Optimizing targeted vaccination across cyber–physical networks: an empirically based mathematical simulation stud
Targeted vaccination, whether to minimize the forward transmission of infectious diseases or their clinical impact, is one of the ‘holy grails’ of modern infectious disease outbreak response, yet it is difficult to achieve in practice due to the challenge of identifying optimal targets in real time....
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Journal of the Royal Society Interface
2021
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| Online Access: | https://hdl.handle.net/1721.1/130254 |
| _version_ | 1811092721381670912 |
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| author | Mones, Enys Stopczynski, Arkadiusz Pentland, Alex Hupert, Nathaniel Lehmann, Sune |
| author_facet | Mones, Enys Stopczynski, Arkadiusz Pentland, Alex Hupert, Nathaniel Lehmann, Sune |
| author_sort | Mones, Enys |
| collection | MIT |
| description | Targeted vaccination, whether to minimize the forward transmission of infectious diseases or their clinical impact, is one of the ‘holy grails’ of modern infectious disease outbreak response, yet it is difficult to achieve in practice due to the challenge of identifying optimal targets in real time. If interruption of disease transmission is the goal, targeting requires knowledge of underlying person-to-person contact networks. Digital communication networks may reflect not only virtual but also physical interactions that could result in disease transmission, but the precise overlap between these cyber and physical networks has never been empirically explored in real-life settings. Here, we study the digital communication activity of more than 500 individuals along with their person-to-person contacts at a 5-min temporal resolution. We then simulate different disease transmission scenarios on the person-to-person physical contact network to determine whether cyber communication networks can be harnessed to advance the goal of targeted vaccination for a disease spreading on the network of physical proximity. We show that individuals selected on the basis of their closeness centrality within cyber networks (what we call ‘cyber-directed vaccination’) can enhance vaccination campaigns against diseases with short-range (but not full-range) modes of transmission. |
| first_indexed | 2024-09-23T15:23:15Z |
| format | Article |
| id | mit-1721.1/130254 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:23:15Z |
| publishDate | 2021 |
| publisher | Journal of the Royal Society Interface |
| record_format | dspace |
| spelling | mit-1721.1/1302542021-03-30T03:05:25Z Optimizing targeted vaccination across cyber–physical networks: an empirically based mathematical simulation stud Mones, Enys Stopczynski, Arkadiusz Pentland, Alex Hupert, Nathaniel Lehmann, Sune Targeted vaccination, whether to minimize the forward transmission of infectious diseases or their clinical impact, is one of the ‘holy grails’ of modern infectious disease outbreak response, yet it is difficult to achieve in practice due to the challenge of identifying optimal targets in real time. If interruption of disease transmission is the goal, targeting requires knowledge of underlying person-to-person contact networks. Digital communication networks may reflect not only virtual but also physical interactions that could result in disease transmission, but the precise overlap between these cyber and physical networks has never been empirically explored in real-life settings. Here, we study the digital communication activity of more than 500 individuals along with their person-to-person contacts at a 5-min temporal resolution. We then simulate different disease transmission scenarios on the person-to-person physical contact network to determine whether cyber communication networks can be harnessed to advance the goal of targeted vaccination for a disease spreading on the network of physical proximity. We show that individuals selected on the basis of their closeness centrality within cyber networks (what we call ‘cyber-directed vaccination’) can enhance vaccination campaigns against diseases with short-range (but not full-range) modes of transmission. 2021-03-29T16:21:40Z 2021-03-29T16:21:40Z 2018-01-03 Article https://hdl.handle.net/1721.1/130254 Mones, E., Stopczynski, A., Pentland, A. S., Hupert, N., & Lehmann, S. (2018). Optimizing targeted vaccination across cyber–physical networks: an empirically based mathematical simulation study. Journal of The Royal Society Interface, 15(138), 20170783. en Attribution-NonCommercial-ShareAlike 3.0 United States http://creativecommons.org/licenses/by-nc-sa/3.0/us/ application/pdf Journal of the Royal Society Interface |
| spellingShingle | Mones, Enys Stopczynski, Arkadiusz Pentland, Alex Hupert, Nathaniel Lehmann, Sune Optimizing targeted vaccination across cyber–physical networks: an empirically based mathematical simulation stud |
| title | Optimizing targeted vaccination across cyber–physical networks: an empirically based mathematical simulation stud |
| title_full | Optimizing targeted vaccination across cyber–physical networks: an empirically based mathematical simulation stud |
| title_fullStr | Optimizing targeted vaccination across cyber–physical networks: an empirically based mathematical simulation stud |
| title_full_unstemmed | Optimizing targeted vaccination across cyber–physical networks: an empirically based mathematical simulation stud |
| title_short | Optimizing targeted vaccination across cyber–physical networks: an empirically based mathematical simulation stud |
| title_sort | optimizing targeted vaccination across cyber physical networks an empirically based mathematical simulation stud |
| url | https://hdl.handle.net/1721.1/130254 |
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