Individual quarantine versus active monitoring of contacts for the mitigation of COVID-19: a modelling study

Abstract

Background Voluntary individual quarantine and voluntary active monitoring of contacts are core disease control strategies for emerging infectious diseases such as COVID-19. Given the impact of quarantine on resources and individual liberty, it is vital to assess under what conditions individual quarantine can more effectively control COVID-19 than active monitoring. As an epidemic grows, it is also important to consider when these interventions are no longer feasible and broader mitigation measures must be implemented.Methods To estimate the comparative efficacy of individual quarantine and active monitoring of contacts to control severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we fit a stochastic branching model to reported parameters for the dynamics of the disease. Specifically, we fit a model to the incubation period distribution (mean 5•2 days) and to two estimates of the serial interval distribution: a shorter one with a mean serial interval of 4•8 days and a longer one with a mean of 7•5 days. To assess variable resource settings, we considered two feasibility settings: a high-feasibility setting with 90% of contacts traced, a half-day average delay in tracing and symptom recognition, and 90% effective isolation; and a low-feasibility setting with 50% of contacts traced, a 2-day average delay, and 50% effective isolation. FindingsModel fitting by sequential Monte Carlo resulted in a mean time of infectiousness onset before symptom onset of 0•77 days (95% CI -1•98 to 0•29) for the shorter serial interval, and for the longer serial interval it resulted in a mean time of infectiousness onset after symptom onset of 0•51 days (95% CI -0•77 to 1•50). Individual quarantine in high-feasibility settings, where at least 75% of infected contacts are individually quarantined, contains an outbreak of SARS-CoV-2 with a short serial interval (4•8 days) 84% of the time. However, in settings where the outbreak continues to grow (eg, low-feasibility settings), so too will the burden of the number of contacts traced for active monitoring or quarantine, particularly uninfected contacts (who never develop symptoms). When resources are prioritised for scalable interventions such as physical distancing, we show active monitoring or individual quarantine of high-risk contacts can contribute synergistically to mitigation efforts. Even under the shorter serial interval, if physical distancing reduces the reproductive number to 1•25, active monitoring of 50% of contacts can result in overall outbreak control (ie, effective reproductive number <1).Interpretation Our model highlights the urgent need for more data on the serial interval and the extent of presymptomatic transmission to make data-driven policy decisions regarding the cost-benefit comparisons of individual quarantine versus active monitoring of contacts. To the extent that these interventions can be implemented, they can help mitigate the spread of SARS-CoV-2.

COVID-19: US federal accountability for entry, spread, and inequities—lessons for the future

“…Symptom screening alone is unlikely to provide a significant barrier to a virus like SARS-CoV-2 that is capable of presymptomatic transmission [ 22 ], but may be an effective component of mitigation if supplemented by a coherent central strategy to delay case importation. While like-for-like comparisons of government responses to COVID-19 should be interpreted with caution, the benefits of such an approach are well-illustrated by Australia: like the US, Australia is a large and well-developed economy with major metropolitan cities, substantial international travel, and wide variations in population density.…”

Reducing community infection by institutional interventions: a minimal SEIRJ model applied to COVID-19

“…The total population N pop ≈ 6.055 × 10 7 is based on the 2019 population, with an assumption that the number of confirmed cases is C = J = 155/N pop , and the number of asymptomatic cases I = 2J is assumed to be 2 times the number of confirmed cases, which is within the range of previous fitting simulations and surveyed conditions [5][6][7]15 . The estimated serial intervals 7,27,30 as well as incubation times (see Table S1 of the supplementary material) are both around 5-7 days, and so we find it reasonable that given I + J actual infections, there are already R 0 = 2.4 times as many exposed individuals as I + J, where R 0 is the basic reproductive number; its value is obtained from literature rather than the simulation results. We assume that no case had yet been recovered.…”

“…Isolation and case identification is enforced by healthcare personnel at a rate of χ, which is the inverse of the mean time from the onset of being infectious until diagnosis. Previous studies of COVID-19 show that individuals may be infectious hours or days before symptom onset 13,27,28 . Moreover, proper isolation is not always practiced because individuals may find it difficult to interpret mild symptoms and diagnosis, especially in the absence of known contact with COVID-19 cases, occurs days after symptom onset.…”

Containment, Contact Tracing and Asymptomatic Transmission of Novel Coronavirus Disease (COVID-19): A Modelling Study

“…During the early course of the COVID-19 pandemic, the possibility of containment was discussed by a mathematical model, accounting for pre-symptomatic transmission and asymptomatic infection, even when strong evidence of substantial asymptomatic infection was not yet available [ 15 , 16 ]. Several studies have quantified the difficulty of detecting cases by means of dynamic simulation modelling using empirical contact survey data [ 17 , 18 ].…”