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Infection

Infection

When a pathogen enters the body and reproduces, it can cause an infection, damage body cells, and cause illness symptoms that eventually lead to disease. Therefore, its prevention requires breaking the chain of infection.
The chain begins with pathogens: bacteria, viruses, fungi, prions, or parasites such as protozoa helminths. These can be present on the skin as transient or resident flora, or they can be acquired from the environment. Identifying and treating the type of infection and...

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Related Experiment Video

Updated: Nov 17, 2025

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

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

Published on: August 22, 2012

Stochastic challenges to interrupting helminth transmission.

Robert J Hardwick¹, Marleen Werkman¹, James E Truscott¹

¹London Centre for Neglected Tropical Disease Research (LCNTDR), Department of Infectious Disease Epidemiology, St. Mary's Campus, Imperial College London, London WC2 1PG, UK; The DeWorm3 Project, the Natural History Museum of London, London SW7 5BD, UK; MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, UK.

|February 11, 2021

Summary

Mathematical models help predict helminth infection control. This study compares deterministic and stochastic models, finding stochastic models better capture real-world transmission dynamics and migration impacts for soil-transmitted helminths (STH) control.

Keywords:

Control policies Mathematical models Monitoring and evaluation Soil-transmitted helminths Transmission breakpoints

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Area of Science:

Mathematical modeling
Parasitology
Epidemiology

Background:

Mathematical models are crucial for predicting helminth infection control outcomes.
Accounting for uncertainty is essential for robust predictions in disease modeling.
Deterministic models are standard, but their limitations in capturing stochastic variations are increasingly recognized.

Purpose of the Study:

To compare predictions from standard deterministic models with individual-based stochastic simulations for helminth transmission.
To investigate the applicability of deterministic concepts like 'breakpoints' in a stochastic context.
To explore the impact of human migration on disease transmission and control within a community.

Main Methods:

Developed and utilized an individual-based stochastic model framework.
Focused on soil-transmitted helminths (STH) control via mass drug administration (MDA).
Analyzed the influence of infected human migration on transmission dynamics.

Main Results:

Identified a 'stochastic breakpoint' where noise surrounds the deterministic breakpoint.
Highlighted limitations of deterministic models in predicting transmission 'fade-out' or extinction.
Established a relationship between migration rates and the effectiveness of chemotherapeutic control for transmission elimination.

Conclusions:

Stochastic models provide a more accurate representation of helminth transmission and control, especially considering migration.
The concept of 'interruption of transmission' is critical and distinct from 'breakpoints'.
A new open-source Python package for STH stochastic simulation has been developed, facilitating further research and application.