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Determining Inaccurate Coordinates in Electronic Data Collection for Surveillance and Immunization Supportive Supervision: A Case Study of Nigeria EPI Supportive Supervision Module

  • Bello, Isah Mohammed1
  • Akpan, Godwin Ubong2
  • Gital, Abdulsalam Yau3
  • Iliyasu, Musa3
  • Mohammed, Danlami4
  • Barau, Faysal Shehu5
  • Rasheed, Daniel Oyaole5
  • Bedada, Erbeto Tesfaye5
  • Maleghemi, Sylvester6
  • 1 Inter-Country Support Team Office for East and Southern Africa, World Health Organization (WHO), Harare , (Zimbabwe)
  • 2 Regional Office for Africa, World Health Organization (WHO), Brazzaville
  • 3 Department of Computer Science, Abubakar Tafawa Balewa University, Bauchi , (Nigeria)
  • 4 Department of Computer Science, Abubakar Tatari Ali Polytechnic, Bauchi , (Nigeria)
  • 5 Nigeria Country Office, World Health Organization (WHO), Abuja , (Nigeria)
  • 6 WHO Country Office, World, Health Organization (WHO), Juba , (South Sudan)
Published Article
Frontiers in Digital Health
Frontiers Media S.A.
Publication Date
Jun 09, 2022
DOI: 10.3389/fdgth.2022.907004
  • Digital Health
  • Original Research


The mobile phone global positioning system (GPS) is used to reconnaissance a mobile phone user's location, e.g., at work, home, shops, etc. Such information can be used to feed data gathering expeditions, the actual position of the interviewer/surveyor using the mobile phone inert settings of location mode via GPS, WIFI, and Mobile networks. Mobile devices are becoming progressively erudite and now integrate diverse and robust sensors. The new generation of smartphones is multi-laden with sensors, including GPS sensors. The study describes and evaluates a data-gathering process used by the World Health Organization (WHO–Nigeria, EPI Program) that uses phone-based in-built GPS sensors to identify the position of users while they undergo supportive supervision. This form of spatial data is collected intrinsically using the Open Data Kit (ODK) GPS interface, which interlaces with the mobile phone GPS sensor to fetch the geo-coordinates during the process. It represents a step in building a methodology of matching places on the map with the geo-coordinates received from the mobile phones to investigate deviation patterns by devices and location mode. The empirical results can help us to understand the variation in geospatial data collation across devices and highlight critical criteria for choosing mobile phones for mobile surveys and data campaigns. This study reviewed the existing data gathered inadvertently from 10 brands of smartphones over 1 year of using the mobile data collection with over 80,000 field visits to predict the deviation pattern for spatial data acquisition via mobile phones by different brands.

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