A comparison of spatial-based targeted disease mitigation strategies using mobile phone data
Abstract Epidemic outbreaks are an important healthcare challenge, especially in developing countries where they represent one of the major causes of mortality. Approaches that can rapidly target subpopulations for surveillance and control are critical for enhancing containment and mitigation proces...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2018-06-01
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| Series: | EPJ Data Science |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1140/epjds/s13688-018-0145-9 |
| _version_ | 1818338770432294912 |
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| author | Stefania Rubrichi Zbigniew Smoreda Mirco Musolesi |
| author_facet | Stefania Rubrichi Zbigniew Smoreda Mirco Musolesi |
| author_sort | Stefania Rubrichi |
| collection | DOAJ |
| description | Abstract Epidemic outbreaks are an important healthcare challenge, especially in developing countries where they represent one of the major causes of mortality. Approaches that can rapidly target subpopulations for surveillance and control are critical for enhancing containment and mitigation processes during epidemics. Using a real-world dataset from Ivory Coast, this work presents an attempt to unveil the socio-geographical heterogeneity of disease transmission dynamics. By employing a spatially explicit meta-population epidemic model derived from mobile phone Call Detail Records (CDRs), we investigate how the differences in mobility patterns may affect the course of a hypothetical infectious disease outbreak. We consider different existing measures of the spatial dimension of human mobility and interactions, and we analyse their relevance in identifying the highest risk sub-population of individuals, as the best candidates for isolation countermeasures. The approaches presented in this paper provide further evidence that mobile phone data can be effectively exploited to facilitate our understanding of individuals’ spatial behaviour and its relationship with the risk of infectious diseases’ contagion. In particular, we show that CDRs-based indicators of individuals’ spatial activities and interactions hold promise for gaining insight of contagion heterogeneity and thus for developing mitigation strategies to support decision-making during country-level epidemics. |
| first_indexed | 2024-12-13T15:16:23Z |
| format | Article |
| id | doaj.art-947c66a53701471284c88e08c3a790e8 |
| institution | Directory Open Access Journal |
| issn | 2193-1127 |
| language | English |
| last_indexed | 2024-12-13T15:16:23Z |
| publishDate | 2018-06-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EPJ Data Science |
| spelling | doaj.art-947c66a53701471284c88e08c3a790e82022-12-21T23:40:42ZengSpringerOpenEPJ Data Science2193-11272018-06-017111510.1140/epjds/s13688-018-0145-9A comparison of spatial-based targeted disease mitigation strategies using mobile phone dataStefania Rubrichi0Zbigniew Smoreda1Mirco Musolesi2SENSE, Orange LabsSENSE, Orange LabsDepartment of Geography, University College LondonAbstract Epidemic outbreaks are an important healthcare challenge, especially in developing countries where they represent one of the major causes of mortality. Approaches that can rapidly target subpopulations for surveillance and control are critical for enhancing containment and mitigation processes during epidemics. Using a real-world dataset from Ivory Coast, this work presents an attempt to unveil the socio-geographical heterogeneity of disease transmission dynamics. By employing a spatially explicit meta-population epidemic model derived from mobile phone Call Detail Records (CDRs), we investigate how the differences in mobility patterns may affect the course of a hypothetical infectious disease outbreak. We consider different existing measures of the spatial dimension of human mobility and interactions, and we analyse their relevance in identifying the highest risk sub-population of individuals, as the best candidates for isolation countermeasures. The approaches presented in this paper provide further evidence that mobile phone data can be effectively exploited to facilitate our understanding of individuals’ spatial behaviour and its relationship with the risk of infectious diseases’ contagion. In particular, we show that CDRs-based indicators of individuals’ spatial activities and interactions hold promise for gaining insight of contagion heterogeneity and thus for developing mitigation strategies to support decision-making during country-level epidemics.http://link.springer.com/article/10.1140/epjds/s13688-018-0145-9Spatial networksMobile phone dataHuman mobilityEpidemic spread |
| spellingShingle | Stefania Rubrichi Zbigniew Smoreda Mirco Musolesi A comparison of spatial-based targeted disease mitigation strategies using mobile phone data EPJ Data Science Spatial networks Mobile phone data Human mobility Epidemic spread |
| title | A comparison of spatial-based targeted disease mitigation strategies using mobile phone data |
| title_full | A comparison of spatial-based targeted disease mitigation strategies using mobile phone data |
| title_fullStr | A comparison of spatial-based targeted disease mitigation strategies using mobile phone data |
| title_full_unstemmed | A comparison of spatial-based targeted disease mitigation strategies using mobile phone data |
| title_short | A comparison of spatial-based targeted disease mitigation strategies using mobile phone data |
| title_sort | comparison of spatial based targeted disease mitigation strategies using mobile phone data |
| topic | Spatial networks Mobile phone data Human mobility Epidemic spread |
| url | http://link.springer.com/article/10.1140/epjds/s13688-018-0145-9 |
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