Table 1.
R0 estimates for cities and provinces within China.
| Author | Location | Estimation period | Methods | R0 | 95% CI |
| Li JH[7] | Wuhan | January 10–23, 2020 | EGR | 5.54 | 5.07–6.06 |
| Liu T[8] | Wuhan | By February 7, 2020 | EGR | 4.40 | 4.30–4.60 |
| Liu T[8] | China | By February 7, 2020 | EGR | 4.50 | 4.40–4.60 |
| Sanche S[9] | Wuhan | January 15–30, 2020 | EGR | 5.70 | 3.80–8.90 |
| Song QQ[10] | China | January 15–31, 2020 | EGR | 3.74 | 3.63–3.87 |
| Wang Y[5] | China | Jan 17 to February 8, 2020 | EGR | 3.49 | 3.42–3.58 |
| Zhao QY[11] | Wuhan | By January 23, 2020 | EGR | 5.70 | 3.40–9.20 |
| Zhao S[12] | China | January 10–24, 2020 | EGR | 2.24 | 1.96–2.55 |
| Zhao S[12] | China | January 10–24, 2020 | EGR | 3.58 | 2.89–4.39 |
| Zhao S[13] | Wuhan | January 1–15, 2020 | EGR | 2.56 | 2.49–2.63 |
| Li JH 7 | Wuhan | January 10–23, 2020 | SEIR | 3.55 | 2.97–4.21 |
| Read J[14] | China | January 1–22, 2020 | SEIR | 3.11 | 2.39–4.13 |
| Shen MW[15] | China | December 12, 2019 to January 22, 2020 | SEIR | 4.71 | 4.50–4.92 |
| Song QQ[10] | China | January 15–31, 2020 | SEIR | 3.91 | 3.71–4.11 |
| Tang B[16] | China | By January 22, 2020 | SEIR | 6.47 | 5.71–7.23 |
| Zhou T[17] | China | By 25 January, 2020 | SEIR | 2.80–3.30 (3.05) | / |
| Zhou WK[18] | China | By January 10, 2020 | SEIR | 5.32 | / |
| Cao ZD[19] | China | By January 23, 2020 | SEIRDC | 4.08 | |
| Chen TM[20] | Wuhan | December 7, 2019 to January 1, 2020 | SEIAR | 3.58 | / |
| LI Y[21] | China | By January 23, 2020 | SEIQR | 5.60 | / |
| Li JH[7] | Wuhan | January 10–23, 2020 | MLE | 2.65 | 2.64–2.67 |
| Song QQ[10] | China | January 15–31, 2020 | MLE | 3.16 | 2.90–3.43 |
| Tang B[22] | China | January 1–23, 2020 | MLE | 3.80 | 3.50–4.20 |
| Tang B[22] | Guangdong | January 19–31, 2020 | MLE | 3.00 | 2.60–3.30 |
| Wang Y[5] | China | January 17 to February 8, 2020 | MLE | 2.99 | 2.93–3.06 |
| Jung SM[23] | China | By January 24, 2020 | Epidemic growth model | 2.10 | 2.00–2.20 |
| Jung SM[23] | China | By January 24, 2020 | Epidemic growth model | 3.20 | 2.70–3.70 |
| Li JH[7] | Wuhan | January 10–23, 2020 | Sequential Bayesian method | 1.68 | 1.09–2.33 |
| Wang Y[5] | China | January 17 to February 8, 2020 | Sequential Bayesian method | 2.80 | 2.42–3.15 |
| Li JH[7] | Wuhan | January 10–23, 2020 | Time dependent reproduction number | 5.95 | 4.96–7.03 |
| Wang Y[5] | China | January 17 to February 8, 2020 | Time dependent reproduction number | 4.48 | 4.26–4.71 |
| Cao ZD[24] | Wuhan | By January 23, 2020 | Geo-stratified debiasing estimation framework | 3.24 | / |
| Chinazzi M[25] | China | By January 23, 2020 | GLEAM and SLIR | 2.57 | 2.37–2.78 (90% CI) |
| Li Q[26] | China | By January 22, 2020 | Fitted transmission model with zoonotic infection | 2.20 | 1.40–3.90 |
| Du ZW[27] | Wuhan | By January 22, 2020 | Hierarchical model | 1.90 | 1.47–2.59 |
| Imai N[28] | China | By January 18, 2020 | Mathematical model | 1.50–3.50 | / |
| Majumder M[29] | Wuhan | December 8, 2019 to January 26, 2020 | Incidence Decay and Exponential Adjustment (IDEA) model | 2.00–3.10 (2.50) | / |
| Wu J[30] | Wuhan | December 31, 2019 to January 28, 2020 | Markov Chain Monte Carlo methods | 2.68 | 2.47–2.86 |
| Riou J[31] | China | By January 18, 2020 | Stochastic simulations of early outbreak trajectories | 2.20 | 1.40–3.80 (90% HDI) |
CI = confidence interval, EGR = exponential growth rate, GLEAM = global epidemic and mobility model, HDI = high-density interval, MLE = maximum likelihood estimation, SEIAR = susceptible, exposed symptomatic, infectious asymptomatic, infectious removed, SEIQR = susceptible, exposed, infected but not hospitalized, infectious and isolated recovered, SEIR = susceptible-exposed-infected-removed, SEIRDC = SEIR with death cumulative, SLIR = susceptible latent infectious recovered.