Background: 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.

Methodology: 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.

Principal findings: 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.

Conclusions: 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.

The authors have declared that no competing interests exist.

Figure 1

Figure 1. Flow-chart showing the steps used...

Figure 1. Flow-chart showing the steps used to assemble the GNTD database.

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Figure 2

Figure 2. African map of schistosomiasis survey...

Figure 2. African map of schistosomiasis survey locations based on current progress of the GNTD...

Figure 3

Figure 3. Observed prevalence of S. mansoni ...

Figure 3. Observed prevalence of S. mansoni based on current progress of the GNTD database...

Figure 4

Figure 4. Observed prevalence of S. haematobium ...

Figure 4. Observed prevalence of S. haematobium based on current progress of the GNTD database...