8 research outputs found

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

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    Abstract 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

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

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    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

    Observed prevalence of <i>S. mansoni</i> based on current progress of the GNTD database in Africa.

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    <p>The data included 4604 georeferenced survey locations. Prevalence equal to 0% in yellow dots, low infection rates (0.1–9.9%) in orange dots, moderate infection rates (10.0–49.9%) in light brown dots and high infection rates (≥50%) in brown dots. Cut-offs follow WHO recommendations <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-WHO3" target="_blank">[35]</a>.</p

    Observed prevalence of <i>S. haematobium</i> based on current progress of the GNTD database in Africa.

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    <p>The data included 5807 georeferenced survey locations. Prevalence equal to 0%, low infection rates (0.1–9.9%), moderate infection rates (10.0–49.9%) and high infection rates (≥50%) indicated by a red scale from light red to dark red. Cut-offs follow WHO recommendations <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-WHO3" target="_blank">[35]</a>.</p

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

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    <p>Survey locations are represented by pink squares for <i>S. matthei</i>, blue diamonds for <i>S. margrebowiei</i>, yellow stars for <i>S. intercalatum</i>, green crosses for <i>S. bovis</i>, brown dots for <i>S. mansoni</i> and red triangles for <i>S. haematobium</i>. Surveys where subjects were screened for co-occurrence of multiple species are indicated with overlapping symbols.</p

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

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    <p>1. PubMed <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-PubMed1" target="_blank">[24]</a>, ISI Web of Knowledge <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-ISI1" target="_blank">[25]</a>, African Journal Online (AJOL) <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-African1" target="_blank">[26]</a>, Institut de Recherche pour le Développement (IRD)-resources documentaries <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-IRD1" target="_blank">[28]</a>, WHO library archive <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-WHO2" target="_blank">[27]</a>, Doumenge et al. <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-Doumenge1" target="_blank">[17]</a>; 2. Dissertations and theses in local universities or public health departments, ministry of health reports, other reports and personal communication. 3. Proforma and MySQL database include: (i) data source (authors); (ii) document type; (iii) location of the survey; (iv) area information (rural or urban); (v) coordinates (lat long in decimal degrees); (vi) method of the sample recruitment and diagnostic technique; (vii) description of survey (community-, school- or hospital-based); (viii) date of survey (month/year); and (ix) prevalence information (number of subjects examined and positive by age group and parasite species).</p
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