MOC - Public Health & Epidemiology

How infections behave in populations — surveillance, outbreak investigation, prevention, and the governance around them.

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Computational partners: MOC - Bioinformatics in Microbiology · MOC - AI in Microbiology

Overview

Clinical microbiology answers “what does this patient have?”; epidemiology answers “who else, where, why now, and how do we stop it?” Genomics has merged the two: the same isolate that guides therapy also becomes a surveillance data point.

flowchart LR
  Case[Case / isolate] --> Lab[Laboratory confirmation]
  Lab --> Seq[[Whole-Genome Sequencing]]
  Lab --> Notify[Notification / reporting]
  Seq --> Clust[[MLST and cgMLST]]
  Clust --> Inv[Outbreak investigation]
  Notify --> Signal[[AI for Outbreak Detection]]
  Signal --> Inv
  Inv --> Act[Control measures]
  Act --> Eval[Impact evaluation]

Key Subtopics

Measuring disease

  • Epidemiology — incidence, prevalence, R₀/Rt, study designs, outbreak investigation steps

Surveillance

Prevention and control

AMR at population scale

Data governance

Core Concepts

  • A cluster in time and space is a hypothesis; genomics tests it
  • Surveillance quality is limited by metadata, not sequencing
  • Interventions must be evaluated, not assumed
  • Prevention (vaccines, hygiene) usually outperforms treatment at population scale

Build Status

ClusterStatus
MOC scaffolddone
Genomic surveillance linksdone
Core notes: Epidemiology, Infection Prevention and Control, Vaccination, One Healthdone
Outbreak investigation worked example; food/water-borne disease notesbacklog