the kemri/cdc health & demographic surveillance system · the kemri/cdc health &...
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The KEMRI/CDC Health & Demographic Surveillance System
Kayla Laserson, ScDDirector, KEMRI/CDC Program
KEMRI/CDC Field Research StationKisumu, Kenya
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Introduction
Timely and accurate population-based information is critical in the fight against disease and poverty
The Millennium Development Goals as a framework for poverty reduction and sustainable development comes with obligations to monitor progress
Global health initiatives like the Global Fund to combat AIDS, TB and Malaria, PEPFAR, or PMI require monitoring of progress and evaluation of impact
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The KEMRI/CDC DSS
• Provides a platform for action-oriented research to test and evaluate public health interventions
• Provides a suitable sampling frame for clinical research, including vaccine trials
Provides timely information for policy formulation and rational resource allocation
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Nyanza ProvinceMalaria – intense and holoendemic: highest incidence in country (EIR 100-300 annually)
HIV highest prevalence in country (15%, DHS)
TB – greatest burden in Kenya
Other infectious diseasesSchistosomiasis endemic Diarrhea (Shigellae including dysenteriae, cholera, rotavirus)
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Demographic Surveillance System (DSS)
Launched in September 2001 • As a collaborative effort between the Kenya Medical Research
Institute (KEMRI) and the Centers for Disease Control and Prevention (CDC)
Continuous demographic monitoring of a geographically defined population in Bondo and Siaya districts, Nyanza province• 135,000 since 2001[Asembo and Gem]; 85,000 added in April
2007 [Karemo]• Birth rates• Mortality rates• Causes of death• Morbidity• Migration• Socio-economic indicators• EIR data since 1990’s• Includes Siaya District Hospital
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q
q
q
q
q
0 10 20 Kilometers
Lwak H.
Asembo
GemKaremo
KombewaBondo D. H.
Kombewa Sub D.H.
Siaya D. H.
Yala Sub D.H.
*Kisian
*Kisumu
The Demographic Surveillance Area
Lake Victoria
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DSS Methods
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KEMRI/CDC DSS Study Area
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Field Operations and Data Processing
Mapping of compounds and enumeration of households
Household surveillance and socio-economic surveys• Immunization survey• HIV status/ care-seeking survey• Marriage status form
Health facility surveillance
Entomology surveillance and insecticide treated bednets
Quality control
Data entry and management
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Verbal Autopsy (VA)Indirect method of ascertaining cause of death from information about symptoms and signs obtained from bereaved relatives
Conducted for both children & adults• Child VA data (from 2001 to date)• Adult VA data (from 2003 to date)
Both questionnaires (child and adult) adopted from INDEPTH
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Results
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The Surveillance Population: Asembo and Gem
Population: 135,887 (2005 mid-year pop.)• 95% Luo ethnic group• 217 villages, 500 sq km• Males: 47%• Children <15 years: 44%• Children <5 years: 16%• Adults ≥65+: 7%• Total Fertility Rate = 5.2•• Rural subsistence Rural subsistence
agriculture, fishingagriculture, fishing
20.0 15.0 10.0 5.0 0.0 5.0 10.0 15.0 20.0
0-4
15-19
30-34
45-49
60-64
75-79
90-94
Age
Proportion (%)
Male Female
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Age Specific Migration Rates by Year (Males)
0
50
100
150
200
250
300
350
0-4 10-14 20-24 30-34 40-44 50-54 60-64
Age group
Out
-mig
ratio
n ra
te (p
er 1
,000
pyo
) 2003 2004 2005 2006
0
50
100
150
200
250
300
350
0-4 10-14 20-24 30-34 40-44 50-54 60-64
Age group
In-m
igra
tion
rate
(per
1,0
00 p
yo)
2003 2004 2005 2006
Out Migration
In Migration
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Age Specific Migration Rates by Year (Females)
0
50
100
150
200
250
300
350
0-4 10-14 20-24 30-34 40-44 50-54 60-64
Age group
Out
-mig
ratio
n ra
te (p
er1,
000
pyo)
2003 2004 2005 2006
0
50
100
150
200
250
300
350
0-4 10-14 20-24 30-34 40-44 50-54 60-64
Age group
In-m
igra
tion
rate
(per
1,0
00 p
yo)
2003 2004 2005 2006
Out Migration
In Migration
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Causes of Clinic Attendance Among Children, 2003-2006
0
10
20
30
40
50
60
70
80
90
Malaria URTI Worms Gastroenteritis Pneumonia Diarrhea Anemia
Diagnosis
% o
f sic
k vi
sits
2003 2004 2005 2006
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Life Expectancy at Birth for the Resident Population, 2002-2006
36.137.6 38.7
41.739.7 39.9
4344.8
0
10
20
30
40
50
2003 2004 2005 2006
Life
exp
ecta
ncy
at b
irth
(yrs
)
Males
Females
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Age-specific Mortality Rates (2003-2006)
0
20
40
60
80
100
120
140
160
180
0-4 10-14 20-24 30-34 40-44 50-54 60-64 70-74 80+
Age at Death
Mor
talit
y ra
te (p
er 1
,000
pyo
) Male Female
121/1000 live births – IMR (2005)241/1000 live births – U5MR (2005)
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Causes of Death Among Infants and Children, 2003-2005
0
5
10
15
20
25
30
35
Malaria
Pneumonia
Anemia
Dehydratio
n
Diarrhoea/V
omiting
Malnutrition
Meningitis
HIV/TB
Undetermined
Others
Prop
ortio
n (%
) dea
ths
2003 2004 2005
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Causes of Death Among Adults and Adolescents, 2003-2006
0
10
20
30
40
50
60
70
HIV/TB
Malaria
Pneumoni
a
Anemia
Dehyd
ratio
n/Diar
rhea
Stroke
/CCF
Menin
gitis
Injur
y
Other
s
Prop
ortio
n (%
) dea
ths
2003 2004 2005 2006
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HIV Prevalence by Age & Sex, 2003/2004
1 1
10
18
3632
20
10
41
3033
0
10
20
30
40
50
13-14 15-19 20-24 25-29 30-34 All
Age group
Prev
alen
ce (%
)
Male Female
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School Enrollment for Residents Aged 6-9, 2002-2006
0
20
40
60
80
100
Age 6 Age 7 Age 8 Age 9
Prro
port
ion
(%) e
nrol
led
2003200420052006
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School Dropout
Approximately 9% of children aged 10-17 dropped out of school in 2003-2006
Reasons proffered for drop out include– Inability to pay fees– Ill health (of child or parent)– Poor performance– Early marriage and child bearing
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Operational Research in the DSS
KEMRI/CDC DSS allows operational research where malaria transmission is intense, ITN coverage is high, and HIV prevalence is high
Expansion to include Siaya District Hospital will facilitate more clinic-based research– Siaya District Hospital Annex, with pharmacy, laboratory,
surgical suite, patient support center, and training/conference rooms, will allow rigorous clinical trial research
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Malaria– Drug efficacy, including in pregnant and HIV(+) persons– Intermittent preventive treatment of malaria in infants/
pregnant mothers– Transmission reduction
• ITN coverage use, resistance• Larval breeding sites• Vector control interventions
Tuberculosis– TB prevalence survey
SchistosomiasisEmerging infections – Population-based morbidity surveillance– Diarrheal diseases surveillance: incidence and etiology– Expanded flu/respiratory surveillance
Operational Research in the DSS
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Operational Research in the DSSHIV – Baseline cross-sectional surveys– Collection of self-reported status, care-seeking– Impact of ARVs at population level – Orphan prevalence/incidence – Planned comprehensive evaluation of HIV home-based
testing, community-based care and treatment service delivery, and circumcision uptake and feasibility
Vaccine trials• Rotavirus – Phase III• Malaria – Phase III• TB vaccine trial site development
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Training and Collaborations in the DSS
Training– Provide data for MA theses & PhD dissertations– Data for epidemiological capacity building
Cross-site collaboration – Contributed data to the cross-site cause-specific
mortality analysis initiated by the INDEPTH and published in WHO Bulletin 84(3)
– Contributed data to the cross-site “Patterns of age-specific malaria mortality in children in endemic areas of sub-Saharan Africa” initiated by the INDEPTH and accepted for publication AJTMH
– Participating in the cross-site HIV research proposal initiated by INDEPTH
– Contributing a chapter to the INDEPTH monograph on Migration, Urbanization & Health
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Concluding Remarks
The KEMRI/CDC DSS data have shown excessively high mortality and morbidity rates among the DSS residents– Resulting largely from infectious diseases (malaria &
HIV/AIDS)
The life expectancy at birth for the resident population is among the lowest in the world, but appears to be improving
The morbidity and mortality epidemiological profile in the KEMRI/CDC DSS is well-characterized; the DSS is well-positioned, and intends, to provide the platform to measure the impact of coming interventions (vaccines, scale up of HIV services, etc)
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AcknowledgementsDr Adazu KubajeDSS staffKEMRI/CDC program, past and presentDr John Vulule, KEMRI
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EXTRA SLIDES
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Age Specific Migration Rates by Sex
0
50
100
150
200
250
300
350
0-4 10-14 20-24 30-34 40-44 50-54 60-64
Age
Out
Mig
ratio
n ra
te (p
er 1
,000
pyo
)Male_out Female_out
Male
0
50
100
150
200
250
300
350
0-4 10-14 20-24 30-34 40-44 50-54 60-64
Age
In m
igra
tion
rate
(per
1,0
00 p
yo) Male_in Female_in
Out migration
In migration
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0
2000
4000
6000
Num
ber o
f vi
sits
Jan
Feb
Mar Apr
May Jun
Jul
Aug
Sep
Oct
Nov
Dec
12-59 mo 0-11 mo
Monthly Clinic Attendance Among Children, 2003-2006
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Reasons for Dropping Out Among Children Aged 10-17 (KHDSS, 2003)
0
10
20
30
40
50
Death/si
ck Paren
tMarria
ge/p regnancy Fee
Poor perfo
rmance
Employment
Expelled
Il health
Reason
Pro
porti
on (%
) of d
ropo
uts
Male
Female
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Age-specific Mortality Rates by Year (2003-2006)
0
20
40
60
80
100
120
140
160
180
0-4 10-14 20-24 30-34 40-44 50-54 60-64 70-74 80+
Age at Death
Mor
talit
y ra
te (p
er 1
,000
pyo
) 2003 2004 2005 2006
0
20
40
60
80
100
120
140
160
180
0-4 10-14 20-24 30-34 40-44 50-54 60-64 70-74 80+
Age at Death
Mor
talit
y ra
te (p
er 1
,000
pyo
)
2003 2004 2005 2006
Males
Females
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Literacy by Sex for Residents aged 10+, 2003-2006
0
20
40
60
80
100
Male03 Female03 Male04 Female04 Male05 Female05 Male06 Female06
Prop
otio
n (%
) of p
opul
atio
n
Not at all With dif f iculty Easily