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Electronic data collection for
a modular household survey
in Ethiopia
Keith Tomlin
IDEAS Data Manager/Epidemiologist
Improving health worldwide
www.lshtm.ac.uk
The Project
• IDEAS (Informed DEcisions for ActionS)
• Aims to improve the health and survival of mothers and newbornsby generating evidence to inform policy and practice.
• Working in Ethiopia, North-Eastern Nigeria and the Indian States of Uttar Pradesh and West Bengal.
The Survey
• Ethiopia follow-up survey
• Aim to gather data on pregnancies, deliveries and newborn care from women in households, from frontline workers and from health facilities
• Household survey comprised in-depth interviews with women of child-bearing age
• 80 randomly sampled clusters
• 75 households per clusters (6,000 in total)
• 12 survey teams, each with 6 interviewers and one supervisor
• Fieldwork carried out during April 2015
Ethiopia
Survey cluster locations
Household survey structure
Clusters (80) Cluster Name
01 DEGA AMBA
02 BARIKA ADIS SEBHA
03 BARIKA ADIS SEBHA
04 MADO TEMKET
05 GEREWERE
06 BEYA
07 LORI
08 SATA MIDIRARO
09 ERGOYE
etc…
Clusters (80) Cluster Name
04 MADO TEMKET
Households (75)
04/01
04/02
04/03
04/04
04/05
04/06
04/07
04/08
etc…
Household survey structure
75 households within each cluster
Household survey structure
Clusters (80) Cluster Name
04 MADO TEMKET
Households (75)
04/08
Residents (household roster)
ID number Name Gender Date of Birth Eligible
04/08/01 Teklay Male 08/05/1970 No
04/08/02 Azmera Female 08/12/1982 Yes
04/08/03 Birhdan Female 24/02/1987 Yes
04/08/04 Semere Male 15/10/1990 No
04/08/05 Meaza Female 30/08/1993 Yes
04/08/06 Mebrhit Female 05/06/2002 No
A roster is taken of all residents in each household
Household survey structure
Clusters (80) Cluster Name
04 MADO TEMKET
Households (75)
04/08
Residents (household roster)
ID number Name Gender Date of Birth Eligible
04/08/01 Teklay Male 08/05/1970 No
04/08/02 Azmera Female 08/12/1982 Yes
04/08/03 Birhdan Female 24/02/1987 Yes
04/08/04 Semere Male 15/10/1990 No
04/08/05 Meaza Female 30/08/1993 Yes
04/08/06 Mebrhit Female 05/06/2002 No
The programme identifies women of child-bearing age (15-49)
Household survey structure
Clusters (80) Cluster Name
04 MADO TEMKET
Households (75)
04/08
Women aged 15 - 49
ID number Name Gender Date of Birth Eligible
04/08/02 Azmera Female 08/12/1982 Yes
04/08/03 Birhdan Female 24/02/1987 Yes
04/08/05 Meaza Female 30/8/1993 Yes
• Request to interview each woman if present• Return to the household up to three times if a
woman was temporarily absent
Household survey structure
Women aged 15 - 49
ID number Name Gender Date of Birth Eligible
04/08/03 Birhdan Female 24/02/1987 Yes
Pregnancy roster
Baby ID Name Gender Date of Birth
04/08/03/01 Azmera Female 12/09/2007
04/08/03/02 Semere Male 03/07/2009
04/08/03/03 Mebrhit Female 12/09/2013
A roster of births for each woman was taken
Household survey structure
Women aged 15 - 49
ID number Name Gender Date of Birth Eligible
04/08/03 Birhdan Female 24/02/1987 Yes
Pregnancy roster
Baby ID Name Gender Date of Birth
04/08/03/01 Azmera Female 12/09/2007
04/08/03/02 Semere Male 03/07/2009
04/08/03/03 Mebrhit Female 12/09/2013
If the most recent birthhad taken place in the two years prior to the interview, additionalquestions were asked
Language considerations
English Pleased to meet you
Amharic ስለተዋወቅን ደስ ብሎኛል
Oromo si argun naaf gammachudha
Triginya ጽቡቕ ሌላ
Software considerations
• Affordable (and preferably free)
– and runs on affordable hardware
• Accommodate modular structure, and automatically generate & carry forward ID numbers between clusters, households, adults and pregnancies, with no manual entering of numbers
• Accepts Unicode to allow for Amharic and Tigrinya languages
• No dependence on the internet, because there mostly isn’t any
Software comparison
(as at June 2014)
Provider No cost to develop/deploy
Runs onAndroid OS
Accommodatesmodular structure
RecognisesUnicode
CSProAndroid
EpiCollect
ODK
Pendragon Forms
Surveybe
Hardware considerations
• Run Android
• Inexpensive (84 units + cases + extra batteries + import duties)
• Readily available in bulk
• Robust
• Excellent battery life
• Small enough to be held in one hand, but with a large enough screen so that long option lists could be displayed without scrolling
And the winner is…
In-field data reporting
In each survey team, data weretransferred at the end of each day from the tablets to thesupervisor’s laptop, using USB Cables.
In-field data reporting
Data were automatically imported into a Microsoft Access database to create a daily monitoring and query report
Data encryption
• Built-in Android encryption on tablets
• TrueCrypt encryption on laptops
The biggest lesson was…
ስለተዋወቅን…..Some non-Latin characters (such as those used in Amharic) can take up more computer memory than Latin characters. This has the potential to slow down data collection programmes. Many thanks to the CSPro developers for rapidly responding to this problem and releasing a new version of the Android software in time for our survey.