This presentation was given at the technical mash-up meeting on "Mapping for Maternal and Newborn Health", hosted by ICS Integrare and the University of Southampton, with the support of the Norwegian Agency for International Development (NORAD) in Southampton (UK), 11-12th March 2013. Further details are available here http://integrare.es/?cat=33 This presentation describes research which aims to develop an accurate cost surface map to calculate distances to health facilities in Ghana. By Zoe Matthews, University of Southampton

1. Too far to walk – calibrating distances to
maternity health facilities for women in
Ghana using GIS tools
Zoë Matthews

2. Coauthors
• Fiifi Amoako-Johnson, Social Statistics, University of Southampton
• Faustina Frempong-Aiguah, (RIPS) University of Ghana
• Peter Gething, Spatial Epidemiology, Dept Zoology, University of Oxford
• Peter Atkinson, School of Geography, University of Southampton
• Angela Baschieri, London School of Hygiene and Tropical Medicine
• Philomena E. Nyarko, (RIPS) University of Ghana and GSS
• Francis Nii-Amoo Dodoo, (RIPS) University of Ghana
• Jane C. Falkingham, Centre for Population Change, University of Southampton
• Patrick Aboagye, Ghana Health Services, Accra, Ghana

3. Acknowledgements
• ESRC/DFID – for funding project
• IMMPACT – for use of survey data from Ghana
• CERSGIS – University of Ghana, for use of GIS data
• Ghana Statistical Service – for use of GIS and facility data

4. Outline
• Background
• Ghana
• Aims
• Methods
– Stage 1: Build a model of physical access
– Stage 2: Calibrate the model using survey data of actual physical access in a
small area
– Stage 3: Apply nationally
• Building and calibrating a model to measure physical access to facilities
– Data sources in Ghana
• Results – not yet!
• Why the results (when we get them!) will be an advance – and how they will be
useful

5. Policy efforts to break down
barriers to effective coverage
COST
•2003 Fee Exemption Policy
•4 regions targeted for the policy
•Policy ended in 2005 but free care for all
pregnant women via national insurance
scheme announced 2007/2008
DISTANCE
•CHPS strategy for reaching the unreached is part of
the national poverty reduction strategy.
•CHPS districts deploy professional health workers to
provide community-based health care, including safe
motherhood and family planning
QUALITY
•MAF plans to upgrade family planning, skilled
delivery and EmONC
•Includes equipment, improved education and
support for health workers as well as commodities
and support for governance

6. Existing data: health system
infrastructure
Average distance to nearest hospital
As measured
on census
2000…but
these are not
maternity
facilities

7. Existing data

8. Aim
• To give an accurate picture of distances to
maternal health facilities in Ghana – down to small
areas – nationwide.
• To provide ‘cost-surface’ maps of Ghana for
maternity facilities as has been done in Kenyan
districts for malaria
WHY?
– To facilitate understanding of the extent to
which distance, or distance related factors are a
Journey
barrier to use time
(minutes)
– To monitor the success of policies
– For planning and targetting

9. How?
– Stage 1: Build a model of distance to facility
using GIS catchment techniques
– Stage 2: Calibrate model using survey data
on a small area with actual travel distances
and times
– Stage 3: Apply nationally

10. Data sources
• Stage 1
– Facility locations
– Land cover
– Transport routes
– Elevation map
• Stage 2
– Actual distances for a smaller area – survey data
– Should include residence location, facility location and actual
time/distance
– Should be specific to maternity
• Stage 3
– As for Stage 1 – covering whole country
– Accurately parameterised model from Stage 2 incorporating facility
choice and bypassing

11. Stage 1: for Ghana we have
• Facility map
• Land cover including:
– Road and path networks
– Natural barriers – lakes, rivers, swamps,
nat.parks by season
– Contour maps for gradient

12. Building a GIS model to
measure physical access to
health facilities
• How far?
• Which is nearest?
Facility A Facility B

13. Catchment modelling
• Simple approach is Euclidean distance
Facility A Facility B

14. Catchment modelling
• BUT Euclidean distance not a good measure
• Affected by:
Facility A Facility B

15. Catchment modelling
…natural barriers
Facility A Facility B

16. Catchment modelling
…elevation / gradient / slope
Facility B
Facility A Facility B

17. Catchment modelling
…transport network
Facility B
Facility A Facility B

18. Catchment modelling
• SO journey time likely to be a better metric
Facility B
Facility A Facility B

19. Catchment modelling
• Modelling step 1: production of ‘impedance’ grid
Natural barriers + Roads/paths = Impedance

20. Catchment modelling
• Step 2: Incorporation of effect of gradient on speeds
•Used variation of
Naysmith’s rule
Spatial analysis and GIS for the mapping of
malaria in Kenya

21. Catchment modelling
• Step 3: Design of algorithm to calculate journey-time
– Assumes parameters based on number of gradient
categories, base speeds by mode of transport and
conversion of travel speeds to friction/impedance
– Uses 100m by 100m raster grid
– Uses region-growing approach from each facility
– Calculates cumulative sum of journey time to each pixel
– Incorporates a facility choice component
Journey time
(minutes)

22. Stage 2: Calibrate using real data
from a survey
• IMMPACT out-of-pocket-costs survey in two regions Volta
and Central – over 2,000 women surveyed
• Includes distances to maternity facilities and times as well
as forms of transport
To calibrate: Repeatedly COMPARE different versions (with
alternative parameterisations) of the MODEL applied to
locations in the survey with the REAL TIMES from the
survey… then choose the optimum best-performing model
with least squared differences
Proceed to Stage 3…APPLY MODEL MORE WIDELY

24. Results:
travel time

25. Results: % of women who live within 2 or 4 hrs
travel time