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Predicting global variation in infectious disease severity: A bottom-up approach

Background and objectives: Understanding the underlying causes for the variation in case-fatality-ratios (CFR) is important for assessing the mechanism governing global disparity in the burden of infectious diseases. Variation in CFR is likely to be driven by factors such as population genetics, dem...

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Autores principales: Jensen, Per M., De Fine Licht, Henrik H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4790778/
https://www.ncbi.nlm.nih.gov/pubmed/26884415
http://dx.doi.org/10.1093/emph/eow005
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author Jensen, Per M.
De Fine Licht, Henrik H.
author_facet Jensen, Per M.
De Fine Licht, Henrik H.
author_sort Jensen, Per M.
collection PubMed
description Background and objectives: Understanding the underlying causes for the variation in case-fatality-ratios (CFR) is important for assessing the mechanism governing global disparity in the burden of infectious diseases. Variation in CFR is likely to be driven by factors such as population genetics, demography, transmission patterns and general health status. We present data here that support the hypothsis that changes in CFRs for specific diseases may be the result of serial passage through different hosts. For example passage through adults may lead to lower CFR, whereas passage through children may have the opposite effect. Accordingly changes in CFR may occur in parallel with demographic transitions. Methodology: We explored the predictability of CFR using data obtained from the World Health Organization (WHO) disease databases for four human diseases: mumps, malaria, tuberculosis and leptospirosis and assessed these for association with a range of population characteristics, such as crude birth and death rates, median age of the population, mean body mass index, proportion living in urban areas and tuberculosis vaccine coverage. We then tested this predictive model on Danish historical demographic and population data. Results: Birth rates were the best predictor for mumps and malaria CFR. For tuberculosis CFR death rates were the best predictor and for leptospirosis population density was a significant predictor. Conclusions and implications: CFR predictors differed among diseases according to their biology. We suggest that the overall result reflects an interaction between the forces driving demographic change and the virulence of human-to-human transmitted diseases.
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spelling pubmed-47907782016-03-16 Predicting global variation in infectious disease severity: A bottom-up approach Jensen, Per M. De Fine Licht, Henrik H. Evol Med Public Health Original Research Article Background and objectives: Understanding the underlying causes for the variation in case-fatality-ratios (CFR) is important for assessing the mechanism governing global disparity in the burden of infectious diseases. Variation in CFR is likely to be driven by factors such as population genetics, demography, transmission patterns and general health status. We present data here that support the hypothsis that changes in CFRs for specific diseases may be the result of serial passage through different hosts. For example passage through adults may lead to lower CFR, whereas passage through children may have the opposite effect. Accordingly changes in CFR may occur in parallel with demographic transitions. Methodology: We explored the predictability of CFR using data obtained from the World Health Organization (WHO) disease databases for four human diseases: mumps, malaria, tuberculosis and leptospirosis and assessed these for association with a range of population characteristics, such as crude birth and death rates, median age of the population, mean body mass index, proportion living in urban areas and tuberculosis vaccine coverage. We then tested this predictive model on Danish historical demographic and population data. Results: Birth rates were the best predictor for mumps and malaria CFR. For tuberculosis CFR death rates were the best predictor and for leptospirosis population density was a significant predictor. Conclusions and implications: CFR predictors differed among diseases according to their biology. We suggest that the overall result reflects an interaction between the forces driving demographic change and the virulence of human-to-human transmitted diseases. Oxford University Press 2016-03-14 /pmc/articles/PMC4790778/ /pubmed/26884415 http://dx.doi.org/10.1093/emph/eow005 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of the Foundation for Evolution, Medicine, and Public Health. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research Article
Jensen, Per M.
De Fine Licht, Henrik H.
Predicting global variation in infectious disease severity: A bottom-up approach
title Predicting global variation in infectious disease severity: A bottom-up approach
title_full Predicting global variation in infectious disease severity: A bottom-up approach
title_fullStr Predicting global variation in infectious disease severity: A bottom-up approach
title_full_unstemmed Predicting global variation in infectious disease severity: A bottom-up approach
title_short Predicting global variation in infectious disease severity: A bottom-up approach
title_sort predicting global variation in infectious disease severity: a bottom-up approach
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4790778/
https://www.ncbi.nlm.nih.gov/pubmed/26884415
http://dx.doi.org/10.1093/emph/eow005
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