Developing a Novel Contact Tracing Mobile Application for Coronavirus Disease 2019 (COVID-19) for Improving Testing Capacity and Controlling the Spread of COVID-19 in Nigeria

Adesola Zaidat Musa; Kazeem Adewale Osuolale; Abideen Olurotimi Salako; Adekunle Temu Ifeta; Babatunde Lawal Salako

doi:doi:10.11648/j.sjph.20241205.13

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| Peer-Reviewed

Developing a Novel Contact Tracing Mobile Application for Coronavirus Disease 2019 (COVID-19) for Improving Testing Capacity and Controlling the Spread of COVID-19 in Nigeria

Adesola Zaidat Musa

, Kazeem Adewale Osuolale^*

, Abideen Olurotimi Salako

, Adekunle Temu Ifeta

, Babatunde Lawal Salako

Published in Science Journal of Public Health (Volume 12, Issue 5)

Received: 27 August 2024 Accepted: 21 September 2024 Published: 18 October 2024

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Abstract

In this study, a novel contact tracing model that leverages smartphone technology to enhance efficiency, reduce costs, and extend the duration of contact tracing efforts is developed. This model utilizes smartphones as identification systems, collecting data on the proximity of other smartphone users through integrated Bluetooth and GPS technology. The study examines the frequency, duration, and proximity of interactions between smartphone devices in a clinical setting, highlighting potential implications for infectious disease transmission to pilot the mobile application developed. Contact data from six pairs of devices were analyzed, focusing on metrics such as total contacts, total contact time, average contact time, average distance, and the percentage of contacts occurring within 1.5 meters. The results showed varying levels of interaction across device pairs, with Devices 1 & 3 showing the highest number of contacts (175), and Devices 3 & 4 displaying the longest average contact time (20,133,193.01 seconds). Correlation analysis revealed weak and statistically insignificant relationships between total contacts and average distance (r = 0.13, p = 0.81), contact time and the percentage of close contacts (r = -0.15, p = 0.78). These findings suggest that while there are observable trends in contact patterns, the statistical insignificance highlights the need for further investigation to establish stronger associations that could inform infection control practices in healthcare settings.

Published in	Science Journal of Public Health (Volume 12, Issue 5)
DOI	10.11648/j.sjph.20241205.13
Page(s)	169-177
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Contact Tracing, Smartphone Technology, Bluetooth and GPS, Infectious Disease Transmission, Correlation Analysis

References

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APA Style

Musa, A. Z., Osuolale, K. A., Salako, A. O., Ifeta, A. T., Salako, B. L. (2024). Developing a Novel Contact Tracing Mobile Application for Coronavirus Disease 2019 (COVID-19) for Improving Testing Capacity and Controlling the Spread of COVID-19 in Nigeria. Science Journal of Public Health, 12(5), 169-177. https://doi.org/10.11648/j.sjph.20241205.13

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ACS Style

Musa, A. Z.; Osuolale, K. A.; Salako, A. O.; Ifeta, A. T.; Salako, B. L. Developing a Novel Contact Tracing Mobile Application for Coronavirus Disease 2019 (COVID-19) for Improving Testing Capacity and Controlling the Spread of COVID-19 in Nigeria. Sci. J. Public Health 2024, 12(5), 169-177. doi: 10.11648/j.sjph.20241205.13

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AMA Style

Musa AZ, Osuolale KA, Salako AO, Ifeta AT, Salako BL. Developing a Novel Contact Tracing Mobile Application for Coronavirus Disease 2019 (COVID-19) for Improving Testing Capacity and Controlling the Spread of COVID-19 in Nigeria. Sci J Public Health. 2024;12(5):169-177. doi: 10.11648/j.sjph.20241205.13

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@article{10.11648/j.sjph.20241205.13,
  author = {Adesola Zaidat Musa and Kazeem Adewale Osuolale and Abideen Olurotimi Salako and Adekunle Temu Ifeta and Babatunde Lawal Salako},
  title = {Developing a Novel Contact Tracing Mobile Application for Coronavirus Disease 2019 (COVID-19) for Improving Testing Capacity and Controlling the Spread of COVID-19 in Nigeria
},
  journal = {Science Journal of Public Health},
  volume = {12},
  number = {5},
  pages = {169-177},
  doi = {10.11648/j.sjph.20241205.13},
  url = {https://doi.org/10.11648/j.sjph.20241205.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjph.20241205.13},
  abstract = {In this study, a novel contact tracing model that leverages smartphone technology to enhance efficiency, reduce costs, and extend the duration of contact tracing efforts is developed. This model utilizes smartphones as identification systems, collecting data on the proximity of other smartphone users through integrated Bluetooth and GPS technology. The study examines the frequency, duration, and proximity of interactions between smartphone devices in a clinical setting, highlighting potential implications for infectious disease transmission to pilot the mobile application developed. Contact data from six pairs of devices were analyzed, focusing on metrics such as total contacts, total contact time, average contact time, average distance, and the percentage of contacts occurring within 1.5 meters. The results showed varying levels of interaction across device pairs, with Devices 1 & 3 showing the highest number of contacts (175), and Devices 3 & 4 displaying the longest average contact time (20,133,193.01 seconds). Correlation analysis revealed weak and statistically insignificant relationships between total contacts and average distance (r = 0.13, p = 0.81), contact time and the percentage of close contacts (r = -0.15, p = 0.78). These findings suggest that while there are observable trends in contact patterns, the statistical insignificance highlights the need for further investigation to establish stronger associations that could inform infection control practices in healthcare settings.
},
 year = {2024}
}

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TY  - JOUR
T1  - Developing a Novel Contact Tracing Mobile Application for Coronavirus Disease 2019 (COVID-19) for Improving Testing Capacity and Controlling the Spread of COVID-19 in Nigeria

AU  - Adesola Zaidat Musa
AU  - Kazeem Adewale Osuolale
AU  - Abideen Olurotimi Salako
AU  - Adekunle Temu Ifeta
AU  - Babatunde Lawal Salako
Y1  - 2024/10/18
PY  - 2024
N1  - https://doi.org/10.11648/j.sjph.20241205.13
DO  - 10.11648/j.sjph.20241205.13
T2  - Science Journal of Public Health
JF  - Science Journal of Public Health
JO  - Science Journal of Public Health
SP  - 169
EP  - 177
PB  - Science Publishing Group
SN  - 2328-7950
UR  - https://doi.org/10.11648/j.sjph.20241205.13
AB  - In this study, a novel contact tracing model that leverages smartphone technology to enhance efficiency, reduce costs, and extend the duration of contact tracing efforts is developed. This model utilizes smartphones as identification systems, collecting data on the proximity of other smartphone users through integrated Bluetooth and GPS technology. The study examines the frequency, duration, and proximity of interactions between smartphone devices in a clinical setting, highlighting potential implications for infectious disease transmission to pilot the mobile application developed. Contact data from six pairs of devices were analyzed, focusing on metrics such as total contacts, total contact time, average contact time, average distance, and the percentage of contacts occurring within 1.5 meters. The results showed varying levels of interaction across device pairs, with Devices 1 & 3 showing the highest number of contacts (175), and Devices 3 & 4 displaying the longest average contact time (20,133,193.01 seconds). Correlation analysis revealed weak and statistically insignificant relationships between total contacts and average distance (r = 0.13, p = 0.81), contact time and the percentage of close contacts (r = -0.15, p = 0.78). These findings suggest that while there are observable trends in contact patterns, the statistical insignificance highlights the need for further investigation to establish stronger associations that could inform infection control practices in healthcare settings.

VL  - 12
IS  - 5
ER  -

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Author Information

Adesola Zaidat Musa

Biostatistics Sub-Unit, Grant, Monitoring and Evaluation Unit, Nigerian Institute of Medical Research, Lagos, Nigeria

Contact Email

http://orcid.org/0000-0002-6533-2984
Kazeem Adewale Osuolale

Biostatistics Sub-Unit, Grant, Monitoring and Evaluation Unit, Nigerian Institute of Medical Research, Lagos, Nigeria

Contact Email

http://orcid.org/0000-0002-4759-2432
Abideen Olurotimi Salako

Clinical Sciences Department, Nigerian Institute of Medical Research, Lagos, Nigeria

Contact Email

http://orcid.org/0000-0002-3018-3712
Adekunle Temu Ifeta

Corner Stone Resources Limited, Ibadan, Nigeria

Contact Email

http://orcid.org/0009-0005-4331-1487
Babatunde Lawal Salako

Clinical Sciences Department, Nigerian Institute of Medical Research, Lagos, Nigeria

Contact Email

http://orcid.org/0000-0002-0963-7302

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Plain Text BibTeX RIS

APA Style

Musa, A. Z., Osuolale, K. A., Salako, A. O., Ifeta, A. T., Salako, B. L. (2024). Developing a Novel Contact Tracing Mobile Application for Coronavirus Disease 2019 (COVID-19) for Improving Testing Capacity and Controlling the Spread of COVID-19 in Nigeria. Science Journal of Public Health, 12(5), 169-177. https://doi.org/10.11648/j.sjph.20241205.13

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ACS Style

Musa, A. Z.; Osuolale, K. A.; Salako, A. O.; Ifeta, A. T.; Salako, B. L. Developing a Novel Contact Tracing Mobile Application for Coronavirus Disease 2019 (COVID-19) for Improving Testing Capacity and Controlling the Spread of COVID-19 in Nigeria. Sci. J. Public Health 2024, 12(5), 169-177. doi: 10.11648/j.sjph.20241205.13

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AMA Style

Musa AZ, Osuolale KA, Salako AO, Ifeta AT, Salako BL. Developing a Novel Contact Tracing Mobile Application for Coronavirus Disease 2019 (COVID-19) for Improving Testing Capacity and Controlling the Spread of COVID-19 in Nigeria. Sci J Public Health. 2024;12(5):169-177. doi: 10.11648/j.sjph.20241205.13

Copy | Download

@article{10.11648/j.sjph.20241205.13,
  author = {Adesola Zaidat Musa and Kazeem Adewale Osuolale and Abideen Olurotimi Salako and Adekunle Temu Ifeta and Babatunde Lawal Salako},
  title = {Developing a Novel Contact Tracing Mobile Application for Coronavirus Disease 2019 (COVID-19) for Improving Testing Capacity and Controlling the Spread of COVID-19 in Nigeria
},
  journal = {Science Journal of Public Health},
  volume = {12},
  number = {5},
  pages = {169-177},
  doi = {10.11648/j.sjph.20241205.13},
  url = {https://doi.org/10.11648/j.sjph.20241205.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjph.20241205.13},
  abstract = {In this study, a novel contact tracing model that leverages smartphone technology to enhance efficiency, reduce costs, and extend the duration of contact tracing efforts is developed. This model utilizes smartphones as identification systems, collecting data on the proximity of other smartphone users through integrated Bluetooth and GPS technology. The study examines the frequency, duration, and proximity of interactions between smartphone devices in a clinical setting, highlighting potential implications for infectious disease transmission to pilot the mobile application developed. Contact data from six pairs of devices were analyzed, focusing on metrics such as total contacts, total contact time, average contact time, average distance, and the percentage of contacts occurring within 1.5 meters. The results showed varying levels of interaction across device pairs, with Devices 1 & 3 showing the highest number of contacts (175), and Devices 3 & 4 displaying the longest average contact time (20,133,193.01 seconds). Correlation analysis revealed weak and statistically insignificant relationships between total contacts and average distance (r = 0.13, p = 0.81), contact time and the percentage of close contacts (r = -0.15, p = 0.78). These findings suggest that while there are observable trends in contact patterns, the statistical insignificance highlights the need for further investigation to establish stronger associations that could inform infection control practices in healthcare settings.
},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - Developing a Novel Contact Tracing Mobile Application for Coronavirus Disease 2019 (COVID-19) for Improving Testing Capacity and Controlling the Spread of COVID-19 in Nigeria

AU  - Adesola Zaidat Musa
AU  - Kazeem Adewale Osuolale
AU  - Abideen Olurotimi Salako
AU  - Adekunle Temu Ifeta
AU  - Babatunde Lawal Salako
Y1  - 2024/10/18
PY  - 2024
N1  - https://doi.org/10.11648/j.sjph.20241205.13
DO  - 10.11648/j.sjph.20241205.13
T2  - Science Journal of Public Health
JF  - Science Journal of Public Health
JO  - Science Journal of Public Health
SP  - 169
EP  - 177
PB  - Science Publishing Group
SN  - 2328-7950
UR  - https://doi.org/10.11648/j.sjph.20241205.13
AB  - In this study, a novel contact tracing model that leverages smartphone technology to enhance efficiency, reduce costs, and extend the duration of contact tracing efforts is developed. This model utilizes smartphones as identification systems, collecting data on the proximity of other smartphone users through integrated Bluetooth and GPS technology. The study examines the frequency, duration, and proximity of interactions between smartphone devices in a clinical setting, highlighting potential implications for infectious disease transmission to pilot the mobile application developed. Contact data from six pairs of devices were analyzed, focusing on metrics such as total contacts, total contact time, average contact time, average distance, and the percentage of contacts occurring within 1.5 meters. The results showed varying levels of interaction across device pairs, with Devices 1 & 3 showing the highest number of contacts (175), and Devices 3 & 4 displaying the longest average contact time (20,133,193.01 seconds). Correlation analysis revealed weak and statistically insignificant relationships between total contacts and average distance (r = 0.13, p = 0.81), contact time and the percentage of close contacts (r = -0.15, p = 0.78). These findings suggest that while there are observable trends in contact patterns, the statistical insignificance highlights the need for further investigation to establish stronger associations that could inform infection control practices in healthcare settings.

VL  - 12
IS  - 5
ER  -

Copy | Download