Assessment of COVID-19 management and its consequences on healthcare professionals: a cross-sectional study from Bangladesh.

OBJECTIVE: This explorative study aims to identify the gaps in COVID-19 management and their consequences on physicians in terms of contracting infection and psychological well-being during the early phase of the pandemic. DESIGN, SETTINGS AND PARTICIPANTS: We conducted a nationwide cross-sectional online study to collect information from 420 intern doctors who were at their internship in government medical colleges from February to August 2020. METHODS: We performed univariate and bivariate analyses to assess COVID-19 management. We investigated the consequences of COVID-19 management on infection risk, experiencing stress, developing anxiety, depression and sleep disturbance using five sets of multivariable logistic regression analyses. RESULTS: Findings indicate a delay in first-case detection and identify people's tendency to hide COVID-19 symptoms as one of the possible causes of that delay. About 56% of the intern doctors experienced that patients were trying to hide COVID-19 symptoms in the earlier phase of the pandemic. More than half of the respondents did not get any training on COVID-19 from their working institutions. About 30% and 20% of the respondents did not use personal protective equipment (PPE) and masks while treating patients. Respondents who treated patients without PPE, masks, face shields and gloves were almost two times as likely to be infected by COVID-19. The odds of experiencing COVID-19-related stress was almost twofold among respondents who treated patients without wearing PPE and masks. Experiencing COVID-19-related stress was further associated with an increased risk of developing anxiety and depression that led to sleep disturbance. CONCLUSION: Ensuring the maximum utilization of limited resources during any public health crisis such as COVID-19 needs developing coping mechanisms by projecting future demand. Ensuring proper training and safety measures can reduce physical and psychological hazards among physicians.

Epidemiology and phylodynamics of multiple clades of H5N1 circulating in domestic duck farms in different production systems in Bangladesh.

Waterfowl are considered to be natural reservoirs of the avian influenza virus (AIV). However, the dynamics of transmission and evolutionary patterns of AIV and its subtypes within duck farms in Bangladesh remain poorly documented. Hence, a cross-sectional study was conducted in nine districts of Bangladesh between 2019 and 2021, to determine the prevalence of AIV and its subtypes H5 and H9, as well as to identify risk factors and the phylodynamics of H5N1 clades circulating in domestic duck farms. The oropharyngeal and cloacal swab samples were tested for the AIV Matrix gene (M-gene) followed by H5, H7, and H9 subtypes using rRT-PCR. The exploratory analysis was performed to estimate AIV and its subtype prevalence in different production systems, and multivariable logistic regression model was used to identify the risk factors that influence AIV infection in ducks. Bayesian phylogenetic analysis was conducted to generate a maximum clade credibility (MCC) tree and the maximum likelihood method to determine the phylogenetic relationships of the H5N1 viruses isolated from ducks. AIV was detected in 40% (95% CI: 33.0-48.1) of the duck farms. The prevalence of AIV was highest in nomadic ducks (39.8%; 95% CI: 32.9-47.1), followed by commercial ducks (24.6%; 95% CI: 14.5-37.3) and backyard ducks (14.4%; 95% CI: 10.5-19.2). The H5 prevalence was also highest in nomadic ducks (19.4%; 95% CI: 14.0-25.7). The multivariable logistic regression model revealed that ducks from nomadic farms (AOR: 2.4; 95% CI: 1.45-3.93), juvenile (AOR: 2.2; 95% CI: 1.37-3.61), and sick ducks (AOR: 11.59; 95% CI: 4.82-32.44) had a higher risk of AIV. Similarly, the likelihood of H5 detection was higher in sick ducks (AOR: 40.8; 95% CI: 16.3-115.3). Bayesian phylogenetic analysis revealed that H5N1 viruses in ducks belong to two distinct clades, 2.3.2.1a, and 2.3.4.4b. The clade 2.3.2.1a (reassorted) has been evolving silently since 2015 and forming at least nine subgroups based on >90% posterior probability. Notably, clade 2.3.4.4b was introduced in ducks in Bangladesh by the end of the year 2020, which was genetically similar to viruses detected in wild birds in Japan, China, and Africa, indicating migration-associated transmission of an emerging panzootic clade. We recommend continuing AIV surveillance in the duck production system and preventing the intermingling of domestic ducks with migratory waterfowl in wetlands.

Annual trading patterns and risk factors of avian influenza A/H5 and A/H9 virus circulation in turkey birds (Meleagris gallopavo) at live bird markets in Dhaka city, Bangladesh.

The impacts of the avian influenza virus (AIV) on farmed poultry and wild birds affect human health, livelihoods, food security, and international trade. The movement patterns of turkey birds from farms to live bird markets (LBMs) and infection of AIV are poorly understood in Bangladesh. Thus, we conducted weekly longitudinal surveillance in LBMs to understand the trading patterns, temporal trends, and risk factors of AIV circulation in turkey birds. We sampled a total of 423 turkeys from two LBMs in Dhaka between May 2018 and September 2019. We tested the swab samples for the AIV matrix gene (M-gene) followed by H5, H7, and H9 subtypes using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We used exploratory analysis to investigate trading patterns, annual cyclic trends of AIV and its subtypes, and a generalized estimating equation (GEE) logistic model to determine the factors that influence the infection of H5 and H9 in turkeys. Furthermore, we conducted an observational study and informal interviews with traders and vendors to record turkey trading patterns, demand, and supply and turkey handling practices in LBM. We found that all trade routes of turkey birds to northern Dhaka are unidirectional and originate from the northwestern and southern regions of Bangladesh. The number of trades from the source district to Dhaka depends on the turkey density. The median distance that turkey was traded from its source district to Dhaka was 188 km (Q1 = 165, Q3 = 210, IQR = 45.5). We observed seasonal variation in the median and average distance of turkey. The qualitative findings revealed that turkey farming initially became reasonably profitable in 2018 and at the beginning of 2019. However, the fall in demand and production in the middle of 2019 may be related to unstable market pricing, high feed costs, a shortfall of adequate marketing facilities, poor consumer knowledge, and a lack of advertising. The overall prevalence of AIV, H5, and H9 subtypes in turkeys was 31% (95% CI: 26.6-35.4), 16.3% (95% CI: 12.8-19.8), and 10.2% (95% CI: 7.3-13.1) respectively. None of the samples were positive for H7. The circulation of AIV and H9 across the annual cycle showed no seasonality, whereas the circulation of H5 showed significant seasonality. The GEE revealed that detection of AIV increases in retail vendor business (OR: 1.71; 95% CI: 1.12-2.62) and the bird's health status is sick (OR: 10.77; 95% CI: 4.31-26.94) or dead (OR: 11.33; 95% CI: 4.30-29.89). We also observed that winter season (OR: 5.83; 95% CI: 2.80-12.14) than summer season, dead birds (OR: 61.71; 95% CI: 25.78-147.75) and sick birds (OR 8.33; 95% CI: 3.36-20.64) compared to healthy birds has a higher risk of H5 infection in turkeys. This study revealed that the turkeys movements vary by time and season from the farm to the LBM. This surveillance indicated year-round circulation of AIV with H5 and H9 subtypes in turkey birds in LBMs. The seasonality and health condition of birds influence H5 infection in birds. The trading pattern of turkey may play a role in the transmission of AIV viruses in the birds. The selling of sick turkeys infected with H5 and H9 highlights the possibility of virus transmission to other species of birds sold at LBMs and to people.

Epidemiology and molecular characterization of avian influenza A viruses H5N1 and H3N8 subtypes in poultry farms and live bird markets in Bangladesh.

Avian influenza virus (AIV) remains a global threat, with waterfowl serving as the primary reservoir from which viruses spread to other hosts. Highly pathogenic avian influenza (HPAI) H5 viruses continue to be a devastating threat to the poultry industry and an incipient threat to humans. A cross-sectional study was conducted in seven districts of Bangladesh to estimate the prevalence and subtypes (H3, H5, and H9) of AIV in poultry and identify underlying risk factors and phylogenetic analysis of AIVs subtypes H5N1 and H3N8. Cloacal and oropharyngeal swab samples were collected from 500 birds in live bird markets (LBMs) and poultry farms. Each bird was sampled by cloacal and oropharyngeal swabbing, and swabs were pooled for further analysis. Pooled samples were analyzed for the influenza A virus (IAV) matrix (M) gene, followed by H5 and H9 molecular subtyping using real-time reverse transcription-polymerase chain reaction (rRT-PCR). Non-H5 and Non-H9 influenza A virus positive samples were sequenced to identify possible subtypes. Selected H5 positive samples were subjected to hemagglutinin (HA) and neuraminidase (NA) gene sequencing. Multivariable logistic regression was used for risk factor analysis. We found that IAV M gene prevalence was 40.20% (95% CI 35.98-44.57), with 52.38%, 46.96%, and 31.11% detected in chicken, waterfowl, and turkey, respectively. Prevalence of H5, H3, and H9 reached 22%, 3.4%, and 6.9%, respectively. Waterfowl had a higher risk of having AIV (AOR: 4.75), and H5 (AOR: 5.71) compared to chicken; more virus was detected in the winter season than in the summer season (AOR: 4.93); dead birds had a higher risk of AIVs and H5 detection than healthy birds, and the odds of H5 detection increased in LBM. All six H5N1 viruses sequenced were clade 2.3.2.1a-R1 viruses circulating since 2015 in poultry and wild birds in Bangladesh. The 12 H3N8 viruses in our study formed two genetic groups that had more similarity to influenza viruses from wild birds in Mongolia and China than to previous H3N8 viruses from Bangladesh. The findings of this study may be used to modify guidelines on AIV control and prevention to account for the identified risk factors that impact their spread.

Potential risk zones and climatic factors influencing the occurrence and persistence of avian influenza viruses in the environment of live bird markets in Bangladesh.

Live bird markets (LBMs) are critical for poultry trade in many developing countries that are regarded as hotspots for the prevalence and contamination of avian influenza viruses (AIV). Therefore, we conducted weekly longitudinal environmental surveillance in LBMs to determine annual cyclic patterns of AIV subtypes, environmental risk zones, and the role of climatic factors on the AIV presence and persistence in the environment of LBM in Bangladesh. From January 2018 to March 2020, we collected weekly fecal and offal swab samples from each LBM and tested using rRT-PCR for the M gene and subtyped for H5, H7, and H9. We used Generalized Estimating Equations (GEE) approaches to account for repeated observations over time to correlate the AIV prevalence and potential risk factors and the negative binomial and Poisson model to investigate the role of climatic factors on environmental contamination of AIV at the LBM. Over the study period, 37.8% of samples tested AIV positive, 18.8% for A/H5, and A/H9 was, for 15.4%. We found the circulation of H5, H9, and co-circulation of H5 and H9 in the environmental surfaces year-round. The Generalized Estimating Equations (GEE) model reveals a distinct seasonal pattern in transmitting AIV and H5. Specifically, certain summer months exhibited a substantial reduction of risk up to 70-90% and 93-94% for AIV and H5 contamination, respectively. The slaughtering zone showed a significantly higher risk of contamination with H5, with a three-fold increase in risk compared to bird-holding zones. From the negative binomial model, we found that climatic factors like temperature and relative humidity were also significantly associated with weekly AIV circulation. An increase in temperature and relative humidity decreases the risk of AIV circulation. Our study underscores the significance of longitudinal environmental surveillance for identifying potential risk zones to detect H5 and H9 virus co-circulation and seasonal transmission, as well as the imperative for immediate interventions to reduce AIV at LBMs in Bangladesh. We recommend adopting a One Health approach to integrated AIV surveillance across animal, human, and environmental interfaces in order to prevent the epidemic and pandemic of AIV.

Assessment of poultry rearing practices and risk factors of H5N1 and H9N2 virus circulating among backyard chickens and ducks in rural communities.

BACKGROUND: The avian influenza virus (AIV) causes significant economic losses by infecting poultry and occasional spillover to humans. Backyard farms are vulnerable to AIV epidemics due to poor health management and biosecurity practices, threatening rural households' economic stability and nutrition. We have limited information about the risk factors associated with AIV infection in backyard poultry in Bangladesh. Hence, we conducted a cross-sectional survey comprising epidemiological and anthropological investigations to understand the poultry rearing practices and risk factors of AIV circulation among backyard poultry in selected rural communities. METHODS: We sampled 120 poultry from backyard farms (n = 30) of the three selected communities between February 2017 and January 2018. We tested swab samples for the matrix gene (M gene) followed by H5, H7, and H9 subtypes using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We applied multivariable logistic regression for risk factor analysis. Furthermore, we conducted an observational study (42 hours) and informal interviews (n = 30) with backyard farmers to record poultry-raising activities in rural communities. RESULTS: We detected that 25.2% of the backyard poultry tested positive for AIV, whereas 5% tested positive for H5N1 and 10.8% tested positive for H9N2. Results showed that scavenging in both household garden and other crop fields has higher odds of AIV than scavenging in the household garden (AOR: 24.811; 95% CI: 2.11-292.28), and keeping a cage inside the house has higher odds (AOR:14.5; 95% CI: 1.06-198.51) than keeping it in the veranda, cleaning the cage twice a week or weekly has a higher risk than cleaning daily (AOR: 34.45; 95% CI: 1.04-1139.65), dumping litter or droppings (AOR: 82.80; 95% CI: 3.91-1754.59) and dead birds or wastage (AOR: 109.92, 95% CI: 4.34-2785.29) near water bodies and bushes have a higher risk than burring in the ground, slaughtering and consuming sick birds also had a higher odd of AIV (AOR: 73.45, 95% CI: 1.56-3457.73) than treating the birds. The anthropological investigation revealed that household members had direct contact with the poultry in different ways, including touching, feeding, slaughtering, and contacting poultry feces. Poultry is usually kept inside the house, sick poultry are traditionally slaughtered and eaten, and most poultry raisers do not know that diseases can transmit from backyard poultry to humans. CONCLUSIONS: This study showed the circulation of H5N1 and H9N2 virus in backyard poultry in rural communities; associated with species, scavenging area of the poultry, location of the poultry cage, the practice of litter, wastage, droppings, and dead bird disposal, and practice of handling sick poultry. We suggest improving biosecurity practices in backyard poultry and mass awareness campaigns to reduce incidences of AIV in household-level poultry farms in rural communities in Bangladesh.

Patterns and risk factors of avian influenza A(H5) and A(H9) virus infection in pigeons and quail at live bird markets in Bangladesh, 2017-2021.

The avian influenza virus (AIV) impacts poultry production, food security, livelihoods, and the risk of transmission to humans. Poultry, like pigeons and quail farming, is a growing sector in Bangladesh. However, the role of pigeons and quails in AIV transmission is not fully understood. Hence, we conducted this study to investigate the prevalence and risk factors of AIV subtypes in pigeons and quails at live bird markets (LBMs) in Bangladesh. We collected oropharyngeal and cloacal swab samples from 626 birds in 8 districts of Bangladesh from 2017 to 2021. We tested the swab samples for the matrix gene (M gene) followed by H5, H7, and H9 subtypes using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We then used exploratory analysis to investigate the seasonal and temporal patterns of AIV and a mixed effect logistic model to identify the variable that influences the presence of AIV in pigeons and quails. The overall prevalence of AIV was 25.56%. We found that the prevalence of AIV in pigeons is 17.36%, and in quail is 38.75%. The prevalence of A/H5, A/H9, and A/H5/H9 in quail is 4.17, 17.92, and 1.67%, respectively. Furthermore, the prevalence of A/H5, A/H9, and A/H5/H9 in pigeons is 2.85, 2.59, and 0.26%. We also found that the prevalence of AIV was higher in the dry season than in the wet season in both pigeons and quail. In pigeons, the prevalence of A/untyped (40%) increased considerably in 2020. In quail, however, the prevalence of A/H9 (56%) significantly increased in 2020. The mixed-effect logistic regression model showed that the vendors having waterfowl (AOR: 2.13; 95% CI: 1.04-4.33), purchasing birds from the wholesale market (AOR: 2.96; 95% CI: 1.48-5.92) instead of farms, mixing sick birds with the healthy ones (AOR: 1.60; 95% CI: 1.04-2.45) and mingling unsold birds with new birds (AOR: 3.07; 95% CI: 2.01-4.70) were significantly more likely to be positive for AIV compared with vendors that did not have these characteristics. We also found that the odds of AIV were more than twice as high in quail (AOR: 2.57; 95% CI: 1.61-4.11) as in pigeons. Furthermore, the likelihood of AIV detection was 4.19 times higher in sick and dead birds (95% CI: 2.38-7.35) than in healthy birds. Our study revealed that proper hygienic practices at the vendors in LBM are not maintained. We recommend improving biosecurity practices at the vendor level in LBM to limit the risk of AIV infection in pigeons and quail in Bangladesh.