Infodemics, often including rumors, stigma, and conspiracy theories, have been common during the COVID-19 pandemic. Monitoring social media data has been identified as the best method for tracking rumors in real time and as a possible way to dispel misinformation and reduce stigma. However, the detection, assessment, and response to rumors, stigma, and conspiracy theories in real time are a challenge. Therefore, we followed and examined COVID-19related rumors, stigma, and conspiracy theories circulating on online platforms, including fact-checking agency websites, Facebook, Twitter, and online newspapers, and their impacts on public health. Information was extracted between December 31, 2019 and April 5, 2020, and descriptively analyzed. We performed a content analysis of the news articles to compare and contrast data collected from other sources. We identified 2,311 reports of rumors, stigma, and conspiracy theories in 25 languages from 87 countries. Claims were related to illness, transmission and mortality (24%), control measures (21%), treatment and cure (19%), cause of disease including the origin (15%), violence (1%), and miscellaneous (20%). Of the 2,276 reports for which text ratings were available, 1,856 claims were false (82%). Misinformation fueled by rumors, stigma, and conspiracy theories can have potentially serious implications on the individual and community if prioritized over evidence-based guidelines. Health agencies must track misinformation associated with the COVID-19 in real time, and engage local communities and government stakeholders to debunk misinformation.

Introduction Rumors and conspiracy theories, can contribute to vaccine hesitancy. Monitoring online data related to COVID-19 vaccine candidates can track vaccine misinformation in real-time and assist in negating its impact. This study aimed to examine COVID-19 vaccine rumors and conspiracy theories circulating on online platforms, understand their context, and then review interventions to manage this misinformation and increase vaccine acceptance. Method In June 2020, a multi-disciplinary team was formed to review and collect online rumors and conspiracy theories between 31 December 2019–30 November 2020. Sources included Google, Google Fact Check, Facebook, YouTube, Twitter, fact-checking agency websites, and television and newspaper websites. Quantitative data were extracted, entered in an Excel spreadsheet, and analyzed descriptively using the statistical package R version 4.0.3. We conducted a content analysis of the qualitative information from news articles, online reports and blogs and compared with findings from quantitative data. Based on the fact-checking agency ratings, information was categorized as true, false, misleading, or exaggerated. Results We identified 637 COVID-19 vaccine-related items: 91% were rumors and 9% were conspiracy theories from 52 countries. Of the 578 rumors, 36% were related to vaccine development, availability, and access, 20% related to morbidity and mortality, 8% to safety, efficacy, and acceptance, and the rest were other categories. Of the 637 items, 5% (30/) were true, 83% (528/637) were false, 10% (66/637) were misleading, and 2% (13/637) were exaggerated. Conclusions Rumors and conspiracy theories may lead to mistrust contributing to vaccine hesitancy. Tracking COVID-19 vaccine misinformation in real-time and engaging with social media to disseminate correct information could help safeguard the public against misinformation.

The COVID-19 vaccine has been made available for emergency use in Bangladesh. However, willingness to receive the vaccine may be affected by varying factors across the country. Therefore, this study aimed to investigate the factors that influence willingness to receive the vaccine among Bangladeshi adults. A population-based cross-sectional online survey was conducted among a sample of 1,725 Bangladesh adults (age 18 years and older). The statistical analysis included univariate, bivariate and multivariate regression model. Findings show that 85% ( n = 1463) of respondents were willing to receive the vaccine. Respondents with 1–2 children (aOR: 1.77, 95% CI: 1.00–3.13, P = . 048), perceived risk of being infected (aOR: 1.48, 95% CI: 1.03–2.14, P = . 03), perceived impact on daily life (aOR: 2.53, 95%CI: 1.45–4.44, P = . 001), history of co-morbidities (aOR: 2.04, 95% CI: 1.37–3.04, P < . 01), price of the vaccine (aOR: 3.58, 95% CI: 2.34–5.47), physician’s recommendation to receive vaccine (aOR: 2.06, 95% CI: 1.38–3.06, P < . 01), vaccines supplied by government (aOR: 2.31, 95% CI: 1.64–3.25, P < . 01) were found to be motivating factors for willingness to receive the vaccine. Findings indicate that willingness to receive the vaccine is likely to be affected by socio-demographic, and health system factors. This should be carefully considered in the rollout of the vaccination plans in Bangladesh.

Background Healthcare workers (HCWs), such as doctors, nurses, and support staffs involved in direct or indirect patient care, are at increased risk of influenza virus infections due to occupational exposures. Vaccination is the most effective way to prevent influenza. Despite the World Health Organization (WHO) recommendations, Bangladesh lacks a seasonal influenza vaccination policy for HCWs, and thus vaccination rates remain low. The current project aims to investigate the effect of interventions on influenza vaccine awareness and availability of vaccine supply, explore HCWs’ knowledge and perceptions about influenza vaccination, understand the barriers and motivators for influenza vaccine uptake, and understand policymakers' views on the practicality of influenza vaccination among HCWs. Method We will conduct the study at four tertiary care teaching hospitals in Bangladesh, using a cluster randomized controlled trial approach, with the hospital as the unit of randomization and intervention. The study population will include all types of HCWs.The four different types of intervention will be randomly allocated and implemented in four study hospitals separately. The four interventions will be: i) ensuring the availability of influenza vaccine supply; ii) developing influenza vaccine awareness; iii) both ensuring influenza vaccine supply and developing influenza vaccine awareness and iv) control arm with no intervention. Both quantitative and qualitative approaches will be applied to assess the intervention effect. We will estimate the Difference in Differences (DID) with 95% CI of the proportion of vaccine uptake between each intervention and control (non-intervention) arm, adjusting for the clustering effect. The qualitative data will be summarised using a framework matrix method. Discussion The results of this study will inform the development and implementation of a context-specific strategy to enhance influenza vaccination rates among Bangladeshi HCWs. Trial registration Clinicaltrials.gov NCT05521763. Version 2.0 was registered in September 2022, and the first participant enrolled in March 2022. Retrospectively registered.

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