Surveillance in Humanitarian Emergencies

Methods of Data Collection

Assessment Survey Surveillance

Objective Rapid appraisalMedium-term appraisal

Continuous appraisal

Data TypeQualitative/

Cross sectional snapshot

Quantitative/

Cross sectional

snapshot

Quantitative/ Longitudinal trends

MethodObservational /

Secondary source

Sample with survey instrument

Periodic, standardized data collection

What factors make surveillance especially important, in emergency settings?

Why Is Surveillance Especially Important In Emergencies?

• Host– Morbidity and mortality are higher among malnourished

persons– New arrivals may have no natural immunity

• Organism– Crowding can mean higher infective dose– Displacement may result in exposure to new pathogens

• Environment– Lack of clean water and poor sanitation are favorable to

spreading disease– Poor access to care can increase case fatality ratios

What Diseases or Conditions Will You Conduct Surveillance For?

Types of Data Dollected in Surveillance Systems in Emergencies

• Mortality• Morbidity

– diseases of public health importance– diseases of epidemic potential

• Nutritional Status• Program Indicators• Indicators of the quality of the system

itself

Health Surveillance In Emergencies

One over-riding principle

ONLY COLLECT DATA WHICH AREONLY COLLECT DATA WHICH ARE

USEFUL AND CAN BE ACTED UPON USEFUL AND CAN BE ACTED UPON

IN THE FIELD!!!IN THE FIELD!!!

Who Conducts Surveillance in Emergencies?

• WHO has overall responsibility for surveillance

• UNHCR often manages surveillance in refugee camp situations

But

Implementing partners (usually NGOs) actually carry it out

Objectives Of A Surveillance System

• To determine main health problems requiring intervention

• To follow trends in health status in order to revise health priorities

• To target resources to area of greatest need • To detect and respond rapidly to epidemics• To evaluate program effectiveness

– Coverage– Quality of care – Impact

Principles Of Health Surveillance In Emergencies

• Include all facilities and health partners

• Use simple standardized case definitions

• Use a simple standardized data collection form

• Collect data regularly (daily, weekly, or monthly)

• If possible, augment clinic-based surveillance with community-based surveillance

• Analyze data and provide timely feedback

Mortality Surveillance

• Potential data sources for deaths?

• Limitations?

• What role could SC/US play in mortality

reporting?

Mortality Surveillance

• Potential data sources – Hospitals / clinics– Community and

religious leaders– Burial grounds– Shroud distribution– Body collectors– Other sources

• Limitations

– Deaths under-reported

– Exaggerated– Concealed– Denominator inflated

Surveillance Emergencies:Mortality

• Important indicators in emergencies

• Reported number of deaths

• Mortality rates - CMR, U5MR

• Age/Sex specific mortality rates

• Cause specific mortality rates

• Case fatality rates - measles, cholera etc.

What Are Some Expected Case-Fatality Rates?

• Cholera

• Shigella dysentery

• Typhoid

• Measles

Expected Case-Fatality Rates

• Cholera: 1% or lower

• Shigella dysentery: 1% or lower

• Typhoid: 1% or lower

• Measles: 3%

Mortality Form

No. of deaths Totalmales females males females

Watery diarrheaBloody diarrheaSuspected choleraRespiratory tract diseaseMeaslesMalariaMaternal deathSuspected meninigitsOther/unknownTotal by age and sexTotal <5 yrs

0-4 yrs 5+ yrs

Leading Causes of Mortality in Under 5

Susp. Malaria

24%

All other58%

Severe Malnutr.

10%

Jaundice3%ARI

5%

Leading Causes of Mortality in Over 5

ARI3%

Susp. Malaria

21%

All other59%

Severe Malnutr.

5%

Jaundice12%

Leading Causes of Mortality, Darfur, Sudan, May-September 2004 (N=1,514)

War-Related Trauma and Mortality of Refugees

War-relatedTrauma

63%

Natural19%

Non War-relatedTrauma

37%

Chronic51%

Unknown22%

Infectious3%

Other5%

Kosovo: Feb ’98 –Jul ‘99

0

100

200

300

400

500

600

700

800

900

1000

Landmine UXO Other/Unknown

Nu

mb

er

of

vic

tim

s

18 yr and older

under 18 years

..

37%

54%

9%

Landmine/UXO Injuries – AfghanistanExplosive Type by Age Group

Morbidity Form

Diagnosis Totalmales females males females

Watery diarrheaBloody diarrheaSuspected choleraRespiratory tract diseaseMeaslesMalariaSuspected meninigitsSkin diseaseSexually transmitted infectionsTrauma/accidentOther/unknownTotal by age and sexTotal <5 yrs

0-4 yrs 5+ yrs

Keep case definitions simple

Disease Definition

Measles

Malaria

Watery Diarrhea

Lower RespiratoryInfection

For other examples, refer to WHO guidelines

Fever, Rash + cough or rash or conjunctivitis

Fever and periodic shaking, chills

More than 4 stools per day, but no blood or rice-water in stool

Fever, cough, rapid breathing(x breaths per minute-dep. upon age)

Surveillance in Emergencies: Morbidity

• Record ONLY ONE diagnosis per patient choose most ‘important’

• Take new (incident) cases not repeat cases record and register if case is new or repeat

• In post emergency phase, consider including lab diagnosis as part of case-definition to improve sensitivity of clinical diagnosis

Rates: Problems With Denominator

Population refugee camp: April 2001Camp committee: 45,000UNHCR estimate: 25,000Census April 8: 11,500

Population refugee camp: February 2001Camp committee: 30,000UNHCR estimate: 23,000Count after relocation: 20,000

Mortality Rates In Refugee Camps In Guinea, 2001 (Original Populations Estimates)

Emergencythreshholds

Mortality Rates In Refugee Camps In Guinea, 2001 (Population Estimates Revised Downward)

Case Study

Surveillance in Darfur

http://www.reliefweb.int/w/map.nsf/home?openForm

Early Warning and Response Network (EWARN) - Darfur

• Established in May 2004 by WHO and Sudanese MoH aiming:– To ensure timely detection, response and control

of outbreaks among IDPs in Darfur region– To monitor trends of communicable diseases in

order to take appropriate public health actions– To estimate workload of different health units

involved in the system in order to rationalize resource allocation

Thanks to Ondrej Mach, M.D., CDC

Darfur Surveillance

• What kind of system would you set up?

• Would you collect surveillance data from every location?

• What conditions would you include?

• Would you use this system to collect mortality data?

Stakeholders in EWARN

• MoH (Federal and Local)– Coordination– Data collection and data entry

• WHO– Coordination– Data entry and analysis– Presentation and dissemination of results

• NGOs– Data collection– Communications– Logistics

EWARN Reporting Area

EWARN Weekly Reporting Cycle

Health Center in Mossei Camp, South Darfur

DataGathered

Field Clinics

1

DataEntered

WHO States

2

ReportWHO Khartoum

3

Health Events Under Surveillance

• 10 communicable diseases/syndromes– Acute Watery Diarrhea– Bloody Diarrhea– AFP– ARI– Neonatal Tetanus– Malaria– Suspected measles– Suspected meningitis– Acute Jaundice syndrome– Acute unknown fever

• Severe malnutrition• Injuries• Other

Reporting

• There are 56 reporting units (health facilities) in the three states

• Four indicators are collected for each Event:– Count of new cases diagnosed

• Under 5 years of age• Above 5 years of age

– Count of deaths in the week caused by event• Under 5 years of age• Above 5 years of age

Reporting Cycle

• Reporting is weekly• Data is sent from reporting units to state

capitals• Data is entered in state capitals and

forwarded to WHO office in Khartoum and the Federal MoH

• Epi Info 6 with EPI Data are used for data processing

• MMWB is prepared and distributed every Sunday

Leading Causes of Morbidity in Under 5

ARI20%

All other57% Severe

Malnutr.3%

Susp. Malaria

15%

Bloody Diarrhea

5%

Leading Causes of Morbidity in Over 5

ARI14%

Bloody Diarrhea

5%

Susp. Malaria

16%

All other61%

Injuries4%

Outbreak Detection

• Acute Jaundice Syndrome (Hepatitis E)

• Measles

• Meningitis

• Cases of Acute Flaccid Paralysis (infection with wild polio virus)

Measles Outbreak Darfur, May-September 2005

0

20

40

60

80

100

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160

# o

f C

as

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May23

June6

June20

July4

July18

Aug1

Aug15

Aug29

Sept12

Sept26

Week Beginning

EPI Curve - 2004 Measles

VaccinationCampaign

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# o

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as

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May23

June6

June20

July4

July18

Aug1

Aug15

Aug29

Sept12

Sept26

Week Beginning

EPI Curve - Meningitis in Morni Camp

VaccinationStarts

Acute Jaundice (Hepatitis E)

Children Under 5

Over 5 years of age

Cases 1,232 7,678

Deaths 7 105

Case Fatality Rate 0.6 % 1.4 %

Attack Rate in Camps 0.7% (0.13% - 9.1%)

August 1, 2004 (Week 30)n = 330

August 15, 2004 (Week 32)n = 734

August 29, 2004 (Week 34)n = 768

September 12, 2004 (Week 36)n = 1,267

Bloody diarrhea and Acute Jaundice cases in Morni Camp, West Darfur

Morni

0

100

200

300

400

500

600

21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38

Week

AJS

cas

es

0

200

400

600

800

1000

1200

1400

Blo

od

y D

iarr

hea

cas

es

AJS Bloody diarrhea

Epidemic prone diseases:CholeraShigellosisTyphoid feverAcute Lower Respiratory

InfHepatitis A, EMeaslesMeningitisInfluenza

Diseases with increased risk due to flooding:

Tetanus in adults Leptospirosis (rats)DengueMalaria

Diseases linked to overcrowding: All diarrhoeasAcute respiratory tract infectionHepatitis A, EInfluenzaMeningitisMeaslesTuberculosis

Vector borne diseases: DengueMalariaScrub TyphusLymphatic FilariasisJapanese encephalitis

Zoonosis present: Leptospirosis Anthrax RabiesTrichinosis Melioidosis Brucellosis Nipah virus

WHO: Health Risks for Communicable Diseases Following Asian Tsunami

WHO: Suggested Health Events For EWAR

Acute watery diarrhoea (suspect cholera)Acute diarrhoeaAcute bloody diarrhoeaAcute Jaundice syndromeSuspected meningitis Acute Lower Respiratory Infection Suspected measles Fever of unknown originsSuspected malaria Acute hemorrhagic feverUnknown diseases occurring in a cluster