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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
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 l...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9218187/ https://www.ncbi.nlm.nih.gov/pubmed/35754460 http://dx.doi.org/10.3389/fdgth.2022.907004 |
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author | Bello, Isah Mohammed Akpan, Godwin Ubong Gital, Abdulsalam Yau Iliyasu, Musa Mohammed, Danlami Barau, Faysal Shehu Rasheed, Daniel Oyaole Bedada, Erbeto Tesfaye Maleghemi, Sylvester |
author_facet | Bello, Isah Mohammed Akpan, Godwin Ubong Gital, Abdulsalam Yau Iliyasu, Musa Mohammed, Danlami Barau, Faysal Shehu Rasheed, Daniel Oyaole Bedada, Erbeto Tesfaye Maleghemi, Sylvester |
author_sort | Bello, Isah Mohammed |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9218187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92181872022-06-24 Determining Inaccurate Coordinates in Electronic Data Collection for Surveillance and Immunization Supportive Supervision: A Case Study of Nigeria EPI Supportive Supervision Module Bello, Isah Mohammed Akpan, Godwin Ubong Gital, Abdulsalam Yau Iliyasu, Musa Mohammed, Danlami Barau, Faysal Shehu Rasheed, Daniel Oyaole Bedada, Erbeto Tesfaye Maleghemi, Sylvester Front Digit Health Digital Health 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. Frontiers Media S.A. 2022-06-09 /pmc/articles/PMC9218187/ /pubmed/35754460 http://dx.doi.org/10.3389/fdgth.2022.907004 Text en Copyright © 2022 Bello, Akpan, Gital, Iliyasu, Mohammed, Barau, Rasheed, Bedada and Maleghemi. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Digital Health Bello, Isah Mohammed Akpan, Godwin Ubong Gital, Abdulsalam Yau Iliyasu, Musa Mohammed, Danlami Barau, Faysal Shehu Rasheed, Daniel Oyaole Bedada, Erbeto Tesfaye Maleghemi, Sylvester Determining Inaccurate Coordinates in Electronic Data Collection for Surveillance and Immunization Supportive Supervision: A Case Study of Nigeria EPI Supportive Supervision Module |
title | Determining Inaccurate Coordinates in Electronic Data Collection for Surveillance and Immunization Supportive Supervision: A Case Study of Nigeria EPI Supportive Supervision Module |
title_full | Determining Inaccurate Coordinates in Electronic Data Collection for Surveillance and Immunization Supportive Supervision: A Case Study of Nigeria EPI Supportive Supervision Module |
title_fullStr | Determining Inaccurate Coordinates in Electronic Data Collection for Surveillance and Immunization Supportive Supervision: A Case Study of Nigeria EPI Supportive Supervision Module |
title_full_unstemmed | Determining Inaccurate Coordinates in Electronic Data Collection for Surveillance and Immunization Supportive Supervision: A Case Study of Nigeria EPI Supportive Supervision Module |
title_short | Determining Inaccurate Coordinates in Electronic Data Collection for Surveillance and Immunization Supportive Supervision: A Case Study of Nigeria EPI Supportive Supervision Module |
title_sort | determining inaccurate coordinates in electronic data collection for surveillance and immunization supportive supervision: a case study of nigeria epi supportive supervision module |
topic | Digital Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9218187/ https://www.ncbi.nlm.nih.gov/pubmed/35754460 http://dx.doi.org/10.3389/fdgth.2022.907004 |
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