Spatiotemporal co-distribution and time lagged cross correlation of malaria and dengue in Loreto, Peru.

Malaria and dengue account for most vector-borne disease-related cases and deaths worldwide, disproportionately affecting tropical regions such as Peru. Previously identified social, environmental, and climate determinants for both diseases are similar despite differences in vector ecologies. Control strategies for both rely on interventions such as removal of breeding sites or insecticide-based strategies, which could be integrated. We assessed synchrony (temporal correlations, temporal order, lagged relationships) and spatial correlations between malaria and dengue incidence in the Loreto region of Peru. We conducted a time-lagged cross-correlation (TLCC) analysis between district-level dengue and malaria time series in Loreto between 2000-2021. We identified temporal patterns of dengue that could precede malaria patterns or vice versa. We grouped districts based on shared temporal and spatial patterns in dengue and malaria incidence and explored how the two diseases co-occurred geographically. Our analysis shows a growing number of districts reporting both dengue and malaria over time. Maximum TLCC coefficients varied in magnitude and direction between districts, as did corresponding lag times. In the Northwest, increases in malaria often preceded increases in dengue, while in the Northeast increases in malaria preceded decreases in dengue cases. We found spatial correlation between coefficients in some regions in the Northwest, suggesting that characteristics of a geographic area may influence the observed associations. The identification of districts with strong associations between dengue and malaria incidence can inform implementation of targeted integrated interventions, while identification of distinct patterns of association can inform future studies assessing drivers of both diseases in different settings.