Finland COVID-19 R-value estimate March - August (Q6707960)

This dataset contains the time-dependent effectivereproduction numberRtof the COVID-19 epidemic in Finland for the period Feb 27th2020 - August 14th 2020. The reproduction number wasestimated using the daily new coronavirus cases in the infectious diseases registry ofFinlandwith an unscented RTS smoother and the SEIR epidemicmodel. The SEIR model was defined as \(S(t+1) = S(t) - \frac{R_t(t)}{T_i} I(t) \frac{S(t)}{N} + \omega_{S}\\ E(t+1) = E(t) + \frac{R_t(t)}{T_i} I(t) \frac{S(t)}{N} - \frac{E(t)}{T_e} + \omega_{E}\\ I(t+1) = I(t) + \frac{E(t)}{T_e}-\frac{I(t)}{T_i} + \omega_{I} \\ R_t(t+1) = R_t(t) + \omega_{R_t}\) with S, E, and Ibeing the susceptible, exposed, andinfective populations, Rtthe time-dependent effective reproduction number, ands are normally distributed random numbers with zero mean and small (1e-8) variance except forRt whose variance was set to 0.00025. The exposed state duration was set toTe=3 days and infective state duration Ti=5 days. The measurement model (from the SEIR state to observed daily new cases)was defined as \(P_\text{new cases}(k) \propto \mathcal{N}\left[ \alpha \frac{R_t(t-5 days)}{T_i}I(t-5\text{days}) \frac{S(t-5\text{days})}{N}, \sigma_\text{new cases}^2(t) \right]\), i.e., via a time-delayed gaussian process whose variance was computed by the observed daily new cases with a 7-day rolling mean. Here the detection rate is set to 10%, but has no significant affect on the computed R-values. The data is a CSV-format file with the columns date = ISO 8601 date string Rt = maximum a posteriori estimate of Rt Rt_lower50 = lower limitof the 50% credible interval for Rt Rt_upper50 = upper limit of the 50% credible interval for Rt Rt_lower90 = lower limitof the 90% credible interval for Rt Rt_upper90 = upper limit of the 90% credible interval for Rt