| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T51 |
0-20 |
Sentence |
denotes |
Short-term forecasts |
| T52 |
21-139 |
Sentence |
denotes |
We calibrate each model to the daily cumulative reported case counts for Hubei and other provinces (all except Hubei). |
| T53 |
140-267 |
Sentence |
denotes |
While the outbreak began in December 2019, available data on cumulative case counts are available starting on January 22, 2020. |
| T54 |
268-377 |
Sentence |
denotes |
Therefore, the first calibration process includes 15 observations: from January 22, 2020 to February 5, 2020. |
| T55 |
378-566 |
Sentence |
denotes |
Each subsequent calibration period increases by one day with each new published daily data, with the last calibration period between January 22, 2020 and February 9, 2020 (19 data points). |
| T56 |
567-666 |
Sentence |
denotes |
We estimate the best-fit model solution to the reported data using nonlinear least squares fitting. |
| T57 |
667-1049 |
Sentence |
denotes |
This process yields the set of model parameters Θ that minimizes the sum of squared errors between the model f(t,Θ) and the data yt; where ΘGLM = (r, p, K), ΘRich = (r, a, K), and ΘSub = (r, p, K 0 , q, C thr) correspond to the estimated parameter sets for the GLM, the Richards model, and the sub-epidemic model, respectively; parameter descriptions are provided in the Supplement. |
| T58 |
1050-1145 |
Sentence |
denotes |
Thus, the best-fit solution f(t,Θˆ) is defined by the parameter set Θˆ=argmin∑t=1n(f(t,Θ)−yt)2. |
| T59 |
1146-1199 |
Sentence |
denotes |
We fix the initial condition to the first data point. |
| T60 |
1200-1333 |
Sentence |
denotes |
We then use a parametric bootstrap approach to quantify uncertainty around the best-fit solution, assuming a Poisson error structure. |
| T61 |
1334-1440 |
Sentence |
denotes |
A detailed description of this method is provided in prior studies (Chowell, 2017; Roosa & Chowell, 2019). |
| T62 |
1441-1596 |
Sentence |
denotes |
The models are refitted to the M = 200 bootstrap datasets to obtain M parameter sets, which are used to define 95% confidence intervals for each parameter. |
| T63 |
1597-1739 |
Sentence |
denotes |
Each of the M model solutions to the bootstrap curves is used to generate m = 30 simulations extended through a forecasting period of 15 days. |
| T64 |
1740-1823 |
Sentence |
denotes |
These 6000 (M × m) curves construct the 95% prediction intervals for the forecasts. |
