Evidence map›Paper›PMID 36126054›Full record

ArticlePloS one2022

Spatial modeling and ecological suitability of monkeypox disease in Southern Nigeria.

Temitope Emmanuel Arotolu, Ayoola Ebenezer Afe, HaoNing Wang, JiaNing Lv, Kun Shi, LiYa Huang, XiaoLong Wang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.3field-weighted citation impact, top 17% 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

10 citing papers in PubMed, 18 citations in OpenAlex.

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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

7 authors at 4 institutions in 1 country.

Temitope Emmanuel ArotoluCenter of Conservation Medicine & Ecological Safety, Northeast Forestry University, Harbin, Heilongjiang Province, P. R. China.
Ayoola Ebenezer AfeAnimal Genetic Engineering and Geoplasm Innovation, Graduate School of Chinese Academy of Agricultural Sciences, Beijing, P. R. China.
HaoNing WangSchool of Geography and Tourism, Harbin University, Harbin, Heilongjiang Province, P. R. China.
JiaNing LvCollege of Wildlife and Protected Area, Northeast Forestry University, Harbin, Heilongjiang Province, P. R. China.
Kun ShiWildlife Institute, Beijing Forestry University, Beijing, Beijing, P. R. China.
LiYa HuangChangbai Mountain Academy of Sciences, Antu, Jilin Province, P. R. China.
XiaoLong WangCenter of Conservation Medicine & Ecological Safety, Northeast Forestry University, Harbin, Heilongjiang Province, P. R. China.ORCID 0000-0002-9293-5289
Northeast Forestry University · CNBeijing Forestry University · CNChinese Academy of Agricultural Sciences · CNHarbin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The reemergence of monkeypoxvirus (MPXV) in 2017 after about 39 years of no reported cases in Nigeria, and the recent incidence in countries such as the United States of America, United Kingdom, Singapore, and Israel which have been reportedly linked with travelers from Africa, have heightened concern that MPXV may have emerged to occupy the vacant ecological and immunological niche created by the extinct smallpox virus. This study was carried out to identify environmental conditions and areas that are environmentally suitable (risky areas) for MPXV in southern Nigeria. One hundred and sixteen (116) spatially unique MPXV occurrence data from 2017-2021 and corresponding environmental variables were spatially modeled by a maximum entropy algorithm to evaluate the contribution of the variables to the distribution of the viral disease. A variance inflation analysis was adopted to limit the number of environmental variables and minimize multicollinearity. The five variables that contributed to the suitability model for MPXV disease are precipitation of driest quarter (47%), elevation (26%), human population density (17%), minimum temperature in December (7%), and maximum temperature in March (3%). For validation, our model had a high AUC value of 0.92 and standard deviation of 0.009 indicating that it had excellent ability to predict the suitable areas for monkeypox disease. Categorized risk classes across southern states was also identified. A total of eight states were predicted to be at high risk of monkeypox outbreak occurrence. These findings can guide policymakers in resources allocation and distribution to effectively implement targeted control measures for MPXV outbreaks in southern Nigeria.

Indexed as

Mpox, MonkeypoxDisease OutbreaksHumansMonkeypox virusNigeriaUnited KingdomUnited States

Identifiers

PMID36126054
PMCPMC9488772
OpenAlexW4296800340

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.