The impact of surveillance and control on highly pathogenic avian influenza outbreaks in poultry in Dhaka division, Bangladesh

Abstract

In Bangladesh, the poultry industry is an economically and socially important sector, but it is persistently threatened by the effects of H5N1 highly pathogenic avian influenza. Thus, identifying the optimal control policy in response to an emerging disease outbreak is a key challenge for policy-makers. To inform this aim, a common approach is to carry out simulation studies comparing plausible strategies, while accounting for known capacity restrictions. In this study we perform simulations of a previously developed H5N1 influenza transmission model framework, fitted to two separate historical outbreaks, to assess specific control objectives related to the burden or duration of H5N1 outbreaks among poultry farms in the Dhaka division of Bangladesh. In particular, we explore the optimal implementation of ring culling, ring vaccination and active surveillance measures when presuming disease transmission predominately occurs from premises-to-premises, versus a setting requiring the inclusion of external factors. Additionally, we determine the sensitivity of the management actions under consideration to differing levels of capacity constraints and outbreaks with disparate transmission dynamics. While we find that reactive culling and vaccination policies should pay close attention to these factors to ensure intervention targeting is optimised, across multiple settings the top performing control action amongst those under consideration were targeted proactive surveillance schemes. Our findings may advise the type of control measure, plus its intensity, that could potentially be applied in the event of a developing outbreak of H5N1 amongst originally H5N1 virus-free commercially-reared poultry in the Dhaka division of Bangladesh.

A Decade of Avian Influenza in Bangladesh: Where Are We Now?

“…To identify future reassortment in Bangladesh, monitoring for both HPAI and LPAI viruses of diverse subtypes will be crucial [100]. Although active surveillance can be expensive and time-consuming and may face difficulties surviving, the intensification of surveillance has been key to early detection and controlling and limiting the spread of HPAI viruses among poultry on national scale [54,103,104]. Active surveillance is also needed to track the likely chain of transmission and the genetic diversity of circulating strains.…”

“…In the backyard sector, efforts have focused on raising awareness about AIV and measures to be followed to prevent zoonotic transmission [25,26]. The GoB, development partners, private sectors and non-governmental organizations (NGO), were involved in building awareness among communities with respect to biosecurity and HPAI (Table 2) [26,44,46,50,51,52,53,54].…”

Virus-like Particle Vaccines: A Prospective Panacea Against an Avian Influenza Panzootic

“…The effectiveness of bird culling, vaccination, and surveillance as control measures to curb AI transmission in Bangladesh was analysed. The ideal control measure was one that employed all three measures [ 68 ]. Furthermore, from the first LPAI H9N2 outbreak in China in 1994 and the first HPAI H5N1 outbreak in 1996, several outbreaks of these AIVs were recorded and they were described as being enzootic in China [ 69 , 70 ].…”

“…The first line of control during an AI outbreak is the culling of the infected birds, which is then followed by an antiviral treatment regimen [ 68 ]. Current AI treatments include antiviral agents that disrupt viral assembly, attachment, or replication, while other AI regimens act via RNA interference [ 71 , 72 ].…”

Dynamics of the 2004 avian influenza H5N1 outbreak in Thailand: The role of duck farming, sequential model fitting and control

“…The spatial distribution of HPAI H5N1 has been studied in several countries and regions using spatial statistical models ( Gilbert et al, 2006 , Gilbert et al, 2007 , Gilbert et al, 2008 , Gilbert et al, 2010 , Gilbert et al, 2014 ; Tiensin et al, 2007a , Tiensin et al, 2007b , Tiensin et al, 2009 ; Paul et al, 2010 , Paul et al, 2014 , Paul et al, 2016 ; Stegeman et al, 2011 ; Ssematimba et al, 2012 ; Artois et al, 2017 ) and mathematical models ( Truscott et al, 2007 ; Tiensin et al, 2007a , b ; Boender et al, 2007 ; Sharkey et al, 2008 ; Jewell et al, 2009a , b , c ; Minh et al, 2011 ; Walker et al, 2012 ; Hill et al, 2017 , Hill et al, 2018 ). Evidence from previous work suggests that different landscapes, production systems and water-related variables are risk factors that will promote disease transmission.…”