Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics
Cell, ISSN: 0092-8674, Vol: 186, Issue: 26, Page: 5690-5704.e20
2023
- 4Citations
- 19Captures
- 11Mentions
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations4
- Citation Indexes4
- CrossRef4
- Captures19
- Readers19
- 19
- Mentions11
- News Mentions10
- 10
- Blog Mentions1
- 1
Most Recent Blog
Social distancing was more effective at preventing local COVID-19 transmission than border closures
Elucidating human contact networks could help predict and prevent the transmission of SARS-CoV-2 and future pandemic threats. A new study from Scripps Research scientists and
Most Recent News
Social Distancing Was More Effective at Preventing Local COVID-19 Transmission …
Scripps Research scientists and collaborators uncovered the relative effectiveness of different COVID-19 mandates, helping guide public health policy for future viral threats. December 14, 2023
Article Description
The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of “local” when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0092867423012783; http://dx.doi.org/10.1016/j.cell.2023.11.024; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85180565043&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/38101407; https://linkinghub.elsevier.com/retrieve/pii/S0092867423012783; https://dx.doi.org/10.1016/j.cell.2023.11.024
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know