- Open Access
Tracking the polio virus down the Congo River: a case study on the use of Google Earth™ in public health planning and mapping
© Kamadjeu; licensee BioMed Central Ltd. 2009
- Received: 02 December 2008
- Accepted: 22 January 2009
- Published: 22 January 2009
The use of GIS in public health is growing, a consequence of a rapidly evolving technology and increasing accessibility to a wider audience. Google Earth™ (GE) is becoming an important mapping infrastructure for public health. However, generating traditional public health maps for GE is still beyond the reach of most public health professionals. In this paper, we explain, through the example of polio eradication activities in the Democratic Republic of Congo, how we used GE Earth as a planning tool and we share the methods used to generate public health maps.
The use of GE improved field operations and resulted in better dispatch of vaccination teams and allocation of resources. It also allowed the creation of maps of high quality for advocacy, training and to help understand the spatiotemporal relationship between all the entities involved in the polio outbreak and response.
GE has the potential of making mapping available to a new set of public health users in developing countries. High quality and free satellite imagery, rich features including Keyhole Markup Language or image overlay provide a flexible but yet powerful platform that set it apart from traditional GIS tools and this power is still to be fully harnessed by public health professionals.
- Public Health Professional
- Shape File
- Polio Eradication
- Polio Virus
- District Medical Officer
"Finishing the job of polio eradication is our best buy. We must do it. We are leaving a perpetual gift to generations of children to come" WHO Director-General Dr. Margaret Chan .
Mapping in public health is not new. The cholera map by John Snow marked a critical turn in the use of maps to understand geographic patterns and disease . Geographic Information System (GIS) technology is increasingly used by public health professionals, policy makers and other public health actors to better understand how geographic relationships affect disease transmission patterns [3–6], access to health care [7–11] and health outcome[12, 13].
The use of GIS in public health is growing, a consequence of a rapidly evolving technology and increased accessibility to a wider audience. The recent development of web based mapping application like Google Maps™ (GE)  which provides free and easy access to geographic data and tools have contributed to the popularity of these new mapping approaches both within the general audience and among public health professionals.
The use of satellite images in public health has increased over time and covers areas as diverse as research, disaster management, outbreak response, emergency preparedness and humanitarian crisis [3, 15–19]. Unfortunately, public health professionals still have difficulties in accessing relevant satellite data based on quality, time and cost . GE is a virtual globe that maps the earth by the superimposition of images obtained from satellites imagery and aerial photography. The availability of free satellites images in GE  has contributed to its popularity in the general public and among public health professionals. If GE is becoming a key mapping infrastructure for public health [23–29]; there are however, some characteristics that set it apart from traditional GIS software, notably its limited spatial data processing, analysis and modelling capabilities .
GE is packaged under two different licenses: Google Earth™, a free version with limited functionality and Google Earth Pro™ which has more functionality and is intended for commercial used. A third license called Google Earth Plus™ was discontinued . All GE versions are available for use on personal computers running Microsoft Windows Operating systems, Mac OS X10.9 and above, Linux and FreeBSD .
Google Earth™ imagery
Images in GE come from satellites and aerial photography (images from airplanes, kites and balloons). Some images are also provided by city or state governments. These images are not real time; the average age of high resolution images varies between 6 months to 5 years . For this reason, GE images should be checked for accuracy when used for planning, because they may no reflect recent changes in landscape (new urban development, recent disasters etc.) Most lands are covered with a resolution of 15 meters per pixel and some populated centres of North America and Europe are covered with an even higher resolution (few meters by pixel), while oceans are covered with a much lower resolution, in the order of 500 m. In general the level of details of images in GE varies greatly; they tend to be more accurate in North America and Europe but are far less accurate when it comes to rural areas in developing countries. Clouds, shadows and heavy vegetal coverage also affect the visibility of some places of interest [31, 32].
Because GE is primary a map viewer, it provides little functionality for creating traditional public health maps from scratch, although GE Pro™ allows the importation of the popular ESRI shape file (*.shp) and geospatial data (latitude and longitude) in tabular format . Generating traditional public health maps with GE is still beyond the reach of most public health professionals, since this process requires a new set of skills (KML, geocoding) normally not prevalent in this group of professionals.
In this article, we describe how we used GE in public health planning, through the example of poliomyelitis (polio) eradication activities in the Democratic Republic of Congo (DRC) and we share the methods we used to generate public health maps for advocacy, training and to help understand the relationship between the entities involved in the polio outbreak and response. The method describes in this paper is applicable to all the current versions of GE and complement methods previously described to demonstrate the potential of these technologies and to help public health professionals and neogeographers face the "geo-rich society" [34, 35].
Polio eradication initiative and recent polio outbreaks in DRC
In 1988, the World Health Assembly voted to set the global goal for polio eradication . Since then, the Global Polio Eradication Initiative remains the largest, internationally coordinated public health project. By the end of 2007, only 4 countries remained endemic for polio: Afghanistan, India, Pakistan and Nigeria  with persistent risks of exportation of the virus to polio free countries. This was the case in the Democratic Republic of the Congo (DRC), a country free from polio virus circulation since 2004, where 54 cases of polio caused by wild polio virus type 1 (WPV1) were reported in 4 provinces from February 2006 to December 2007 . In response to this outbreak, mass immunization campaigns, also known as Supplemental Immunization Activities (SIA), were launched to interrupt the circulation of the virus and eliminate the risk of exportation; internally to unaffected provinces and externally to neighbouring countries. From the beginning of the outbreak in February 2006 to September 2007, 6 rounds of SIA, targeting all children aged 9 to 59 months and living in affected and high risk districts, were conducted. The initial impact of the campaign to alter the progression of the polio outbreak was low, as it seemed to progress north-east, following the course of the Congo River. A review of SIA activities conducted in August 2007 recommended specific strategies and actions to improve the quality of vaccination campaigns and consequently halt the circulation of WPV1. This resulted in the adoption of the "River Strategy", specifically targeting populations neighbouring the river. Since the beginning of 2008 the outbreak seems to be contained; by the time of this report, only one polio case due to WPV1 was reported, with onset of paralysis in February 2008.
The Congo River and the polio outbreak
The Congo River is the second longest river in Africa (4700 km). Because it is readily navigable in sections, especially between Kinshasa and Kisangani, it is a major trade route and sees intense movement of persons and goods .
GE images are not real time; this should be taken into consideration when deciding to use it as a source of image. It will be inappropriate to use it for features likely to quickly change over time (e.g. seasonal flooding, rapid urban development), because available images may not reflect the current reality. However GE can significantly improve our knowledge of the topography and provide key information for planning. Addition of KML layers and the use of other GE features provide an opportunity to design powerful visual effects for planning, teaching and advocacy.
GE has the potential of making mapping accessible to a new set of public health users in developing countries. High quality satellite imagery, rich features, including KML or image overlay provide a flexible but yet powerful platform that set it apart from traditional mapping tools.
Ethical consideration s: the project did not directly involve human subjects; therefore, approval from an institutional review board was not sought.
Micro-planning is critical for successful implementation of polio SIA. It identifies population groups likely to be missed and recommends special activities to reach them with vaccination services. For the River Strategy, the micro planning process included key field players: district medical officers, consultants, community members, fishermen, boat drivers, and sailors.
Google Earth™ and the Congo River
The use of maps is well established in immunization. Hand-drawn maps have been used by vaccination teams on the ground to plan their daily activities; choropleth (colour coded) or composite maps have been used intensively to display vaccine preventable diseases and immunization coverage information across geographical units. GE has been used increasingly as a source of maps but the system is primary a viewer and provided limited options for creating traditional public health maps. Also, the skills require to dynamically generate complex KML map files using computer programming languages is still beyond the reach of public health professionals.
Keyhole Markup Language (KML) is an XML-based language for expressing geographic annotation and visualization on Web-based, two-dimensional maps and three-dimensional Earth browsers like Google Earth [39–41]. To generate thematic KML maps, we went through three basic steps:
Step 1 – Conversion of shape file into KML
The ESRI shapefile (*.shp) stores geospatial vector data in a tabular format for GIS software. It is developed and regulated by ESRI  as an open specification for data interoperability among ESRI and other software products. A shape file is a set of three files that are mandatory to store the content of the shape file. The three mandatory files that make up the shapefile are: 1) the shape file (*.shp) format describing the feature geometry, 2) the shape index (*.shx) format storing the positional index of the geographic feature and 3) the data format (*.dbf) storing the columnar attribute for each shape in dBase III format .
We generated district and province boundary KML files by converting existing shape files into KML using a shape-to-kml converter . The tool we used is a free utility that inputs shape file and outputs a KML file formatted based on user's specifications. Several shape-to-kml applications; both free and license exist but were not fully evaluated.
Step 2 – Loading geographic feature names and coordinates in the database
Step 3 – dynamic generation of KML using php
KML files were dynamically generated using simple scripts written with the web scripting language PHP . Additional file 3 demonstrates how we used PHP to dynamically fill the content of KML polygons with colour based on the value of immunization coverage/population density for each district. In dot-mapping, polio cases were mapped using the lat/long coordinate of the district of residence of the case. To clustering avoid of points from the same districts (same latitude and longitude data), the first occurrence of the district's latitude and longitude was taken as the central coordinate around which subsequent identical points were randomly dispersed.
To explore and visualize the relationship of the current outbreak with impact measures e.g. natural structures, dot maps, choropleth maps and combinations of both were generated using available 2007 data (additional file 4).
Acute flaccid paralysis (AFP), routine immunization coverage and population data were obtained from the DRC Ministry of Health and the World Health Organization DRC country office. The data were reformatted and stored in the database hosted on a local Apache/PHP/MySQL server [45–48].
The DRC subset of the GEOnet Names Server (GSN), a comprehensive database of foreign geographic feature names provided by the US National Geospatial Intelligence Agency  was used to extract coordinates (Latitudes and Longitudes) information for place names. Polio cases data are stored in the AFP database which includes location information (village, district and province of residence of case, but no geo-codes), clinical and laboratory information. Since the AFP database does not provide geo-codes, location of case was approximated to the most completely available geographical unit, which in this case was the district of residence of the case. Coordinates values for cases were obtained by linking the AFP database with the GSN database using the district of residence of cases
Notes about GSN country file table
The GSN provides geographical names and geographic coordinates on DMS (Degrees – Minutes – Seconds) and decimal formats for a considerable number of geographic features and places around the world. The GSN table for DRC available for download on November 2008 consisted of 31834 records of geographic names information (tab separated text format), amenable to easy input into database management systems or spreadsheets. An overview of the GSN table shows that there can be more than one entry information for the same feature/place and more than one feature/place can have the same name. This lack of normalization makes the exploitation of the database prone to ambiguity and inconsistency; this should be kept in mind and acted upon when using any GSN dataset.
I would like to acknowledge my colleagues in the Democratic Republic of the Congo, both from the Ministry of Health and from the World Health Organization for the hard work and commitment to the task. We also acknowledge the Google Earth team for providing a free copy of Google Earth Pro™.
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