GIS Training: Module 5 Geocoding and Importing Health Data

GIS Training: Module 5 Geocoding and importing health data

IER/HSI/GIS

2010

The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted lines on maps represent approximate borderlines for which there may not yet be full agreement.

The mention of specific companies or of certain manufacturers' products does not imply that they are endorsed or recommended by the World Health Organization in preference to others of a similar nature that are not mentioned. Errors and omissions excepted, the names of proprietary products are distinguished by initial capital letters.

The World Health Organization does not warrant that the information contained in this publication is complete and correct and shall not be liable for any damages incurred as a result of its use.

Module 5: Geocoding and Importing Health Data

Aim The aim of this module is to introduce and understand the principals of geocoding health data at country level, sub-national level, and city or settlement data.

Overview Geocoding is a GIS operation that matches attribute data in one database with similar attributes in a georeferenced database. The result can be displayed as a feature on a map or used for analytical purposes. In practical terms, health data must be associated with a spatial location in order to make it "mappable" and to conduct geospatial analysis on it. Thus, the majority of disease data and health care data must be linked to a spatial component in order to view it in a GIS environment.

Learning Objectives By the end of this module, you should be able to:

 Understand the basis and importance of geocoding.  Learn about country level coding systems.  Learn about sub-national level reference datasets.  Understand how to access standard geocodes.  Adequately prepare a database for mapping.  Apply global standards for geocoding a database

Exercises  Geocoding country level health data  Geocoding sub-national level health data  Geocoding city/settlement level health data

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5.1. Understanding Geocoding

5.1.1 What is Geocoding? The majority of disease data and health care data must be linked to a spatial component to view them in a GIS environment. Simply put, to make health data mappable and to subsequently conduct geospatial analyses the health data must be associated with a spatial location.

Geocoding refers as a GIS operation that matches attribute data in one database with similar attributes in a georeferenced database. The result can be displayed as a feature on a map or used for analytical purposes.

There are two methods used to geocode data:

1. Joining health data to geographical areas – This process means linking health data with geographic features (countries, regions, subdivisions). The association is based on a common coding system that must be part of both the health data and the geographic data. 2. Address matching to locate a health event – This process means assigning geographic coordinates (latitude and longitude) to health data so that it is readily mappable. It requires a reference dataset, which is the underlying geographic database containing geographic features, and a program or a specialized software application that calculates location of the health events. 5.2. Country level coding systems In many instances, standard codes are already attached with health data. If not, you may choose any one of the standard coding systems. This code allows for the health data to be associated with a spatial location on a map and is the attribute used for the spatial join.

Different country level coding systems are available and adopted by different agencies. The standard coding systems used by WHO include ISO 3166-1 alpha-2 code and ISO 3166-1 alpha-3 code.

ISO 3166-1 alpha-2 code ISO 3166-1 alpha-2 codes are two-letter country codes defined in ISO 3166-1, part of the ISO 3166 standard published by the International Organization for Standardization (ISO), to represent countries, dependent territories, and special areas of geographical interest.

ISO 3166-1 alpha-3 code ISO 3166-1 alpha-3 codes are three-letter country codes defined in ISO 3166-1, part of the ISO 3166 standard published by the International Organization for Standardization (ISO), to represent countries, dependent territories, and special areas of geographical interest. They allow a better visual association between the codes and the country names than the two-letter alpha-2 codes.

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The WHO standard map templates contain both ISO-2 and ISO-3 codes in the geographic layers. It is important to note that the ISO-2 codes are two-letter country codes and are most widely used. However, the ISO-3 code, the three letter coding system, is recommended for thematic mapping at the national level. 5.3. Sub- national level coding systems For administrative or health subdivision, reference datasets used for geocoding are composed of polygon data. There are many geographic databases for the world administrative divisions that are often difficult to maintain up-to-date as sub- national entities change on a regular basis.

The data sources can vary greatly in terms of coverage and accuracy. Most of the time, different agencies within the country use different coding systems and might have different numbers of units. This makes mapping sub-national data quite a challenge. There are some standard reference databases and coding systems for sub-national level at global scale. These are SALB codes, FAO GAUL codes, GADM codes, and WHO HealthMapper codes. It would be advisable to receive reference geographic data during the data collection process from the respective countries. Use the codes attached to the geographic data to assign to your health data. If this is not possible, one of the above reference geographic data can be used. Each of the standard reference data sets has certain pros and cons. It is advisable to contact the data owners of these reference data before deciding which coding system to adopt for your health data. WHO generally seeks out sub- national data from the sources in the following order: SALB, GAUL, GADM, HealthMapper.

SALB SALB is a UN project, which has been launched in the context of the activities of United Nations Geographic Information Working Group (UNGIWG) to provide the international community with a global standardized GIS layer containing the delimitation of the administrative boundaries down to the 2nd sub-national level. SALB is the data received from national mapping agencies of WHO member states and is considered a UN official source. SALB contains a record of historical changes of boundaries since 1990. In many cases, the codes are available, but not the spatial data.

FAO GAUL The Global Administrative Unit Layers (GAUL), an initiative implemented by FAO, compiles and disseminates spatial information on administrative units for all the countries in the world, providing a contribution to the standardization of the spatial dataset representing administrative units. The GAUL always maintains global layers with a unified coding system at country, first (e.g. regions), and second administrative levels (e.g. districts). The GAUL is released once a year and the target beneficiary of the GAUL data is the UN community, universities, and other authorized international and national institutions/agencies.

Data might not be officially validated by authoritative national sources and cannot be distributed to the general public.

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GADM dataset GADM, the Database of Global Administrative Areas, is a spatial database of the location of the world's administrative areas for use in GIS and similar software. Administrative areas in this database are countries and lower level subdivisions such as provinces, departments, districts, counties, etc. GADM describes where these administrative areas are (the "spatial features"), and for each area it provides some attributes, foremost being the name and variant names.

GADM was developed to support various activities, including georeferencing of textual locality descriptions (the BioGeomancer project) and for mapping census type data. The development is led by Robert Hijmans, in collaboration with Nell Garcia and John Wieczorek. Major contributions have also been made by Arnel Rala, and Aileen Maunahan at the International Rice Research Institute and by Julian Kapoor at the Univeristy of California, Berkeley, Museum of Vertebrate Zoology.

WHO HealthMapper dataset The WHO HealthMapper dataset contains comprehensive data in terms of global coverage. This is a collection of geospatial data from countries through various health data collection mechanisms. These data are good for mapping, but require further cleaning for advanced geospatial analysis. The purpose of this dataset is to cater to the WHO health community and provide data visualization, not to generate a standardized global coverage. It contains layers on a country-by- country basis, down to third, fourth, and lowers levels. Updates are performed as per request and need from the community.

The table below provides a brief overview of each of the reference datasets.

SEARCH NAME INFORMATION ORDER Global Administrative Unit Layers (Levels 1 Description 1 FAO GAUL and 2) Coverage Worldwide Description UN Second Administrative Level Boundaries 2 SALB Coverage Worldwide but sparse Description Global Administrative areas 3 GADM Coverage Worldwide Administrative divisions (Levels 1 to 4)/ Description WHO Health Divisions (Levels 1 and 2) 4 HealthMapper Worldwide/ Coverage Worldwide but sparse 5.4. How to access standard geocodes Standard geocodes can be located in a variety of places. Below you will find specific for finding geocodes at the country, sub-national, and city/settlement levels. In addition, information is provided on a geocoding web services tool being developed by WHO which will give access to geocodes used by WHO or the UN.

Country level geocodes  ISO 3166-1 alpha-2 code

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A complete list of ISO-2 codes can be found on the International Organization for Standardization website: http://www.iso.org/iso/country_codes/iso_3166_code_lists/english_country_name s_and_code_elements.htm

A complete list of ISO-3 codes is available by request from the International Organization for Standardization (http://www.iso.org/iso/country_codes). A list is also available on Wikipedia at http://en.wikipedia.org/wiki/ISO_3166-1_alpha-3

Sub-national level geocodes  FAO GAUL The GAUL layer can be downloaded from the FAO Geonetwork site at: http://www.fao.org/geonetwork/srv/en/metadata.show?id=1269

 SALB The SALB layer can be downloaded from the UNGIWG SALB website at: http://www.unsalb.org/

 GADM GADM layers are available for download from the GADM website at: http://www.gadm.org/

 WHO HealthMapper The HealthMapper geocodes provide details of the exact location of geospatial points (UNITID) or geospatial polygons (LVLID).

Units/points  Units are the smallest entities: towns, villages, schools, safe water points, hospitals and health service centres  Different unit levels for the same country are hierarchically linked e.g. town  village  school  Each unit has its unique identifier or UNITID (8 digits). For example:  MLP00234 : country=Mali, hierarchy type=Politic, sequence no.=00234  ETH00234 : country=Ethiopia, hierarchy type=Health, sequence no.=00234  Select the symbology tab and click on the box labelled symbol.  Select the image for Square 1

Polygons  Polygons are administrative areas and health districts.  Different polygons are hierarchically linked and the highest levels (admin1, health1) are directly linked to the respective country code.  Up to 4 levels possible (admin1, ..., admin4 / health1, …, health4) (Levels 5 and 6 exist in the db, but are not used yet.)  Each polygon has its unique identifier (21 digits): LVLID  The table below provides several examples of polygon or LVLID codes:

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ISO S Hierarchy 1 2 3 4 5 6 Note countrye code code q ML u P 002 001 324 000 000 000 (1) ET H 002 000 324 000 000 000 (2) BF1. S P 002 000 000 000 000 000 (3) 1. Sequence number 324 of administrative sub-district level 3 in Mali. 2. Sequence number 324 of health sub-district level 3 in Ethiopia. No health district level 2 defined, as surely not yet traced. 3. Burkina Faso country level. You can get access to all the HealthMapper geocodes from views in SQL server. The geocodes correspond to a global database containing geographic data for all countries. The views are stored in a database on a production server. You will find below the parameters to connect to it:

 Server: GVA1SWLULUS  User: HealthmapGeocodeUser  Password: HealthmapGeocodeUser SQL views for polygons:

 Healthmap.dbo.vw_AdminLevel1  Healthmap.dbo.vw_AdminLevel2  Healthmap.dbo.vw_AdminLevel3  Healthmap.dbo.vw_AdminLevel4 SQL views for points:

 Healthmap.dbo.vw_units

City/settlement level geocodes There are various web services available for city level geocoding purposes. The most frequently used geocoding web services are Google maps, Geonames, and Yahoo map. These are available through various web sites. It is advisable to use one of these web sites if you have few events to be geocoded.

You can use any of the following URLs to find the latitude and longitude of a place: http://itouchmap.com/latlong.html http://www.backups.nl/geocoding/index.html http://www.opengeocoding.org/geocoding/geocod.html http://www.gpsvisualizer.com/geocoding.html http://www.mapchannels.com/GeocoderSimple.aspx

WHO geocoding services Geocoding services will be created on the WHO web map server (ArcGIS server) to give access to geocodes used by WHO or UN. This online service will work like the

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ArcGIS Online address locator and users will be able to access it with ArcGIS desktop within WHO.

This geocoding framework will provide composite address locators and/or geocode services. For administrative or health subdivision, the main reference datasets used for geocoding will be made available through this service:

 FAO GAUL  SALB  GADM  Healthmapper At the moment, you can search the geocodes using the REST interface. REST, shorthand for Representational State Transfer, is used as a mechanism to identify and work with any Web resource, such as Web pages and Web resources. Essentially, REST enables users to issue a series of operations or commands against URLs and other Web resources (for example, URIs).

Step 1. Type the server URL http://gva1swjuno/ArcGIS/rest/services Step 2. Click on Global_places Step 3. Click on SALB admin2. You should see all the details concerning this layer such as the geometry type and the list of fields.

Step 4. Click on Query layer. Step 5. Enter Zambia as the CNTRY_NAME. Step 6. For the result options, enter the return fields names with comma separated: CNTRY_NAME,ADM2_NAME,ADM2_CODE

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Step 7. Click on Find. You should see the list of all the admin2 names and codes for Zambia from the SALB reference dataset.

5.5. Preparing health data The more carefully you format your table, the better the geocoding process will work. It is important that your data formatting is consistent throughout the database. If you are using a spreadsheet to create this data set, make the first row the field names, and start your actual records on the second row. Do not put in other formatting or rows or columns, e.g., no titles, or spacer rows. The field names should not include spaces or odd characters in the field name, and a maximum of 10 characters. Each row of data should contain only one province or one district name.

It is advisable to use the geocodes from the reference dataset during the data collection process. If it is not possible, you will need to format the dataset in order to assign geocodes to the health data.

The Cholera Outbreaks 2010 table below is a good example of many of the issues that can come up when dealing with geocoding sub-national level data. Can you find some of the potential problems with this data set?

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CHOLERA OUTBREAKS 2010 Disease Start End Country Provinces / Districts WHO Region Cholera 19-Oct-09 28-Mar-10 Zambia Lusaka, Copperbelt, AFRO Southern Cholera 01-Jan-10 10-Apr-10 Mozambique Cabo Delgado, Niassa, AFRO Zambezia, Sofala, Nampula

Answers:

1. No title and no spacer rows. The first line of the spreadsheet should be the column names.

2. There should be no spaces in the field names.

3. There should only be one province/district per row.

A correct table should look like the following:

DISEASE START END COUNTRY PROVINCE/DISTRICT WHOREGION GEOCODE Cholera 19-Oct-09 28-Mar-10 Zambia Lusaka AFRO ` Cholera 19-Oct-09 28-Mar-10 Zambia Copperbelt AFRO Cholera 19-Oct-09 28-Mar-10 Zambia Southern AFRO Cholera 01-Jan-10 10-Apr-10 Mozambique Cabo Delgado AFRO Cholera 01-Jan-10 10-Apr-10 Mozambique Niassa AFRO Cholera 01-Jan-10 10-Apr-10 Mozambique Zambezia AFRO Cholera 01-Jan-10 10-Apr-10 Mozambique Sofala AFRO Cholera 01-Jan-10 10-Apr-10 Mozambique Nampula AFRO

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Exercises: Geocoding health data The first step in geocoding health data is to determine the granularity or resolution of available data. Is your data country level, sub-national level, or city/settlement specific data? This set of exercises will explain how to geocode all three types of health data.

Exercise 1: Geocoding country level data

For this exercise we will be geocoding a IMCI training coverage dataset called IMCI_training_country_geocoding which can be found in the MDX_geocoding folder.

Mostly disease data or health data are only represented at country level. Capturing these data in GIS involves spatial joining. A spatial join is like joining two tables by matching attribute values. In order to accomplish this, both tables must have a common attribute. You will be using the joining method for country level data.

Task 1. Choose reference data/standard coding scheme. In many instances, standard codes are already attached with health data. If not, you may choose any one of the standard coding schemes. This code allows for the health data to be associated with a spatial location on a map and is the attribute used for the spatial join mentioned above.

For this exercise we will be using the ISO-3 coding system.

Task 2. Task 2: Assign geocodes to the data. The most common format of input data is Excel or MS Access but it can also be from a variety of databases with OLEDB capabilities. You can assign geocodes by transforming your input data (manual assignment) or by using an excel spreadsheet with standard geocodes. For this exercise we will review both methods.

Option 1: Modify your input data manually

To modify your input data manually take the following steps:

Step 1. Open the IMCI_training_country_geocoding data file. Step 2. Create a new column called ISO3 in your data table. Step 3. Add a unique country code for each country from the selected coding system to the column. You can access a complete list of ISO-3 codes at http://en.wikipedia.org/wiki/ISO_3166-1_alpha-3 Step 4. When you have completed entering data, you can save the excel spreadsheet and close it. Once the ISO3 columns have been added, your data table should look like the following:

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NAME VALUE ISO3 Afghanistan 35.000 AFG Armenia 35.000 ARM Benin 65.000 BEN Bolivia 85.000 BOL Brazil 15.000 BRA Cote d'Ivoire 5.000 CIV Cameroon 5.000 CMR

Option 2: Use the data entry template with ISO codes

Another option is to use an excel worksheet created by WHO called the DataEntryTemplate which will help to automate the process of assigning codes.

To modify your input data using the DataEntryTemplate, take the following steps:

Step 1. Open the excel spreadsheet called DataEntryTemplate.xls under the folder MXD_geocoding, The list of countries is already populated along with the ISO codes. Step 2. You can enter your data in the last columns: indicator1, indicator2, indicator3, indicator4. Enter the data from IMCI_training_country_geocoding into the column indicator1. Step 3. When you have completed entering data, you can save the excel spreadsheet and close it.

Your data is now ready to be mapped.

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Exercise 2: Geocoding sub-national level data

For this exercise we will be geocoding a cholera outbreak dataset called healthdata_subnational_formatted_result.xls which can be found in the MDX_geocoding folder.

Disease data or health data can be reported by area name (administrative subdivision, province, district, health subdivision, etc.). Capturing these data in GIS involves geocoding using world administrative divisions as a reference dataset then doing a spatial join to link the health data to the geographic data.

For this exercise we will be using the WHO HealthMapper coding system.

Task 2. Assign geocodes to the data. Step 1. Open the excel spreadsheet called healthdata_subnational_formatted_result.xls Step 2. Add a column 'GEOCODE' to your data sheet Step 3. Your table should be similar to the one below Step 4. Without closing Excel, save your excel spreadsheet. Step 5. Start ArcMap and open the Global_detailed template located in the folder MDX_geocoding. Step 6. Save the map file with a new name under MXD_geocoding. Under File, select Save as and name the file subnational_geodocoding. Step 7. Click the Add Data button. Step 8. Click the Connect to folder button. Step 9. Connect to the folder corresponding to the GIS curriculum data sources and click OK. Step 10. In the Add Data dialog box, double-click on Geodatabase.mdb and select the layer Merge_Admin1and2. Click Add. Step 11. This layer contains all the administrative divisions for Africa with a unique geocode (LVLID) for first, second, third and fourth administrative levels. Step 12. Right-click on the Merge_Admin1and2 layer and select Open attribute table. Step 13. In the table options menu, select Find and replace.

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Step 14. Enter the name of the administrative division to search "Lusaka" and click Find Next. Step 15. You should find the row corresponding to the Lusaka province. Step 16. Right-click on the LVLID (ZMP001000000000000000) and select copy. Step 17. Switch to your excel spreadsheet healthdata_subnationallevel_formatted.xls Step 18. Paste the LVLID for Lusaka in the column Geocode. Step 19. Repeat the same operation for each row. Step 20. At the end of the process your table should correspond to the one below.

Disease Start End Country Provinces WHO Geocode / Districts Reg. Cholera 19- 28- Zambia Lusaka AFRO ZMP0010000 Oct- Mar 00000000000 09 -10 Cholera 19- 28- Zambia Copperbelt AFRO ZMP0020000 Oct- Mar 00000000000 09 -10 Cholera 19- 28- Zambia Southern AFRO ZMP0080000 Oct- Mar 00000000000 09 -10 Cholera 01- 10- Mozambique Cabo AFRO MZP0060000 Jan- Apr- Delgado 00000000000 10 10 Cholera 01- 10- Mozambique Niassa AFRO MZP0070000 Jan- Apr- 00000000000 10 10 Cholera 01- 10- Mozambique Zambezia AFRO MZP0100000 Jan- Apr- 00000000000 10 10 Cholera 01- 10- Mozambique Sofala AFRO MZP0080000 Jan- Apr- 00000000000 10 10 Cholera 01- 10- Mozambique Nampula AFRO MZP0010000 Jan- Apr- 00000000000 10 10

Step 21. Save the excel spreadsheet and close it. Your data is now ready to be mapped.

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Exercise 3: Geocoding city or settlement level data

Some health events are geo-referenced at the city or village level. The place name can be converted to a point on a map by capturing latitude and longitude. Capturing these data components requires address matching. It is also possible to geocode a street address.

In case you have to geocode a list of place names in Excel or Access, you can use the online geocoding tasks from Arcgis online. The World Places Locator service can be used to geocode world places including countries, states and provinces, administrative areas, cities, landmarks, water bodies, and more. It is limited to 1,000 batches geocodes in a year.

For this exercise we will be geocoding a list of GOARM partners using two different methods: ArcView address locator and alternative web services.

Option 1: Assign geo-codes using the ArcView address locator method.

Step 1. Open the excel spreadsheet called GOARN partners in the MDX_geocoding folder and look at the file structure. You will notice that there is a column called LOCATION with place names. Close the file. Step 2. Start ArcMap and open the Global_detailed template located in the MDX_geocoding folder. Step 3. Click the Add Data button. Step 4. In the Add Data dialog box, browse to where your data is stored and highlight the appropriate file GOARN Partners.xls. The worksheet is called Partners. Click Add. To add an ArcGIS Online address locator to an ArcMap document:

Step 5. Click the Tools menu, point to Geocoding, then click Address Locator Manager. Step 6. Click Add in the Address Locator Manager dialog box. Step 7. In the Look in drop-down menu, select GIS Servers, click Add ArcGIS Server to highlight it, and click Add. Step 8. In the Add ArcGIS Server wizard, Select Use GIS Services and click Next. Step 9. Select Internet and enter the following Server URL: http://tasks.arcgisonline.com/arcgis/services Click Finish. Step 10. In the ArcGIS Server list, select "arcgis on tasks.arcgisonline.com" and click Add. Step 11. Select the Locators folder and click Add. Step 12. Select the locator you want to add to the ArcMap document ESRI_Places_World and click Add. Step 13. Click Close. Step 14. Right click on the table Partners in the TOC and select Geocode addresses.

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Step 15. Select the Address locator to use Locators/ESRI_Places_World and click OK. Step 16. In the PlaceName dropdown list select LOCATION. Step 17. Select the folder and the name of the output shapefile that will be created and click OK. Step 18. A new shapefile should be added in ArcMap. Step 19. After a table of addresses is geocoded and saved in a geocoded feature class, you may need to review matched addresses or geocode ones that went unmatched. When the geocoded feature class is added to the map, the Review/Rematch Addresses button on the Geocoding toolbar is enabled. Clicking the button opens the Interactive Rematch dialog box, where you can review and select records to rematch. Option 2: Assign geo-codes using a web service.

Step 1. Open the excel file city_web_geocoding and take a look at the fields: NAME, LATITUDE, AND LONGITUDE. All of the cities need latitude and longitude coordinates. Step 2. Open a web browser and open the geocoding web site: http://www.backups.nl/geocoding/index.html Step 3. Enter the place name you are looking for and click on search. Step 4. The geocoding web service will return the geographic location as 'latitude (lat)' and 'longitude (long).' Step 5. Copy the value that appears under the latitude box to your data file under the latitude column. Step 6. Copy the value that appears under the longitude box your data file under the longitude column. Step 7. Repeat for all the cities on your list. Save and close the file when complete. Step 8. Start ArcMap and open the detailed template located in the MDX_geocoding folder. Step 9. Click the Add Data button. Step 10. In the Add Data dialog box, browse to where the city_web_geocoding file and highlight then click Add. Step 11. Right click on the data table you have added and select Display XY data. Step 12. Indicate the longitude column for the X field. Step 13. Indicate the latitude column for the Y field. Step 14. Click OK. Step 15. The places should be displayed on the map.

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