Evidence map›Paper›PMID 29338736›Full record

ArticleInternational journal of health geographics2018

Spatial panorama of malaria prevalence in Africa under climate change and interventions scenarios.

Francois M Moukam Kakmeni, Ritter Y A Guimapi, Frank T Ndjomatchoua, Sansoa A Pedro, James Mutunga, Henri E Z Tonnang

Open access · goldAbstract read
In one paragraph

Article in International journal of health geographics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
5.2field-weighted citation impact, top 4% 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

19 citing papers in PubMed, 58 citations in OpenAlex.

  1. Article
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  8. Digital health for climate change mitigation and response: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2022
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  9. Article
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  17. Characterizing the Spatial Determinants and Prevention of Malaria in Kenya.International journal of environmental research and public health · 2019
    Article
  18. Article
  19. Article
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 at 5 institutions in 3 countries.

Francois M Moukam KakmeniHuman Health Division, International Center of Insect Physiology and Ecology, P.O. Box 30772-00100, Nairobi, Kenya.
Ritter Y A GuimapiHuman Health Division, International Center of Insect Physiology and Ecology, P.O. Box 30772-00100, Nairobi, Kenya.
Frank T NdjomatchouaHuman Health Division, International Center of Insect Physiology and Ecology, P.O. Box 30772-00100, Nairobi, Kenya.
Sansoa A PedroHuman Health Division, International Center of Insect Physiology and Ecology, P.O. Box 30772-00100, Nairobi, Kenya.
James MutungaHuman Health Division, International Center of Insect Physiology and Ecology, P.O. Box 30772-00100, Nairobi, Kenya.
Henri E Z TonnangHuman Health Division, International Center of Insect Physiology and Ecology, P.O. Box 30772-00100, Nairobi, Kenya. h.tonnang@cgiar.org.
International Centre of Insect Physiology and Ecology · KEEduardo Mondlane University · MZJomo Kenyatta University of Agriculture and Technology · KEUniversité de Yaoundé I · CMUniversity of Buea · CM

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMalaria is highly sensitive to climatic variables and is strongly influenced by the presence of vectors in a region that further contribute to parasite development and sustained disease transmission. Mathematical analysis of malaria transmission through the use and application of the value of the basic reproduction number (R

methodsTemperature dependence aspect of R

resultsThe inclusion of the coupling between patches in dynamical model seems to have no effects on the estimate of the optimal temperature (about 25 °C) for malaria transmission. In patches environment, we were able to establish a threshold value (about α = 5) representing the ratio between the migration rates from one patch to another that has no effect on the magnitude of R

conclusionsThe approach employed here is a sole study that defined the limits of contemporary malaria transmission, using R

Indexed as

Climate ChangeGeographic Information SystemsModels, TheoreticalAfricaAnimalsGeographic MappingHumansMalariaMosquito VectorsPlasmodium falciparumPrevalenceBasic reproduction numberGeographical information system (GIS)Network modelTransmissionVector-borne disease

Identifiers

PMID29338736
PMCPMC5771136
OpenAlexW2783211351

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.