Estimating the between-farm transmission rates for highly pathogenic avian influenza subtype H5N1 epidemics in Bangladesh between 2007 and 2013.

Highly Pathogenic Avian Influenza (HPAI) is classified by the World Organization for Animal Health as one of the notifiable diseases. Its occurrence is associated with severe socio-economic impacts and is also zoonotic. Bangladesh HPAI epidemic data for the period between 2007 and 2013 were obtained and split into epidemic waves based on the time lag between outbreaks. By assuming the number of newly infected farms to be binomially distributed, we fit a Generalized Linear Model to the data to estimate between-farm transmission rates (β). These parameters are then used together with the calculated infectious periods to estimate the respective basic reproduction numbers (R0 ). The change in β and R0 with time during the course of each epidemic wave was explored. Finally, sensitivity analyses of the effects of reducing the delay in detecting infection on a farm as well as extended infectiousness of a farm beyond the day of culling were assessed. The point estimates obtained for β ranged from 0.08 (95% CI: 0.06-0.10) to 0.11 (95% CI: 0.08-0.20) per infectious farm per day while R0 ranged from 0.85 (95% CI: 0.77-1.02) to 0.96 (95% CI: 0.72-1.20). Sensitivity analyses reveal that the estimates are quite robust to changes in the assumptions about the day in reporting infection and extended infectiousness. In the analysis allowing for time-varying transmission parameters, the rising and declining phases observed in the epidemic data were synchronized with the moments when R0 was greater and less than one, respectively. From an epidemiological perspective, the consistency of these estimates and their magnitude (R0  ≈ 1) indicate that the effectiveness of the deployed control measures was largely invariant between epidemic waves and the trend of the time-varying R0 supports the hypothesis of sustained farm-to-farm transmission that is possibly initiated by a few unique introductions.