[1] Dhungel B, Rahman S, Rahman M, Bhandari AKC, Le PM, Biva NA, et al. Reliability of early estimates of the basic reproduction number of COVID-19: a systematic review and meta-analysis. Int J Environ Res Public Health 2022;19(18):11613. http://dx.doi.org/10.3390/IJERPH191811613CrossRef
[2] Gostic KM, McGough L, Baskerville EB, Abbott S, Joshi K, Tedijanto C, et al. Practical considerations for measuring the effective reproductive number, Rt. PLoS Comput Biol 2020;16(12):e1008409. http://dx.doi.org/10.1371/journal.pcbi.1008409CrossRef
[3] Ferguson NM, Donnelly CA, Anderson RM. Transmission intensity and impact of control policies on the foot and mouth epidemic in Great Britain. Nature 2001;413(6855):542 − 8. http://dx.doi.org/10.1038/35097116CrossRef
[4] Linka K, Peirlinck M, Kuhl E. The reproduction number of COVID-19 and its correlation with public health interventions. Comput Mech 2020;66(4):1035 − 50. http://dx.doi.org/10.1007/s00466-020-01880-8CrossRef
[5] Pijpers FP. A non-parametric method for determining epidemiological reproduction numbers. J Math Biol 2021;82(5):37. http://dx.doi.org/10.1007/s00285-021-01590-6CrossRef
[6] Navarro Valencia VA, Díaz Y, Pascale JM, Boni MF, Sanchez-Galan JE. Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R0 for the Republic of Panama in the 1999-2022 period. Heliyon 2023;9(4):e15424. http://dx.doi.org/10.1016/j.heliyon.2023.e15424CrossRef
[7] Takahashi S, Liao QH, Van Boeckel TP, Xing WJ, Sun JL, Hsiao VY, et al. Hand, foot, and mouth disease in China: modeling epidemic dynamics of enterovirus serotypes and implications for vaccination. PLoS Med 2016;13(2):e1001958. http://dx.doi.org/10.1371/journal.pmed.1001958CrossRef
[8] Anderson RM, May RM. Infectious diseases of humans: dynamics and control. Oxford: Oxford University Press. 1991. https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0950268800059896.https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0950268800059896
[9] Zhang XB, Yan DY, Chen C, Jiang DX, Ding C, Lan L, et al. Research progress on the basic and effective reproductive number in the epidemiology of infectious diseases. Chin J Dis Control Prev 2021;25(7):753-7, 790. http://dx.doi.org/10.16462/j.cnki.zhjbkz.2021.07.003. (In Chinese). http://dx.doi.org/10.16462/j.cnki.zhjbkz.2021.07.003
[10] Ridenhour B, Kowalik JM, Shay DK. Unraveling R0: considerations for public health applications. Am J Public Health 2014;104(2):e32 − 41. http://dx.doi.org/10.2105/AJPH.2013.301704CrossRef
[11] Guerra FM, Bolotin S, Lim G, Heffernan J, Deeks SL, Li Y, et al. The basic reproduction number (R0) of measles: a systematic review. Lancet Infect Dis 2017;17(12):e420 − 8. http://dx.doi.org/10.1016/S1473-3099(17)30307-9CrossRef
[12] Liu Y, Rocklöv J. The effective reproductive number of the Omicron variant of SARS-CoV-2 is several times relative to Delta. J Travel Med 2022;29(3):taac037. http://dx.doi.org/10.1093/jtm/taac037CrossRef
[13] Green WD, Ferguson NM, Cori A. Inferring the reproduction number using the renewal equation in heterogeneous epidemics. J Roy Soc Interface 2022;19(188):20210429. http://dx.doi.org/10.1098/rsif.2021.0429CrossRef
[14] Cori A, Ferguson NM, Fraser C, Cauchemez S. A new framework and software to estimate time-varying reproduction numbers during epidemics. Am J Epidemiol 2013;178(9):1505 − 12. http://dx.doi.org/10.1093/aje/kwt133CrossRef
[15] Thompson RN, Stockwin JE, van Gaalen RD, Polonsky JA, Kamvar ZN, Demarsh PA, et al. Improved inference of time-varying reproduction numbers during infectious disease outbreaks. Epidemics 2019;29:100356. http://dx.doi.org/10.1016/j.epidem.2019.100356CrossRef
[16] Nishiura H, Chowell G. The effective reproduction number as a prelude to statistical estimation of time-dependent epidemic trends. In: Chowell G, Hyman JM, Bettencourt LMA, Castillo-Chavez C, editors. Mathematical and statistical estimation approaches in epidemiology. Dordrecht: Springer. 2009. http://dx.doi.org/10.1007/978-90-481-2313-1_5.http://dx.doi.org/10.1007/978-90-481-2313-1_5
[17] Gressani O, Wallinga J, Althaus CL, Hens N, Faes C. EpiLPS: a fast and flexible Bayesian tool for estimation of the time-varying reproduction number. PLoS Comput Biol 2022;18(10):e1010618. http://dx.doi.org/10.1371/journal.pcbi.1010618CrossRef
[18] Lal R, Huang WD, Li ZQ, Prasad S. An assessment of transmission dynamics via time-varying reproduction number of the second wave of the COVID-19 epidemic in Fiji. Roy Soc Open Sci 2022;9(8):220004. http://dx.doi.org/10.1098/rsos.220004CrossRef
[19] Creswell R, Augustin D, Bouros I, Farm HJ, Miao S, Ahern A, et al. Heterogeneity in the onwards transmission risk between local and imported cases affects practical estimates of the time-dependent reproduction number. Philos Trans Roy Soc A Math Phys Eng Sci 2022;380(2233):20210308. http://dx.doi.org/10.1098/RSTA.2021.0308CrossRef
[20] Eales O, Ainslie KEC, Walters CE, Wang HW, Atchison C, Ashby D, et al. Appropriately smoothing prevalence data to inform estimates of growth rate and reproduction number. Epidemics 2022;40:100604. http://dx.doi.org/10.1016/j.epidem.2022.100604CrossRef
[21] Fraser C. Estimating individual and household reproduction numbers in an emerging epidemic. PLoS One 2007;2(8):e758. http://dx.doi.org/10.1371/journal.pone.0000758CrossRef
[22] Dietz K. The estimation of the basic reproduction number for infectious diseases. Stat Methods Med Res 1993;2(1):23 − 41. http://dx.doi.org/10.1177/096228029300200103CrossRef
[23] Gao DZ, Lou YJ, He DH, Porco TC, Kuang Y, Chowell G, et al. Prevention and control of zika as a mosquito-borne and sexually transmitted disease: a mathematical modeling analysis. Sci Rep 2016;6:28070. http://dx.doi.org/10.1038/srep28070CrossRef
[24] Martcheva M. An introduction to mathematical epidemiology. New York: Springer. 2015. http://dx.doi.org/10.1007/978-1-4899-7612-3.http://dx.doi.org/10.1007/978-1-4899-7612-3
[25] Guo XH, Guo YC, Zhao ZY, Yang ST, Su YH, Zhao BH, et al. Computing R0 of dynamic models by a definition-based method. Infect Dis Model 2022;7(2):196 − 210. http://dx.doi.org/10.1016/j.idm.2022.05.004CrossRef
[26] He SB, Peng YX, Sun KH. SEIR modeling of the COVID-19 and its dynamics. Nonlinear Dyn 2020;101(3):1667 − 80. http://dx.doi.org/10.1007/s11071-020-05743-yCrossRef
[27] Goel S, Bhatia SK, Tripathi JP, Bugalia S, Rana M, Bajiya VP. SIRC epidemic model with cross-immunity and multiple time delays. J Math Biol 2023;87(3):42. http://dx.doi.org/10.1007/S00285-023-01974-WCrossRef
[28] Jain S, Kumar S. Dynamic analysis of the role of innate immunity in SEIS epidemic model. Eur Phys J Plus 2021;136(4):439. http://dx.doi.org/10.1140/epjp/s13360-021-01390-3CrossRef
[29] Tang B, Wang X, Li Q, Bragazzi NL, Tang SY, Xiao YN, et al. Estimation of the transmission risk of the 2019-nCoV and its implication for public health interventions. J Clin Med 2020;9(2):462. http://dx.doi.org/10.3390/jcm9020462CrossRef
[30] Zhou WK, Wang AL, Xia F, Xiao YN, Tang SY. Effects of media reporting on mitigating spread of COVID-19 in the early phase of the outbreak. Math Biosci Eng 2020;17(3):2693 − 707. http://dx.doi.org/10.3934/mbe.2020147CrossRef
[31] Yakob L, Clements ACA. A mathematical model of chikungunya dynamics and control: the major epidemic on Réunion Island. PLoS One 2013;8(3):e57448. http://dx.doi.org/10.1371/journal.pone.0057448CrossRef
[32] Rudge JW, Webster JP, Lu DB, Wang TP, Fang GR, Basáñez MG. Identifying host species driving transmission of schistosomiasis japonica, a multihost parasite system, in China. Proc Natl Acad Sci USA 2013;110(28):11457 − 62. http://dx.doi.org/10.1073/pnas.1221509110CrossRef
[33] Li Y, Zhang JH, Zhang XN. Modeling and preventive measures of hand, foot and mouth disease (HFMD) in China. Int J Environ Res Public Health 2014;11(3):3108 − 17. http://dx.doi.org/10.3390/ijerph110303108CrossRef
[34] Unwin HJT, Cori A, Imai N, Gaythorpe KAM, Bhatia S, Cattarino L, et al. Using next generation matrices to estimate the proportion of infections that are not detected in an outbreak. Epidemics 2022;41:100637. http://dx.doi.org/10.1016/j.epidem.2022.100637CrossRef
[35] Bidari S, Chen XY, Peters D, Pittman D, Simon PL. Solvability of implicit final size equations for SIR epidemic models. Math Biosci 2016;282:181 − 90. http://dx.doi.org/10.1016/j.mbs.2016.10.012CrossRef
[36] Penn MJ, Donnelly CA. Asymptotic analysis of optimal vaccination policies. Bull Math Biol 2023;85(3):15. http://dx.doi.org/10.1007/s11538-022-01114-3CrossRef
[37] Shaw CL, Kennedy DA. What the reproductive number R0 can and cannot tell us about COVID-19 dynamics. Theor Popul Biol 2021;137:2 − 9. http://dx.doi.org/10.1016/j.tpb.2020.12.003CrossRef
[38] Nash RK, Nouvellet P, Cori A. Real-time estimation of the epidemic reproduction number: scoping review of the applications and challenges. PLoS Digit Health 2022;1(6):e0000052. http://dx.doi.org/10.1371/journal.pdig.0000052CrossRef
[39] Griffin J, Casey M, Collins Á, Hunt K, McEvoy D, Byrne A, et al. Rapid review of available evidence on the serial interval and generation time of COVID-19. BMJ Open 2020;10(11):e040263. http://dx.doi.org/10.1136/bmjopen-2020-040263CrossRef
[40] Boëlle PY, Ansart S, Cori A, Valleron AJ. Transmission parameters of the A/H1N1 (2009) influenza virus pandemic: a review. Influenza Other Respir Viruses 2011;5(5):306 − 16. http://dx.doi.org/10.1111/j.1750-2659.2011.00234.xCrossRef
[41] Svensson Å. A note on generation times in epidemic models. Math Biosci 2007;208(1):300 − 11. http://dx.doi.org/10.1016/j.mbs.2006.10.010CrossRef
[42] Koh WM, Bogich T, Siegel K, Jin J, Chong EY, Tan CY, et al. The epidemiology of hand, foot and mouth disease in Asia: a systematic review and analysis. Pediatr Infect Dis J 2016;35(10):e285 − 300. http://dx.doi.org/10.1097/INF.0000000000001242CrossRef
[43] Nouvellet P, Cori A, Garske T, Blake IM, Dorigatti I, Hinsley W, et al. A simple approach to measure transmissibility and forecast incidence. Epidemics 2018;22:29 − 35. http://dx.doi.org/10.1016/j.epidem.2017.02.012CrossRef
[44] Townsend SE, Sumantra IP, Pudjiatmoko, Bagus GN, Brum E, Cleaveland S, et al. Designing programs for eliminating canine rabies from islands: Bali, Indonesia as a case study. PLoS Negl Trop Dis 2013;7(8):e2372. http://dx.doi.org/10.1371/journal.pntd.0002372CrossRef
[45] Abbott S, Hickson J, Funk S, Badr HS, Monticone P, Ellis P, et al. epiforecasts/EpiNow2: 1.3.4 release. Zenodo; 2023. http://dx.doi.org/10.5281/zenodo.7611804.http://dx.doi.org/10.5281/zenodo.7611804
[46] Obadia T, Haneef R, Boëlle PY. The R0 package: a toolbox to estimate reproduction numbers for epidemic outbreaks. BMC Med Inform Decis Mak 2012;12:147. http://dx.doi.org/10.1186/1472-6947-12-147CrossRef