New methodologies for the estimation of population vulnerability to diseases: a case study of Lassa fever and Ebola in Nigeria and Sierra Leone
Author(s) -
Olumayowa T. Kajero,
Victor Del Rio Vilas,
James L. N. Wood,
Giovanni Lo Iacono
Publication year - 2019
Publication title -
philosophical transactions of the royal society b biological sciences
Language(s) - English
Resource type - Journals
eISSN - 1471-2970
pISSN - 0962-8436
DOI - 10.1098/rstb.2018.0265
Subject(s) - sierra leone , lassa fever , lassa virus , vulnerability (computing) , population , ebola virus , virology , dengue fever , viral hemorrhagic fever , biology , outbreak , geography , environmental health , medicine , socioeconomics , computer security , computer science , virus , sociology
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’.
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