Foot-and-mouth disease (FMD) is endemic in Bangladesh, and to implement an effective FMD control programme, it is essential to understand the complex epidemiology of the disease. Here, we report on the characterization of FMD virus (FMDV) recovered from FMD outbreaks in Bangladesh in late 2009. All isolated viruses belonged to the FMDV serotype O. The phylogenetic reconstruction showed that all isolates belonged to the Middle East-South Asia (ME-SA) topotype, but fell into two distinct sublineages, one named Ind-2001 (the other has not been named). Within both sublineages, the 2009 Bangladesh isolates were most closely related to viruses from Nepal collected during 2008 and 2009. Additionally, both sublineages contained older viruses from India collected in 2000 and 2001. In South Asia, there is extensive cross-border cattle movement from Nepal and India to Bangladesh. Both these findings have implications for the control of FMD in Bangladesh. Because of the porous borders, a regional FMD control strategy should be developed. Further, animal identification and monitoring animal movements are necessary to identify the cross-border movements and market chain interactions of ruminants, leading to improved border and movement controls. Additionally, a vaccination strategy should be developed with the initial objective of protecting small-scale dairy herds from disease. For any successful FMD control programme, long-term Government commitment and adequate resources are necessary. A sustainable programme will also need farmer education, commitment and financial contributions.

Summary Mortality in ducks and geese caused by highly pathogenic avian influenza A (H5N1) infection had not been previously identified in Bangladesh. In June–July 2011, we investigated mortality in ducks, geese and chickens with suspected H5N1 infection in a north-eastern district of the country to identify the aetiologic agent and extent of the outbreak and identify possible associated human infections. We surveyed households and farms with affected poultry flocks in six villages in Netrokona district and collected cloacal and oropharyngeal swabs from sick birds and tissue samples from dead poultry. We conducted a survey in three of these villages to identify suspected human influenza-like illness cases and collected nasopharyngeal and throat swabs. We tested all swabs by real-time RT-PCR, sequenced cultured viruses, and examined tissue samples by histopathology and immunohistochemistry to detect and characterize influenza virus infection. In the six villages, among the 240 surveyed households and 11 small-scale farms, 61% (1789/2930) of chickens, 47% (4816/10 184) of ducks and 73% (358/493) of geese died within 14 days preceding the investigation. Of 70 sick poultry swabbed, 80% (56/70) had detectable RNA for influenza A/H5, including 89% (49/55) of ducks, 40% (2/5) of geese and 50% (5/10) of chickens. We isolated virus from six of 25 samples; sequence analysis of the hemagglutinin and neuraminidase gene of these six isolates indicated clade 2.3.2.1a of H5N1 virus. Histopathological changes and immunohistochemistry staining of avian influenza viral antigens were recognized in the brain, pancreas and intestines of ducks and chickens. We identified ten human cases showing signs compatible with influenza-like illness; four were positive for influenza A/H3; however, none were positive for influenza A/H5. The recently introduced H5N1 clade 2.3.2.1a virus caused unusually high mortality in ducks and geese. Heightened surveillance in poultry is warranted to guide appropriate diagnostic testing and detect novel influenza strains.

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SummaryA case control study was conducted during 2011 involved 90 randomly selected commercial layer farms infected with highly pathogenic avian influenza type A subtype H5N1 (HPAI) and 175 control farms randomly selected from within 5km of infected farms. A questionnaire was designed to obtain information about potential risk factors for contracting HPAI and was administered to farm owners or managers. Logistic regression analyses were conducted to identify significant risk factors. A total of 20/43 risk factors for contracting HPAI were identified after univariable logistic regression analysis. A multivariable logistic regression model was derived by forward stepwise selection. Both unmatched and matched analyses were done. The key risk factors identified were numbers of staff, frequency of veterinary visits, presence of village chickens roaming on the farm and staff trading birds. Aggregating these findings with those from other studies resulted in a list of 16 key risk factors identified in Bangladesh. Most of these related to biosecurity. It is considered feasible for Bangladesh to achieve a very low incidence of HPAI. Using the cumulative list of risk factors to enhance biosecurity pertaining to commercial farms would facilitate this objective.

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