Evidence map›Paper›PMID 38012226›Full record

ArticleScientific reports2023

Ecological correlates and predictors of Lassa fever incidence in Ondo State, Nigeria 2017-2021: an emerging urban trend.

Simeon Cadmus, Olalekan John Taiwo, Victor Akinseye, Eniola Cadmus, Gboyega Famokun, Stephen Fagbemi, Rashid Ansumana, Anddy Omoluabi, Adekunle Ayinmode, Daniel Oluwayelu and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

  1. Pooled it
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  8. Review
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  12. Review
  13. Lassa Fever: Critical Review and Prospects for Control.Tropical medicine and infectious disease · 2024
    Review
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

12 authors.

Simeon Cadmus *Department of Veterinary Public Health and Preventive Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria. simeonc5@gmail.com.
Olalekan John Taiwo *Department of Geography, University of Ibadan, Ibadan, Oyo State, Nigeria. Brainbox_taiwo@yahoo.com.
Victor AkinseyeDamien Foundation Genomics and Mycobacteria Research and Training Centre, University of Ibadan, Ibadan, Oyo State, Nigeria.
Eniola CadmusDepartment of Community Medicine, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Gboyega FamokunDepartment of Epidemiology and Disease Control, Ondo State Ministry of Health, Ondo State, Nigeria.
Stephen FagbemiDepartment of Epidemiology and Disease Control, Ondo State Ministry of Health, Ondo State, Nigeria.
Rashid AnsumanaSchool of Community Health Sciences, Njala University, Bo, Sierra Leone.
Anddy OmoluabiPeltom Global Services, Abuja, Nigeria.
Adekunle AyinmodeCentre for Control and Prevention of Zoonoses, Faculty of Veterinary Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Daniel OluwayeluCentre for Control and Prevention of Zoonoses, Faculty of Veterinary Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Solomon OdemuyiwaCentre for Control and Prevention of Zoonoses, Faculty of Veterinary Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Oyewale TomoriAfrican Centre of Excellence for Genomics of Infectious Diseases, Redeemer's University, Ede, Osun State, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lassa fever (LF) is prevalent in many West African countries, including Nigeria. Efforts to combat LF have primarily focused on rural areas where interactions between rodents and humans are common. However, recent studies indicate a shift in its occurrence from rural to urban areas. We analysed secondary data of reported LF outbreaks from 2017 to 2021 in Ondo State, Nigeria to identify the distribution pattern, ecological variations, and other determinants of disease spread from the ward level using nearest neighbour statistics and regression analysis. Data utilised include LF incidence, ecological variables involving population, nighttime light intensity, vegetation, temperature, market presence, road length, and building area coverage. ArcGIS Pro 3.0 software was employed for spatial analysis. Results revealed spatio-temporal clustering of LF incidents between 2017 and 2021, with an increasing trend followed by a decline in 2021. All wards in Owo Local Government Area were identified as LF hotspots. The ecological variables exhibited significant correlations with the number of LF cases in the wards, except for maximum temperature. Notably, these variables varied significantly between wards with confirmed LF and those without. Therefore, it is important to prioritise strategies for mitigating LF outbreaks in urban areas of Nigeria and other LF-endemic countries.

Indexed as

Lassa FeverAfrica, WesternAnimalsDisease OutbreaksHumansIncidenceLassa virusNigeriaRodentia

Identifiers

PMID38012226
PMCPMC10682180

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Registered trials

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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.