Disaster Epidemiology and Emergency Surveillance Training Course

Participants can design the core architecture of an emergency surveillance system.

• Surveillance system components: sources, collection, analysis, dissemination and response
• Indicator-based surveillance compared with event-based surveillance approaches
• Passive, active, sentinel and community-based surveillance system choices
• Select surveillance objectives using priority risks and operational decisions
• Reporting chains from community informants to incident management teams
• Data flow diagrams identifying handovers, delays and accountability points

Participants can plan and interpret a rapid health assessment for an affected population.

• Rapid health assessment objectives during the first 72 hours
• Secondary data review using census, facility, hazard and displacement records
• SMART sampling principles for population-based emergency assessments
• Key informant interviews structured around health risks and service disruption
• Facility assessments covering staffing, supplies, functionality and referral capacity
• Prioritisation matrices combining severity, scale, trend and response capacity

Participants can calculate and interpret measures used in emergency health surveillance.

• Population estimation methods for camps, host communities and mobile populations
• Person-time, population-at-risk and denominator selection for emergency rates
• Calculate cumulative incidence, incidence rate, prevalence and attack rate
• Crude mortality rate and under-five mortality rate calculations
• Proportional morbidity tables for identifying dominant reported conditions
• Interpret denominators affected by displacement, access barriers and registration gaps

Participants can create standard case definitions and practical reporting instruments.

• Standard case definition components: clinical criteria, laboratory criteria and epidemiological links
• Suspected, probable and confirmed case classifications for emergency reporting
• Create syndrome definitions where laboratory confirmation is unavailable
• Line-list design for person, place, time and outcome variables
• Weekly aggregate reporting forms for priority conditions and deaths
• Data dictionaries specifying variables, codes, validation rules and ownership

Participants can select and monitor priority diseases based on emergency risk profiles.

• Prioritise epidemic-prone diseases using transmission, severity and control feasibility
• Cholera surveillance indicators: acute watery diarrhoea, dehydration and deaths
• Measles surveillance using fever, rash and immunisation status
• Acute jaundice syndrome reporting for hepatitis outbreak detection
• Malaria, dengue and vector-borne disease surveillance after disasters
• Vaccine-preventable disease indicators linked to immunisation response planning

Participants can apply EWARN and IDSR principles to emergency disease reporting.

• WHO EWARN objectives, minimum datasets and reporting frequency
• IDSR functions for detection, reporting, analysis, investigation and feedback
• Zero reporting procedures for high-priority epidemic-prone conditions
• Immediate notification criteria for unusual public health events
• Alert lists and weekly reporting schedules for participating facilities
• Feedback bulletins that improve reporting completeness and clinical recognition

Participants can establish event-based reporting channels and verification procedures.

• Event-based surveillance signals from rumours, media, hotlines and community reports
• Community-based surveillance roles for volunteers, leaders and health workers
• Signal triage using relevance, credibility, urgency and potential impact
• Rumour logs recording source, event, location, verification and disposition
• Verification interviews that protect confidentiality and avoid harmful speculation
• Escalation criteria for clusters, deaths, exposures and unusual syndromes

Participants can assess surveillance data quality and manage sensitive information responsibly.

• Completeness, timeliness, accuracy, consistency and representativeness quality dimensions
• Routine data quality assessment using source-document verification and recounts
• Duplicate detection using identifiers, dates, locations and clinical variables
• Missing-data analysis distinguishing reporting failure from true zero counts
• Confidentiality controls for line lists, case investigation forms and reports
• Data access rules, retention schedules and secure file transfer procedures

Participants can analyse emergency surveillance data by person, place and time.

• Person analysis using age, sex, occupation, displacement and risk factors
• Place analysis through facility catchments, settlements, camps and administrative areas
• Time analysis using daily counts, weekly trends and epidemic curves
• Construct epidemic curves by date of onset and reporting date
• Spot maps identifying geographic clustering, access barriers and exposure patterns
• Rate comparisons using appropriate denominators and population subgroups

Participants can establish alert thresholds and interpret signals requiring action.

• Alert thresholds based on absolute counts, rates and expected baselines
• Cumulative sum methods for detecting departures from historical patterns
• Moving averages and seasonal baselines for routine surveillance comparison
• Interpret threshold breaches alongside reporting completeness and case definition changes
• Alert verification decisions considering severity, transmissibility and population vulnerability
• Document alert status from signal receipt through closure

Participants can organise an outbreak investigation while maintaining response operations.

• Outbreak investigation steps adapted for insecure and resource-limited settings
• Verify diagnosis, confirm outbreak existence and establish case definitions
• Develop descriptive hypotheses from person, place and time patterns
• Analytical study choices: cohort studies, case-control studies and environmental sampling
• Calculate risk ratios, odds ratios and attributable risk
• Control measures initiated before investigation completion when risks are severe

Participants can monitor mortality, service disruption and health-system performance during emergencies.

• Mortality surveillance sources: facilities, burial sites, communities and registration systems
• Verbal autopsy principles for deaths outside health facilities
• Excess mortality estimation against pre-emergency mortality baselines
• Health facility utilisation indicators: consultations, admissions, referrals and bed occupancy
• Service availability monitoring for essential medicines, staff and electricity
• Interpret declining attendance alongside access constraints and population movement

Participants can integrate laboratory, environmental and clinical information for response decisions.

• Specimen referral pathways from peripheral sites to reference laboratories
• Laboratory turnaround times and their effect on case classification
• Environmental sampling for water quality, vectors and contamination hazards
• Chain-of-custody records for specimens and environmental samples
• Link laboratory results with line lists and outbreak databases
• Interpret negative tests considering sample timing, quality and test sensitivity

Participants can assess public health risks and recommend proportionate response actions.

• WHO risk assessment dimensions: hazard, exposure, vulnerability and capacity
• Risk matrices ranking likelihood, impact, uncertainty and urgency
• Scenario planning for disease spread, displacement and service interruption
• Identify populations requiring targeted surveillance and protective measures
• Response triggers linking risk levels to predefined operational actions
• Document assumptions, evidence gaps and confidence in risk judgements

Participants can prepare decision-focused surveillance products for emergency coordination structures.

• Situation report structure: key findings, actions, gaps and priorities
• Select tables showing cases, deaths, rates and reporting completeness
• Design epidemic curves with clear scales, labels and annotation
• Maps communicating affected locations, service gaps and response coverage
• Interpret findings without overstating causality or data certainty
• Recommendation writing tied to evidence, responsibility and response timelines

Participants can coordinate surveillance partners and communicate findings ethically during emergencies.

• Health cluster information roles, reporting agreements and partner coordination
• Incident action plans connecting surveillance findings to operational objectives
• Risk communication principles: timeliness, transparency, empathy and uncertainty
• Community feedback mechanisms for rumours, concerns and protective behaviours
• Ethical surveillance principles: necessity, proportionality, privacy and non-discrimination
• Cross-border reporting responsibilities under International Health Regulations

Participants can develop preparedness measures that enable rapid surveillance activation.

• Surveillance readiness assessments covering people, tools, systems and partnerships
• Pre-approved case definitions, forms and reporting channel arrangements
• Training plans for facility staff, community informants and supervisors
• Stock lists for registers, communication devices and specimen materials
• Simulation objectives testing alerts, escalation, reporting and decision-making
• After-action review methods converting response lessons into improvement actions

Participants can build, review and present a complete emergency surveillance plan for a defined disaster scenario.

• Define scenario-specific surveillance objectives, populations, risks and decision users
• Specify priority conditions, case definitions, indicators and reporting frequency
• Map reporting pathways, data responsibilities, quality checks and escalation points
• Set alert thresholds, verification procedures and outbreak investigation triggers
• Prepare situation report outputs, visualisations and recommendation formats
• Review plan feasibility against staffing, communications, security and laboratory constraints