A Unified Framework for the Infection Dynamics of Zoonotic Spillover and Spread

Lo Iacono, Giovanni, Cunningham, Andrew A., Fichet-Calvet, Elisabeth, Garry, Robert F., Grant, Donald S., Leach, Melissa, Moses, Lina M., Nichols, Gordon, Schieffelin, John S., Shaffer, Jeffrey G. et al, Webb, Colleen T. and Wood, James L. N. (2016) A Unified Framework for the Infection Dynamics of Zoonotic Spillover and Spread PLOS Neglected Tropical Diseases, 10 (9).

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Abstract

A considerable amount of disease is transmitted from animals to humans and many of these zoonoses are neglected tropical diseases. As outbreaks of SARS, avian influenza and Ebola have demonstrated, however, zoonotic diseases are serious threats to global public health and are not just problems confined to remote regions. There are two fundamental, and poorly studied, stages of zoonotic disease emergence: ‘spillover’, i.e. transmission of pathogens from animals to humans, and ‘stuttering transmission’, i.e. when limited human-to-human infections occur, leading to self-limiting chains of transmission. We developed a transparent, theoretical framework, based on a generalization of Poisson processes with memory of past human infections, that unifies these stages. Once we have quantified pathogen dynamics in the reservoir, with some knowledge of the mechanism of contact, the approach provides a tool to estimate the likelihood of spillover events. Comparisons with independent agent-based models demonstrates the ability of the framework to correctly estimate the relative contributions of human-to-human vs animal transmission. As an illustrative example, we applied our model to Lassa fever, a rodent-borne, viral haemorrhagic disease common in West Africa, for which data on human outbreaks were available. The approach developed here is general and applicable to a range of zoonoses. This kind of methodology is of crucial importance for the scientific, medical and public health communities working at the interface between animal and human diseases to assess the risk associated with the disease and to plan intervention and appropriate control measures. The Lassa case study revealed important knowledge gaps, and opportunities, arising from limited knowledge of the temporal patterns in reporting, abundance of and infection prevalence in, the host reservoir.

Item Type:	Article
Divisions :	Faculty of Health and Medical Sciences > School of Veterinary Medicine
Authors :	Name Email ORCID Lo Iacono, Giovanni g.loiacono@surrey.ac.uk Cunningham, Andrew A. Fichet-Calvet, Elisabeth Garry, Robert F. Grant, Donald S. Leach, Melissa Moses, Lina M. Nichols, Gordon Schieffelin, John S. Shaffer, Jeffrey G. Webb, Colleen T. Wood, James L. N.
Date :	2 September 2016
Identification Number :	10.1371/journal.pntd.0004957
Copyright Disclaimer :	© 2016 Lo Iacono et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Additional Information :	Author Summary: Many dangerous diseases emerge via spillover from animals, with limited human-to-human infection (stuttering-transmission) often being the first stage of human disease spread. Understanding the conditions (biological, environmental and socio-economic factors) that regulate spillover and disease spread is key to its mitigation. Here we are interested in questions such as: If we have quantified pathogen dynamics in the reservoir, with some knowledge of the mechanism of contact, can we estimate the likelihood of spillover events? Can we tease apart how much the disease is transmitted by animals and how much by humans? We developed a unified mathematical framework, based on Poisson processes with memory of past events, to understand the dynamics of spillover and stuttering-transmission. This framework, which can be applied across the disease transmission spectrum, allows the teasing apart of the disease burden attributed to animal-human and human-human transmission. Using this model, we can infer human disease risk based on knowledge of infection patterns in the animal reservoir host and the contact mechanisms required for transmission to humans.
Depositing User :	Clive Harris
Date Deposited :	03 Nov 2017 11:45
Last Modified :	15 Mar 2018 08:09
URI:	http://epubs.surrey.ac.uk/id/eprint/844819

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