Table 7.
Included studies covering decision support.
| Studies | Technique(s) |
|---|---|
| Healthcare resource planning | |
| Ivorra (91), Kandula et al. (93) | CM: including or predicting hospitalization rates |
| Moa et al. (94) | Linear model |
| Hadley et al. (63) | Agent-based modeling |
| Lorenzen et al. (92) | Random Forest using electronic health records |
| NPI evaluation | |
| Schüler et al. (40), Aravindakshan et al. (26), Khedher et al. (38), Giordano et al. (31), Prague et al. (35), Dandekar and Barbastathis (56) | CM: introducing NPI effect on transmission rate and reproduction number |
| Mader and Rüttenauer (95) | SCT: analyze effect of vaccinations |
| NPI scenario planning and forecasts | |
| Khedher et al. (38), Giordano et al. (31), Prague et al. (35), Kissler et al. (96) | CM |
| Staffini et al. (53), Shattock et al. (55), Colosi et al. (54), Hoertel et al. (50), Hinch et al. (51), Kerr et al. (52), Silva et al. (58) | ABM and hybrid ABM |
| Flaxman et al. (97) | Bayesian hierarchical model |
| Yeung et al. (49), Nader et al. (48), Barros et al. (98), Haug et al. (99) | ML |
| NPI development | |
| Kwak et al. (100), Colas et al. (101), Khadilkar et al. (102), Padmanabhan et al. (103), Chadi and Mousannif (104) | CM and RL: including health and economic costs |
| Capobianco et al. (59) | Hybrid ABM and RL |
CM, compartmental models; NPI, non-pharmaceutical intervention; SCT, synthetic control technique; ABM, agent-based modeling; ML, machine learning; RL, reinforcement learning.