Health burden, spatiotemporal heterogeneity, and productivity losses associated with malaria in Peru: a multisource longitudinal study

Malaria persists in Peru, with transmission concentrated in the Amazon and Plasmodium vivax predominating. Integrating disease burden, geographic heterogeneity, and productivity losses may inform elimination efforts. To characterize malaria burden, demographic and spatiotemporal dynamics, and productivity losses. We conducted a retrospective, ecological, longitudinal, multisource study using surveillance data for 2000–2024, confirmed episodes for 2009–2023, district-level risk for 2019–2023, and ENAHO microdata. Negative binomial, generalized additive, segmented, and Bayesian spatiotemporal models characterized notified transmission. Productivity losses were estimated using the human capital approach and Monte Carlo simulation. GBD 2023 estimates for 1990–2023 provided a secondary comparative layer; modeled burden, notified episodes, and economic losses were analyzed as separate estimands. We identified 41 persistent P. vivax and 17 persistent P. falciparum hotspots. P. vivax predominated, and notified rates were higher at younger ages and, for P. vivax , among males. During 2017–2021, annual rates decreased by 22.7% for P. vivax and 29.8% for P. falciparum . The segmented P. vivax annual change during 2022–2023 was + 37.7% (95% CI + 3.5% to + 83.1%) and varied across sensitivity specifications. In 2023, national productivity losses were S/ 9.6 million (95% UI, S/ 8.6–10.6 million); the Loreto scenario combining productivity losses and direct costs was S/ 11.6 million (95% UI, S/ 10.7–12.6 million). In the secondary GBD comparison, age-standardized incidence decreased from approximately 2,700 to 140 per 100,000 population during 1990–2023. Persistent species-specific hotspots provide a geographic basis for targeting malaria elimination efforts in Peru. Separating notified transmission, modeled burden, and economic losses identifies complementary priorities for surveillance, sustained interventions, and resource allocation.