Evidence map›Paper›PMID 31216349›Full record

ArticlePloS one2019

Potential distribution of dominant malaria vector species in tropical region under climate change scenarios.

Godwin E Akpan, Kayode A Adepoju, Olakunle R Oladosu

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
5.1field-weighted citation impact, top 5% of its field
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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 44 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
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  6. Review
  7. Review
  8. Human Blood Index ofJournal of tropical medicine · 2025
    Review
  9. Range dynamics ofEcology and evolution · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. High Prevalence ofJournal of veterinary research · 2022
    Article
  15. Article
  16. A hot topic at the environment-health nexus: investigating the impact of climate change on infectious diseases.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
    Article
  17. Article
  18. Article
  19. Review
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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

3 authors at 2 institutions in 2 countries.

Godwin E AkpanAfrican Regional Centre for Space Science and Technology Education in English (ARCSSTEE), Obafemi Awolowo University (OAU), Ile-Ife, Osun State, Nigeria.ORCID 0000-0001-8204-9219
Kayode A AdepojuDepartment of Geography, University of The Free State, Qwaqwa Campus, Qwaqwa, Phuthaditjhaba, South Africa.
Olakunle R OladosuAfrican Regional Centre for Space Science and Technology Education in English (ARCSSTEE), Obafemi Awolowo University (OAU), Ile-Ife, Osun State, Nigeria.
Obafemi Awolowo University · NGUniversity of the Free State · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Risk assessment regarding the distribution of malaria vectors and environmental variables underpinning their distribution under changing climates is crucial towards malaria control and eradication. On this basis, we used Maximum Entropy (MaxEnt) Model to estimate the potential future distribution of major transmitters of malaria in Nigeria-Anopheles gambiae sensu lato and its siblings: Anopheles gambiae sensu stricto, and Anopheles arabiensis under low and high emissions scenarios. In the model, we used mosquito occurrence data sampled from 1900 to 2010 alongside land use and terrain variables, and bioclimatic variables for baseline climate 1960-1990 and future climates of 2050s (2041-2060) and 2070s (2061-2080) that follow RCP2.6 and RCP8.5 scenarios. The Anopheles gambiae species are projected to experience large shift in potential range and population with increased distribution density, higher under high emissions scenario (RCP8.5) and 2070s than low emission scenario (RCP2.6) and 2050s. Anopheles gambiae sensu stricto and Anopheles arabiensis are projected to have highest invasion with 47-70% and 10-14% percentage increase, respectively in Sahel and Sudan savannas within northern states in 2041-2080 under RCP8.5. Highest prevalence is predicted for Humid forest and Derived savanna in southern and North Central states in 2041-2080; 91-96% and 97-99% for Anopheles gambiae sensu stricto, and 67-71% and 72-75% for Anopheles arabiensis under RCP2.6 and RCP8.5, respectively. The higher magnitude of change in species prevalence predicted for the later part of the 21st century under high emission scenario, driven mainly by increasing and fluctuating temperature, alongside longer seasonal tropical rainfall accompanied by drier phases and inherent influence of rapid land use change, may lead to more significant increase in malaria burden when compared with other periods and scenarios during the century; especially in Humid forest, Derived savanna, Sahel and Sudan savannas.

Indexed as

Animal DistributionClimate ChangeAnimalsAnophelesComputer SimulationForestsMalariaMosquito VectorsNigeriaTropical Climate

Identifiers

PMID31216349
PMCPMC6583992
OpenAlexW2949389678

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.