Toward an Open-Access Global Database for Mapping, Control, and Surveillance of Neglected Tropical Diseases

Abstract

BackgroundAfter 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.MethodologyWith 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 FindingsAt 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.ConclusionsAn 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.

Changing Policy and Practice in the Control of Pediatric Schistosomiasis

“…Nevertheless, schistosome prevalence levels among preschool-aged children are closely related to those of older children and adults in the same countries, and this map is consistent with those published for the older populations. 5 Of the African countries in which schistosomiasis is endemic, 28 countries have or are currently implementing a schistosomiasis control program (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) as listed in the WHO database on preventative chemotherapy of neglected tropical diseases (http:// www.who.int/neglected_diseases/ preventive_chemotherapy/en/). However, none of these countries includes children aged #5 years, despite .60% of them reporting significant schistosome infection levels in this age group.…”

The global distribution and transmission limits of lymphatic filariasis: past and present

“…Our approach to identify suitable data follows that developed originally by Norman Stoll in his seminal work This Wormy World in 1947 [70], and adopted by efforts to map malaria [71,72] as well as soil-transmitted helminth and schistosome infections [73][74][75]. Relevant data on the prevalence of LF were identified through a combination of (i) structured searches of electronic bibliographic databases, (ii) additional searches of the 'grey' literature, including unpublished surveys and government and international archives, and (iii) direct contact with researchers and control programme managers.…”

Mapping and prediction of schistosomiasis in Nigeria using compiled survey data and Bayesian geospatial modelling

“…For a detailed description of the various data sources, the data extraction process, the database system and internal quality checks, the reader is invited to consult recently published papers, e.g. Hürlimann et al (2011 and Stensgaard et al (2013). Studies lacking information about the geographical coordinates of survey locations were retrospectively geo-referenced using a variety of sources, such as GEOnet Names Servers (http://earthinfo.nga.mil/gns/html/index.html) and Google maps (http://maps.google.com).…”