• Journal: Proceedings of the National Academy of Sciences
  • Date: Oct. 20, 2015
  • DOI: 10.1073/pnas.1501375112
  • Category: Scientific Research


A team of researchers, led by Dr. Willem van Panhuis of the University of Pittsburgh, used Project Tycho data on dengue cases in eight southeast Asian countries to examine the relationship between dengue cases and climate patterns, such as El Niño events.


Willem G. van Panhuis

Marc Choisy

Xin Xiong

Nian Shong Chok

Pasakorn Akarasewid

Sopon Iamsirithawornd

Sai K. Lam

Chee K. Chong

Fook C. Lam

Bounlay Phommasak

Phengta Vongphrachanh

Khamphaphongphane Bouaphanh

Huy Rekol

Nguyen Tran Hien

Pham Quang Thai

Tran Nhu Duong

Jen-Hsiang Chuang

Yu-Lun Liu, Lee-Ching Ng

Yuan Shi

Enrique A. Tayag

Vito G. Roque, Jr.

Lyndon L. Lee Suyo,

Richard G. Jarman

Robert V. Gibbons

John Mark S. Velasco

In-Kyu Yoon

Donald S. Burke

Derek A. T. Cummings

Related Project Tycho Datasets

Cambodia - Dengue

Cambodia - Dengue Hemorrhagic Fever

Cambodia - Dengue without warning signs

Lao People's Democratic Republic - Dengue

Lao People's Democratic Republic - Dengue Hemorrhagic Fever

Lao People's Democratic Republic - Dengue without warning signs

Malaysia - Dengue

Malaysia - Dengue Hemorrhagic Fever

Malaysia - Dengue without warning signs

Philippines - Dengue

Philippines - Dengue Hemorrhagic Fever/a>

Philippines - Dengue without warning signs

Singapore - Dengue

Singapore - Dengue Hemorrhagic Fever

Singapore - Dengue without warning signs

Taiwan, Province of China - Dengue

Thailand - Dengue

Thailand - Dengue without warning signs

Viet Nam - Dengue

Viet Nam - Dengue Hemorrhagic Fever

Viet Nam - Dengue without warning signs


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 ∼107 km2. 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.

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