edoc

Defining the relationship between infection prevalence and clinical incidence of Plasmodium falciparum malaria

Cameron, Ewan and Battle, Katherine E. and Bhatt, Samir and Weiss, Daniel J. and Bisanzio, Donal and Mappin, Bonnie and Dalrymple, Ursula and Hay, Simon I. and Smith, David L. and Griffin, Jamie T. and Wenger, Edward A. and Eckhoff, Philip A. and Smith, Thomas A. and Penny, Melissa A. and Gething, Peter W.. (2015) Defining the relationship between infection prevalence and clinical incidence of Plasmodium falciparum malaria. Nature communications, Vol. 6 , Article Nr. 8170.

Full text not available from this repository.

Official URL: http://edoc.unibas.ch/dok/A6428794

Downloads: Statistics Overview

Abstract

In many countries health system data remain too weak to accurately enumerate Plasmodium falciparum malaria cases. In response, cartographic approaches have been developed that link maps of infection prevalence with mathematical relationships to predict the incidence rate of clinical malaria. Microsimulation (or 'agent-based') models represent a powerful new paradigm for defining such relationships; however, differences in model structure and calibration data mean that no consensus yet exists on the optimal form for use in disease-burden estimation. Here we develop a Bayesian statistical procedure combining functional regression-based model emulation with Markov Chain Monte Carlo sampling to calibrate three selected microsimulation models against a purpose-built data set of age-structured prevalence and incidence counts. This allows the generation of ensemble forecasts of the prevalence-incidence relationship stratified by age, transmission seasonality, treatment level and exposure history, from which we predict accelerating returns on investments in large-scale intervention campaigns as transmission and prevalence are progressively reduced.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Health Systems Research and Dynamic Modelling > Dynamical Modelling (Smith)
UniBasel Contributors:Smith, Thomas A. and Penny, Melissa
Item Type:Article, refereed
Bibsysno:Link to catalogue
Publisher:Nature Publishing Group
ISSN:2041-1723
Note:Publication type according to Uni Basel Research Database: Journal article
Related URLs:
Identification Number:
Last Modified:02 Oct 2015 10:01
Deposited On:02 Oct 2015 10:01

Repository Staff Only: item control page