Research Article: Mathematical Models for a New Era of Malaria Eradication

Date Published: November 25, 2008

Publisher: Public Library of Science

Author(s): Maciej F Boni, Caroline O Buckee, Nicholas J White

Abstract: Maciej Boni and colleagues discuss a new model exploring how a switch in antimalarial drug use to artemisinin-based combination therapies will affect malaria prevalence and incidence in endemic regions.

Partial Text: The renewed focus on malaria control and eradication in recent years has shifted the design of malaria control programs away from short-term, local solutions towards more wide-ranging and long-term strategies. This new era of malaria control will require sustained commitment and funding, with proposed control programs being evaluated in terms of geographic scope and long-term feasibility [1]. Because this type of evaluation cannot be done experimentally, mathematical modeling has emerged as a popular tool for comparing the possible strategies for the control and elimination of malaria.

In this issue of PLoS Medicine, Lucy Okell and colleagues present a mathematical model exploring how a switch in antimalarial drug use to artemisinin-based combination therapies (ACT) will affect malaria prevalence and incidence in endemic regions [7]. ACTs, increasingly used as a first-line treatment for uncomplicated malaria, work rapidly and act on the transmission stages of the parasite. Their role in reducing transmission makes them a potentially important component of future malaria elimination and eradication efforts. Theoretical studies of the kind presented by Okell and colleagues provide valuable insights into how best to use ACTs in different regions.

We predict an increase in malaria mathematical modeling and a danger of increased confusion among policy makers as each investigation strives for a novel result of “interest.” Malaria models predictably generate heat, but less often light. The keys to a sound and understandable modeling conclusion are appropriate design, working within the model’s assumptions, a careful analysis of the model’s sensitivity to these assumptions, and a clear statement of the model’s limitations. Following these basic precepts will make modeling accessible to the medical and public health communities, who need to trust and understand the modelers’ recommendations. In predicting the effects of antimalarial drugs on malaria incidence and prevalence, we have to be clear that our estimates of transmission dynamics, and in particular the effects of antimalarial drugs on malaria transmission and their interaction with host immunity, are poor. Research on this critical area has not kept up with developments in other areas of malaria research.

Source:

http://doi.org/10.1371/journal.pmed.0050231

 

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