16-Year-Old Student Designs Model to Double Malaria Net Effectiveness

Rajarshi Mandal, a rising junior at Lexington High School, developed a sophisticated ODE model of malaria transmission that accounts for factors often ignored in standard distribution plans, including insecticide resistance, seasonal variation, and the gradual loss of net efficacy. His simulation compared a conventional population-based allocation of roughly 200 million annual insecticide-treated nets with an optimized strategy, finding that the latter could prevent twice as many infections using the same number of nets.

Early versions of the model incorrectly drove infection rates to zero, but after consulting experts and incorporating the concept of backward bifurcation, the model achieved realistic persistence of disease. The project was inspired by images of fishermen repurposing donated nets, prompting Mandal to explore the mismatch between distribution assumptions and on-the-ground realities. He initially tried a Deep Q Network approach, but switched to a scoring architecture after encountering instability.

The research earned him a $50,000 Davidson Fellows Scholarship and underscores the potential of data-driven allocation to enhance public-health outcomes. Mandal also balances his academic pursuits with piano performances at Carnegie Hall and holds a black belt in karate.