Evidence map›Paper›PMID 35712128›Full record

ArticleParasite epidemiology and control2022

Models for predicting bulinids species habitats in southwestern Nigeria.

Opeyemi G Oso, Joseph O Sunday, Alex B Odaibo

Abstract read
In one paragraph

Article in Parasite epidemiology and control, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Opeyemi G OsoParasitology Research Unit, Department of Zoology, University of Ibadan, Ibadan, Nigeria.
Joseph O SundayDepartment of Zoology, Kwara State University, Malete, Nigeria.
Alex B OdaiboParasitology Research Unit, Department of Zoology, University of Ibadan, Ibadan, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Schistosomiasis prevalence is high in southwestern Nigeria and planorbids of the genus Methods: Satellite imagery and geographic information system (GIS) were used to develop models for predicting the habitats suitable for bulinid species. Monthly snail sample collection was done in twenty-three randomly selected water contact sites using the standard method for a period of two years. Remotely sensed variables such as Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) were extracted from Landsat TM, ETM Results: The following environmental variables: flat-moderate slope (0.01-15.83), LST (21.1 °C-23.4 °C), NDVI (0.19-0.52), rainfall (> 1569.34 mm) and elevation (1-278 m) contributed to the model used in predicting habitat suitable for bulinids snail intermediate hosts. Exploratory regression models showed that LST, NDVI and slope were predictors of Conclusion: The predictive risk models of bulinid species in this study provided a robust output for the study area which could be used as base-line for other areas in that ecological zone. It will be useful in appropriate allocation of scarces resources in the control of schistosomiasis in that environment.

Indexed as

Bulinid speciesGIS/RSNigeriaSchistosomiasis

Identifiers

PMID35712128
PMCPMC9194844

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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.