Evidence map›Paper›PMID 41022841›Full record

ArticleNature communications2025

Rising dengue risk with increasing El Niño-Southern Oscillation amplitude and teleconnections.

Yunyu Tian, Yiting Xu, Yilin Liang, Ziqin Zhou, Katie M Susong, Yuyang Chen, Kishen Joshi, Amy M Campbell, Ahyoung Lim, Qiushi Lin and 12 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Yunyu Tian *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, School of National Safety and Emergency Management, Beijing Normal University, Beijing, China.
Yiting Xu *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, School of National Safety and Emergency Management, Beijing Normal University, Beijing, China.
Yilin Liang *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, School of National Safety and Emergency Management, Beijing Normal University, Beijing, China.ORCID http://orcid.org/0009-0009-9618-0619
Ziqin ZhouNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, School of National Safety and Emergency Management, Beijing Normal University, Beijing, China.
Katie M SusongCentre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Yuyang ChenNational Engineering Research Center of Eco-Environment in the Yangtze River Economic Belt, China Three Gorges Corporation, Wuhan, China.
Kishen JoshiCentre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Amy M CampbellCentre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Ahyoung LimCentre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.ORCID http://orcid.org/0000-0003-4445-5034
Qiushi LinDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Zixuan MaCollege of Letters & Science, University of Wisconsin-Madison, Madison, WI, USA.
Yuanlong WeiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, School of National Safety and Emergency Management, Beijing Normal University, Beijing, China.
Yun YangState Key Laboratory of Remote Sensing and Digital Earth, Beijing Key Laboratory of Surveillance, Early Warning and Pathogen Research on Emerging Infectious Diseases, Beijing Research Center for Respiratory Infectious Diseases, Center for Global Change and Public Health, Beijing Normal University, Beijing, China.ORCID http://orcid.org/0000-0001-5031-3273
Cheng SunState Key Laboratory of Remote Sensing and Digital Earth, Beijing Key Laboratory of Surveillance, Early Warning and Pathogen Research on Emerging Infectious Diseases, Beijing Research Center for Respiratory Infectious Diseases, Center for Global Change and Public Health, Beijing Normal University, Beijing, China.ORCID http://orcid.org/0000-0003-0474-7593
Juan FengState Key Laboratory of Remote Sensing and Digital Earth, Beijing Key Laboratory of Surveillance, Early Warning and Pathogen Research on Emerging Infectious Diseases, Beijing Research Center for Respiratory Infectious Diseases, Center for Global Change and Public Health, Beijing Normal University, Beijing, China.ORCID http://orcid.org/0000-0002-2382-8500
Qixin HeDepartment of Biological Sciences, Purdue University, West Lafayette, IN, USA.ORCID http://orcid.org/0000-0003-1696-8203
Zengmiao WangState Key Laboratory of Remote Sensing and Digital Earth, Beijing Key Laboratory of Surveillance, Early Warning and Pathogen Research on Emerging Infectious Diseases, Beijing Research Center for Respiratory Infectious Diseases, Center for Global Change and Public Health, Beijing Normal University, Beijing, China.
Bernard CazellesInstitut de Biologie de l'École Normale Supérieure UMR 8197, Eco-Evolutionary Mathematics, École Normale Supérieure, Paris, France.ORCID http://orcid.org/0000-0002-7972-361X
Yuanfang GuoSchool of Computer Science and Engineering, Beihang University, Beijing, China.
Kai LiuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, School of National Safety and Emergency Management, Beijing Normal University, Beijing, China.ORCID http://orcid.org/0000-0001-6571-0327
Oliver J BradyCentre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK. Oliver.Brady@lshtm.ac.uk.ORCID http://orcid.org/0000-0002-3235-2129
Huaiyu TianNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, School of National Safety and Emergency Management, Beijing Normal University, Beijing, China. tianhuaiyu@gmail.com.ORCID http://orcid.org/0000-0002-4466-0858

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Global climate variability has been linked with some of the largest dengue outbreaks, including the record-breaking 2023-2024 epidemic, but the understanding of their mechanism and evidence for their association is lacking. By incorporating reported dengue cases and climate data from 57 countries across the Americas and Asia from 1980 to 2024, we unpacked the global climate teleconnection and quantifying its impact on dengue cases. We revealed that the heterogeneity in the association between global climate variability and dengue cases across regions is affected by the strength and types of global climate teleconnections with temperature and precipitation. By controlling for the heterogeneity, 63% of the variation in dengue cases can be attributed to El Niño-Southern Oscillation fluctuations, with higher values in endemic regions. The 1982-83, 1997-98, 2015-16, and 2023-24 El Niño events were estimated to have induced an additional 0.2, 1.4, 4.1, and 9.6 million dengue cases, respectively, over regular seasonal patterns. Due to human-induced warming, El Niño events and teleconnections may cause a 39.0-81.7% increase in cumulative cases in 2020-2099. Our findings quantify the association between global climate variability and dengue epidemics and caution about the potential future risk.

Indexed as

DengueEl Nino-Southern OscillationAmericasAsiaClimateDisease OutbreaksHumansSeasonsTemperature

Identifiers

PMID41022841
PMCPMC12480917

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.