WASH Information Management Training Course

Participants can apply recognised WASH service definitions when specifying data requirements and indicators.

• Sphere WASH standards used for emergency programme design
• JMP service ladders for drinking water, sanitation and hygiene
• WASH Cluster indicator definitions for coordinated response monitoring
• Water quantity, quality, accessibility and continuity measurement concepts
• Sanitation containment, emptying, transport, treatment and disposal chains
• Hygiene behaviour indicators distinguished from commodity distribution counts

Participants can translate operational decisions into a structured WASH information requirements matrix.

• Decision matrix linking users, questions, data sources and products
• Prioritising critical information requirements during rapid-onset emergencies
• Disaggregating requirements by sex, age, disability and location
• Defining geographic units, population groups and reporting periods
• Assumptions register for uncertain population and service estimates
• Data collection burden balanced against decision value and urgency

Participants can plan WASH assessments with appropriate methods, sampling logic and field protocols.

• Rapid assessment objectives, respondent groups and minimum datasets
• Household, facility, water-point and market assessment approaches
• Probability and purposive sampling matched to assessment decisions
• Sample size assumptions, confidence levels and margin of error
• Enumerator protocols for observation, interviewing and consent procedures
• Assessment plan covering timelines, teams, supervision and logistics

Participants can design structured digital WASH data-collection forms using KoboToolbox principles.

• KoboToolbox form structure using groups, repeats and relevance conditions
• Question wording that reduces ambiguity and respondent burden
• Skip logic for household, facility and water-point pathways
• Constraints, required fields and range checks preventing invalid entries
• Choice lists, cascading selections and controlled vocabulary design
• Metadata capture for enumerator, timestamp, GPS and device identifiers

Participants can establish a data structure and indicator documentation set for WASH monitoring.

• Relational tables for households, facilities, sites, activities and partners
• Unique identifiers preventing duplicate records across reporting cycles
• Indicator reference sheets defining numerator, denominator and disaggregation
• Baseline, target, actual and cumulative reporting value rules
• Data dictionary fields for variables, codes, formats and ownership
• Version control for forms, indicators and reporting templates

Participants can apply responsible data procedures to collect, store and share WASH information safely.

• Personal data identification within household and facility WASH records
• Data minimisation principles for assessments and routine monitoring
• Informed consent wording, voluntary participation and withdrawal procedures
• Role-based access controls for sensitive datasets and reports
• Data-sharing agreements defining purpose, recipients, restrictions and retention
• Disclosure risk review for maps, tables and public dashboards

Participants can inspect, clean and document WASH datasets before analysis and reporting.

• Completeness checks for required fields, records and reporting sites
• Range, logic and consistency checks across related questionnaire responses
• Duplicate detection using identifiers, dates, coordinates and household attributes
• Outlier review for water quantities, household sizes and service values
• Cleaning log documenting corrections, exclusions, assumptions and approvals
• Data quality assessment dimensions: accuracy, timeliness, completeness and validity

Participants can calculate and interpret WASH coverage, access and functionality indicators.

• Coverage calculations using verified populations and service denominators
• Water-point functionality rates separated by technology and management arrangement
• Litres per person per day estimated from source data
• Queue time, collection time and distance analysed for access barriers
• Sanitation access classified by facility type and shared use
• Equity analysis comparing service levels across population groups

Participants can organise and interpret water-quality and disease-risk information for WASH action.

• Water quality sampling records linked to source, date and location
• Free residual chlorine readings interpreted against operational monitoring plans
• Turbidity, pH and bacteriological results recorded with laboratory metadata
• Household water treatment and safe-storage monitoring indicators
• Cholera risk signals triangulated with water, sanitation and hygiene data
• Thresholds and alert rules for corrective action escalation

Participants can prepare WASH location data and produce maps that support operational decisions.

• Coordinate reference systems and GPS accuracy for field locations
• Administrative boundaries, settlement layers and population datasets
• Point mapping for water sources, latrines, facilities and distribution sites
• Service-area buffers showing access distances around water points
• Choropleth maps presenting coverage, functionality and assessment findings
• Map layout standards for titles, legends, sources, dates and scale

Participants can manage partner activity data using standardised reporting structures and validation rules.

• Who, What, Where, When and for Whom reporting fields
• Partner reporting templates aligned with agreed WASH activity definitions
• Activity coding for water supply, sanitation, hygiene and solid waste
• Partner data validation against locations, populations and reporting periods
• Gap and overlap analysis using partner presence and activity data
• HXL tags for interoperable humanitarian data exchange

Participants can design clear WASH dashboards that communicate operational status and priority actions.

• Dashboard audience analysis for managers, coordinators, donors and field teams
• Key performance indicators selected from approved indicator reference sheets
• Bar charts, line charts and maps matched to questions
• Disaggregation controls for location, population group, partner and period
• Traffic-light thresholds supported by documented decision rules
• Visual checks preventing misleading scales, labels and cumulative totals

Participants can prepare concise WASH information products for operational and external reporting.

• Situation report structure: needs, response, gaps, risks and actions
• Narrative claims supported by verified figures and cited sources
• Results tables distinguishing outputs, outcomes, targets and achievements
• Donor evidence packs linking activities, indicators, records and photographs
• Data limitations stated clearly without weakening operational recommendations
• Publication calendar coordinating internal, cluster and donor deadlines

Participants can establish a practical WASH information workflow under emergency response conditions.

• First 72-hour information priorities during sudden-onset WASH emergencies
• Rapid dataset triage for population, locations, infrastructure and partners
• Daily reporting cadence balancing speed, verification and staff capacity
• Incident information board for outbreaks, service failures and urgent repairs
• Contingency procedures for connectivity loss, damaged devices and access constraints
• Handover notes preserving data continuity during staff rotation

Participants can build, review and present a complete WASH information management package for a response scenario.

• Response scenario translated into decisions, users and information requirements
• Assessment form and indicator reference sheet assembled for priority services
• Dataset cleaning rules and quality-control workflow documented clearly
• Coverage analysis, partner gaps and priority locations presented visually
• Dashboard and situation report prepared for senior decision-makers
• Peer review against usability, data quality, protection and actionability criteria