Eveline Hürlimann 1 , 2 , Nadine Schur 1 , 2 , Konstantina Boutsika 1 , 2 , Anna-Sofie Stensgaard 3 , 4 , Maiti Laserna de Himpsl 1 , 2 , Kathrin Ziegelbauer 1 , 2 , Nassor Laizer 2 , 5 , 6 , Lukas Camenzind 2 , 5 , Aurelio Di Pasquale 1 , 2 , Uwem F. Ekpo 7 , Christopher Simoonga 8 , 9 , Gabriel Mushinge 8 , Christopher F. L. Saarnak 4 , Jürg Utzinger 1 , 2 , Thomas K. Kristensen 4 , Penelope Vounatsou 1 , 2 , *
13 December 2011
After many years of general neglect, interest has grown and efforts came under way for the mapping, control, surveillance, and eventual elimination of neglected tropical diseases (NTDs). Disease risk estimates are a key feature to target control interventions, and serve as a benchmark for monitoring and evaluation. What is currently missing is a georeferenced global database for NTDs providing open-access to the available survey data that is constantly updated and can be utilized by researchers and disease control managers to support other relevant stakeholders. We describe the steps taken toward the development of such a database that can be employed for spatial disease risk modeling and control of NTDs.
With an emphasis on schistosomiasis in Africa, we systematically searched the literature (peer-reviewed journals and ‘grey literature’), contacted Ministries of Health and research institutions in schistosomiasis-endemic countries for location-specific prevalence data and survey details (e.g., study population, year of survey and diagnostic techniques). The data were extracted, georeferenced, and stored in a MySQL database with a web interface allowing free database access and data management.
At the beginning of 2011, our database contained more than 12,000 georeferenced schistosomiasis survey locations from 35 African countries available under http://www.gntd.org. Currently, the database is expanded to a global repository, including a host of other NTDs, e.g. soil-transmitted helminthiasis and leishmaniasis.
An open-access, spatially explicit NTD database offers unique opportunities for disease risk modeling, targeting control interventions, disease monitoring, and surveillance. Moreover, it allows for detailed geostatistical analyses of disease distribution in space and time. With an initial focus on schistosomiasis in Africa, we demonstrate the proof-of-concept that the establishment and running of a global NTD database is feasible and should be expanded without delay.
There is growing interest in the scientific community, health ministries, and other organizations to control and eventually eliminate neglected tropical diseases (NTDs). Control efforts require reliable maps of NTD distribution estimated from appropriate models and survey data on the number of infected people among those examined at a given location. This kind of data is often available in the literature as part of epidemiological studies. However, an open-access database compiling location-specific survey data does not yet exist. We address this problem through a systematic literature review, along with contacting ministries of health, and research institutions to obtain disease data, including details on diagnostic techniques, demographic characteristics of the surveyed individuals, and geographical coordinates. All data were entered into a database which is freely accessible via the Internet ( http://www.gntd.org). In contrast to similar efforts of the Global Atlas of Helminth Infections (GAHI) project, the survey data are not only displayed in form of maps but all information can be browsed, based on different search criteria, and downloaded as Excel files for further analyses. At the beginning of 2011, the database included over 12,000 survey locations for schistosomiasis across Africa, and it is continuously updated to cover other NTDs globally.