Dengue is a mosquito-transmitted virus infection that causes epidemics of febrile illness and hemorrhagic fever across the tropics and subtropics worldwide. Annual epidemics are commonly observed, but there is substantial spatiotemporal heterogeneity in intensity. A better understanding of this heterogeneity in dengue transmission could lead to improved epidemic prediction and disease control. Time series decomposition methods enable the isolation and study of temporal epidemic dynamics with a specific periodicity (e.g., annual cycles related to climatic drivers and multiannual cycles caused by dynamics in population immunity). We collected and analyzed up to 18 y of monthly dengue surveillance reports on a total of 3.5 million reported dengue cases from 273 provinces in eight countries in Southeast Asia, covering ∼10 7 km 2 . We detected strong patterns of synchronous dengue transmission across the entire region, most markedly during a period of high incidence in 1997-1998, which was followed by a period of extremely low incidence in 2001-2002. This synchrony in dengue incidence coincided with elevated temperatures throughout the region in 1997-1998 and the strongest El Niño episode of the century. Multiannual dengue cycles (2-5 y) were highly coherent with the Oceanic Niño Index, and synchrony of these cycles increased with temperature. We also detected localized traveling waves of multiannual dengue epidemic cycles in Thailand, Laos, and the Philippines that were dependent on temperature. This study reveals forcing mechanisms that drive synchronization of dengue epidemics on a continental scale across Southeast Asia.is an arbovirus transmitted by Aedes mosquitos in the tropics and subtropics of the world. The virus causes an estimated 390 million infections per year, resulting in 96 million clinically symptomatic cases (1). DENV has four serotypes (DENV-1, DENV-2, DENV-3, and DENV-4) that each circulate worldwide. The spatial propagation of dengue transmission at short distances by the mosquito vector is well-understood, but the mechanism of long-distance spread has remained unclear. Disease transmission over large geographical distances is difficult to measure directly, but epidemiological coupling of locations revealed by synchrony in population-level disease patterns has been used successfully in the past to infer mechanisms of spread