General simulation framework
infection, STH infections
INFECTION
For the current simulation study, we adapted the framework described by Coffeng and colleagues [Inter-individual variability in mean egg intensity due to variation in infection levels between individuals (assumed to follow a gamma distribution);Day-to-day variability in mean egg intensity within an individual due to heterogeneous egg excretion over time (assumed to follow a gamma distribution);Variability in egg counts between repeated aliquots of a stool sample due to the aggregated distribution of eggs in stool (assumed to follow a Poisson or a gamma-Poisson (i.e., negative binomial) distribution);Inter-individual variability in the effect of drug administration in terms of the ERR (assumed to follow a beta distribution).For the quantification of each gamma distribution, we followed the approach of Denwood et al [Using this framework, we simulated egg counts for all survey designs across four scenarios, each representing different population average baseline FECs. The selection of these scenarios was based on infection levels in the nationwide mapping of STH infections in Ethiopia [