Malaria risk assessment and mapping using satellite imagery and boosted regression trees in the Peruvian Amazon

Malaria remains a significant source of suffering and death. Annually, in Peru, many cases are reported, with 95% of these occurring in the Department of Loreto. Since 2018, the "Zero Malaria Plan" (ZMP) has implemented interventions to eliminate malaria from Peru by 2030. This program promotes a community-based model with three overlapping development phases:
(1) Malaria control during the first three years, focusing on eliminating symptomatic infections,
and using testing and treating to reduce 70% of the malaria burden. (2) Control during the
middle ten years, targeting both asymptomatic and low-parasite-density infections to reduce
99% of the malaria burden. (3) interventions during the entire program to eliminate residual
malaria transmission foci, including reintroductions.
There is a need for accurate and timely identification of high malaria transmission areas so that
cost-effective malaria prevention, diagnosis, and treatment strategies can be implemented when
and where they are needed.
This research is an original study that assesses the risk of co-endemic Plasmodium
vivax and Plasmodium falciparum transmission in the Peruvian Amazon using boosted
regression tree (BRT) models based on social and environmental predictors derived from
satellite imagery and data to assess and predict high and very high malaria transmission in the department, at the village level. This research also generates technical proposals for malaria
control program in the Department of Loreto.