Improving health worldwide

www.lshtm.ac.uk

GIS: A project by project prospective

Chris Grundy

chris.grundy@lshtm.ac.uk

Why project by project

• Each project will have different data requirements / issues

• Basic rules / considerations– Size of dataset– Confidentiality– Accuracy: time & location

• Examples– 20mph zones in London– Use of satellite imagery in surveys

20mph zones in London

20mph zones on road injury

• What effect have implementation of 20mph zones in London had on road injury between 1986 - 2006

• GIS used– Locate 20mph zones– Link road injury to roads– Build dataset ready for analysis

Methods

• Controlled interrupted time series analysis– Measures the change in the number of casualties on

each road in London from 1987-2006– Control group is all “outside” roads in London

• 20 years of road casualty data (STATS19)

• Each road defined by year as– Inside a 20mph zone– Adjacent to a 20mph zone– Outside 20mph zones

20mph Zones & road casualties

Results

All casualties Killed and seriously injured (KSI)

Child casualties Child KSI casualties0%

10%

20%

30%

40%

50%

60%

70%

Data considerations

• Large dataset (6 million rows)– Each stats run took 6 – 10 hours (20 runs)

• Accuracy– Collisions not always accurate – lots of checks– During 20 years roads physically changed

• Confidentiality– Full road injury dataset confidential– Confidential server too slow to handle size– Data anonymised for use elsewhere

Satellite imagery in surveys

GIS and mapping in surveys

• Surveys vital part of public health studies

• GIS widely used– Planning logistics– Random selection of household– Population estimation methods– Locating house holds for return visits– Mapping results

Using imagery

• Satellite images increasingly available– Google earth– Commercial images– Commissioned images

• Structures visible

• On screen digitizing

Am Timan town, Chad

Stratum 1

Stratum 2

Stratum 3

Methods: quadrat survey

• Area split into grid– 50 m2 grid defined– Existing city street grid

• 15 “quadrats” (blocks) per

stratum

• Visit each structure

• Population = Population density x Area

Method: manual structure count

• Structures located by eye

• Type of structure determined by user– Traditional hut– Non residential building

• Grid used to ensure

systematic counting

• Count checked – Missed features / errors

Methods: Population estimation

• Using satellite images to estimate population:

Population = n structures x n people / structure

Manual counts Small structure occupancy survey

Methods: random survey

• Select & visit random

structures

• Combine pre-located

structures and GPS

• Coordinates allow structure

to be revisited easily

Survey structure

Results: Population estimates

Stratum Quadrat Survey

Imagery Method

Manual Count

Automated Count

1 14337 12996 12229

(10751 – 19117) (11655 – 14490) (10968 – 13635)

2 16877 16920 16802

(12581 – 22639) (15175 – 18866) (15069 – 18734)

3 25176 16709 16369

(10473 – 60523) (14986 – 18631) (14680 – 18251)

Total 49722 46625 45400

(29 431 – 84003) (41817 – 51987) (40718 – 50620)

Trial in different areas

Location Manual estimate

Reference Population

Difference

Kutupalong 12 058 11 047 +1011 (+9.2%)

Breidjing 34 896 26 770 +8126 (+30.4%)

Farchana 22 944 19 070 +3874 (+20.3%)

Bambu 7637 5871 +1766 (+30.1%)

Mugunga III 2986 1969 +1017 (+51.7%)

Sherkole 8355 13 958 -5603 (-40.1%)

Shimelba 11 994 13 043 -1049 (-8.0%)

Champs-de-Mars 12 513 23 214 -10 701 (-46.1%)

Delmas 24 20 612 39 349 -18 737 (-47.6%)

Kakuma 88 457 90 457 -2000 (-2.2%)

Bairro Esturro 8940 9523 -583 (-6.1%)

Data considerations

• Image data licensed– Images licenses, not allowed to be shared– Named users verses number of users– Getting suitable image within time period an issue– Not all locations have identifiable structures

• Confidentiality– Main dataset not confidential– Confidential survey data stored separately

• Ethics / Population security– Dangers of mapping at risk populations

Summary

Don’t forget

• Time: How current is data

• Preparation: Planning is everything

• Disk space

• Confidentiality & ethics: storage & publication

• Share data wherever possible

Tip: Map your data

• Check data as it comes in

• Explore your data

• Use maps at every opportunity