TY - JOUR AB - BackgroundThere is an increased focus on whether mass drug administration (MDA) programmes alone can interrupt the transmission of soil-transmitted helminths (STH). Mathematical models can be used to model these interventions and are increasingly being implemented to inform investigators about expected trial outcome and the choice of optimum study design. One key factor is the choice of threshold for detecting elimination. However, there are currently no thresholds defined for STH regarding breaking transmission.MethodsWe develop a simulation of an elimination study, based on the DeWorm3 project, using an individual-based stochastic disease transmission model in conjunction with models of MDA, sampling, diagnostics and the construction of study clusters. The simulation is then used to analyse the relationship between the study end-point elimination threshold and whether elimination is achieved in the long term within the model. We analyse the quality of a range of statistics in terms of the positive predictive values (PPV) and how they depend on a range of covariates, including threshold values, baseline prevalence, measurement time point and how clusters are constructed.ResultsEnd-point infection prevalence performs well in discriminating between villages that achieve interruption of transmission and those that do not, although the quality of the threshold is sensitive to baseline prevalence and threshold value. Optimal post-treatment prevalence threshold value for determining elimination is in the range 2% or less when the baseline prevalence range is broad. For multiple clusters of communities, both the probability of elimination and the ability of thresholds to detect it are strongly dependent on the size of the cluster and the size distribution of the constituent communities. Number of communities in a cluster is a key indicator of probability of elimination and PPV. Extending the time, post-study endpoint, at which the threshold statistic is measured improves AU - Truscott,JE AU - Werkman,M AU - Wright,JE AU - Farrell,SH AU - Sarkar,R AU - Ásbjörnsdóttir,K AU - Anderson,RM DO - 10.1186/s13071-017-2256-8 PY - 2017/// SN - 1756-3305 TI - Identifying optimal threshold statistics for elimination of hookworm using a stochastic simulation model T2 - Parasites & Vectors UR - http://dx.doi.org/10.1186/s13071-017-2256-8 UR - http://hdl.handle.net/10044/1/49828 VL - 10 ER -