This tool estimates national trends in daily confirmed cases, hospitalizations, ICU occupancy and deaths using a negative binomial generalized linear model. The model uses reported numbers as the response and date and weekend (0: work day, 1: weekend) as predictors. Confirmed cases and hospitalizations are further stratified by canton and age groups. Due to reporting delays, the last 3 and 5 days of confirmed cases and hospitalizations/deaths are removed, respectively. Lines and ribbons show the maximum likelihood estimate of the exponential increase/decrease and the 95% prediction intervals of the model fit, respectively.

We present a mathematical model that leverages empirically determined distributions of incubation period, infectivity, and generation time to quantify how the duration of quarantine affects onward transmission of SARS-CoV-2. With this model we address the impact of shortening the quarantine for returning travellers and traced contacts of confirmed cases, both in terms of prevented transmission and the ratio of prevented transmission to days spent in quarantine. We also consider the impact of

1. test-and-release strategies;
2. additional hygiene measures imposed upon release after a negative test;
3. the development of symptoms during quarantine;
4. the relationship between quarantine duration and adherence; and
5. the specificity of quarantine.

When considering the benefit versus cost utility of quarantine, we find that the diminishing impact of longer quarantine on transmission prevention may support a quarantine duration below 10 days. A greater gain of utility can be achieved through a test-and-release strategy, and this can be even further strengthened by imposed hygiene measures post-release. We also find that unless a test-and-release strategy is considered, the fraction of individuals in quarantine that are infected does not affect the optimal duration of quarantine under our utility metric. Ultimately, we show that there are quarantine strategies based on a test-and-release protocol that, from an epidemiological viewpoint, perform almost as well as the standard 10 day quarantine, but with a lower cost in terms of person days spent in quarantine. This applies to both travellers and contacts, but the specifics depend on the context.

Read the full preprint on medRxiv.

We present a mathematical model that leverages empirically determined distributions of incubation period, infectivity, and generation time to quantify how test-trace-isolate-quarantine (TTIQ) strategies can reduce the transmission of SARS-CoV-2. The TTIQ strategy is determined by five independent parameters:

1. f : the fraction of infected individuals who test positive and are isolated from the community;
2. Δ₁ : the delay between symptom onset of an infected individual and the time they are isolated from the community;
3. τ : the duration of time for which close contacts are traced prior to symptom onset;
4. g : the fraction of close contacts per index case that are successfully traced and quarantined;
5. Δ₂ : the delay between isolating the index case and quarantining the secondary cases.

This is work in progress. This has not yet been peer-reviewed.