difficulties. We provide first meta-analytic estimate of suicidal ideation based on large sample from different countries and populations. The rate of suicidal ideations during COVID pandemic is higher than that reported in studies on general population prior to pandemic and may result in higher suicide rates in future.
Project description:Questions persist as to the origin of the COVID-19 pandemic. Evidence is building that its origin as a zoonotic spillover occurred prior to the officially accepted timing of early December, 2019. Here we provide novel methods to date the origin of COVID-19 cases. We show that six countries had exceptionally early cases, unlikely to represent part of their main case series. The model suggests a likely timing of the first case of COVID-19 in China as November 17 (95% CI October 4). Origination dates are discussed for the first five countries outside China and each continent. Results infer that SARS-CoV-2 emerged in China in early October to mid-November, and by January, had spread globally. This suggests an earlier and more rapid timeline of spread. Our study provides new approaches for estimating dates of the arrival of infectious diseases based on small samples that can be applied to many epidemiological situations.