New methodologies for the estimation of population vulnerability to diseases: a case study of Lassa fever and Ebola in Nigeria and Sierra Leone
Kajero, Olumayowa, Del Rio Vilas, Victor, Wood, James L. N. and Lo Iacono, Giovanni (2019) New methodologies for the estimation of population vulnerability to diseases: a case study of Lassa fever and Ebola in Nigeria and Sierra Leone Philosophical Transactions of the Royal Society B, 374, 20180265.
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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. But, vulnerability is well defined for natural hazards, for public health threats the concept remains undetermined. Here, we developed 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 example, we focused on the vulnerability of Nigeria and Sierra Leone to Lassa Fever and Ebola. We developed a simple analytical form that can be used to estimate vulnerability scores for different spatial units of interest, e.g. countries or regions. We showed how some populations can be highly vulnerable despite low impact threats. We finally outlined future research to more comprehensively inform vulnerability with the incorporation of relevant factors depicting local heterogeneities (e.g. bio-physical and socio-economic factors).
Item Type: | Article | |||||||||||||||
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Divisions : | Faculty of Health and Medical Sciences > School of Veterinary Medicine | |||||||||||||||
Authors : |
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Date : | July 2019 | |||||||||||||||
Funders : | FHMS Research Support Fund | |||||||||||||||
DOI : | 10.1098/rstb.2018.0265 | |||||||||||||||
Grant Title : | Pump Prime Grant: New methodologies towards the assessment of countries’ vulnerabilities to diseases | |||||||||||||||
Copyright Disclaimer : | © 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. | |||||||||||||||
Uncontrolled Keywords : | Impact; Adaptive capacity; Zoonosis; Mathematical modelling | |||||||||||||||
Additional Information : | This article is part of the theme issue ‘Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants Part 2’. | |||||||||||||||
Depositing User : | Clive Harris | |||||||||||||||
Date Deposited : | 05 Apr 2019 07:36 | |||||||||||||||
Last Modified : | 30 May 2019 13:41 | |||||||||||||||
URI: | http://epubs.surrey.ac.uk/id/eprint/850974 |
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