innovating hdss for greater efficiency in population based data in low-middle-income countries
TRANSCRIPT
Innovating HDSS
for greater efficiency
in generating population-based data
in low- and middle-income countries
Children, Adolescents, Adults, Old People
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Prof. Osman Sankoh, Executive Director
Accra, Ghana
UNICEF, Florence, Italy 13-15 Oct 2014
International
Network for the
Demographic
Evaluation of
Populations and
Their
Health
in low- and middle-income countries
What is INDEPTH Network?
INDEPTH Builds on Two Competitive Advantages
Ensuring efficiency: leverage both ongoing data collection and the
teams across the network
Increasing quality: link top scientists across the 42 member centres
Maximising impact: merge data across sites and assessing
implications for science, practice and policy
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Longitudinal Data (HDSS):
Enabling true analysis of
changes, correlations and
cause & effect
Network of Centres:
Leveraging capabilities from
one centre across entire
network.
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Birth
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ot in
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A)
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De
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ot in
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Birth
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De
ath
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Time
Birth
(in
DS
A)
Mo
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Mo
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(in
DS
A)
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Observed Exposed Interval
Life
Examples of Observed Exposed Intervals
Prospective monitoring – the core
Verbal autopsy
for cause of
death
Capturing episodes of
disease and hospital
admission
Measure characteristics of
environment or household
members (e.g. SES, vaccines,
HIV, nutrition)
RU
RA
L -
UR
BA
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Example of our work… Mortality
Cause-specific childhood
mortality in Africa and Asia:
evidence from 18 INDEPTH
HDSS Sites
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Results
1. 28,751 childhood deaths during 4,387,824 person-years over 18 sites
2. Infant mortality: 16 to 86 per 1,000 live births
3. Under-5 mortality: 23 to 134 per 1,000 live births
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Conclusions
1. Many children continue to die from relatively preventable causes, particularly in areas with high malaria and HIV endemicity
2. Neonatal mortality persists at relatively high, and perhaps sometimes under-documented, rates
3. External causes of death are a significant problem in some settings
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Age-sex-time standardised cause-specific mortality fractions (CSMF) for major cause of death groups for neonates at 18 INDEPTH sites during 2006-2012.
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Age-sex-time standardised cause-specific mortality fractions (CSMF) for major cause of death groups for infants (1-11months) at 18 INDEPTH sites during 2006-2012.
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Age-sex-time standardised cause-specific mortality fractions (CSMF) for major cause of death groups for children aged 1-4 years at 18 INDEPTH sites during 2006-2012.
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INDEPTH
Centre1,...,N
INDEPTH
Project
Multi-Centre
INDEPTHStats
INDEPTH
Data
Repository
www.indepth-ishare.org
External
partners
Data available online
Funded by:
Sida, Hewlett Foundation, Wellcome Trust
Innovation: Data Integration
• Integration across population and health facility data systems:
linking demographic, mortality, morbidity, clinical, laboratory, household and other contextual data
unique electronic individual identification system
• This will generate the empirical, unbiased data that are essential for intervention development and evaluation
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Innovation: sub-cohorts
• Sub-cohorts within full HDSS populations will be followed
monitor morbidity incidence
collect clinical data and laboratory specimens
o frequent scheduled household visits (active surveillance) and unscheduled visits triggered by mobile phone contacts from households (passive surveillance).
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Innovation: a combined system
• In addition, sentinel health facility data will provide information
on severe cases arising in the community and their associated etiologies, with outcomes being traced back to the household level in real-time
• The system will provide:
both numerators and denominators to determine population-based disease and etiology-specific incidences and mortality disaggregated by finely specified age-groups
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Examples of what we can generate more
efficiently and quickly on a regular basis…
1. Incidence of disease (diarrhoea, acute respiratory infection, and fever) – Severe Disease
2. Incidence of pathogen specific disease in under-fives and other age groups
3. Infant mortality rates (IMR) and under-five mortality rates (U5MR) and cause specific mortality fractions (other age groups)
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Data collection, management, integration
HDSS• household sample frames for morbidity surveillance
cohorts
• denominators for the household incidence outcomes
• Rich contextual data on households to understand selected risk factors for morbidity and mortality
• Unique electronic & biometric identifier ID code for data integration (households, health facilities & laboratories)
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What we need: i-INNOVATE
Partnerships
Partnerships
Partnerships
However:
- We want to have our scientists trained
- We want to be able to be first authors too
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