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1.
IJID Reg ; 1: 92-99, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1466396

ABSTRACT

Objective: The aim of this study was to estimate the proportion of symptomatic and asymptomatic laboratory-confirmed coronavirus disease 2019 (COVID-19) cases among the population of Bangladesh. Methods: A cross-sectional survey was conducted in Dhaka City and other districts of Bangladesh between April 18 and October 12, 2020. A total of 32 districts outside Dhaka were randomly selected, and one village and one mahalla was selected from each district; 25 mahallas were selected from Dhaka City. From each village or mahalla, 120 households were enrolled through systematic random sampling. Results: A total of 44 865 individuals were interviewed from 10 907 households. The majority (70%, n = 31 488) of the individuals were <40 years of age. Almost half of the individuals (49%, n = 21 888) reported more than four members in their household. It was estimated that 12.6% (n = 160) of the households had one or more severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals, among whom 0.9% (n = 404) of individuals had at least one COVID-19-like symptom, at the national level. The prevalence of COVID-19 in the general population was 6.4%. Among the SARS-CoV-2-positive individuals, 87% were asymptomatic. Conclusions: The substantial high number of asymptomatic cases all over Bangladesh suggests that community-level containment and mitigation measures are required to combat COVID-19. Future studies to understand the transmission capability could help to define mitigation and control measures.

2.
PLoS One ; 16(5): e0251605, 2021.
Article in English | MEDLINE | ID: covidwho-1225816

ABSTRACT

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.


Subject(s)
COVID-19/psychology , Information Dissemination/methods , Vaccination Refusal/psychology , COVID-19 Vaccines/pharmacology , Communication , Cross-Sectional Studies , Humans , Information Dissemination/ethics , Public Health , SARS-CoV-2/pathogenicity , Social Media , Surveys and Questionnaires , Vaccination/methods
3.
Am J Trop Med Hyg ; 103(4): 1621-1629, 2020 10.
Article in English | MEDLINE | ID: covidwho-713541

ABSTRACT

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-19-related 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.


Subject(s)
Betacoronavirus , Coronavirus Infections , Pandemics , Pneumonia, Viral , Public Health , Social Media , COVID-19 , Data Analysis , Data Collection/methods , Global Health , Humans , Public Health/trends , Retrospective Studies , SARS-CoV-2 , Social Discrimination/psychology , Social Media/standards , Social Media/trends , Social Stigma
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