25.05.2020

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

Modeling InfectiologyLockdown
Peak CM et al
Lancet Infect Dis

Main result

Adjustment of the sequential Monte Carlo model resulted in a mean pre-symptom onset of infectivity of 0.77 days (95% CI [-1.98;0.29]) using the short serial interval and a mean post-symptom onset of infectivity of 0.51 days (95% CI [-0.77;1.50]) using the longer serial interval.
The well-respected individual quarantine (at least 75% of infected contacts in individual quarantine) contains the Covid-19 epidemic with a short serial interval 84% of the time. If it is less respected, the epidemic is less contained.
When resources are prioritized over adjustable measures (such as physical distancing), active monitoring or individual quarantine of at-risk contacts can synergistically contribute to reducing efforts.
Even with the short serial interval time, if physical distancing reduces the reproductive number to 1.25, active monitoring of 50% of contacts can contain the epidemic (reducing the actual reproductive number to below 1).

Takeaways

In this modelling study, the results on the effectiveness of individual quarantine or active monitoring are highly dependent on the parameters entered, and in particular on the serial interval time and presymptomatic transmission.
The onset of infectivity relative to the onset of symptoms ranges from -0.8 to +0.5 days.
Individual quarantine and active monitoring help to limit the epidemic.
Further studies are needed to refine the parameters used in the model.

Strength of evidence Weak

- Modeling study with a SEIR model
- Using different scenarios with sensible assumptions
- But parameters entered from other studies and containing a strong approximation (defined in the early stages of the epidemic)
- No consideration of susceptible depletion in the model
- Strong assumption of constant R0 according to the scenarios

Objectives

To compare the effectiveness of individual quarantine and active contact monitoring in different scenarios on the control of the Covid-19 outbreak.

Method

Modelling study using a stochastic SEIR (Susceptible, Exposed, Infected, Recovered) branch model with already described epidemiological parameters: one incubation period distribution (mean 5.2 days) and two serial interval distributions (mean 4.8 and 7.5 days).
The model was fitted via these parameters in a sequential Monte Carlo algorithm.
Different scenarios were used, varying the proportion of contacts traced, the time to trace and recognize symptoms and the effectiveness of individual isolation.

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