Table 1.
Literature review of absolute density estimates of the snail intermediate host species of schitosomiasis in sub-Saharan Africa.
Studies are subdivided by sampling method. Details are given for the size of the habitat for exhaustive sampling and quadrat size and number of replicates per sample (in parentheses) for quadrat sampling. Standard errors of the mean where computed from the reported confidence intervals assuming they were given for the 95% interval.
Fig 1.
Situation map of field sites and habitats.
a. Burkina Faso with its capital (Ouagadougou) and the location of the two field sites (in red) along the precipitation gradient (2014-2017 average, CHIRPS data [51]). The map was produced with QGIS (version 3.6) with country boundaries provided by GADM (version 3.4). Sampled habitats in Lioulgou included an ephemeral pond (b) and a river (c), and a permanent stream in Panamasso (d).
Table 2.
Equations are given for the alternatives of transfer function, measurement model and zero-occurrence parameter. All combinations of the three components were tested. The number of free parameters in each equation is denoted n.
Fig 2.
Quadrat sampling scheme performance.
Reported are the distribution of standard errors (), relative standard errors (SE/μ [-]), the index of dispersion (ID = σ2/μ [-]) and the mean density (μ [snails/m2]) by habitat and intermediate host species.
Fig 3.
Ecological monitoring data of intermediate hosts of schistosomiasis in Burkina Faso.
Data was collected in three different habitats in two distinct sites, one in the Sudano-Sahelian climatic zone (pond and river, village of Lioulgou), and one in the Sudanian climatic zone (stream, village of Panamasso). Data are presented in terms of the number of observed counts (grey points) by intermediate host genera for the quadrat (top row) and time-based method (bottom row) protocols with blue rectangles indicating timing of the rainy season (July-September). Monthly means (red points) for the quadrat method consist of the average of the 8 quadrat replicates on the sampling date, and the mean of the weekly time-based counts grouped to the closest month start, along with their 95% CI (red errorbars, mean ±1.96 SE). Note that quadrat data in the months of June-October of 2016 were not collected in the permanent stream in Panamasso due to logistical constraints.
Fig 4.
Comparison of monthly mean densities from the quadrat and time-based sampling schemes.
Horizontal and vertical errorbars give the 95% CI of the time-based and quadrat-based means respectively.
Table 3.
Model structure probabilities.
The probability that each model lies within the 95% confidence set were computed by summing AIC weights for the functional form of the transfer function and for zero-inflation in the measurement model. The probability of constant vs. logistic zero-inflation parameter was computed using the ratio of their respective AIC weights to their sum.
Fig 5.
Model simulations of the relations between time-based and quadrat sampling strategies.
Simulations were performed using the 95% credible model set (S1 Table) for each species-habitat configuration. Simulations are shown in terms of the mean (black line) as well as the 95% (light gray ribbon) and 50% (dark gray ribbon) simulation envelops for 5000 simulations per time-based count. Quadrat counts (gray dots) are given as in the first row of Fig 3 along with monthly means (red dots).