Risk for Infection with Highly Pathogenic Avian Influenza Virus (H5N1) in Backyard Chickens, Bangladesh

Risk factors were feeding slaughter remnants of purchased chickens, having a body of water nearby, and contact with pigeons

Avian Influenza Outbreaks in Chickens, Bangladesh

To determine the epidemiology of outbreaks of avian influenza A virus (subtypes H5N1, H9N2) in chickens in Bangladesh, we conducted surveys and examined virus isolates. The outbreak began in backyard chickens. Probable sources of infection included egg trays and vehicles from local live bird markets and larger live bird markets

Spatio-Temporal Magnitude and Direction of Highly Pathogenic Avian Influenza (H5N1) Outbreaks in Bangladesh

BACKGROUND: The number of outbreaks of HPAI-H5N1 reported by Bangladesh from 2007 through 2011 placed the country among the highest reported numbers worldwide. However, so far, the understanding of the epidemic progression, direction, intensity, persistence and risk variation of HPAI-H5N1 outbreaks over space and time in Bangladesh remains limited. METHODOLOGY/PRINCIPAL FINDINGS: To determine the magnitude and spatial pattern of the highly pathogenic avian influenza A subtype H5N1 virus outbreaks over space and time in poultry from 2007 to 2009 in Bangladesh, we applied descriptive and analytical spatial statistics. Temporal distribution of the outbreaks revealed three independent waves of outbreaks that were clustered during winter and spring. The descriptive analyses revealed that the magnitude of the second wave was the highest as compared to the first and third waves. Exploratory mapping of the infected flocks revealed that the highest intensity and magnitude of the outbreaks was systematic and persistent in an oblique line that connects south-east to north-west through the central part of the country. The line follows the Brahmaputra-Meghna river system, the junction between Central Asian and East Asian flyways, and the major poultry trading route in Bangladesh. Moreover, several important migratory bird areas were identified along the line. Geostatistical analysis revealed significant latitudinal directions of outbreak progressions that have similarity to the detected line of intensity and magnitude. CONCLUSION/SIGNIFICANCE: The line of magnitude and direction indicate the necessity of mobilizing maximum resources on this line to strengthen the existing surveillance

Ecological Determinants of Highly Pathogenic Avian Influenza (H5N1) Outbreaks in Bangladesh

BACKGROUND: The agro-ecology and poultry husbandry of the south Asian and south-east Asian countries share common features, however, with noticeable differences. Hence, the ecological determinants associated with risk of highly pathogenic avian influenza (HPAI-H5N1) outbreaks are expected to differ between Bangladesh and e.g., Thailand and Vietnam. The primary aim of the current study was to establish ecological determinants associated with the risk of HPAI-H5N1 outbreaks at subdistrict level in Bangladesh. The secondary aim was to explore the performance of two different statistical modeling approaches for unmeasured spatially correlated variation. METHODOLOGY/PRINCIPAL FINDINGS: An ecological study at subdistrict level in Bangladesh was performed with 138 subdistricts with HPAI-H5N1 outbreaks during 2007-2008, and 326 subdistricts with no outbreaks. The association between ecological determinants and HPAI-H5N1 outbreaks was examined using a generalized linear mixed model. Spatial clustering of the ecological data was modeled using 1) an intrinsic conditional autoregressive (ICAR) model at subdistrict level considering their first order neighbors, and 2) a multilevel (ML) model with subdistricts nested within districts. Ecological determinants significantly associated with risk of HPAI-H5N1 outbreaks at subdistrict level were migratory birds' staging areas, river network, household density, literacy rate, poultry density, live bird markets, and highway network. Predictive risk maps were derived based on the resulting models. The resulting models indicate that the ML model absorbed some of the covariate effect of the ICAR model because of the neighbor structure implied in the two different models. CONCLUSIONS/SIGNIFICANCE: The study identified a new set of ecological determinants related to river networks, migratory birds' staging areas and literacy rate in addition to already known risk factors, and clarified that the generalized concept of free grazing duck and duck-rice cultivation interacted ecology are not significant determinants for Bangladesh. These findings will refine current understanding of the HPAI-H5N1 epidemiology in Bangladesh

Prevalence of avian influenza A(H5) and A(H9) in live bird markets in Bangladesh

We conducted a cross-sectional study in live bird markets (LBMs) in Dhaka and Chittagong, Bangladesh, to estimate the prevalence of avian influenza A(H5) and A(H9) viruses in different types of poultry and environmental areas by using Bayesian hierarchical logistic regression models. We detected these viruses in nearly all LBMs. Prevalence of A(H5) virus was higher in waterfowl than in chickens, whereas prevalence of A(H9) virus was higher in chickens than in waterfowl and, among chicken types, in industrial broilers than in cross-breeds and indigenous breeds. LBMs with >1 wholesaler were more frequently contaminated by A(H5) virus than retail-only LBMs. Prevalence of A(H9) virus in poultry and level of environmental contamination were also higher in LBMs with >1 wholesaler. We found a high level of circulation of both avian influenza viruses in surveyed LBMs. Prevalence was influenced by type of poultry, environmental site, and trading patterns because our study included previously collected data

A qualitative stakeholder analysis of avian influenza policy in Bangladesh

Avian influenza is a major animal and public health concern in Bangladesh. A decade after development and implementation of the first national avian influenza and human pandemic influenza preparedness and response plan in Bangladesh, a two-stage qualitative stakeholder analysis was performed in relation to the policy development process and the actual policy. This study specifically aimed to identify the future policy options to prevent and control avian influenza and other poultry-related zoonotic diseases in Bangladesh. It was recommended that the policy should be based on the One Health concept, be evidence-based, sustainable, reviewed and updated as necessary. The future policy environment that is suitable for developing and implementing these policies should take into account the following points: the need to formally engage multiple sectors, the need for clear and acceptable leadership, roles and responsibilities, and the need for a common pool of resources and provision for transferring resources. Most of these recommendations are directed towards the Government of Bangladesh. However, other sectors, including research and poultry production stakeholders, also have a major role to play to inform policy-making and actively participate in the multi-sectoral approach

Prevalence and Characterization of Motile Salmonella in Commercial Layer Poultry Farms in Bangladesh

Salmonella is a globally widespread food-borne pathogen having major impact on public health. All motile serovars of Salmonella enterica of poultry origin are zoonotic, and contaminated meat and raw eggs are an important source to human infections. Information on the prevalence of Salmonella at farm/holding level, and the zoonotic serovars circulating in layer poultry in the South and South-East Asian countries including Bangladesh, where small-scale commercial farms are predominant, is limited. To investigate the prevalence of Salmonella at layer farm level, and to identify the prevalent serovars we conducted a cross-sectional survey by randomly selecting 500 commercial layer poultry farms in Bangladesh. Faecal samples from the selected farms were collected following standard procedure, and examined for the presence of Salmonella using conventional bacteriological procedures. Thirty isolates were randomly selected, from the ninety obtained from the survey, for serotyping and characterized further by plasmid profiling and pulsed-field gel electrophoresis (PFGE). Results of the survey showed that the prevalence of motile Salmonella at layer farm level was 18% (95% confidence interval 15–21%), and Salmonella Kentucky was identified to be the only serovar circulating in the study population. Plasmid analysis of the S. Kentucky and non-serotyped isolates revealed two distinct profiles with a variation of two different sizes (2.7 and 4.8 kb). PFGE of the 30 S. Kentucky and 30 non-serotyped isolates showed that all of them were clonally related because only one genotype and three subtypes were determined based on the variation in two or three bands. This is also the first report on the presence of any specific serovar of Salmonella enterica in poultry in Bangladesh

Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.

The highly pathogenic avian influenza A virus subtype H5N1 (HPAI H5N1) is a deadly zoonotic pathogen. Its persistence in poultry in several countries is a potential threat: a mutant or genetically reassorted progenitor might cause a human pandemic. Its world-wide eradication from poultry is important to protect public health. The global trend of outbreaks of influenza attributable to HPAI H5N1 shows a clear seasonality. Meteorological factors might be associated with such trend but have not been studied. For the first time, we analyze the role of meteorological factors in the occurrences of HPAI outbreaks in Bangladesh. We employed autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to assess the roles of different meteorological factors in outbreaks of HPAI. Outbreaks were modeled best when multiplicative seasonality was incorporated. Incorporation of any meteorological variable(s) as inputs did not improve the performance of any multivariable models, but relative humidity (RH) was a significant covariate in several ARIMA and SARIMA models with different autoregressive and moving average orders. The variable cloud cover was also a significant covariate in two SARIMA models, but air temperature along with RH might be a predictor when moving average (MA) order at lag 1 month is considered