DougManuel
commented
4 years ago Here are recent references for serial interval time from the Imperial College group that suggests the mean infectious period is quite a bit lower than 14 days. https://sangeetabhatia03.github.io/covid19-short-term-forecasts/index.html (Note, however, a shorter infectious period created unexpected results for scenarios of higher social distancing. see Bug Issue #506).
"Our main analysis assumes a gamma distributed serial interval with mean 6.48 days and standard deviation of 3.83 days following (4). The serial interval estimates observed from various studies thus far may be biased toward lower values due to observation bias whereby, in contact tracing studies, long serial intervals tend to be under-represented. To account for this, as a sensitivity analysis, we also use a shorter serial interval of mean 4.80 days and standard deviation of 2.70 days (5). Results using this shorter interval are presented in the section Sensitivity Analyses. While using a longer serial interval has very little impact on the weekly forecasts produced, it results in much higher estimates of transmissibility."
StanTraykov
Can you check your assumptions for this default value for gamma γ = 1/14, where 14 days?
The value of 14 days seems high. Most other models use 7 days or a range from 3 to 7 days. (Wolfel et. al).
γ is the inverse of the mean infectious period. right?
There is a reference in the documentation, "γ: the CDC is recommending 14 days of self-quarantine, we'll use γ=1/14."
Is this is referencing the CDC period of active monitoring? Which is based on >97.5CI incubation period Lauer et al., rather than the mean infection period.
γ is referred to in different places in the documentation as the inverse of mean recovery time or the average infection period (in documentation Model/Parameters). The mean recovery time is about 14 days (Verity et al.) is different from the average infectious period. In the application, the term "infectious days" is used.