Table 2.

The 23 selected papers on other (not compartmental) COVID-19 models.

Models	Model type	Study area	Outcomes	References
Agent based model	Stochastic	38 countries or provinces in Asia, Europe and North America (Kai & Guy-PhilippeGoldstein, 2020), Singapore (Koo, Cook, Park, & Sun, 2020)	The impact of universal Masking (Kai & Guy-PhilippeGoldstein, 2020), the likelihood of human-to-human transmission of SARS-CoV-2 (Koo et al., 2020)	(Kai & Guy-PhilippeGoldstein, 2020; Koo et al., 2020)
Branching process model	Stochastic	Wuhan	The impact of contact tracing and isolation	Hellewell et al. (2020)
Bayesian method	Stochastic	Outside Hubei in Chinese mainland(J. Zhang et al., 2020, Zhang et al., 2020), China(Verity, Okell, Dorigatti, & Winskill, 2020), Singapore, Tianjin(Ganyani et al., 2020)	R0, Incubation period, serial interval (J. Zhang et al., 2020, Zhang et al., 2020), age-stratified estimates of CFR and IFR (Verity et al., 2020), generation interval (Ganyani et al., 2020)	(Ganyani et al., 2020; Verity et al., 2020; J.; Zhang et al., 2020, Zhang et al., 2020)
Generalized Linear Models	Stochastic	China	Incubation period, the effect of human mobility and control measures	Kraemer et al. (2020)
Generalized growth model	Stochastic	Lima (Munayco et al., 2020), Iran (Muniz-Rodriguez et al., 2020), South Korea (Shim, Tariq, Choi, Lee, & Chowell, 2020)	R0(Munayco et al., 2020; Muniz-Rodriguez et al., 2020; Shim et al., 2020), the impact of social distancing (Munayco et al., 2020; Muniz-Rodriguez et al., 2020),doubling time (Shim et al., 2020)	(Munayco et al., 2020; Muniz-Rodriguez et al., 2020; Shim et al., 2020)
Linear growth & exponential growth model	Stochastic	Italy, Japan	The effect of the changes in testing rates on epidemic growth rate	Omori, Mizumoto, and Chowell (2020)
Exponential growth	Stochastic	China	R0 (Thompson, 2020; S. Zhao, Q. Li, Pei, et al., 2020; S. Zhao et al., 2020, Zhao et al., 2020, Zhao et al., 2020), the estimates of the unreported number of COVID-19 (Zhao et al., 2020, Zhao et al., 2020, Zhao et al., 2020), the risk of sustained transmission (Thompson, 2020), the impact of reporting rate (S. Zhao, Q. Li, Pei, et al., 2020)	(Thompson, 2020; S. Zhao, Q. Li, Pei, et al., 2020; Zhao et al., 2020, Zhao et al., 2020, Zhao et al., 2020)
Second derivative model	Stochastic	China	The assessment the detection rate	Chen and Yu (2020)
Poisson Transmission Model	Stochastic	China	R0	Zhu and Chen (2020)
Segmented Poisson model	Stochastic	Canada, France, Germany, Italy, UK and USA	Turning point, duration and attack rate	Zhang et al., 2020, Zhang et al., 2020
Analytically solvable model	Stochastic	China	The estimates of the contribution of different transmission routes, generation time	Ferretti et al. (2020)
Gaussian distribution theory	Stochastic	China, South Korea, Italy, Iran	R0, incubation period	(L. Li, Pei, et al., 2020)
Phenomenological models	Stochastic	China, Hubei(Roosa et al., 2020a), Guangdong, Zhejiang(Roosa et al., 2020b)	Short-term prediction of cumulative confirmed cases	(Roosa et al., 2020a, 2020b)
Transmission model with zoonotic infections	Stochastic	Wuhan	R0, doubling time, incubation period, serial interval	(Q. Li, Pei, et al., 2020)
Data-driven and model-free estimations	–	Canada	The prediction of epidemic trends with different public health interventions, mortality	Scarabel, Pellis, Bragazzi, and Wu (2020)