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Related Experiment Video

Updated: Feb 27, 2026

Determining Soil-transmitted Helminth Infection Status and Physical Fitness of School-aged Children
10:57

Determining Soil-transmitted Helminth Infection Status and Physical Fitness of School-aged Children

Published on: August 22, 2012

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Identifying optimal threshold statistics for elimination of hookworm using a stochastic simulation model.

James E Truscott1,2, Marleen Werkman3,4, James E Wright3,4

  • 1London Centre for Neglected Tropical Disease Research (LCNTDR), Department of Infectious Disease Epidemiology, St. Mary's Campus, Imperial College London, W2 1PG, London, UK. j.truscott@imperial.ac.uk.

Parasites & Vectors
|July 2, 2017
PubMed
Summary

Mathematical models help determine if mass drug administration (MDA) can eliminate soil-transmitted helminths (STH). Optimal thresholds for elimination are crucial, especially considering cluster size and baseline prevalence for effective public health strategies.

Keywords:
Cluster randomized trialsElimination of transmissionMass drug administrationPositive/Negative predictive valueSoil-transmitted helminthsStochastic models

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Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Public Health Interventions

Background:

  • Mass drug administration (MDA) programs are increasingly evaluated for their sole effectiveness in interrupting soil-transmitted helminths (STH) transmission.
  • Mathematical modeling aids in predicting intervention outcomes and optimizing study designs for STH elimination.
  • Establishing reliable thresholds for detecting transmission interruption is critical but currently lacking for STH.

Purpose of the Study:

  • To develop and utilize a simulation of an elimination study to analyze the relationship between study endpoint elimination thresholds and long-term elimination.
  • To assess the positive predictive values (PPV) of various statistics under different covariates, including threshold values, baseline prevalence, measurement time, and cluster construction.
  • To inform the design of STH elimination studies and MDA programs by identifying key sensitivities.

Main Methods:

  • An individual-based stochastic disease transmission model was developed, incorporating MDA, sampling, diagnostics, and cluster construction, based on the DeWorm3 project.
  • Simulations were used to analyze the correlation between elimination thresholds and sustained elimination within the model.
  • The predictive power of different statistics was evaluated based on covariates such as threshold values, baseline prevalence, and cluster design.

Main Results:

  • End-point infection prevalence effectively distinguishes between villages with and without transmission interruption, though threshold sensitivity to baseline prevalence and value was noted.
  • An optimal post-treatment prevalence threshold of 2% or less is suggested for broad baseline prevalence ranges.
  • Cluster size and community distribution significantly impact elimination probability and threshold detection; larger clusters and more communities per cluster enhance elimination probability and PPV.
  • Extending the post-study measurement time improves the PPV for discriminating between eliminating and rebounding clusters.

Conclusions:

  • Elimination probability and PPV are highly sensitive to baseline prevalence at the individual community level.
  • Cluster construction introduces significant sensitivities to elimination threshold values, influenced by cluster size and population structure.
  • Study simulations are valuable for proactively investigating sensitivities in elimination studies and program designs, enabling tailored interventions.