Mathematical Models for a New Era of Malaria Eradication

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. Historically, the mathematical models of Ross, Macdonald, and Dietz gave us insights into the power of certain malaria control strategies, such as targeting female anopheline mosquitoes and using integrated approaches for malaria control [2]. These and other early modeling efforts [3–5] contributed to policy and provoked widespread discussion and new theoretical and experimental work. Early models usually had simple designs aimed at understanding the basic principles of the parasites’ population biology and evolution. These models gave us a threshold principle in mosquito control, which states that mosquito numbers need only to be reduced below a certain threshold in order to set the parasites on a path to extinction, as well as combination therapies as a means of delaying resistance evolution. With increasing computing power over the past decades, mathematical models have become more detailed and complex. Recently, the largest malaria modeling project known to date was funded by the Bill & Melinda Gates Foundation and uses a network of volunteer computers to run many variations of a highly complex malaria model [6]. While these complex models can make specific, quantitative predictions about strategies for control, simple models are often more appropriate for deriving general principles about malaria epidemiology. Both approaches will be important for developing coordinated malaria control policies.