Evidence map›Paper›PMID 37952006›Full record

ArticleScientific data2023

Twenty-nine years of continuous monthly capture-mark-recapture data of multimammate mice (Mastomys natalensis) in Morogoro, Tanzania.

Herwig Leirs, Lucinda Kirkpatrick, Vincent Sluydts, Christopher Sabuni, Benny Borremans, Abdul Katakweba, Apia Massawe, Rhodes Makundi, Loth Mulungu, Robert Machang'u and 1 more

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Climate-driven host ecology as a framework for zoonotic disease risk: Understanding transferability across arenavirus systems.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  9. Efficiency of anthelmintic treatment and its effect on microparasite dynamics in wildInternational journal for parasitology. Parasites and wildlife · 2025
    Article
  10. Article
  11. Modelling Lassa virus dynamics in West AfricanJournal of the Royal Society, Interface · 2024
    Article
  12. 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

11 authors.

Herwig LeirsEvolutionary Ecology Group, Department of Biology, University of Antwerp, Antwerp, Belgium.
Lucinda KirkpatrickEvolutionary Ecology Group, Department of Biology, University of Antwerp, Antwerp, Belgium.
Vincent SluydtsEvolutionary Ecology Group, Department of Biology, University of Antwerp, Antwerp, Belgium.
Christopher SabuniInstitute of Pest Management, Sokoine University of Agriculture, Morogoro, Tanzania.
Benny BorremansEvolutionary Ecology Group, Department of Biology, University of Antwerp, Antwerp, Belgium.ORCID 0000-0002-7779-4107
Abdul KatakwebaInstitute of Pest Management, Sokoine University of Agriculture, Morogoro, Tanzania.
Apia MassaweInstitute of Pest Management, Sokoine University of Agriculture, Morogoro, Tanzania.
Rhodes MakundiInstitute of Pest Management, Sokoine University of Agriculture, Morogoro, Tanzania.
Loth MulunguInstitute of Pest Management, Sokoine University of Agriculture, Morogoro, Tanzania.
Robert Machang'uInstitute of Pest Management, Sokoine University of Agriculture, Morogoro, Tanzania.
Joachim MariënEvolutionary Ecology Group, Department of Biology, University of Antwerp, Antwerp, Belgium. joachim.marien@uantwerpen.be.ORCID 0000-0001-7023-445X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The multimammate mice (Mastomys natalensis) is the most-studied rodent species in sub-Saharan Africa, where it is an important pest species in agriculture and carrier of zoonotic diseases (e.g. Lassa virus). Here, we provide a unique dataset that consists of twenty-nine years of continuous monthly capture-mark-recapture entries on one 3 ha mosaic field (MOSA) in Morogoro, Tanzania. It is one of the most accurate and long-running capture-recapture time series on a small mammal species worldwide and unique to Africa. The database can be used by ecologists to test hypotheses on the population dynamics of small mammals (e.g. to test the effect of climate change), or to validate new algorithms on real long-term field data (e.g. new survival analyses techniques). It is also useful for both scientists and decision-makers who want to optimize rodent control strategies and predict outbreaks of multimammate mice.

Indexed as

MurinaePopulation DynamicsAnimalsMiceTanzania

Identifiers

PMID37952006
PMCPMC10640561

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.