Challenges in control of Covid-19: short doubling time and long delay to effect of interventions
The unconstrained growth rate of COVID-19 is crucial for measuring the impact of interventions, assessing worst-case scenarios, and calibrating mathematical models for policy planning. However, robust estimates are limited, with scientific focus on the time-insensitive basic reproduction number R0....
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Cold Spring Harbor Laboratory
2020
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| _version_ | 1797056105593962496 |
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| author | Pellis, L Scarabel, F Stage, HB Overton, CE Chappell, LHK Lythgoe, KA Fearon, E Bennett, E Curran-Sebastian, J Das, R Fyles, M Lewkowicz, H Pang, X Vekaria, B Webb, L House, TA Hall, I |
| author_facet | Pellis, L Scarabel, F Stage, HB Overton, CE Chappell, LHK Lythgoe, KA Fearon, E Bennett, E Curran-Sebastian, J Das, R Fyles, M Lewkowicz, H Pang, X Vekaria, B Webb, L House, TA Hall, I |
| author_sort | Pellis, L |
| collection | OXFORD |
| description | The unconstrained growth rate of COVID-19 is crucial for measuring the impact of interventions, assessing worst-case scenarios, and calibrating mathematical models for policy planning. However, robust estimates are limited, with scientific focus on the time-insensitive basic reproduction number R0. Using multiple countries, data streams and methods, we consistently estimate that European COVID-19 cases doubled every three days when unconstrained, with the impact of physical distancing interventions typically seen about nine days after implementation, during which time cases grew eight-fold. The combination of fast growth and long detection delays explains the struggle in countries' response better than large values of R0 alone, and warns against relaxing physical distancing measures too quickly. Testing and tracing are fundamental in shortening such delays, thus preventing cases from escalating unnoticed. |
| first_indexed | 2024-03-06T19:18:41Z |
| format | Journal article |
| id | oxford-uuid:194e030f-f90d-45a9-b425-127df7b35c7f |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:18:41Z |
| publishDate | 2020 |
| publisher | Cold Spring Harbor Laboratory |
| record_format | dspace |
| spelling | oxford-uuid:194e030f-f90d-45a9-b425-127df7b35c7f2022-03-26T10:48:17ZChallenges in control of Covid-19: short doubling time and long delay to effect of interventionsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:194e030f-f90d-45a9-b425-127df7b35c7fEnglishSymplectic ElementsCold Spring Harbor Laboratory2020Pellis, LScarabel, FStage, HBOverton, CEChappell, LHKLythgoe, KAFearon, EBennett, ECurran-Sebastian, JDas, RFyles, MLewkowicz, HPang, XVekaria, BWebb, LHouse, TAHall, IThe unconstrained growth rate of COVID-19 is crucial for measuring the impact of interventions, assessing worst-case scenarios, and calibrating mathematical models for policy planning. However, robust estimates are limited, with scientific focus on the time-insensitive basic reproduction number R0. Using multiple countries, data streams and methods, we consistently estimate that European COVID-19 cases doubled every three days when unconstrained, with the impact of physical distancing interventions typically seen about nine days after implementation, during which time cases grew eight-fold. The combination of fast growth and long detection delays explains the struggle in countries' response better than large values of R0 alone, and warns against relaxing physical distancing measures too quickly. Testing and tracing are fundamental in shortening such delays, thus preventing cases from escalating unnoticed. |
| spellingShingle | Pellis, L Scarabel, F Stage, HB Overton, CE Chappell, LHK Lythgoe, KA Fearon, E Bennett, E Curran-Sebastian, J Das, R Fyles, M Lewkowicz, H Pang, X Vekaria, B Webb, L House, TA Hall, I Challenges in control of Covid-19: short doubling time and long delay to effect of interventions |
| title | Challenges in control of Covid-19: short doubling time and long delay to effect of interventions |
| title_full | Challenges in control of Covid-19: short doubling time and long delay to effect of interventions |
| title_fullStr | Challenges in control of Covid-19: short doubling time and long delay to effect of interventions |
| title_full_unstemmed | Challenges in control of Covid-19: short doubling time and long delay to effect of interventions |
| title_short | Challenges in control of Covid-19: short doubling time and long delay to effect of interventions |
| title_sort | challenges in control of covid 19 short doubling time and long delay to effect of interventions |
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