Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts
Summary: Background: Isolation of cases and contact tracing is used to control outbreaks of infectious diseases, and has been used for coronavirus disease 2019 (COVID-19). Whether this strategy will achieve control depends on characteristics of both the pathogen and the response. Here we use a math...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-04-01
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| Series: | The Lancet Global Health |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214109X20300747 |
| _version_ | 1818127410161254400 |
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| author | Joel Hellewell, PhD Sam Abbott, PhD Amy Gimma, MSc Nikos I Bosse, BSc Christopher I Jarvis, PhD Timothy W Russell, PhD James D Munday, MSc Adam J Kucharski, PhD W John Edmunds, ProfPhD Sebastian Funk, PhD Rosalind M Eggo, PhD Fiona Sun Stefan Flasche Billy J Quilty Nicholas Davies Yang Liu Samuel Clifford Petra Klepac Mark Jit Charlie Diamond Hamish Gibbs Kevin van Zandvoort |
| author_facet | Joel Hellewell, PhD Sam Abbott, PhD Amy Gimma, MSc Nikos I Bosse, BSc Christopher I Jarvis, PhD Timothy W Russell, PhD James D Munday, MSc Adam J Kucharski, PhD W John Edmunds, ProfPhD Sebastian Funk, PhD Rosalind M Eggo, PhD Fiona Sun Stefan Flasche Billy J Quilty Nicholas Davies Yang Liu Samuel Clifford Petra Klepac Mark Jit Charlie Diamond Hamish Gibbs Kevin van Zandvoort |
| author_sort | Joel Hellewell, PhD |
| collection | DOAJ |
| description | Summary: Background: Isolation of cases and contact tracing is used to control outbreaks of infectious diseases, and has been used for coronavirus disease 2019 (COVID-19). Whether this strategy will achieve control depends on characteristics of both the pathogen and the response. Here we use a mathematical model to assess if isolation and contact tracing are able to control onwards transmission from imported cases of COVID-19. Methods: We developed a stochastic transmission model, parameterised to the COVID-19 outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like pathogen. We considered scenarios that varied in the number of initial cases, the basic reproduction number (R0), the delay from symptom onset to isolation, the probability that contacts were traced, the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort. Findings: Simulated outbreaks starting with five initial cases, an R0 of 1·5, and 0% transmission before symptom onset could be controlled even with low contact tracing probability; however, the probability of controlling an outbreak decreased with the number of initial cases, when R0 was 2·5 or 3·5 and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R0 of 1·5 were controllable with less than 50% of contacts successfully traced. To control the majority of outbreaks, for R0 of 2·5 more than 70% of contacts had to be traced, and for an R0 of 3·5 more than 90% of contacts had to be traced. The delay between symptom onset and isolation had the largest role in determining whether an outbreak was controllable when R0 was 1·5. For R0 values of 2·5 or 3·5, if there were 40 initial cases, contact tracing and isolation were only potentially feasible when less than 1% of transmission occurred before symptom onset. Interpretation: In most scenarios, highly effective contact tracing and case isolation is enough to control a new outbreak of COVID-19 within 3 months. The probability of control decreases with long delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts. Funding: Wellcome Trust, Global Challenges Research Fund, and Health Data Research UK. |
| first_indexed | 2024-12-11T07:16:55Z |
| format | Article |
| id | doaj.art-3a2a596f13f642229f0014aa9542f826 |
| institution | Directory Open Access Journal |
| issn | 2214-109X |
| language | English |
| last_indexed | 2024-12-11T07:16:55Z |
| publishDate | 2020-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | The Lancet Global Health |
| spelling | doaj.art-3a2a596f13f642229f0014aa9542f8262022-12-22T01:16:12ZengElsevierThe Lancet Global Health2214-109X2020-04-0184e488e496Feasibility of controlling COVID-19 outbreaks by isolation of cases and contactsJoel Hellewell, PhD0Sam Abbott, PhD1Amy Gimma, MSc2Nikos I Bosse, BSc3Christopher I Jarvis, PhD4Timothy W Russell, PhD5James D Munday, MSc6Adam J Kucharski, PhD7W John Edmunds, ProfPhD8Sebastian Funk, PhD9Rosalind M Eggo, PhD10Fiona SunStefan FlascheBilly J QuiltyNicholas DaviesYang LiuSamuel CliffordPetra KlepacMark JitCharlie DiamondHamish GibbsKevin van ZandvoortCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Correspondence to: Dr Rosalind M Eggo, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKSummary: Background: Isolation of cases and contact tracing is used to control outbreaks of infectious diseases, and has been used for coronavirus disease 2019 (COVID-19). Whether this strategy will achieve control depends on characteristics of both the pathogen and the response. Here we use a mathematical model to assess if isolation and contact tracing are able to control onwards transmission from imported cases of COVID-19. Methods: We developed a stochastic transmission model, parameterised to the COVID-19 outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like pathogen. We considered scenarios that varied in the number of initial cases, the basic reproduction number (R0), the delay from symptom onset to isolation, the probability that contacts were traced, the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort. Findings: Simulated outbreaks starting with five initial cases, an R0 of 1·5, and 0% transmission before symptom onset could be controlled even with low contact tracing probability; however, the probability of controlling an outbreak decreased with the number of initial cases, when R0 was 2·5 or 3·5 and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R0 of 1·5 were controllable with less than 50% of contacts successfully traced. To control the majority of outbreaks, for R0 of 2·5 more than 70% of contacts had to be traced, and for an R0 of 3·5 more than 90% of contacts had to be traced. The delay between symptom onset and isolation had the largest role in determining whether an outbreak was controllable when R0 was 1·5. For R0 values of 2·5 or 3·5, if there were 40 initial cases, contact tracing and isolation were only potentially feasible when less than 1% of transmission occurred before symptom onset. Interpretation: In most scenarios, highly effective contact tracing and case isolation is enough to control a new outbreak of COVID-19 within 3 months. The probability of control decreases with long delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts. Funding: Wellcome Trust, Global Challenges Research Fund, and Health Data Research UK.http://www.sciencedirect.com/science/article/pii/S2214109X20300747 |
| spellingShingle | Joel Hellewell, PhD Sam Abbott, PhD Amy Gimma, MSc Nikos I Bosse, BSc Christopher I Jarvis, PhD Timothy W Russell, PhD James D Munday, MSc Adam J Kucharski, PhD W John Edmunds, ProfPhD Sebastian Funk, PhD Rosalind M Eggo, PhD Fiona Sun Stefan Flasche Billy J Quilty Nicholas Davies Yang Liu Samuel Clifford Petra Klepac Mark Jit Charlie Diamond Hamish Gibbs Kevin van Zandvoort Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts The Lancet Global Health |
| title | Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts |
| title_full | Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts |
| title_fullStr | Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts |
| title_full_unstemmed | Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts |
| title_short | Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts |
| title_sort | feasibility of controlling covid 19 outbreaks by isolation of cases and contacts |
| url | http://www.sciencedirect.com/science/article/pii/S2214109X20300747 |
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