The primary focus of malaria research and control has been on Plasmodium falciparum, the most severe of the four Plasmodium species causing human disease. However, the presence of both P. falciparum and Plasmodium vivax occurs in several countries, including India. We developed a mathematical model describing the dynamics of P. vivax and P. falciparum in the human and mosquito populations and fit this model to Indian clinical case data to understand how enhanced control measures affect the competition between the two Plasmodium species. Around 1997, funding for malaria control in India increased dramatically. Our model predicts that if India had not improved its control strategy, the two species of Plasmodium would continue to coexist. To determine which control measures contributed the most to the decline in the number of cases after 1997, we compared the fit of seven models to the 1997-2010 clinical case data. From this, we determined that increased use of bednets contributed the most to case reduction. During the enhanced control period, the best model predicts that P. vivax is out-competing P. falciparum. However, the reproduction numbers are extremely close to the invasion boundaries. Consequently, we cannot be confident that this outcome is the true future of malaria in India. We address this uncertainty by performing a parametric bootstrapping procedure for each of the seven models. This procedure, applied to the enhanced control period, revealed that the best model predicts that P. vivax outcompeting P. falciparum is the most likely outcome, whereas the remaining candidate models predict the opposite. Moreover, the predictions of the top model are counter to what one expects based on the case data alone. Although the proportion of cases due to falciparum has been increasing, the best fitting model reveals that this observation is insufficient to draw conclusions about the longterm competitive outcome of the two species.
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