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New methodologies for the estimation of population vulnerability to diseases: a case study of Lassa fever and Ebola in Nigeria and Sierra Leone.

Accepted version
Peer-reviewed

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Type

Article

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Authors

Kajero, Olumayowa 
Del Rio Vilas, Victor 
Wood, James LN 
Lo Iacono, Giovanni 

Abstract

Public health practitioners require measures to evaluate how vulnerable populations are to diseases, especially for zoonoses (i.e. diseases transmitted from animals to humans) given their pandemic potential. These measures would be valuable to support strategic and operational decision making and allocation of resources. Although vulnerability is well defined for natural hazards, for public health threats the concept remains undetermined. Here, we develop new methodologies to: (i) quantify the impact of zoonotic diseases and the capacity of countries to cope with these diseases, and (ii) combine these two measures (impact and capacity) into one overall vulnerability indicator. The adaptive capacity is calculated from estimations of disease mortality, although the method can be adapted for diseases with no or low mortality but high morbidity. As an example, we focused on the vulnerability of Nigeria and Sierra Leone to Lassa Fever and Ebola. We develop a simple analytical form that can be used to estimate vulnerability scores for different spatial units of interest, e.g. countries or regions. We show how some populations can be highly vulnerable despite low impact threats. We finally outline future research to more comprehensively inform vulnerability with the incorporation of relevant factors depicting local heterogeneities (e.g. bio-physical and socio-economic factors). 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'.

Description

Keywords

adaptive capacity, impact, mathematical modelling, zoonosis, Disease Susceptibility, Hemorrhagic Fever, Ebola, Humans, Lassa Fever, Models, Biological, Nigeria, Risk Factors, Sierra Leone

Journal Title

Philos Trans R Soc Lond B Biol Sci

Conference Name

Journal ISSN

0962-8436
1471-2970

Volume Title

374

Publisher

The Royal Society

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All rights reserved
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