Evidence map›Paper›PMID 27457660›Full record

ArticleEpidemiology and infection2016

Projections of increased and decreased dengue incidence under climate change.

C R Williams, G Mincham, H Faddy, E Viennet, S A Ritchie, D Harley

Abstract read
In one paragraph

Article in Epidemiology and infection, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Modeling present and future climate risk of dengue outbreak, a case study in New Caledonia.Environmental health : a global access science source · 2022
    Article
  6. Article
  7. Article
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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

6 authors.

C R WilliamsCentre for Population Health Research,University of South Australia,Adelaide,Australia.
G MinchamCentre for Population Health Research,University of South Australia,Adelaide,Australia.
H FaddyAustralian Red Cross Blood Service,Brisbane,Queensland,Australia.
E ViennetNational Centre for Epidemiology and Population Health,Australian National University,Canberra,Australia.
S A RitchieSchool of Public Health,Tropical Medicine and Rehabilitation Sciences,James Cook University,Cairns,Queensland,Australia.
D HarleyNational Centre for Epidemiology and Population Health,Australian National University,Canberra,Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dengue is the world's most prevalent mosquito-borne disease, with more than 200 million people each year becoming infected. We used a mechanistic virus transmission model to determine whether climate warming would change dengue transmission in Australia. Using two climate models each with two carbon emission scenarios, we calculated future dengue epidemic potential for the period 2046-2064. Using the ECHAM5 model, decreased dengue transmission was predicted under the A2 carbon emission scenario, whereas some increases are likely under the B1 scenario. Dengue epidemic potential may decrease under climate warming due to mosquito breeding sites becoming drier and mosquito survivorship declining. These results contradict most previous studies that use correlative models to show increased dengue transmission under climate warming. Dengue epidemiology is determined by a complex interplay between climatic, human host, and pathogen factors. It is therefore naive to assume a simple relationship between climate and incidence, and incorrect to state that climate warming will uniformly increase dengue transmission, although in general the health impacts of climate change will be negative.

Indexed as

Climate ChangeAustraliaClimateDengueDengue VirusHumansIncidenceModels, TheoreticalArbovirusesclimate (impact of)dengue feverinfectious disease epidemiology

Identifiers

PMID27457660
PMCPMC9150423

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.