Evidence map›Paper›PMID 20809105›Full record

ArticleEnvironmental science and pollution research international2011

Potential malaria outbreak in Germany due to climate warming: risk modelling based on temperature measurements and regional climate models.

Marcel Holy, Gunther Schmidt, Winfried Schröder

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental science and pollution research international, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Coupling population dynamics with earth system models: the POPEM model.Environmental science and pollution research international · 2019
    Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. 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

3 authors.

Marcel HolyChair of Landscape Ecology, University of Vechta, PO Box 1553, 49364, Vechta, Germany.
Gunther Schmidt
Winfried Schröder

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeClimate warming can change the geographic distribution and intensity of the transmission of vector-borne diseases such as malaria. The transmitted parasites usually benefit from increased temperatures as both their reproduction and development are accelerated. Lower Saxony (northwestern Germany) has been a malaria region until the 1950s, and the vector species are still present throughout Germany. This gave reason to investigate whether a new autochthonous transmission could take place if the malaria pathogen was introduced again in Germany. MATERIALS AND

methodsThe spatial distribution of potential temperature-driven malaria transmissions was investigated using the basic reproduction rate (R (0)) to model and geostatistically map areas at risk of an outbreak of tertian malaria based on measured (1961-1990, 1991-2007) and predicted (1991-2020, 2021-2050, 2051-2080) monthly mean air temperature data.

resultsFrom the computations, maps were derived showing that during the period 1961-1990, the seasonal transmission gate ranges from 0 to 4 months and then expands up to 5 months in the period 1991-2007. For the projection of future trends, the regional climate models REMO and WettReg were used each with two different scenarios (A1B and B1). Both modelling approaches resulted in prolonged seasonal transmission gates in the future, enabling malaria transmissions up to 6 months in the climate reference period 2051-2080 (REMO, scenario A1B). DISCUSSION: The presented risk prognosis is based on the R (0) formula for the estimation of the reproduction of the malaria pathogen Plasmodium vivax. The presented model focuses on mean air temperatures; thus, other driving factors like the distribution of water bodies (breeding habitats) or population density are not integrated. Nevertheless, the modelling presented in this study can help identify areas at risk and initiate prevention. The described findings may also help in the investigation and assessment of related diseases caused by temperature-dependent vectors and pathogens, including those being dangerous for livestock as well, e.g. insect-borne bluetongue disease transmitted by culicoids.

Indexed as

Models, BiologicalAnimalsAnophelesDisease OutbreaksGermanyGlobal WarmingHumansMalaria, VivaxPlasmodium vivaxRisk AssessmentSeasonsTemperature

Identifiers

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.