TY - JOUR

T1 - Predicting global variation in infectious disease severity

T2 - a bottom-up approach

AU - Jensen, Per Moestrup

AU - de Fine Licht, Henrik Hjarvard

PY - 2016

Y1 - 2016

N2 - 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 his- torical 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.

AB - 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 his- torical 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.

U2 - 10.1093/emph/eow005

DO - 10.1093/emph/eow005

M3 - Journal article

C2 - 26884415

VL - 2016

SP - 85

EP - 94

JO - Evolution, Medicine and Public Health

JF - Evolution, Medicine and Public Health

SN - 2050-6201

IS - 1

ER -