ASSESSING RISK FACTORS ASSOCIATED WITH AVIAN INFLUENZA IN SICK AND DEAD CHICKENS IN SOME SELECTED AREA OF BANGLADESH: A CROSS-SECTIONAL STUDY

Abstract

Avian influenza (AI) continues to pose a substantial risk to chicken productivity and public health in Bangladesh, where both highly pathogenic (HPAI) and low pathogenic (LPAI) strains are common. Dead chickens, which generally have greater virus loads, are useful for understanding how diseases spread on farms with different levels of biosecurity. This study examined the frequency of avian influenza (AI) in sick and deceased chickens from poultry farms in Bangladesh, identified associated risk factors at both individual bird and farm levels, and evaluated biosecurity and management measures pertinent to AI control. A cross-sectional survey was executed among (n=260) farms in Chattogram, Gazipur, and Dhamrai. We took oropharyngeal and cloacal swabs from (n=873) sick and deceased birds and examined them with rRT-PCR for the M gene, H5, and H9 subtypes. A structured questionnaires were used to gather information from farms about the flocks, their biosecurity measures, management practices, and the presence of other livestock. We used both univariable and multivariable random-effects and mixed effect logistic regression analysis in farm and bird level respectively to find important predictors that could affect AI occurrence. The total prevalence of AI was 35.0% (95% CI: 29.21–41.14) at the farm level and 19.93% (95% CI: 17.41–22.72) at the bird level. The prevalence of AI was much higher in dead chickens (20.62%) than in sick chickens (11.25%, p = 0.006). Occurrence was highest during monsoon season (21.68%), compared to winter (14.49%) and summer (20.08%, p = 0.006). At farm level, implementation of control measures after morbidity, was linked to increased AI detection (OR = 3.87, p = 0.014), possibly indicating a reactive adoption following an outbreak. There was a far higher AI incidence (75.0%, p = 0.06) on farms with goats than on farms without goats. There was a clear geographic difference, with Chattogram (41.43%) and Dhamrai (38.03%) having greater rates than Gazipur (12.24%). Respiratory indicators (ruffled feathers 44.91%, coughing 36.98%, dyspnea 18.49%) and gastrointestinal signs (diarrhea 29.81%) were the most common, while neurological signals were less common. Biosecurity issues included not isolating sick birds enough (26.15%), not keeping records of culling, relying on non-professional treatment advice, and water sources that weren't always safe. More than half of the farms (52.31%) treated their animals themselves before consulting a veterinarian. Dead chickens are more likely to test positive for AI than sick birds. The fact that patterns alter with the seasons shows that management efforts should be centered on the months of the monsoon. AI is more likely to develop when people farm with diverse kinds of animals, especially goats, and when biosecurity measures are reactive instead of planned. Better biosecurity on farms, regular checks for AI in places where it is common, and greater support systems for farmers could help minimize the spread of AI in Bangladesh's poultry sector.