Feasibility of controlling 2019-nCoV outbreaks by isolation of cases and contacts


Background: To assess the viability of isolation and contact tracing to control onwards transmission from imported cases of 2019-nCoV. Methods: We developed a stochastic transmission model, parameterised to the 2019-nCoV outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a 2019 nCoV-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 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: While simulated outbreaks starting with only 5 initial cases, R0 of 1.5 and little transmission before symptom onset could be controlled even with low contact tracing probability, the prospects of controlling an outbreak dramatically dropped with the number of initial cases, with higher R0, 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 under 50% of contacts successfully traced. For R0 of 2.5 and 3.5, more than 70% and 90% of contacts respectively had to be traced to control the majority of outbreaks. The delay between symptom onset and isolation played the largest role in determining whether an outbreak was controllable for lower values of R0. For higher values of R0 and a large initial number of cases, contact tracing and isolation was only potentially feasible when less than 1% of transmission occurred before symptom onset. Interpretation: We found that in most scenarios contact tracing and case isolation alone is unlikely to control a new outbreak of 2019-nCov within three months. The probability of control decreases with longer 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. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The named authors (JH, SA, AG, NIB, CIJ, TWR, JDM, AJK, WJE, SF, RME) had the following sources of funding: JH, SA, JDM and SF were funded by the Wellcome Trust (grant number: 210758/Z/18/Z), AG and CIJ were funded by the Global Challenges Research Fund (grant number: ES/P010873/1), TWR and AJK were funded by the Wellcome Trust (grant number: 206250/Z/17/Z), and RME was funded by HDR UK (grant number: MR/S003975/1). This research was partly funded by the National Institute for Health Research (NIHR) (16/137/109) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care. This research was partly funded by the Bill & Melinda Gates Foundation (INV-003174). This research was also partly funded by the Global Challenges Research Fund (GCRF) project ‘RECAP’ managed through RCUK and ESRC (ES/P010873/1). We would like to acknowledge (in a randomised order) the other members of the LSHTM 2019-nCoV modelling group, who contributed to this work: Stefan Flasche, Mark Jit, Nicholas Davies, Sam Clifford, Billy J Quilty, Yang Liu, Charlie Diamond, Petra Klepac and Hamish Gibbs. Their funding sources are as follows: SF and SC (Sir Henry Dale Fellowship (grant number: 208812/Z/17/Z)), MJ, YL, PK (BMGF (grant number: INV-003174)), ND (NIHR (grant number: HPRU-2012-10096)), BJQ (grant number: NIHR (16/137/109)), CD & YL (NIHR (grant number: 16/137/109)), and HG (Department of Health and Social Care (grant number: ITCRZ 03010)) ### Author Declarations All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript. Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes No data are used. Model code is available.

MIDAS Network Members

John Edmunds

Professor of Infectious Disease Modelling
London School of Hygiene & Tropical Medicine


Hellewell Joel, Abbott Sam, Gimma Amy, Bosse Nikos I, Jarvis Christopher I, Russell Timothy W, Munday James D, Kucharski Adam J, Edmunds W John, group CMMID nCoV working, Funk Sebastian, Eggo Rosalind M. (2020). Feasibility of controlling 2019-nCoV outbreaks by isolation of cases and contacts. Cold Spring Harbor Laboratory Press