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Background While vaccines ensure individual protection against COVID-19 infection, delay in receipt or refusal of vaccines will have both individual and community impacts. The behavioral factors of vaccine hesitancy or refusal are a crucial dimension that need to be understood in order to design appropriate interventions. The aim of this study was to explore the behavioral determinants of COVID-19 vaccine acceptance and to provide recommendations to increase the acceptance and uptake of COVID-19 vaccines in Bangladesh. Methods We employed a Barrier Analysis (BA) approach to examine twelve potential behavioral determinants (drawn from the Health Belief Model [HBM] and Theory of Reasoned Action [TRA]) of intended vaccine acceptance. We conducted 45 interviews with those who intended to take the vaccine (Acceptors) and another 45 interviews with those who did not have that intention (Non-acceptors). We performed data analysis to find statistically significant differences and to identify which beliefs were most highly associated with acceptance and non-acceptance with COVID-19 vaccines. Results The behavioral determinants associated with COVID-19 vaccine acceptance in Dhaka included perceived social norms, perceived safety of COVID-19 vaccines and trust in them, perceived risk/susceptibility, perceived self-efficacy, perceived positive and negative consequences, perceived action efficacy, perceived severity of COVID-19, access, and perceived divine will. In line with the HBM, beliefs about the disease itself were highly predictive of vaccine acceptance, and some of the strongest statistically-significant (p Conclusion An effective behavior change strategy for COVID-19 vaccines uptake will need to address multiple beliefs and behavioral determinants, reducing barriers and leveraging enablers identified in this study. National plans for promoting COVID-19 vaccination should address the barriers, enablers, and behavioral determinants found in this study in order to maximize the impact on COVID-19 vaccination acceptance.

Bats are known reservoirs of Nipah virus (NiV) and some filoviruses and also appear likely to harbor the evolutionary progenitors of severe acute respiratory syndrome coronavirus (SARS-CoV), severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), and Middle East respiratory syndrome coronavirus (MERS-CoV). While bats are considered a reservoir of deadly viruses, little is known about people&rsquo, s knowledge, attitudes, and perceptions of bat conservation and ecology. The current study aimed to assess community people&rsquo, s knowledge, attitudes, and perceptions of bat ecology, myths, and the role of bats in transmitting NiV in Bangladesh. Since 2001, NiV has been a continuous threat to public health with a mortality rate of approximately 70% in Bangladesh. Over the years, many public health interventions have been implemented to raise awareness about bats and the spreading of NiV among the community peoples of Nipah outbreak areas (NOAs) and Nipah non-outbreak areas (NNOAs). We hypothesized that people from both areas might have similar knowledge of bat ecology and myths about bats but different knowledge regarding their role in the spreading of NiV. Using a four-point Likert scale-based questionnaire, our analysis showed that most people lack adequate knowledge regarding the role of bats in maintaining the ecological balance and instead trust their beliefs in different myths about bats. Factor score analysis showed that respondents&rsquo, gender (p = 0.01), the outbreak status of the area (p = 0.03), and their occupation (p = 0.04) were significant factors influencing their knowledge of bat ecology and myths. A regression analysis showed that farmers had 0.34 times the odds of having correct or positive knowledge of bat ecology and myths than businesspersons (odds ratio (OR) = 0.34, 95% confidence interval (95% CI) = 0.15&ndash, 0.78, p = 0.01). Regarding the spreading of NiV via bats, people had a lower level of knowledge. In NOAs, age (p = 0.00), occupation (p = 0.00), and level of education (p = 0.00) were found to be factors contributing to the amount of knowledge regarding the transmission of NiV, whereas in NNOAs, the contributing factors were occupation (p = 0.00) and level of education (p = 0.01). Regression analysis revealed that respondents who were engaged in services (OR = 3.02, 95% CI = 1.07&ndash, 8.54, p = 0.04) and who had completed primary education (OR = 3.06, 95% CI = 1.02&ndash, 9.17, p &lt, 0.05) were likely to have correct knowledge regarding the spreading of NiV. Based on the study results, we recommend educational interventions for targeted groups in the community, highlighting the ecosystem services and conservation of bats so as to improve people&rsquo, s current knowledge and subsequent behavior regarding the role of bats in ecology and the spreading of NiV in Bangladesh.

The COVID-19 pandemic has manifested more than a health crisis and has severely impacted on social, economic, and development crises in the world. The relationship of COVID-19 with countries&rsquo, economic and other demographic statuses is an important criterion with which to assess the impact of this current outbreak. Based on available data from the online platform, we tested the hypotheses of a country&rsquo, s economic status, population density, the median age of the population, and urbanization pattern influence on the test, attack, case fatality, and recovery rates of COVID-19. We performed correlation and multivariate multinomial regression analysis with relative risk ratio (RRR) to test the hypotheses. The correlation analysis showed that population density and test rate had a significantly negative association (r = &minus, 0.2384, p = 0.00). In contrast, the median age had a significant positive correlation with recovery rate (r = 0.4654, p = 0.00) and case fatality rate (r = 0.2847, p = 0.00). The urban population rate had a positive significant correlation with recovery rate (r = 0.1610, p = 0.04). Lower-middle-income countries had a negative significant correlation with case fatality rate (r= &minus, 0.3310, p = 0.04). The multivariate multinomial logistic regression analysis revealed that low-income countries are more likely to have an increased risk of case fatality rate (RRR = 0.986, 95% Confidence Interval, CI = 0.97&minus, 1.00, p &lt, 0.05) and recovery rate (RRR = 0.967, 95% CI = 0.95&ndash, 0.98, p = 0.00). The lower-income countries are more likely to have a higher risk in case of attack rate (RRR = 0.981, 95% CI = 0.97&ndash, 0.99, p = 0.00) and recovery rate (RRR = 0.971, 95% CI = 0.96&ndash, 0.98, p = 0.00). Similarly, upper middle-income countries are more likely to have higher risk in case of attack rate (RRR = 0.988, 95% CI = 0.98&ndash, 1.0, p = 0.01) and recovery rate (RRR = 0.978, 95% CI = 0.97&ndash, 0.99, p = 0.00). The low- and lower-middle-income countries should invest more in health care services and implement adequate COVID-19 preventive measures to reduce the risk burden. We recommend a participatory, whole-of-government and whole-of-society approach for responding to the socio-economic challenges of COVID-19 and ensuring more resilient and robust health systems to safeguard against preventable deaths and poverty by improving public health outcomes.

Aim : Antimicrobial residue in animal food products is an important index of food safety. Antimicrobial residues could result from chemotherapeutic or chemoprophylactic use of drugs in food animals. This occurrence of residue in animal food products has received enormous worldwide attention from some local, international, and public health agencies. A crosssectional study was conducted from July to December 2009 to detect the antibiotic residues in tissues and eggs of laying hens at Chittagong of Bangladesh. Materials and Methods : Microbial inhibition test (MIT) and thin layer chromatography (TLC) methods were used to detect antibacterial residues in poultry tissues (liver, kidney, breast, and thigh muscles) and eggs. The bacteria and pH of the MIT method were as follows: Bacillus subtilis on test agar medium with a pH of 7.2, Bacillus cereus with a pH of 6.0, and Escherichia coli at pH with an 8.0. Results : The overall prevalence of antibiotic residues detected by MIT was 64% in liver, 63% in kidney, 56% in breast muscle, 50% in thigh muscle, and 60% in eggs. There was significant variation in results between MIT and TLC (p