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?

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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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Observed Exposed Interval

Life

Examples of Observed Exposed Intervals

HDSS subjects

Homestead /

Compound

Unique ID given

to individuals

In Community / Population

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 -

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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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