Analysing livestock network data for infectious disease control: an argument for routine data collection in emerging economies

Chaters, G.L. et al. (2019) Analysing livestock network data for infectious disease control: an argument for routine data collection in emerging economies. Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1776), 20180264. (doi:10.1098/rstb.2018.0264) (PMID:31104601)

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Abstract

Livestock movements are an important mechanism of infectious disease transmission. Where these are well recorded, network analysis tools have been used to successfully identify system properties, highlight vulnerabilities to transmission, and inform targeted surveillance and control. Here we highlight the main uses of network properties in understanding livestock disease epidemiology and discuss statistical approaches to infer network characteristics from biased or fragmented datasets. We use a ‘hurdle model’ approach that predicts (i) the probability of movement and (ii) the number of livestock moved to generate synthetic ‘complete’ networks of movements between administrative wards, exploiting routinely collected government movement permit data from northern Tanzania. We demonstrate that this model captures a significant amount of the observed variation. Combining the cattle movement network with a spatial between-ward contact layer, we create a multiplex, over which we simulated the spread of ‘fast’ (R0 = 3) and ‘slow’ (R0 = 1.5) pathogens, and assess the effects of random versus targeted disease control interventions (vaccination and movement ban). The targeted interventions substantially outperform those randomly implemented for both fast and slow pathogens. Our findings provide motivation to encourage routine collection and centralization of movement data to construct representative networks. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Rossi, Dr Gianluigi and De Glanville, Dr William and Chaters, Gemma and Mohr, Dr Sibylle and Kao, Professor Rowland and Johnson, Dr Paul and Matthews, Professor Louise and Salvador, Dr Liliana and Cleaveland, Professor Sarah and Crispell, Joseph
Authors: Chaters, G.L., Johnson, P.C.D., Cleaveland, S., Crispell, J., de Glanville, W.A., Doherty, T., Matthews, L., Mohr, S., Nyasebwa, O.M., Rossi, G., Salvador, L.C.M., Swai, E., and Kao, R.R.
College/School:College of Medical Veterinary and Life Sciences > Institute of Biodiversity Animal Health and Comparative Medicine
Journal Name:Philosophical Transactions of the Royal Society B: Biological Sciences
Publisher:The Royal Society
ISSN:0962-8436
ISSN (Online):1471-2970
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Philosophical Transactions of the Royal Society B: Biological Sciences 374(1776): 20180264
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
Data DOI:10.5525/gla.researchdata.733

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
627871Social, economic and environmental drivers of zoonoses in Tanzania (SEEDZ)Sarah CleavelandBiotechnology and Biological Sciences Research Council (BBSRC)BB/L018926/1RI BIODIVERSITY ANIMAL HEALTH & COMPMED