TABLE 1.

Description of R ₀ estimation methods with list of used abbreviations

ID	Methods	Method description with its abbreviation
1	SIR model3, 4, 5, 6, 7, 8, 9	It is a compartmental model in epidemiology that divides an infectious disease into three parts: Susceptible‐Infectious‐Removed (SIR), which is represented as a dynamical system in mathematics.
2	SEIR model10, 11, 12, 13, 14, 15	Susceptible‐Exposed‐Infectious‐Removed (SEIR) model which is another type of compartmental model which differs from SIR model by adding exposed part that represents the delay time of infected by virus and apparing symptoms (latency period).
3	MSIR model 16	Maternally derived immunity‐Susceptible‐Infectious‐Removed (MSIR) compartmental model that babies got protection from maternal antibodies.
4	MSEIR model 16	It is the same as the model MSIR by joining Exposed component and becoming Maternally derived immunity‐Susceptible‐Exposed‐Infectious‐Removed (MSEIR).
5	SEIHR model17, 18	Entering the Hospitalized class to SEIR model to obtain: Susceptible‐Exposed‐Infectious‐Hospitalized‐Removed (SEIHR).
6	SEIAR model 19	A modified SEIR model with another movement class of compartmental model known as Asymptomatic, to get: Susceptible‐Exposed‐Infectious‐Asymptomatic‐Removed (SEIAR).
7	SEQR model 20	Incorporating the quarantine policy to a mathematical model and obtaining Susceptible‐Exposed‐Quarantined‐Removed (SEQR) model.
8	SIRD model 21	It is the SIR model that addresses the removed class with recovered and dead class to be Susceptible‐Infectious‐Recovered‐Dead (SIRD) model.
9	SUQC model 22	In this model, the infectious class of transmission model is separeted as un‐quanrantined, quarantined and confirmed infected. The model is named Susceptible‐Unquanrantined‐Quarantined‐Confirmed (SUQC) model.
10	SIQR model 23	Its modified SIR model with considering quarantine, Susceptible‐Infectious‐Quarantined‐Recovered (SIQR).
11	S E1E2I1I2HR time‐dependent model 24	It is a mathematical model focusing on the effects of medical resourceson transmission of COVID‐19, stands for susceptible S (t), pre‐stage exposed E1(t), post‐stage exposed E2(t), infected with mild symptoms I1(t), infected with serious symptoms I2(t), hospitalized H(t) and recovered R(t) individuals.
12	SIDARTHE model 25	It is a mathematical model that designed to show transsimssion between different stages in infectious disease. The abbrevation refers to: Susceptible‐Infected ‐Diagnosed‐Ailing‐Recognised‐Threatened‐Healed‐Extinct (SIDARTHE) model. In this model, being infected is dividing into 5 types as: undetected asymptomatic infected, detected asymptomatic infected, undetected symptomatic infected, detected symptomatic infected, and infected with detected life‐threatening symptoms; whereas the removed class in compartmental model is classfied into recovered and dead.
13	Exponential growth9, 26, 27, 28, 29, 30, 31	It is a model that varies exponentially with the time by a specific rate.
14	Generalized growth model 32	It is the growth model with two parameters: (r) represents the growth rate parameter with (p) that is the scaling growth rate parameter. Whenever P = 1, the generalized growth model returns to exponential growth and if 0 < P < 1, then it is sub‐exponential (polynomial) growth.
15	Logistic growth model 33	It is a mathematical model that starts exponentially but it gets stabilized due to the capacity of population.
16	Bayesian estimation method 34	It is a paramter estimation method that deals with paramters as random variables in a statistical model.
17	Fudan‐CCDC model 12	Developed model for the growth rate and CCDC stands for Chinese Center for Disease Control.
18	Least square based method 35	It is a procedure to best fit data in statistics.
19	MCMC method 36	Markov Chain Monte Carlo (MCMC) method. In this technique, the posterior distribution of a desired parameter can be found.
20	Maximum Likelihood Estimation30, 37	It is a method used to estimate parameters with knowing their distributions.
21	Phenomenological modelling 33	Statistical method for modelling.