Evidence map›Paper›PMID 37494329›Full record

ArticlePLoS neglected tropical diseases2023

Geostatistical analysis of active human cysticercosis: Results of a large-scale study in 60 villages in Burkina Faso.

Veronique Dermauw, Ellen Van De Vijver, Pierre Dorny, Emanuele Giorgi, Rasmané Ganaba, Athanase Millogo, Zékiba Tarnagda, Assana Kone Cissé, Hélène Carabin

Open access · goldAbstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

9 authors at 7 institutions in 5 countries.

Veronique DermauwDepartment of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.ORCID 0000-0001-8745-5304
Ellen Van De VijverDepartment of Environment, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
Pierre DornyDepartment of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.
Emanuele GiorgiCentre for Health Informatics, Computing, and Statistics, Lancaster University, Lancaster, United Kingdom.
Rasmané GanabaAFRICSanté, Bobo-Dioulasso, Burkina Faso.
Athanase MillogoCentre Hospitalier Universitaire Sourô Sanou, Bobo-Dioulasso, Burkina Faso.
Zékiba TarnagdaInstitut de Recherche en Sciences de la Santé, Bobo-Dioulasso, Burkina Faso.
Assana Kone CisséInstitut de Recherche en Sciences de la Santé, Bobo-Dioulasso, Burkina Faso.
Hélène CarabinDepartment of Pathology and Microbiology, University of Montreal, Montreal, Canada.
Institut de Recherche en Sciences de la Santé · BFInstituut voor Tropische Geneeskunde · BEAFRICSanté · BFGhent University · BELancaster University · GBUniversité Joseph Ki-Zerbo · BFUniversity of Oklahoma Health Sciences Center · US

Funding

EFECAB: Improving pig management to prevent epilepsy in Burkina FasoR01NS064901 · NINDS · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI CARABIN, HELENE · 2010 to 2014
$2.3M
NINDS NIH HHS R01 NS064901
6 · The paper itself

Abstract

Cysticercosis is a neglected tropical disease caused by the larval stage of the zoonotic tapeworm (Taenia solium). While there is a clear spatial component in the occurrence of the parasite, no geostatistical analysis of active human cysticercosis has been conducted yet, nor has such an analysis been conducted for Sub-Saharan Africa, albeit relevant for guiding prevention and control strategies. The goal of this study was to conduct a geostatistical analysis of active human cysticercosis, using data from the baseline cross-sectional component of a large-scale study in 60 villages in Burkina Faso. The outcome was the prevalence of active human cysticercosis (hCC), determined using the B158/B60 Ag-ELISA, while various environmental variables linked with the transmission and spread of the disease were explored as potential explanatory variables for the spatial distribution of T. solium. A generalized linear geostatistical model (GLGM) was run, and prediction maps were generated. Analyses were conducted using data generated at two levels: individual participant data and grouped village data. The best model was selected using a backward variable selection procedure and models were compared using likelihood ratio testing. The best individual-level GLGM included precipitation (increasing values were associated with an increased odds of positive test result), distance to the nearest river (decreased odds) and night land temperature (decreased odds) as predictors for active hCC, whereas the village-level GLGM only retained precipitation and distance to the nearest river. The range of spatial correlation was estimated at 45.0 [95%CI: 34.3; 57.8] meters and 28.2 [95%CI: 14.0; 56.2] km for the individual- and village-level datasets, respectively. Individual- and village-level GLGM unravelled large areas with active hCC predicted prevalence estimates of at least 4% in the south-east, the extreme south, and north-west of the study area, while patches of prevalence estimates below 2% were seen in the north and west. More research designed to analyse the spatial characteristics of hCC is needed with sampling strategies ensuring appropriate characterisation of spatial variability, and incorporating the uncertainty linked to the measurement of outcome and environmental variables in the geostatistical analysis. Trial registration: ClinicalTrials.gov; NCT0309339.

Indexed as

CysticercosisSwine DiseasesTaenia soliumAnimalsBurkina FasoCross-Sectional StudiesHumansPrevalenceSwine

Identifiers

PMID37494329
PMCPMC10370738
OpenAlexW4385284819

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.