Hill, Edward M., House, Thomas A., Dhingra, Madhur S., Kalpravidh, Wantanee, Morzaria, Subhash, Osmani, Muzaffar G., Yamage, Mat, Xiao, Xiangming, Gilbert, Marius and Tildesley, Michael J. (2017) Modelling H5N1 in Bangladesh across spatial scales : model complexity and zoonotic transmission risk. Epidemics, 20 . pp. 37-55. doi:10.1016/j.epidem.2017.02.007

Preview

PDF WRAP_1-s2.0-S1755436517300191-main.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (5Mb) | Preview

Request Changes to record.

Abstract

Highly pathogenic avian influenza H5N1 remains a persistent public health threat, capable of causing infection in humans with a high mortality rate while simultaneously negatively impacting the livestock industry. A central question is to determine regions that are likely sources of newly emerging influenza strains with pandemic causing potential. A suitable candidate is Bangladesh, being one of the most densely populated countries in the world and having an intensifying farming system. It is therefore vital to establish the key factors, specific to Bangladesh, that enable both continued transmission within poultry and spillover across the human–animal interface. We apply a modelling framework to H5N1 epidemics in the Dhaka region of Bangladesh, occurring from 2007 onwards, that resulted in large outbreaks in the poultry sector and a limited number of confirmed human cases. This model consisted of separate poultry transmission and zoonotic transmission components. Utilising poultry farm spatial and population information a set of competing nested models of varying complexity were fitted to the observed case data, with parameter inference carried out using Bayesian methodology and goodness-of-fit verified by stochastic simulations. For the poultry transmission component, successfully identifying a model of minimal complexity, which enabled the accurate prediction of the size and spatial distribution of cases in H5N1 outbreaks, was found to be dependent on the administration level being analysed. A consistent outcome of non-optimal reporting of infected premises materialised in each poultry epidemic of interest, though across the outbreaks analysed there were substantial differences in the estimated transmission parameters. The zoonotic transmission component found the main contributor to spillover transmission of H5N1 in Bangladesh was found to differ from one poultry epidemic to another. We conclude by discussing possible explanations for these discrepancies in transmission behaviour between epidemics, such as changes in surveillance sensitivity and biosecurity practices.

Item Type:	Journal Article
Subjects:	R Medicine > RA Public aspects of medicine S Agriculture > SF Animal culture
Divisions:	Faculty of Science > Centre for Complexity Science Faculty of Science > Life Sciences (2010- ) Faculty of Science > Mathematics Faculty of Science > Centre for Systems Biology
Library of Congress Subject Headings (LCSH):	Avian influenza -- Prevention -- Dhaka (Bangladesh), Avian influenza -- Mathematical models -- Dhaka (Bangladesh), Epidemics, Zoonoses
Journal or Publication Title:	Epidemics
Publisher:	Elsevier BV
ISSN:	1755-4365
Official Date:	September 2017
Dates:	Date Event September 2017 Published 21 February 2017 Available 17 February 2017 Accepted
Volume:	20
Page Range:	pp. 37-55
DOI:	10.1016/j.epidem.2017.02.007
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access
Funder:	Engineering and Physical Sciences Research Council (EPSRC), National Institutes of Health (U.S.) (NIH), Fogarty International Center. Research and Policy in Infectious Disease Dynamics Programme (RAPIDD), United States. Agency for International Development (USAID)
Grant number:	EP/I01358X/1, EP/P511079/1, EP/N033701/1, EP/K000128/1 (EPSRC), 1R01AI101028-01A1 (NIH), SRO/BGD/303/USA (USAID)
Adapted As:

Request changes or add full text files to a record

Repository staff actions (login required)

View Item

Downloads