TY - JOUR
T1 - Geostatistical analysis of active human cysticercosis: results of a large-scale study in 60 villages in Burkina Faso
AU - Dermauw, Veronique
AU - Van De Vijver, Ellen
AU - Dorny, Pierre
AU - Giorgi, Emanuele
AU - Ganaba, Rasmané
AU - Millogo, Athanase
AU - Tarnagda, Zékiba
AU - Cissé, Assana Kone
AU - Carabin, Hélène
N1 - FTX; DOAJ; (CC BY 4.0); Copyright: © 2023 Dermauw et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Animals
KW - Humans
KW - Swine
KW - Burkina Faso/epidemiology
KW - Cross-Sectional Studies
KW - Cysticercosis/parasitology
KW - Taenia solium
KW - Prevalence
KW - Swine Diseases/parasitology
U2 - 10.1371/journal.pntd.0011437
DO - 10.1371/journal.pntd.0011437
M3 - A1: Web of Science-article
C2 - 37494329
SN - 1935-2727
VL - 17
JO - PLoS Neglected Tropical Diseases
JF - PLoS Neglected Tropical Diseases
IS - 7
M1 - e0011437
ER -