arrow_backEmergency WASH

T.17 Health Surveillance Data

Health Surveillance is the continuous and systematic collection, analysis and interpretation of health data. Local and national morbidity, mortality and other epidemiological data on WASH-related diseases will help to inform and guide water, sanitation and hygiene promotion priorities.

Epidemiological data collection systems are useful for all sectors in all emergencies. Such systems should be initiated if absent, or existing ones supported and continuously improved. Surveillance data acts as an early warning system for disease outbreaks and can indicate if the overall response is having the desired effect. These systems are usually managed and collated by the health service or health sector, but data collected by other sectors (e.g. studies on behaviour or nutritional status) can help to interpret the surveillance data. As with all data, the analysis and interpretation are essential; data must be used with care and disaggregated (by gender and age especially) where possible. WASH-related health data (e.g. the incidence of diarrhoea) cannot be used to measure the causal impact of WASH (as diarrhoea is affected by many factors as well as by WASH) but it should be considered when monitoring, prioritising and adapting WASH interventions. Sources of data include local health clinics and hospitals, national health surveillance systems and sometimes community health workers. Secondary data can also be obtained from previously conducted Demographic Health Surveys and Multiple Indicator Cluster Surveys and these are usually available from UNICEF.


Epidemiological data should be sought in all contexts but specific local data may be unavailable if health services are poorly resourced or disrupted. People may be unable to access health services and may not report illness or death – especially if there is a stigma about the disease such as cholera or Ebola. Community health workers often collect basic disease data and this can be useful if no other surveillance system exists. Numbers can be inflated or underestimated if case definitions are unclear and health workers poorly trained.


  • Regularly obtain surveillance data on WASH-related disease and death 

  • Attend inter-sectoral coordination meetings to get an overview and discuss surveillance data

  • Involve communities by discussing data with them, carrying out field studies and feeding back information


  • Do not use raw data or make assumptions based on limited data without analysis and interpretation 

  • Do not collect too much data – prioritise requirements early in the response

  • Do not use only one data point or source

Practical Example

In Haiti the data on cholera incidence was stratified by department and age, but not by gender. A rapid assessment of mortality from cholera was conducted in Artibonite Department where the largest number of cholera cases was reported. The assessment identified that 67% of cases were male and 9.2% were female aged 5-18 years, challenging the assumption that adult women were the most affected. The cholera strategy was then changed to focus more on men.

Key Decision Critria

Response Phase
Acute Response
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Protracted Crisis
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HP Component
Preconditions and Enabling Environment
Community Engagement and Participation
Assessment, Analysis and Planning
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Social and Behaviour Change
Monitoring, Evaluation, Accountability and Learning (MEAL)
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Target Group
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Older People
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Persons with Disabilities
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Local Leaders
Society as a whole
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Application Level
Individual / Household
Community / Municipality
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General reference for all sectors covering the importance of using disaggregated data – including surveillance data in emergencies

Mazurana, D., Benelli, P. et al. (2011): Sex and Age Matter. Improving Humanitarian Response in Emergencies, Feinstein International Center, Tufts University

Health information systems

WHO (undated): Early Warning, Alert and Response Systems (EWARS)

WHO (undated): WHO Toolkit for Routine Health Information Systems Data

Data sources

DHS (undated): Demographic Health Surveys by Country

UNICEF (2019): Reports of Multi Indicator Cluster Surveys (MICS) by country

UN DESA (undated): World Population Prospects 2019. Online Edition Rev. 1