Use of geographic information system as a tool for schistosomiasis surveillance in an endemic Municipality in Eastern Samar, The Philippines

Geospat Health. 2021 May 14;16(1). doi: 10.4081/gh.2021.957.

Abstract

This study aimed to demonstrate the use of geographic information systems (GIS) in identifying factors contributing to schistosomiasis endemicity and identifying high-risk areas in a schistosomiasis- endemic municipality in the Philippines, which was devastated by Typhoon Haiyan in 2013. Data on schistosomiasis determinants, obtained through literature review, the Philippine Department of Health, and concerned local government units, were standardized and incorporated into a GIS map using ArcGIS. Data gathered included modifiable [agriculture, poverty, sanitation, presence of intermediate and reservoir hosts, disease prevalence and mass drug administration (MDA) coverage] and nonmodifiable (geography and climate) determinants for schistosomiasis. Results showed that most barangays (villages) are characterized by favourable conditions for schistosomiasis transmission which include being located in flood-prone areas, presence of vegetation, low sanitary toilet coverage, presence of snail intermediate host, high carabao (water buffalo) population density, previously reported ≥1% prevalence using Kato-Katz technique, and low MDA coverage. Similarly, barangays not known to be endemic for schistosomiasis but also characterized by the same favourable conditions for schistosomiasis as listed above and may therefore be considered as potentially endemic, even if not being high-risk areas. This study demonstrated the importance of GIS technology in characterizing schistosomiasis transmission. Maps generated through application of GIS technology are useful in guiding program policy and planning at the local level for an effective and sustainable schistosomiasis control and prevention.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Agriculture
  • Climate
  • Geographic Information Systems*
  • Humans
  • Philippines / epidemiology
  • Prevalence
  • Schistosomiasis* / epidemiology