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.

The large number of individuals placed into quarantine because of possible SARS-CoV-2 exposure has high societal and economic costs. There is ongoing debate about the appropriate duration of quarantine, particularly since the fraction of individuals who eventually test positive is perceived as being low. We use empirically-determined distributions of incubation period, infectivity, and generation time to quantify how the duration of quarantine affects onward transmission from traced contacts of confirmed SARS-CoV-2 cases and from returning travellers. We also consider the roles of testing followed by release if negative (test-and-release), reinforced hygiene, adherence, and symptoms in calculating quarantine efficacy. We show that there are quarantine strategies based on a test-and-release protocol that, from an epidemiological viewpoint, perform almost as well as a 10 day quarantine, but with fewer person days spent in quarantine. The findings apply 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 : Probability that a symptomatic individual is isolated from the population;
2. Δ₁ : Time delay between symptom onset and isolation;
3. τ : Duration prior to symptom onset in which contacts are identifiable;
4. g : Fraction of identifiable contacts that are successfully traced and quarantined per isolated index case;
5. Δ₂ : Time delay between isolation of the index case and the start of quarantine for the secondary contacts.

We have two further parameters describing the epidemic situation without TTIQ measures:

1. R : the expected number of infections caused by a single infected;
2. α : the fraction of transmission that is attributable to asymptomatic cases.

This is work in progress. This has not yet been peer-reviewed. Read the full preprint on medRxiv.