Trends and cyclical patterns of dengue disease in Mexico: A 40-year time series analysis

To quantify long-term trends and multi-year cycles in dengue in Mexico (1985–2025) and examine recent serotype–severity patterns. We integrated open national surveillance data from the Morbidity Yearbook (1985–2024) and Open Data (2020–2025) using the official estimated-cases definition. Monthly series underwent STL decomposition, Butterworth filtering, periodogram, and autocorrelation analyses. Stationarity was assessed in prespecified windows (1985–2000; 2000–2015; 2015–2025) and by geography (coastal/high-burden vs inland). Serotype distribution and hospitalizations (2020–2025) were summarized among laboratory-confirmed cases and compared across years with χ² tests. Over 40 years we identified 1,715,456 estimated cases; annual burden increased (Mann–Kendall z=3.25; Sen’s slope ≈ +1275 cases/year). A recurrent multi-year oscillation overlaid the seasonal cycle, with a spectral peak near 5.8 years and an ACF secondary maximum at ~4.3 years; the signal persisted in coastal/high-burden states and across historical windows. Since 2023, DENV-3 predominated (86% in 2024; 94.9% by May-2025) and coincided with higher hospitalization proportions. Dengue in Mexico shows a significant long-term rise and a reproducible ~5-year cycle. Cycle-aware baselines, paired with serotype surveillance, could sharpen early-warning thresholds and targeting of vector control. • Dengue burden in Mexico increased over 1985–2025 (~1.72 million estimated cases). • Areproducible 4–6-year multi-annual cycle overlays strong annual seasonality. • Periodicity confirmed by STL/LOESS, FFT periodogram, ACF, and Butterworth filters. • Signal persists across pre-specified windows and is strongest in coastal/high-burden states. • DENV-3 (2023–2025) predominance coincided with higher hospitalization proportions. • Results support cycle-aware surveillance, early-warning thresholds, and vector-control timing.