Evidence map›Paper›PMID 40538425›Full record

ArticleGeoHealth2025

Time of Emergence and Future Projections of Extremes of Malaria Infections in Africa.

Christian L E Franzke, Ruchi Singh Parihar

Abstract read
In one paragraph

Article in GeoHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Christian L E FranzkeCenter for Climate Physics Institute for Basic Science Busan South Korea.ORCID https://orcid.org/0000-0003-4111-1228
Ruchi Singh PariharCenter for Climate Physics Institute for Basic Science Busan South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The spread of malaria is a major health burden, which affects many people in Africa, depends on climate but also socio-economic conditions. Thus, it is important to gauge the impact of anthropogenic global warming on malaria and attribute anthropogenic causes. Here we compute the Time Of Emergence of vector density and of the entomological inoculation rate (EIR) in the SSP3-7.0 scenario using 50 bias-corrected members of Community Earth System Model version 2 Large Ensemble simulations. This reveals that vector density, which depends on climate conditions, and EIR, which depends on both climate and population density, will rise significantly and permanently above the pre-industrial background variability due to anthropogenic causes in Africa. Both the vector density and EIR have areas, mainly in central Africa, where anthropogenic causes have already significantly changed, and many more areas will experience anthropogenic caused changes in the period 2030-2050 and toward the end of this century. Our simulations also show clear evidence that extremes of vector density and EIR increase in the future by almost 100%, suggesting that major malaria epidemic outbreaks will become much more likely. We also perform simulations with constant population and with no global warming which partly reveal underlying malaria dynamics. Our results highlight the need to prepare for an expansion and intensification of the malaria burden if no health interventions are being taken.

Indexed as

extremesinfectious diseasemalariatime of emergence

Identifiers

PMID40538425
PMCPMC12177651

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.