Distribution of malaria exposure in endemic countries in Africa considering country levels of effective treatment

Malaria Journal

Research

Peter Pemberton-Ross¹  Nicolas Maire¹  Thomas A. Smith¹  Melissa A. Penny¹  Olivier J. T. Briët¹  Caitlin A. Bever²  Peter W. Gething³  David L. Smith⁴ 

[1] Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, 4051, Basel, Switzerland;University of Basel, Petersplatz 1, Basel, Switzerland;Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, 4051, Basel, Switzerland;University of Basel, Petersplatz 1, Basel, Switzerland;Institute for Disease Modeling, 98005, Bellevue, WA, USA;Department of Zoology, University of Oxford, Tinbergen Building, South Parks Road, OX1 3PS, Oxford, UK;Department of Zoology, University of Oxford, Tinbergen Building, South Parks Road, OX1 3PS, Oxford, UK;Sanaria Institute of Global Health and Tropical Medicine, 20850, Rockville, MD, USA;

关键词: Malaria;    Transmission;    Case-management;    Simulation;    Dynamic model;   

DOI  :  10.1186/s12936-015-0864-3

 received in 2015-04-28, accepted in 2015-08-23,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundMalaria prevalence, clinical incidence, treatment, and transmission rates are dynamically interrelated. Prevalence is often considered a measure of malaria transmission, but treatment of clinical malaria reduces prevalence, and consequently also infectiousness to the mosquito vector and onward transmission. The impact of the frequency of treatment on prevalence in a population is generally not considered. This can lead to potential underestimation of malaria exposure in settings with good health systems. Furthermore, these dynamical relationships between prevalence, treatment, and transmission have not generally been taken into account in estimates of burden.MethodsUsing prevalence as an input, estimates of disease incidence and transmission [as the distribution of the entomological inoculation rate (EIR)] for Plasmodium falciparum have now been made for 43 countries in Africa using both empirical relationships (that do not allow for treatment) and OpenMalaria dynamic micro-simulation models (that explicitly include the effects of treatment). For each estimate, prevalence inputs were taken from geo-statistical models fitted for the year 2010 by the Malaria Atlas Project to all available observed prevalence data. National level estimates of the effectiveness of case management in treating clinical attacks were used as inputs to the estimation of both EIR and disease incidence by the dynamic models.Results and conclusionsWhen coverage of effective treatment is taken into account, higher country level estimates of average EIR and thus higher disease burden, are obtained for a given prevalence level, especially where access to treatment is high, and prevalence relatively low. These methods provide a unified framework for comparison of both the immediate and longer-term impacts of case management and of preventive interventions.

【 授权许可】

CC BY   
© Penny et al. 2015

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