Genomic Epidemiology & Infectious Disease Surveillance Training Workshop/Seminar

Course overview

The Genomic Epidemiology & Infectious Disease Surveillance Training Workshop equips public health professionals, epidemiologists, laboratory scientists, microbiologists, bioinformatics practitioners and disease surveillance officers with the knowledge and practical skills to understand how pathogen genomic data can strengthen infectious disease surveillance, outbreak investigation and public health response. The training explores the integration of pathogen sequencing results with epidemiological, clinical, laboratory and geographical information to investigate disease transmission, identify pathogen variants, monitor genetic changes and understand relationships between infectious disease cases.

The Genomic Epidemiology & Infectious Disease Surveillance Training Workshop develops practical knowledge of pathogen genomics, genomic surveillance workflows, genetic variation, phylogenetic analysis and molecular outbreak investigation. Designed for epidemiologists, laboratory scientists, microbiologists, bioinformatics practitioners and public health researchers, the training focuses on integrating genomic and epidemiological evidence to investigate outbreaks, monitor pathogen evolution, assess antimicrobial resistance and strengthen infectious disease surveillance.

Course objectives

• Explain the principles and applications of genomic epidemiology in public health.
• Prepare a genomic epidemiology summary to support public health decision-making
• Apply appropriate principles for genomic data management, privacy and responsible reporting.
• Evaluate the limitations of genomic data when inferring transmission events and outbreak origins.
• Explain how genomic surveillance supports variant monitoring and antimicrobial resistance surveillance.
• Apply genomic evidence to outbreak investigation and pathogen transmission assessment.
• Integrate genomic findings with epidemiological and laboratory surveillance data.
• Interpret genetic similarity, phylogenetic trees and genomic clusters.
• Assess basic sequence quality indicators and understand common genomic data quality challenges.
• Explain the role of whole-genome sequencing and other molecular approaches in infectious disease surveillance.
• Interpret basic concepts in pathogen genomes, mutations, genetic variation and sequence comparisons.
• Describe the major stages of pathogen genomic surveillance, from sample collection to reporting.

Who should attend

Course content

• Module 1: Foundations of Genomic Epidemiology Definition and scope of genomic epidemiology, pathogen genomics in public health, molecular epidemiology versus conventional epidemiology, major pathogen groups, applications in outbreak investigation, infecti
• Module 2: Pathogen Genomes and Genetic Variation Basic genome structure of viruses, bacteria and parasites, DNA and RNA genomes, genes and genetic markers, mutations and genetic variation, single-nucleotide variants, insertions and deletions, genetic dive
• Module 3: Genomic Surveillance Systems and Workflows Objectives of genomic surveillance, surveillance sampling strategies, specimen collection and transport, laboratory processing, sequencing workflows, sequence data generation, quality assurance, metadat
• Module 4: Molecular Diagnostics and Sequencing Technologies Principles of polymerase chain reaction (PCR), targeted sequencing, whole-genome sequencing, short-read and long-read sequencing concepts, sequencing platforms and their applications, sequencing
• Module 5: Genomic Data Formats and Quality Assessment Raw sequencing reads, FASTQ and FASTA formats, reference genomes, sequence alignment files, consensus sequences, metadata standards, read quality indicators, coverage and completeness, contamination as
• Module 6: Sequence Alignment and Comparative Genomics Reference-based and reference-free approaches, sequence alignment concepts, genome comparison, identifying genetic differences, variant calling principles, consensus sequence generation, alignment qual
• Module 7: Phylogenetics and Evolutionary Analysis Principles of phylogenetic analysis, evolutionary relationships, phylogenetic trees and branches, genetic distance, sequence divergence, tree rooting and interpretation, molecular clock concepts, evolution
• Module 8: Genomic Clustering and Outbreak Investigation Genomic cluster identification, genetic distance thresholds and their limitations, integrating sequence and case investigation data, identifying related pathogen samples, evaluating possible outbreak
• Module 9: Integration of Genomic and Epidemiological Data Linking genomic sequences to case records, combining laboratory and clinical information, patient and specimen metadata, time and location comparisons, line-list integration, contact tracing inform
• Module 10: Genomic Surveillance of Emerging Pathogens and Variants Monitoring genetic changes, variant classification concepts, lineage identification, genomic diversity, variant emergence and spread, interpreting changes in pathogen populations, linking
• Module 11: Genomic Epidemiology of Antimicrobial Resistance Genetic mechanisms of antimicrobial resistance, resistance-associated mutations, resistance genes, genomic surveillance of resistant organisms, bacterial strain typing, transmission of resistant
• Module 12: Pathogen-Specific Genomic Surveillance Applications Viral genomic surveillance, genomic epidemiology of tuberculosis, genomic surveillance of malaria parasites, foodborne bacterial pathogen tracking, healthcare-associated infections, zoonotic a
• Module 13: Genomic Data Management, Ethics and Governance Genomic data storage and organization, metadata standards, secure data sharing, personal and population privacy, informed consent considerations, access controls, data ownership and governance, res
• Module 14: Genomic Surveillance Reporting and Public Health Decision-Making Interpreting genomic surveillance summaries, reporting sequence quality and coverage, presenting phylogenetic findings, communicating genomic clusters, integrating laboratory and
• Module 15: Practical Genomic Epidemiology Capstone Project Reviewing a sample genomic surveillance dataset, assessing sequence quality summaries, comparing pathogen sequences, interpreting genetic variation, reading a phylogenetic tree, examining potentia

General notes

• Training Methodology The workshop combines expert-led presentations, genomic epidemiology case studies, laboratory workflow demonstrations, guided analysis of sample genomic datasets, phylogenetic tree interpretation, group exercises, integrated surveillance scenarios and a capstone project. Participants work with sample or appropriately anonymized genomic and epidemiological data. Practical activities can be adjusted to the participants’ backgrounds and available infrastructure, ranging from interpretation of pre-generated sequencing results to introductory computational analysis. Wet-laboratory sequencing is not assumed unless specifically included in the training arrangement.
• Recommended Software and Tools Python, R, Excel, SQL, Power BI, QGIS, Jupyter Notebook, SPSS, Stata, DHIS2, Epi Info, WHO disease surveillance resources, enterprise AI tools.
• Practical Exercises and Expected Outputs Review pathogen genomic surveillance records — genomic data inventory, interpret sequencing quality reports — sequence quality assessment summary, compare sample sequences — genetic variation summary, examine a sample alignment — sequence comparison report, interpret a phylogenetic tree — evolutionary relationship summary, assess potential genomic clusters — cluster interpretation worksheet, link genomic records with epidemiological line lists — integrated surveillance dataset, compare genomic and contact tracing evidence — outbreak linkage assessment, review a pathogen variant surveillance report — variant monitoring summary, interpret a sample antimicrobial resistance report — resistance surveillance interpretation, develop a genomic surveillance workflow — workflow diagram, prepare a genomic data governance checklist — data management and privacy checklist, complete the capstone project — genomic epidemiology report with limitations and public health recommendations.
• Expected Learning Outcomes Participants will understand how genomic data complement conventional epidemiology, how pathogen genetic variation is interpreted, and how sequence relationships can contribute to outbreak investigation and surveillance. They will develop skills in interpreting sequence quality reports, understanding phylogenetic relationships, evaluating potential genomic clusters, integrating genomic and epidemiological information, and communicating findings with appropriate attention to uncertainty and limitations. Participants will also gain a practical understanding of genomic surveillance workflows, data governance requirements and the role of genomic evidence in monitoring pathogen evolution and antimicrobial resistance.

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Schedule & fees