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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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Published on: December 7, 2021

Genomic Epidemiology for Estimating Pathogen Burden in a Population.

W Tanner Porter, David M Engelthaler, Crystal M Hepp

Emerging Infectious Diseases

|May 13, 2025

Summary

Genomic surveillance enhances pathogen intelligence for outbreak response. Pathogen genomics allows accurate burden estimation, even with limited data, improving public health insights.

Keywords:

COVID-19 SARS-CoV-2 genomic epidemiology pathogen burden pathogen intelligence respiratory infections viruses

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Area of Science:

Microbiology
Epidemiology
Genomics

Background:

Genomics plays a crucial role in modern outbreak response and pathogen surveillance.
The field has advanced into the era of pathogen intelligence, utilizing genomic data for public health.
Traditional methods for estimating pathogen burden often relied on unreliable data.

Purpose of the Study:

To highlight the expanded role of genomics in pathogen surveillance and outbreak response.
To introduce the concept and utility of pathogen intelligence.
To demonstrate how pathogen genomics can improve the estimation of pathogen burden.

Main Methods:

Leveraging genomic surveillance for the detection and monitoring of pathogens.
Analyzing genomic diversity to estimate pathogen burden in populations and environments.
Utilizing sequencing of a small percentage of cases for burden estimation.

Main Results:

Genomic surveillance enables the detection of novel pathogens, case clusters, and key markers (virulence, antimicrobial resistance, immune escape).
Pathogen genomic diversity can be used to estimate total pathogen burden, overcoming limitations of previous data.
Accurate pathogen burden estimation is achievable even when sequencing a small fraction of cases.

Conclusions:

Genomic surveillance is a powerful tool for real-time pathogen intelligence and outbreak management.
Pathogen genomics offers a more reliable method for estimating disease burden.
Multidisciplinary collaboration is essential for advanced genomic epidemiology and actionable intelligence.