Using current field diagnostics, it is not possible to eliminate malaria by mass distribution of anti-malarial drugs without substantial overtreatment of uninfected people.
New research lead by Jaline Gerardin combines a mathematical model of malaria transmission with field data from Zambia to computationally test a variety of strategies for targeting infected individuals in a population and evaluate each strategy's success at eliminating malaria and avoiding overtreatment.
Millions of people worldwide live at risk for malaria, a parasitic infectious disease transmitted by mosquitoes. Presumptively administering antimalarial drugs to whole populations will effectively clear infections but can also lead to substantial overtreatment and encourage the evolution of drug resistance in parasites.
In their PLOS Computational Biology article, Gerardin et al. show that targeting hotspots identified by testing individuals with currently available diagnostics is highly effective at avoiding overtreatment but also unlikely to lead to elimination as current diagnostics fail to identify enough index cases. Until improved diagnostics are available, mass presumptive treatment is the only effective method of distributing antimalarials as part of an elimination program.