Chigoe Flea Eradication ProjectKelly Wright, M.S. Candidate

University of Southern CaliforniaGeographic Information Science and Technology

SSCI 591: WebGIS, Dr. Jennifer SwiftFinal Project: 03 December, 2015

INTRODUCTION

Tunga penetrans—also called the sand flea, Chigoe flea, or Jigger—is a hematophagic insect whose gravid female parasitizes the skin of its mammal host. Because it cannot jump as high as a domestic cat or dog flea, it primarily infests its host’s feet, living off its host’s blood and producing eggs while embedded inside the skin. In addition to humans, the Jigger infests pigs, dogs, cats, cattle, sheep, horses, mules, rats, and other wild animals.1 Tungiasis is described as an epidermal parasitic skin disease (EPSD) resulting from Chigoe Flea superinfestation (Feldmeier et al. 2009). It is a painful, disfiguring, and debilitating condition. While people rarely die directly from an infestation, it is common for the affected to suffer from secondary infection leading to gangrene and amputation or loss of fingers and toes. Many people are unable to walk due to the pain associated with a superinfection of T. penetrans. Afflicted children are likely to stop attending school due to painful lesions, insomnia from itching, and fear of persecution and ostracism (Njau et al. 2012, Heukelbach 2005, Feldmeier et al. 2002, Feldmeier et al 2014). Removing purulent material and flea remains with dirty needles or razor blades may also lead to transmission of blood-borne pathogens such as hepatitis B and C virus and HIV (Feldmeier et al. 2013).

The purpose of this project is to create a WebGIS application as to enable users to explore and map social and environmental risk factors for Chigoe Flea superinfestation in Kenya. Through subsequent application designs, it is the author’s hope to be able to map the coverage areas and treatment efforts of various aid groups, and collect georeferenced data about jigger victims to better understand risk factors specific to rural Kenya. Esri ArcGIS Server will be used to create this app.

What better use for GIS than improving the lives of millions of people?

STUDY AREA

First recorded by sailors on Christopher Columbus’ ships, T. penetrans is believed to have originated in the Caribbean islands and Central America. Through maritime trade—primarily the Afro-Caribbean slave trade—it was transported around the world, where it thrives in sandy, warm conditions. South America, sub-Saharan Africa, and tropical regions of Asia are the worst afflicted. While T. penetrans is a worldwide tropical pest, most humanitarian aid occurs at the local level. Many studies and aid programs already exist in the vast country of Brazil, with support from all administrative levels of government. It is the author’s belief that a smaller study area, with data available in English, would be a better choice for this project.

1 D.S. Smith, MD, MSc, DTM&H. Tungiasis. Medscape. http://emedicine.medscape.com/article/231037-overview

Kenya is a primarily English-speaking country whose decentralized government does not have the resources or cooperation at hand to effectively address the severity of the Chigoe Flea problem—but it does already have over 40 Chigoe flea-related relief organizations operating throughout its 47 counties (Feldmeier et al. 2013).2,3,4 Kenya is more politically stable than other war-torn nations in the region, and the availability of data is much higher than its neighbors. Many organizations, NGOs and charities in Kenya have embraced the digital age, and are beginning to understand the intrinsic value of spatial information.

Approximately 4% of Kenya's total population suffer from jigger infestation—1.4 million Kenyans. The total population at risk—10 million—are the very young, elderly, or physically and/or developmentally disabled. In some communities, Jigger affliction is believed to be a literal curse and relatives abandon the badly afflicted. Population density within rural areas has increased considerably in the last twenty years; coupled with the construction of roads and increasing mobility, this has led to the proliferation of uncontrolled outbreaks (Feldmeier et al. 2013).

A NOTE ABOUT KENYA’S ADMINISTRATIVE BOUNDARIES:

Figure 2. ArcGIS Desktop showing different administrative boundaries over the last twenty years

2 National Policy Guidelines on Prevention and Control of Jigger Infestations. 2014. Division of Environmental Health, Ministry of Health, Republic of Kenya. Retrieved from http://www.jigger-ahadi.org/National%20Policy%20Guidelines%20for%20Prevention%20and%20Control.pdf3 Ahadi Kenya Trust. 2011. The jigger menace in Kenya report, vol 2. http://www.ahadi-jigger.org4 Sole Hope. “What Are Jiggers?” http://www.solehope.org/jiggers/

Figure 1. Kenya, courtesy of Google Maps

Rapid and dramatic changes in administrative boundaries in Kenya have occurred over the last twenty years. The Ministry of Planning and National development, Central Bureau of Statistics authored a brief history of the census in Kenya, outlining the inherent problems5 in mapping a region in political flux. The legacy system of Provinces, Districts, Divisions, Locations, and sub-locations was continuously updated for over ten years, meaning that GIS datasets produced in Kenya from 1995-2013 had widely varying administrative boundaries. A variance in enumeration units makes spatial analysis difficult; a lack of established standards in data collection over this period resulted in the production of many datasets that are now functionally obsolete. Therefore, it is of the utmost importance to document the dates and administrative boundaries in use when data was collected.

APPLICATION DEVELOPMENT

The Web Application6 and Website7 for this project were designed using a series of Esri programs:

ArcGIS Desktop 10.2 and 1.3 were used for data compilation, editing, and cartographic design.

ArcGIS Server was used to register the database with ArcGIS Online (AGO)

ArcGIS Server Manager was used to create a server environment within the USC SSCI AGO environment.

After analyzing the service and reconciling publishing errors identified by the WNS wizard, the map was published to AGO as a Web Map Service (WMS). It was published to the USC Spatial Sciences Organizational Account.8

In the USC SSCI environment, the web app was configured using ArcGIS WebApp Builder. The organizational account provides greater flexibility of design and better widget options than the free AGO account.

The website, http://www-scf.usc.edu/~kawright/Chigoe/ChigoeEradication.html was designed using Adobe Creative Cloud’s9 Dreamweaver as the web editor. It contains HTML, CSS, JavaScript and JQuery elements. Filezilla10 was used to upload files to the student web server at USC.

Microsoft Windows 10 was used with no issue. VMWare,11 in conjunction with Cisco AnyConnect Secure Mobility Client, was used to access remote virtual machines installed with ArcGIS Server.

5 Odhiambo, E.A., Ndilinge, B.M. 2005. Census Cartography: The Kenyan Experience. Ministry of Planning and National Development, Central Bureau of Statistics. http://www.cartesia.org/geodoc/icc2005/pdf/oral/TEMA26/Session%203/ODHIAMBO%20E.A.pdf6 http://uscssi.maps.arcgis.com/apps/webappviewer/index.html?id=4563a0de487046eb8c74eccfedc94ba07 http://www-scf.usc.edu/~kawright/Chigoe/ChigoeEradication.html8 http://uscssi.maps.arcgis.com/home/index.html9 http://www.adobe.com/creativecloud.html10 https://filezilla-project.org/11 http://www.vmware.com/

Build the Map

Data DiscoveryCartographic Design

Publish Service to

AGO

Analyze ServiceReconcile Errors

Embed in Webpage Test App

The site and app were tested in the following browsers: Chrome Version 46.0.2490.86 m, Microsoft Edge Version 20.10240.16384.0, Opera Version 33.0.1990.115, and Firefox Version 40.0.3.

DATA

The following sites were indispensable for this project: GeoNetwork - Food and Agriculture Organization of the United Nations12

Global Land Cover Network – AFRICOVER Project13

Open Data for Africa WebGIS – Kenya14

Kenya Open Data WebGIS15

Virtual Kenya WebGIS16

World Resources Institute – Kenya GIS Data17

GIS DATA SOURCES:Title Multipurpose Landcover Database for Kenya - AFRICOVEROriginator Food and Agriculture Organization of the United Nations, Ministry of Environment and Natural ResourcesAbstract The full resolution land cover has been produced from visual interpretation of digitally enhanced high-res

LANDSAT TM images (Bands 4,3,2) acquired mainly in the year 1995. The land cover classes have been developed using the FAO/UNEP international standard LCCS classification system.

Publication Date 04 April 2002 Format Esri ShapefileLink http://www.fao.org/geonetwork/srv/en/metadata.show?id=38098&currTab=simple

Title Towns and Urban CentersOriginator Digitized by International Livestock Research Institute, ILRI, GIS group from Kenya topographic sheets scale

1:250,000 for Northern Kenya and 1:50,000 for rest of Kenya from Survey of KenyaAbstract The coverage shows the towns and urban centres in Kenya derived from the Kenya topographic sheets of scale,

1:250,000 for Northern Kenya and 1:50,000 for the rest of Kenya. There are approximately 1620 towns and urban centres captured in this layer. Town_id: Unique identification for each town class. The towns have been classified into 6 categories namely: (1) Municipality; (2) Township/Town; (3) Trading centre; (4) Market centre;(6) Lodges/camps; (11) City.

Publication Date August 2000 Format Esri ShapefileLink http://192.156.137.110/gis/search.asp?id=280

Title Annual RainfallOriginator Japanese International Cooperation Agency (JICA), National Water Master Plan, KenyaAbstract This coverage shows the annual rainfall distribution in millimeters per year for Kenya. It was done by the

Japanese International Co-operation Agency (JICA), National Water Master Plan, Kenya. Classification code for areas with similar rainfall amounts as follows (2) <200 (3) 200-400 (4) 400-600 (5) 600-800 (6) 800-1200 (7) 1200-1600 (8) 1600-2000 (9) 2000-2400 (10) >2400. Hosted by International Livestock Research Institute.

Publication Date Not Listed Format Esri ShapefileLink http://192.156.137.110/gis/search.asp?id=318

Title Health Centers in KenyaOriginator Kenya Medical Research Institute KEMRI/Welcome Trust Collaborative Programme, TALA Research Group,

12 http://www.fao.org/geonetwork/srv/en/main.search?title=africover13 http://www.glcn.org/activities/africover_en.jsp14 http://kenya.opendataforafrica.org/15 https://www.opendata.go.ke/en/16 http://www.virtualkenya.org/17 http://www.wri.org/resources/data-sets/kenya-gis-data

Department of Zoology, University of Oxford, Ministry of Health and Centre for Tropical MedicineAbstract This is a coverage showing health service providers for Kenya. It shows the relative location of health service

providers for Kenya categorised by type and supporting agency.Publication Date 01 July 2007 Format Esri ShapefileLink http://192.156.137.110/gis/search.asp?id=426

Title Malaria Endemicity – Zones Originator PIBHMC, CRED, PIFSC, NMFS, NOAAAbstract This coverage shows the classification of malarial endemicity in Kenya done at district level by Welcome Trust. Publication Date 2000 Format Esri Shapefile Link http://192.156.137.110/gis/search.asp?id=342

Title Census 2009: Population by Sex, Household, Area, Density and DistrictOriginator Kenya National Bureau of StatisticsAbstract Census 2009: Population by Sex, Household, Area, Density and DistrictPublication Date 29 August 2011 Format Excel Spreadsheet XLSX (Exported)Link https://www.opendata.go.ke/Population/Summary-Population-Distribution-by-District/3pt4-nkga

Title Primary Schools in KenyaOriginator School Mapping Database, Ministry of Education, Kenya Open Data, SocrataAbstract This database documents Primary Schools in Kenya from a 2007 study. Attributes: Name of School,

Level of Education, Status of School, Sponsor of School, Institution Type_1 (Girls Only, Boys Only, Mixed), Institution Type_2 (Day Only, Day and Boarding, Boarding Only), Institution Type_3 (Ordinary, Integrated), Pupil Teacher Ratio, Pupil Classroom Ratio, Pupil Toilet Ratio, Total Number of Classrooms, Boys Toilets, Girls Toilets, Teachers Toilets, Total Boys, Total Girls, Total Enrollment, GOK TSC Male, GOK TSC Female, Local Authority Male, Local Authority Female, PTA BOG Male, PTA BOG Female, Other Male, Others Female, Non-Teaching Staff Male, Non-teaching Staff Female, Province, County, District, Division, Location, Constituency, Latitude, Longitude

Publication Date 2007 Format Database (exported as .xlsx)Link https://dev.socrata.com/foundry/#/www.opendata.go.ke/ud2q-hvhq

Title 2009 Administrative Boundaries of KenyaOriginator DIVA GIS: University of California, DavisAbstract This is a shapefile of boundaries in the year 2009. See note on Kenya Administrative boundaries above.Publication Date 01 July 2007 Format Esri ShapefileLink http://www.diva-gis.org/gdata

Title Kenya Poverty Map 1999Originator International Livestock Research Institute and the Central Bureau of Statistics, Ministry of Planning and

National DevelopmentAbstract Attributes: Loc_type: Type of location whether rural or urban. Pop_1999:Population according to 1999

population and housing census. No_poor99: No of poor people 1999 (Individual headcount poverty). Pov_dens99: Density of poor people 1999 (poverty density). Pov_rate99: Proportions of poor people below the poverty line. 1999 Pov_gap99: Percentage gap to bridge for the poor to reach the poverty line 1999.

Publication Date 2001 Format Esri ShapefileLink http://192.156.137.110/gis/search.asp?id=428

WEB PAGE DESIGN

Simplicity and ease-of-use were the two driving factors for this WebGIS. Most users do not have a background in GIS and may not understand the purpose or function of an app. It is for this reason that a detailed Help File was included in the app (see RESULTS section). The app itself was designed to keep all related Widgets together on the left of the screen. Map Controls were only in one spot. All icons were kept to the left side of the app. Too many web applications use vague, stylized icons that are not intuitive to the average user.

While a great deal of written information regarding the project has been developed, it is overwhelming to see it displayed on a computer screen—the large blocks of scientific text and scholarly citations are off-putting to many, and the overall point of this project is to make people aware of what a menace the Chigo flea is, not to make them experts. For this reason, background information on the Chigoe flea was limited to one paragraph at the top of the webpage.

The application itself should be immediately seen—it, after all, is the main component of this project. However, on the webpage it has been constrained to a smaller container than full-screen. The AGO app automatically resizes on different devices, and was tested on an iPad Air and an iPhone 4S.

In another attempt to limit visible information, a JQuery script was embedded, called Accordion18 but at the time of publish an error existed in the JQuery library that preventing the accordion container from resizing its contents. This leaves large open spaces on the webpage and requires the user to scroll up and down to see content. Workarounds are continuing to be explored.

RESULTS

At the time of publish, the following subsections were at the website: What is a Chigoe Flea? Applying Geographic Information Systems to Strategically

Manage the Eradication of the Chigoe Flea in Kenya WebGIS: Exploring Risk Factors for Chigoe Flea Infestation

(embedded WebGIS application) GIS Data Sources Ecological and Clinical Presentation Mapping Risk Factors Distributing Aid, Preventative Treatment, and Education Organizing the Fight The Power of Volunteered Geographic Information (VGI) and

Mobilizing the Masses Related Websites What are Neglected Tropical Diseases? How Can I Help? (a list of Chigoe Flea-related charities)

The website can be viewed at http://www-scf.usc.edu/~kawright/Chigoe/ChigoeEradication.html.

Basic Map Controls are in the upper left-hand corner of the map: Zoom in and out to see more layers, using the +/- button or the mouse scroll wheel. As you

zoom in, different layers become visible.18 https://api.jqueryui.com/accordion/

Figure 3. iPhone 4s WebApp

The Home icon zooms the map out to its full extent.

The Basemap Gallery (four-pane square) allows you to choose different map types. National Geographic is the default.

The Search bar is just that, a search bar.

Figure 4. Full-screen Web App at ArcGIS Online

The black border on the left contains five icons, or Widgets. When any of the icons is clicked, a panel slides open to display the associated application. Each open widget shows as a folder "tab" at the top of the panel:

The Legend only shows layers visible at the current scale--as you zoom in on the map, different layers will appear.

The Layer List (looks like a stack of papers) displays all data associated with the web application, including layers that are currently turned off. Turn a layer on or off by checking or unchecking the box next to it. (Remember, some layers are only visible when zoomed in!)

The Query Attribute tool (looks like a funnel) can be used to display records that match a specific value--explore areas where less than 50mm of rain falls per year, or see schools that lack a toilet by viewing pre-set queries.

The Measure tool (looks like a ruler) allows you to take an approximate measurement of a line or an area. Create a line or shape on the map with a start and end mouse click. The default measure is in kilometers.

The Help feature is what you are reading right now! Be sure to visit the website!

The Analysis tool (looks like a circle with dots in it) is a special tool that performs various location-based queries. It allows you to query the data using spatial constraints, or proximity to other features. It is located on the map, under the search bar (See Figure 3). The following Analysis tools are enabled in the Widget:

o Calculate Densityo Create Bufferso Derive New Locationso Extract Datao Find Existing Locationso Find Nearesto Merge Layerso Overlay Layers

To easily view all Attribute Tables, click on the arrow in the middle of the bottom border of the map. Attribute tables are navigated as tabs.

Figure 5. Web App with Legend and Operational Layers

CONCLUSIONS AND LOOKING FORWARD

The goal of this WebGIS was to enable users to explore different social and environmental risk factors that contribute to Tungiasis in Kenya. While the datasets are old and of different administrative boundaries, the idea is sound. It is hoped that more recent GIS data pertinent to this project will soon

become available, and throughout the publication process other datasets were found, but not integrated due to lack of time. This project is intended to be the first of three WebGIS apps built to help combat the Chigoe Flea:

Compile a directory of charities, NGOs, and government agencies that provide public service with regards to Jigger eradication; design a gateway for registering an organization with the web service, including coverage area and needs. Estimated time of completion: January 2016.

Compile a PPGIS/VGI (potentially offline) component to the web app allowing VGI to be contributed by the registered organizations to better organize and prioritize locations in greatest need. VGI would explore:

o (While patient privacy must be of the utmost importance, individual,) geolocated patient information (Age, sex, education, HIV status, family status, time afflicted, repeat infestations, shelter floor type, cohabitation with livestock, presence of shoes, access to water, frequency of bathing) will be invaluable to researchers and aid workers alike.

o GIS tracking the number, types, and dates of shoes distributed/neededo GIS tracking pesticide/repellant distributed/needed and/or date applied19 o GIS tracking the locations of homesites in need of concrete or plaster for floorso GIS tracking the locations of homesites where livestock cohabit with residents o GIS providing aid workers with nearby areas in need of humanitarian or medical aid

It is this author’s sincerest hope that by combining the latest geo-spatial technology with proven feet-on-the-ground methods, that the Chigoe flea will someday be referred to in the past tense. To be sure, in 1986 Jimmy Carter didn’t believe that in only thirty years, Guinea worm disease would be poised to become the second human disease in history to be eradicated. With this and other global and local efforts, maybe the same will be said of the Jigger in 2045!

REFERENCES

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Feldmeier H, Eisele M, Van Marck E, Mehlhorn H, Ribeiro R, Heukelbach J. (2004) Investigations on the biology, epidemiology, pathology and control of Tunga penetrans in Brazil: IV. Clinical and histopathology. Parasitol Res. Oct. 94(4):275-282.

Feldmeier, H., Heukelbach, J. (2009) Epidermal parasitic skin diseases: a neglected category of poverty-associated plagues. Bulletin of the World Health Organization. 87:152-159. doi: 10.2471/BLT.07.047308

Feldmeier, H., Heukelbach, J. , Eisele, M. , Sousa, A. Q., Barbosa, L. M. M. and Carvalho, C. B. M. (2002) Bacterial superinfection in human tungiasis. Tropical Medicine & International Health, 7: 559–564. doi: 10.1046/j.1365-3156.2002.00904.x

Feldmeier H., Heukelbach J., Ugbomoiko U., Sentongo E., Mbabazi P., von Samson-Himmelstjerna, G., Krantz I. (2014) Tungiasis—A neglected disease with many challenges for global public health. PLoS Neglected Tropical Diseases, 8(10):e3133. doi: 10.1371/journal.pntd.000313319 http://www.who.int/whopes/questions/en/

Feldmeier, H., Kehr, J.D., Heukelbach, J. (2006) A plant-based repellant protects against Tunga penetrans infestation and sand flea disease. Acta Tropica, 99(2-3): 126-136. doi:10.1016/j.actatropica.2006.05.013

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Heukelbach, J., Costa, A.M., Wilcke, T., Mencke, N., Feldmeier, H. (2004) The animal reservoir of Tunga penetrans in severely affected communities of north-east Brazil. Medical and Veterinary Entomology, 18(4):329-35. doi: 10.1111/j.0269-283X.2004.00532.x

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DATA REFERENCES

ke_landcover_ge.shp. 2002. [shapefile] Multipurpose Landcover Database for Kenya. Food and Agriculture Organization of the United Nations. http://www.fao.org/geonetwork/srv/en/metadata.show?id=38098&currTab=simple (06 November 2015)

Health Facilities. 2007. Ministry of Health, Kenya National Bureau of Statistics. Kenya Open Data. https://www.opendata.go.ke/Health/Health-Facilities/89zb-g69r (08 November 2015)

Kenya Primary Schools. 2007. School Mapping Database, Ministry of Education. Kenya Open Data. https://www.opendata.go.ke/Education/Kenya-Primary-Schools/p452-xb7c (08 November 2015)

Water Point Mapping in Kisumu, Busia, Kajiado, Kiamby Counties. 2013. Ministry of Environment, Water and Natural Resources (MEWNR), SNV-Netherlands, and TWAWEZA. Kenya Open Data. https://www.opendata.go.ke/dataset/Water-Point-Mapping-in-Kisumu-Busia-Kajiado-Kiambu/s63d-ajgd (12 November 2015)

kenya_all_towns.shp. [shapefile] International Livestock Research Institute (ILRI). http://192.156.137.110/gis/search.asp?id=280 (16 October 2015)

kenya_rainfall_distribution.shp. [shapefile] Rainfall in Kenya (in millimeters). International Livestock Research Institute (ILRI). http://192.156.137.110/gis/search.asp?id=318 (16 October 2015)

kenya_health.shp. [shapefile] Health Facilities in Keyna. International Livestock Research Institute (ILRI). http://192.156.137.110/gis/search.asp?id=426 (16 October 2015)

kenya_malaria_zones.shp. [shapefile] Malaria Endemicity in Kenya. International Livestock Research Institute (ILRI). http://192.156.137.110/gis/search.asp?id=342 (16 October 2015)

kenya_rivers.shp [shapefile] Rivers of Kenya. International Livestock Research Institute (ILRI). http://192.156.137.110/gis/search.asp?id=382 (16 October 2015)

kenya_poverty_1999.shp. [shapefile] Kenya Poverty 1999. International Livestock Research Institute (ILRI). http://192.156.137.110/gis/search.asp?id=428 (16 October 2015)

kenya_soils.shp [shapefile] Kenya Soils Survey. International Livestock Research Institute (ILRI). http://192.156.137.110/gis/search.asp?id=419 (16 October 2015)

Summary Population Distribution by District. 2009. [RSS feed] Kenya Open Data. Information and Communication Technology Authority (ICT), Ministry of Information Communication and Technology, Government of Kenya. https://www.opendata.go.ke/Population/Summary-Population-Distribution-by-District/3pt4-nkga (08 November 2015)

KEN_adm.zip [shapefiles] Administrative Areas. DIVA GIS. University of California at Davis. http://biogeo.ucdavis.edu/data/diva/adm/KEN_adm.zip (20 November 2015)