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Fig. 4 | Infectious Diseases of Poverty

Fig. 4

From: Leveraging mathematical models of disease dynamics and machine learning to improve development of novel malaria interventions

Fig. 4

Effects of novel malaria interventions on PfPR0–99 and their key drivers of impact. A Distribution of obtained reduction in PfPR0–99 across the simulated scenarios with OpenMalaria following deployment of various malaria interventions under development (shown with different colors) for a range of simulated transmission settings (specified by median true PfPR2–10 rounded values, x-axis). Each boxplot displays the interquartile range (box), the median value (horizontal line), the largest and smallest values within 1.5 times the interquartile range (whiskers), and the remaining outside values (points) of the PfPR0–99 reduction values obtained across all the simulations for each given setting. The remaining panels present the results of global sensitivity analysis showing, across the same simulated PfPR2–10 settings, the contribution of intervention characteristics to the resulting PfPR0–99 reduction for anti-infective monoclonal antibodies (B), anti-infective vaccines (C), transmission-blocking vaccines (D), attractive targeted sugar baits (E), and eave tubes (F)

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