Every year in Costa Rica, dengue fever arrives like the rainy season: people expect it, they prepare for it, but the exact rhythm of outbreaks has remained a mystery. In some cantons, the disease flares up every year; in others, every two or three years. Researchers decided to listen to this rhythm the way a doctor listens to a heartbeat, but instead of a stethoscope, they used satellite images and a mathematical tool that breaks a signal into waves of different lengths.

Twenty years of observations, from 2000 to 2019, were turned into time series: how many people fell ill in each of the 32 cantons each month. Then these series were run through wavelet analysis. While a regular graph shows when a peak occurred, a wavelet reveals which waves make up that peak: fast ones, yearly, or slow ones, multi-year. It turned out that in all cantons, three waves dominate: one-year, two-year, and three-year. Until 2008, the first two were more prominent, but after that, the third strengthened, as if the orchestra changed tempo.

Next came the question: who conducts this orchestra? The scientists compared disease incidence with six variables visible from space: vegetation greenness, its moisture, daytime and nighttime surface temperature, Atlantic temperature, and four El Niño indices. They found that vegetation leads dengue only on the Pacific coast: when foliage flourishes, incidence rises three months later. Surface temperature and El Niño are linked to the disease nationwide, but with a delay: the dengue peak comes 3–6 months after the temperature minimum.

This picture changes the approach to forecasting. Previously, one might think that dengue in Costa Rica follows a single common rhythm, but now it is clear that in different regions, the disease listens to different conductors. On the coast, the main signal comes from foliage, while inland, it is the ocean. Therefore, early warning systems need to be tuned locally: in some places, watch satellite images of vegetation; in others, monitor ocean temperature.

So the ocean and the foliage are no longer just a backdrop. They set the rhythm by which the fever lives, and this rhythm can be heard if you properly decompose the signal into waves. Wavelet analysis, originally created for seismic data, now helps epidemiologists not just count cases but understand when to expect the next wave.