Evidence map›Paper›PMID 42655735›Full record

ArticleViruses2026

ENSO Impact on Global Chikungunya Virus Transmission, 2008-2024: A Multi-Country Distributed-Lag Time-Series Analysis.

Shi-Hui Shan, Long-Tao Chen, Wen-Qi Xie, Chen-Long Lv, Dong Jiang, Fang-Yu Ding, Gang Dong, Li-Qun Fang

Abstract read
In one paragraph

Article in Viruses, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Shi-Hui ShanState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing 100071, China.
Long-Tao ChenState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing 100071, China.
Wen-Qi XieInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Chen-Long LvState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing 100071, China.
Dong JiangInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0000-0002-4154-5969
Fang-Yu DingInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Gang DongState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing 100071, China.
Li-Qun FangState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing 100071, China.ORCID 0000-0002-4981-1483

Funding

Prevention and Control of Emerging and Major Infectious Diseases-National Science and Technology Major Project 2025ZD01900202
6 · The paper itself

Abstract

Chikungunya is undergoing global expansion, but how El Niño-Southern Oscillation (ENSO) influences its transmission remains unclear. We aim to assess the impact of ENSO phases on chikungunya incidence via temperature and precipitation teleconnections and to project future risk burden under climate change. We compiled annual national and subnational chikungunya case data (2008-2024), quantified ENSO-climate teleconnections using the E-index (eastern Pacific El Niño) and C-index (central Pacific La Niña), and applied distributed-lag time-series models to assess the teleconnection-mediated impact of ENSO on chikungunya incidence. We further projected future risk burden under climate change scenarios. Modelling shows that El Niño increased chikungunya risk after a 2-year lag (cumulative relative risk [CRR] = 1.40, 95% confidence interval [CI]: 1.02-1.85), while La Niña suppressed it (CRR = 0.09, 95% CI: 0.07-0.13). Temperature teleconnections were the dominant modifier of spatial heterogeneity in effects. Under all scenarios, El Niño-driven warming led to positive median excess cases, the highest under SSP2-4.5, whereas La Niña-driven changes projected smaller, highly uncertain reductions. ENSO influences chikungunya transmission through asymmetric and spatially heterogeneous teleconnection pathways. Integrating ENSO forecasts into surveillance efforts has the potential to enhance preparedness in climate-sensitive regions.

Indexed as

Chikungunya FeverChikungunya virusEl Nino-Southern OscillationAnimalsClimate ChangeHumansIncidenceTemperaturechikungunyaclimate changeCMIP6disease projectiondistributed-lag time-seriesEl Niño–Southern Oscillation

Identifiers

PMID42655735
PMCPMC13517555

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.