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Steps in Outbreak Investigation

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Related Experiment Video

Updated: Jul 2, 2025

Author Spotlight: Microbial Control and Monitoring Strategies for Cleanroom Environments and Cellular Therapies

Author Spotlight: Microbial Control and Monitoring Strategies for Cleanroom Environments and Cellular Therapies

Published on: March 17, 2023

Optimal environmental testing frequency for outbreak surveillance.

Jason W Olejarz¹, Kirstin I Oliveira Roster¹, Stephen M Kissler²

¹Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA; Center for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.

|February 23, 2024

Summary

This summary is machine-generated.

Optimizing public health surveillance balances pathogen detection with costs. This study models pathogen spread to find the most cost-effective sampling frequency, minimizing disease and surveillance expenses.

Keywords:

Early pathogen detection Environmental surveillance Mathematical modeling Vector trapping Wastewater sampling

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Area of Science:

Epidemiology
Mathematical Modeling
Public Health

Background:

Public health surveillance aims to detect epidemiological shifts like pathogen introductions or prevalence increases.
Surveillance must be balanced against its own costs to avoid outweighing disease-associated expenses.

Purpose of the Study:

To determine the optimal sampling frequency for pathogen surveillance.
To minimize the combined costs of disease burden and surveillance efforts.

Main Methods:

Developed a general mathematical model for exponential pathogen prevalence increase post-introduction.
Derived equations for expected combined cost per unit time based on sampling frequency.
Calculated the sampling frequency yielding the lowest expected total cost per unit time.

Main Results:

Identified a method to calculate optimal surveillance sampling frequency.
Quantified the trade-off between surveillance costs and disease burden.
Provided a framework for cost-effective pathogen detection.

Conclusions:

Optimal sampling frequency minimizes the total economic burden of disease and surveillance.
Mathematical modeling provides a robust approach to optimizing public health surveillance strategies.
Balancing detection sensitivity with resource allocation is crucial for effective pathogen monitoring.