Exploring the behavioral determinants of COVID-19 vaccine acceptance among an urban population in Bangladesh: Implications for behavior change interventions.

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<0.001) predictors of vaccine acceptance in this population are beliefs around both injunctive and descriptive social norms. Specifically, Acceptors were 3.2 times more likely to say they would be very likely to get a COVID-19 vaccine if a doctor or nurse recommended it, twice as likely to say that most people they know will get a vaccine, and 1.3 times more likely to say that most close family and friends will get a vaccine. The perceived safety of vaccines was found to be important since Non-acceptors were 1.8 times more likely to say that COVID-19 vaccines are "not safe at all". Beliefs about one's risk of getting COVID-19 disease and the severity of it were predictive of being a vaccine acceptor: Acceptors were 1.4 times more likely to say that it was very likely that someone in their household would get COVID-19, 1.3 times more likely to say that they were very concerned about getting COVID-19, and 1.3 times more likely to say that it would be very serious if someone in their household contracted COVID-19. Other responses of Acceptors on what makes immunization easier may be helpful in programming to boost acceptance, such as providing vaccination through government health facilities, schools, and kiosks, and having vaccinators maintain proper COVID-19 health and safety protocols. 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

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

Antimicrobial residues in tissues and eggs of laying hens at Chittagong, Bangladesh

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<0.05). Tetracycline residues were found in 48% in liver, 24% in kidneys, 20% in thigh muscles, 26% in breast muscles, and 36% in eggs. Ciprofloxacin residues were found 46% in liver, 42% in kidneys, 34% in thigh muscles, 30% in breast muscles, and 30% in eggs. Enrofloxacin residues were found 40% in livers, 36% in kidneys, 24% in thigh muscles, 20% in breast muscles, and 26% in eggs. Amoxicillin residues were found 48% in livers, 30% in kidneys, 26% in thigh muscles, 22% in breast muscles, and 24% in eggs. The most frequently detected antibiotic residues by both MIT and TLC were found in liver tissue, tetracycline (48%), ciprofloxacin (46%), enrofloxacin (40%), and amoxicillin (42%) were found in liver. Breast muscle tissue was least likely to contain antibiotic residues (24%). Tetracycline (p=0.01) and amoxicillin (p=0.03) residues had significant variation among the various poultry tissues and eggs. Conclusions: A high percentage of tissues and eggs that could be available for human consumption had antibiotic residues. This study suggests that poultry meat and eggs should not be circulated to markets until the end of the drug’s withdrawal period. It is also recommended to observe the withdrawal period of drugs before poultry slaughter or table egg distribution to avoid antimicrobial resistance and to inform both owners and consumers about the risks of antibiotic residues

Transmission Pathways and Genomic Epidemiology of Emerging Variants of SARS-CoV-2 in the Environment

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can spread to the environment through several routes and persist for a more extended period. Therefore, we reviewed pertinent literature to understand the transmission dynamics of SARS-CoV-2 and genomic epidemiology of emerging variants of concern (VOCs) in the environment, their inactivation strategies, and the impact of COVID-19 on the ecosystem. The fallouts of the reviewed studies indicate that SARS-CoV-2 transmits through air and fomite, contaminated surfaces, biomedical wastes, and stool, which contaminates the environment through wastewater. As a result, multiple VOCs of SARS-CoV-2 were circulating in the environment. Genomic epidemiology revealed that the most prevalent VOC was Delta (B.1.617.2; 44.24%), followed by Omicron (B.1.1.529; 43.33%), in the environment. Phylogenetic analysis showed that environmental strains are clustered with a likeness of the human strains of the same or nearby countries, emphasizing the significance of continued environmental surveillance to track the emergence of the new variant. Thus, we should reduce viral dispersion in the environment through rapid and appropriate disinfection strategies. Moreover, the increased production and use of macro and microfiber plastic products should be brought under strict legislation with integrated waste management to control the unrelenting propagation of viral RNA. Finally, a comprehensive understanding of the environmental transmission pathways of SARS-CoV-2 is crucial for forecasting outbreak severity in the community, allowing us to prepare with the correct tools to control any impending pandemic. We recommend wastewater-based SARS-CoV-2 surveillance and air particulates to track the emerging VOCs of SARS-CoV-2 spread in the environment

Molecular Epidemiology of SARS-CoV-2 in Diverse Environmental Samples Globally

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has swamped the global environment greatly in the current pandemic. Wastewater-based epidemiology (WBE) effectively forecasts the surge of COVID-19 cases in humans in a particular region. To understand the genomic characteristics/footprints and diversity of SARS-CoV-2 in the environment, we analyzed 807 SARS-CoV-2 sequences from 20 countries deposited in GISAID till 22 May 2021. The highest number of sequences (n = 638) were reported in Austria, followed by the Netherlands, China, and Bangladesh. Wastewater samples were highest (40.0%) to successfully yield the virus genome followed by a 24 h composite wastewater sample (32.6%) and sewage (18.5%). Phylogenetic analysis revealed that SARS-CoV-2 environmental strains are a close congener with the strains mostly circulating in the human population from the same region. Clade GRY (32.7%), G (29.2%), GR (25.3%), O (7.2%), GH (3.4%), GV (1.4%), S (0.5%), and L (0.4%) were found in environmental samples. Various lineages were identified in environmental samples; nevertheless, the highest percentages (49.4%) of the alpha variant (B.1.1.7) were detected in Austria, Liechtenstein, Slovenia, Czech Republic, Switzerland, Germany, and Italy. Other prevalent lineages were B.1 (18.2%), B.1.1 (9.2%), and B.1.160 (3.9%). Furthermore, a significant number of amino acid substitutions were found in environmental strains where the D614G was found in 83.8% of the sequences. However, the key mutations—N501Y (44.6%), S982A (44.4%), A570D (43.3%), T716I (40.4%), and P681H (40.1%) were also recorded in spike protein. The identification of the environmental belvedere of SARS-CoV-2 and its genetic signature is crucial to detect outbreaks, forecast pandemic harshness, and prepare with the appropriate tools to control any impending pandemic. We recommend genomic environmental surveillance to trace the emerging variants and diversity of SARS-CoV-2 viruses circulating in the community. Additionally, proper disposal and treatment of wastewater, sewage, and medical wastes are important to prevent environmental contamination

Knowledge, Attitudes, and Common Practices of Livestock and Poultry Veterinary Practitioners Regarding the AMU and AMR in Bangladesh

Current evidence indicates that more than half of all antimicrobials are used in the animal food-producing sector, which is considered a significant risk factor for the development, spread, and existence of antimicrobial resistance (AMR) pathogens in animals, humans, and the environment. Among other factors, clinical etiology and the level of knowledge, attitudes, and practices (KAP) of veterinarians are thought to be responsible for inappropriate prescriptions in the animal-source protein production sector in lower-resource settings like Bangladesh. We performed this cross-sectional study to assess factors associated with veterinarians’ antimicrobial prescription behavior and their KAP on antimicrobial use (AMU) and AMR in Bangladesh. Exploratory and multivariate logistic models were used to describe an association between knowledge, attitudes, and practices of AMU and AMR and demographic characteristics of veterinarians. The results demonstrated that when selecting an antimicrobial, there was no to minimal influence of culture and susceptibility tests and patients’ AMU history but moderate to high influence of the farmer’s economic condition and drug instructions among the veterinarians. The results also demonstrated that more than half of the veterinarians had correct KAP regarding AMU and AMR, while the rest had moderate or lower levels of KAP. The factor score analysis revealed that age, level of education, years of experience, gender, and previous training on AMU and AMR were the key influencing factors in their level of KAP. Adjusted logistic regression analysis showed that respondents’ age, current workplace, and previous training on AMU and AMR had a positive association with increased KAP. Considering the results, it is imperative to include AMR issues on vet curricula, and to provide post-education training, awareness campaigns, easy access to, and dissemination of AMR resources. Increasing the veterinary services to the outreach areas of the country and motivating veterinarians to follow the national AMR guidelines could be some other potential solutions to tackle the over-prescriptions of antimicrobials

Knowledge, attitude, and practices on antimicrobial use and antimicrobial resistance among commercial poultry farmers in Bangladesh

Antimicrobial resistance (AMR) has become an emerging health issue globally, posing a threat to zoonotic pathogens and foodborne diseases. In Bangladesh, the poultry sector supplies the majority of the demand for animal-source protein. The irrational and excessive use of antimicrobials (AMU) has been observed in the poultry sector. The development of AMR is associated with many factors, including the knowledge and attitudes of poultry farmers. Therefore, AMR reduction requires intervention from all the stockholders, including the farmers who are considered as end users of antimicrobials. This current research conducted a cross-sectional study to assess the knowledge, attitudes, and practices (KAP) of poultry farmers on AMU and AMR in Bangladesh. We determined the KAP of poultry farmers (broiler and layer farmers) of some selected districts of the country using a tested and paper-based questionnaire. The results demonstrated that most of the respondents have insufficient KAP regarding AMU and AMR. The respondents used a variety of antimicrobials primarily in the treatment of various diseases in poultry. One-third of the farmers did not seek antimicrobials from registered vets. Instead, they depended on others or themselves. The factor score analysis further revealed that the farmers&rsquo; demographic and socioeconomic variables were significant factors influencing the KAP. An adjusted logistic regression analysis showed that older farmers with 9&ndash;12 years of farming experience and graduate-level education, engaging in medium-sized layer farming, were more likely to have correct KAP on AMU and AMR. Further, farmers from the Cox&rsquo;s Bazar region showed correct knowledge, whereas farmers of the Chattogram region showed a correct attitude towards AMU and AMR. A Spearman&rsquo;s rank-order correlation revealed a positive association between knowledge&ndash;attitudes and knowledge&ndash;practices. The findings of the current investigation provide baseline evidence about the KAP of poultry farmers from low-income resources and offer insights into designing interventions and policies for the use of AMU and AMR in Bangladesh