@article{103040,
  keywords = {Leprosy, Geospatial analysis, Case detection, Tools, Leprosy elimination, Cost-effectivines Analysis},
  author = {Fastenau A and Gadah DAY and Bakoubayi AW and Gnossike P and Schwermann F and Willis M and Schlumberger F and Hambridge T and Vedithi SC and Stuetzle SCW and Deps PD and Ortuño-Gutiérrez N},
  editor = {Restrepo D},
  title = {Geospatial tools in leprosy elimination: Enhancing precision in active case detection and resource allocation},
  abstract = {<p>Leprosy, known also as Hansen’s disease, is an infectious highly stigmatizing neglected tropical disease (NTD) that may cause permanent disabilities [1]. Despite significant advances in treatment and control, leprosy remains a global public health concern with close to 200,000 new cases of leprosy notified worldwide annually [2]. Reaching out to missing and hidden cases, along with early diagnosis, are priorities for successful leprosy control and elimination [3]. Geographical Information Systems (GIS) have shown promising results in improving disease control strategies by identifying high-risk areas for targeted interventions [4]. Additionally, GIS provides the ability to display spatial distribution of diseases by integrating geographical data with tabular information from sources such as spreadsheets, tables, and graphs [5]. We advocate for concrete integration of GIS in leprosy control, aiming at the elimination of transmission, underscoring its potential to refine active case detection (ACD), optimize resource allocation, and enhance cost-effectiveness.</p>
},
  year = {2025},
  journal = {PLOS Digital Health},
  volume = {4},
  pages = {1-5},
  publisher = {Public Library of Science (PLoS)},
  issn = {2767-3170},
  url = {https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0001068&type=printable},
  doi = {10.1371/journal.pdig.0001068},
  language = {ENG},
}