Face-to-Face Interactions Estimated Using Mobile Phone Data to Support Contact Tracing Operations
Understanding people’s face-to-face interactions is crucial for effective infectious disease management. Traditional contact tracing, often relying on interviews or smartphone applications, faces limitations such as incomplete recall, low adoption rates, and privacy concerns. This study proposes uti...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Big Data and Cognitive Computing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-2289/9/1/4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832589105936990208 |
|---|---|
| author | Silvino Pedro Cumbane Gyözö Gidófalvi Osvaldo Fernando Cossa Afonso Madivadua Júnior Nuno Sousa Frederico Branco |
| author_facet | Silvino Pedro Cumbane Gyözö Gidófalvi Osvaldo Fernando Cossa Afonso Madivadua Júnior Nuno Sousa Frederico Branco |
| author_sort | Silvino Pedro Cumbane |
| collection | DOAJ |
| description | Understanding people’s face-to-face interactions is crucial for effective infectious disease management. Traditional contact tracing, often relying on interviews or smartphone applications, faces limitations such as incomplete recall, low adoption rates, and privacy concerns. This study proposes utilizing anonymized Call Detail Records (CDRs) as a substitute for in-person meetings. We assume that when two individuals engage in a phone call connected to the same cell tower, they are likely to meet shortly thereafter. Testing this assumption, we evaluated two hypotheses. The first hypothesis—that such co-located interactions occur in a workplace setting—achieved 83% agreement, which is considered a strong indication of reliability. The second hypothesis—that calls made during these co-location events are shorter than usual—achieved 86% agreement, suggesting an almost perfect reliability level. These results demonstrate that CDR-based co-location events can serve as a reliable substitute for in-person interactions and thus hold significant potential for enhancing contact tracing and supporting public health efforts. |
| format | Article |
| id | doaj-art-382cc5430f7a495a970ac777ab899ea9 |
| institution | Kabale University |
| issn | 2504-2289 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj-art-382cc5430f7a495a970ac777ab899ea92025-01-24T13:22:31ZengMDPI AGBig Data and Cognitive Computing2504-22892024-12-0191410.3390/bdcc9010004Face-to-Face Interactions Estimated Using Mobile Phone Data to Support Contact Tracing OperationsSilvino Pedro Cumbane0Gyözö Gidófalvi1Osvaldo Fernando Cossa2Afonso Madivadua Júnior3Nuno Sousa4Frederico Branco5Division of Geoinformatics, Department of Urban Planning and Environment, KTH Royal Institute of Technology, Teknikringen 10A, SE-114 28 Stockholm, SwedenDivision of Geoinformatics, Department of Urban Planning and Environment, KTH Royal Institute of Technology, Teknikringen 10A, SE-114 28 Stockholm, SwedenDepartment of Sciences and Technology, Universidade Aberta, 1269-001 Lisbon, PortugalDepartment of Service Quality, Instituto Nacional das Comunicações de Moçambique-INCM, Praça 16 de Junho, Maputo 848, MozambiqueDepartment of Sciences and Technology, Universidade Aberta, 1269-001 Lisbon, PortugalSchool of Science and Technology, Universidade de Trás-os-Montes e Alto Douro, 5000-801 Vila Real, PortugalUnderstanding people’s face-to-face interactions is crucial for effective infectious disease management. Traditional contact tracing, often relying on interviews or smartphone applications, faces limitations such as incomplete recall, low adoption rates, and privacy concerns. This study proposes utilizing anonymized Call Detail Records (CDRs) as a substitute for in-person meetings. We assume that when two individuals engage in a phone call connected to the same cell tower, they are likely to meet shortly thereafter. Testing this assumption, we evaluated two hypotheses. The first hypothesis—that such co-located interactions occur in a workplace setting—achieved 83% agreement, which is considered a strong indication of reliability. The second hypothesis—that calls made during these co-location events are shorter than usual—achieved 86% agreement, suggesting an almost perfect reliability level. These results demonstrate that CDR-based co-location events can serve as a reliable substitute for in-person interactions and thus hold significant potential for enhancing contact tracing and supporting public health efforts.https://www.mdpi.com/2504-2289/9/1/4Call Detail Records (CDRs)co-locationface-to-face meetingscontact tracingMozambique |
| spellingShingle | Silvino Pedro Cumbane Gyözö Gidófalvi Osvaldo Fernando Cossa Afonso Madivadua Júnior Nuno Sousa Frederico Branco Face-to-Face Interactions Estimated Using Mobile Phone Data to Support Contact Tracing Operations Big Data and Cognitive Computing Call Detail Records (CDRs) co-location face-to-face meetings contact tracing Mozambique |
| title | Face-to-Face Interactions Estimated Using Mobile Phone Data to Support Contact Tracing Operations |
| title_full | Face-to-Face Interactions Estimated Using Mobile Phone Data to Support Contact Tracing Operations |
| title_fullStr | Face-to-Face Interactions Estimated Using Mobile Phone Data to Support Contact Tracing Operations |
| title_full_unstemmed | Face-to-Face Interactions Estimated Using Mobile Phone Data to Support Contact Tracing Operations |
| title_short | Face-to-Face Interactions Estimated Using Mobile Phone Data to Support Contact Tracing Operations |
| title_sort | face to face interactions estimated using mobile phone data to support contact tracing operations |
| topic | Call Detail Records (CDRs) co-location face-to-face meetings contact tracing Mozambique |
| url | https://www.mdpi.com/2504-2289/9/1/4 |
| work_keys_str_mv | AT silvinopedrocumbane facetofaceinteractionsestimatedusingmobilephonedatatosupportcontacttracingoperations AT gyozogidofalvi facetofaceinteractionsestimatedusingmobilephonedatatosupportcontacttracingoperations AT osvaldofernandocossa facetofaceinteractionsestimatedusingmobilephonedatatosupportcontacttracingoperations AT afonsomadivaduajunior facetofaceinteractionsestimatedusingmobilephonedatatosupportcontacttracingoperations AT nunosousa facetofaceinteractionsestimatedusingmobilephonedatatosupportcontacttracingoperations AT fredericobranco facetofaceinteractionsestimatedusingmobilephonedatatosupportcontacttracingoperations |