Projections of dengue epidemics attributable to climate change in Peru

Chang T.; Choi S.; Lee W.; Martel K.S.; Velásquez J.P.; Munayco C.V.; Cho S., iI; Kim S.; Min K.-D. · BMJ Global Health (2026) · DOI: 10.1136/bmjgh-2025-021184

Resumen

Background: Climate change is expected to influence the risk of mosquito-borne diseases by altering mosquito and pathogen ecology. However, the potential impact of climate change on dengue epidemics has rarely been investigated in Peru. In this study, we projected future dengue epidemics in Peru under various climate change scenarios. Methods: We analysed 526 033 reported dengue cases from 15 Peruvian states (2016–2023). Using quasi-Poisson time-series regression with distributed lag non-linear models (DLNMs), we modelled weekly dengue case counts in each state as a function of weekly mean temperature, adjusting for weekly total precipitation and an El Niño Southern Oscillation indicator. These associations were then applied to temperature projections from five CMIP6 general circulation models under three Shared Socioeconomic Pathway scenarios to estimate temperature-attributable dengue cases for the baseline period (2016–2020) and the scenario period (2021–2050). Results: Temperature-attributable dengue cases are projected to rise from the 2030s through 2050, with substantial regional heterogeneity in magnitude and timing. During the scenario period, absolute temperature-attributable burden is likely to remain substantial in the northern coastal states with the highest baseline burden (eg, Piura) and parts of the Amazon. In contrast, the largest relative increases are projected in states with relatively low baseline burden, including Andean/highland states (eg, Ancash and Cajamarca) and parts of the Amazon (eg, Loreto), suggesting a potential geographic shift in climate-driven dengue risk. Conclusion: In addition to climate change mitigation efforts, proactive disease intervention policies are essential to curb the projected increase in dengue transmission risk. Developing adaptable policies tailored to regional needs will enhance the effectiveness of intervention strategies. © Author(s) (or their employer(s)) 2026. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ Group. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: https://creativecommons.org/licenses/by-nc/4.0/.

Instituciones: Universidad Peruana Cayetano Heredia