Estimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing data
While many countries employed digital contact tracing to contain the spread of SARS-CoV-2, the contribution of cospace-time interaction (i.e., individuals who shared the same space and time) to transmission and to super-spreading in the real world has seldom been systematically studied due to the la...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Nature Research
2024
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| _version_ | 1826313646835236864 |
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| author | Wang, Z Yang, P Wang, R Ferretti, L Zhao, L Pei, S Wang, X Jia, L Zhang, D Liu, Y Liu, Z Wang, Q Fraser, C Tian, H |
| author_facet | Wang, Z Yang, P Wang, R Ferretti, L Zhao, L Pei, S Wang, X Jia, L Zhang, D Liu, Y Liu, Z Wang, Q Fraser, C Tian, H |
| author_sort | Wang, Z |
| collection | OXFORD |
| description | While many countries employed digital contact tracing to contain the spread of SARS-CoV-2, the contribution of cospace-time interaction (i.e., individuals who shared the same space and time) to transmission and to super-spreading in the real world has seldom been systematically studied due to the lack of systematic sampling and testing of contacts. To address this issue, we utilized data from 2230 cases and 220,878 contacts with detailed epidemiological information during the Omicron outbreak in Beijing in 2022. We observed that contact number per day of tracing for individuals in dwelling, workplace, cospace-time interactions, and community settings could be described by gamma distribution with distinct parameters. Our findings revealed that 38% of traced transmissions occurred through cospace-time interactions whilst control measures were in place. However, using a mathematical model to incorporate contacts in different locations, we found that without control measures, cospace-time interactions contributed to only 11% (95%CI: 10%–12%) of transmissions and the super-spreading risk for this setting was 4% (95%CI: 3%–5%), both the lowest among all settings studied. These results suggest that public health measures should be optimized to achieve a balance between the benefits of digital contact tracing for cospace-time interactions and the challenges posed by contact tracing within the same setting. |
| first_indexed | 2024-09-25T04:18:13Z |
| format | Journal article |
| id | oxford-uuid:feea5eed-827f-483e-93c0-3888cfb6c902 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:18:13Z |
| publishDate | 2024 |
| publisher | Nature Research |
| record_format | dspace |
| spelling | oxford-uuid:feea5eed-827f-483e-93c0-3888cfb6c9022024-07-21T19:45:05ZEstimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing dataJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:feea5eed-827f-483e-93c0-3888cfb6c902EnglishJisc Publications RouterNature Research2024Wang, ZYang, PWang, RFerretti, LZhao, LPei, SWang, XJia, LZhang, DLiu, YLiu, ZWang, QFraser, CTian, HWhile many countries employed digital contact tracing to contain the spread of SARS-CoV-2, the contribution of cospace-time interaction (i.e., individuals who shared the same space and time) to transmission and to super-spreading in the real world has seldom been systematically studied due to the lack of systematic sampling and testing of contacts. To address this issue, we utilized data from 2230 cases and 220,878 contacts with detailed epidemiological information during the Omicron outbreak in Beijing in 2022. We observed that contact number per day of tracing for individuals in dwelling, workplace, cospace-time interactions, and community settings could be described by gamma distribution with distinct parameters. Our findings revealed that 38% of traced transmissions occurred through cospace-time interactions whilst control measures were in place. However, using a mathematical model to incorporate contacts in different locations, we found that without control measures, cospace-time interactions contributed to only 11% (95%CI: 10%–12%) of transmissions and the super-spreading risk for this setting was 4% (95%CI: 3%–5%), both the lowest among all settings studied. These results suggest that public health measures should be optimized to achieve a balance between the benefits of digital contact tracing for cospace-time interactions and the challenges posed by contact tracing within the same setting. |
| spellingShingle | Wang, Z Yang, P Wang, R Ferretti, L Zhao, L Pei, S Wang, X Jia, L Zhang, D Liu, Y Liu, Z Wang, Q Fraser, C Tian, H Estimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing data |
| title | Estimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing data |
| title_full | Estimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing data |
| title_fullStr | Estimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing data |
| title_full_unstemmed | Estimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing data |
| title_short | Estimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing data |
| title_sort | estimating the contribution of setting specific contacts to sars cov 2 transmission using digital contact tracing data |
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