Table 1.
Coefficients for the linear association between the mean and standard deviation in prevalence of STH infection within districts.
These parameters are meant to represent geographical variation in STH prevalence at the level of implementation units.
Fig 1.
Flowchart describing the different steps of the simulation approach.
First, each of the two models was used to generate a databank of simulations (step 1). Each simulation with a (closed) population size of about 500 individuals can realistically represent transmission within a village. In step 2, implementation units are simulated sampling villages according to a predefined prevalence distribution according to Eq (1). The models are then used to simulate the impact of 4 different PC strategies on prevalence and intensity of infection (step 3). In step 4 (post-control) we consider 4 different sampling strategies and in step 5 we analyse the results by district, PC and sampling strategy.
Fig 2.
Box-plots of model-predicted prevalences of infection among school-age children (SAC) at the district level before and after school-based PC.
Prevalence is measured in all SAC living in each district at two time points: at baseline (2015) and after 5 years of PC (2020). Every randomly generated district has mean baseline prevalence between 20 and 40% (0.01 increments). School-based PC is assumed to cover children of age 2–15 (preSAC and SAC) at 75% and community-based PC is assumed to cover the entire population of age >2 at 75% (allowing for random variation in coverage between individual villages within the district). S1 Fig holds similar plots for results stratified by mean baseline prevalence in districts (20–30% and 30–40%).
Fig 3.
Model-predicted distribution of prevalence of STH infection at the district level in SAC in 2020.
The stacked histogram is used to distinguish between districts that have met the morbidity target in 2020 (turquoise) and those that have not (red). Meeting the morbidity target refers to reaching <1% moderate-to-heavy infections in SAC. The dashed line at 1% represents the recommended prevalence threshold of any infection among SAC required to stop PC. The numbers in grey in each panel represent the overall probability of meeting the target (i.e. the proportion in turquoise). Prevalence is assumed to be measured in all SAC living in each randomly generated district with mean baseline prevalence ranging from 20 to 40%. Only school-based PC are shown as community-based PC always resulted in meeting the morbidity target. S2 Fig provides additional plots stratified by the average pre-control prevalence in a district (20%-30% vs. 30%-40%).
Table 2.
Model-based misclassification probabilities for PC allocation at district level after 5 years of PC.
For each sampling strategy (2 villages, 25%SAC vs 50 villages, 100% SAC) the probability of scaling down or stopping PC is reported against the treatment strategy that is required (based on the true prevalence at district level). The first line represents the probability as assessed by repeated runs using Erasmus MC model and the second row using ICL model.
Fig 4.
Positive predictive value of prevalence of STH infection (any intensity) in SAC in sentinel villages for meeting the morbidity target in 2020 at the district level.
The y-axis represents the probability that the morbidity target is met in 2020 (prevalence of moderate-to-heavy infections in SAC <1% in the district). The x-axis represents the threshold value for prevalence of any infection in SAC in sentinel villages, as measured with a single-slide Kato-Katz. Line colours indicate results stratified by mean district baseline prevalence of infection in SAC. The line type indicates different sampling strategies but with the same total number of SAC tested. Only school-based annual PC is shown as more intensive PC always resulted in meeting the morbidity target.
Fig 5.
Impact of number of sampled sentinel villages on predictive value of prevalence of any infection in SAC for meeting the morbidity target in 2020 at the district level.
The y-axis represents the probability that the morbidity target is met in 2020 (prevalence of moderate-to-heavy infections in SAC <1%, averaged over all villages in the district). The x-axis represents the threshold value for prevalence of any infection in SAC in sentinel villages, as measured with a single-slide Kato-Katz. Line colours indicate results stratified by mean district baseline prevalence of infection in SAC. The line type indicates different number of villages sampled maintaining the same proportion of SAC (100%). Only school-based annual PC is shown as more intensive PC always resulted in meeting the morbidity target.