[1]        Gandon, S. and S. Lion, Targeted vaccination and the speed of SARS-CoV-2 adaptation. Proceedings of the National Academy of Sciences, 2022. 119(3).

       [2]        Chen, F.J.J.o.t.b., A mathematical analysis of public avoidance behavior during epidemics using game theory. 2012. 302: p. 18-28.

       [3]        Wells, C.R., E.Y. Klein, and C.T.J.P.C.B. Bauch, Policy resistance undermines superspreader vaccination strategies for influenza. 2013. 9(3): p. e1002945.

       [4]        Stockwell, M.S., A.G.J.H.v. Fiks, and immunotherapeutics, Utilizing health information technology to improve vaccine communication and coverage. 2013. 9(8): p. 1802-1811.

       [5]        Dharmawardana, K., et al. Predictive model for the dengue incidences in Sri Lanka using mobile network big data. in 2017 IEEE International Conference on Industrial and Information Systems (ICIIS). 2017. IEEE.

       [6]        Bhopal, S. and M.J.A.o.D.i.C. Nielsen, Vaccine hesitancy in low-and middle-income countries: potential implications for the COVID-19 response. 2021. 106(2): p. 113-114.

       [7]        Altmann, D.M., D.C. Douek, and R.J.J.T.L. Boyton, What policy makers need to know about COVID-19 protective immunity. 2020. 395(10236): p. 1527-1529.

       [8]        Holzmann-Littig, C., et al., COVID-19 vaccination acceptance among healthcare workers in Germany. 2021.

       [9]        Madison, A.A., et al., Psychological and behavioral predictors of vaccine efficacy: Considerations for COVID-19. 2021. 16(2): p. 191-203.

     [10]      Cook, T. and J.J.A. Roberts, Impact of vaccination by priority group on UK deaths, hospital admissions and intensive care admissions from COVID‐19. 2021. 76(5): p. 608-616.

     [11]      Razai, M.S., et al., Covid-19 vaccine hesitancy among ethnic minority groups. 2021, British Medical Journal Publishing Group.

     [12]      Buckner, J.H., G. Chowell, and M.R.J.P.o.t.N.A.o.S. Springborn, Dynamic prioritization of COVID-19 vaccines when social distancing is limited for essential workers. 2021. 118(16).

     [13]      Rachaniotis, N.P., et al., A two-phase stochastic dynamic model for COVID-19 mid-term policy recommendations in Greece: a pathway towards mass vaccination. 2021. 18(5): p. 2497.

     [14]      Jadidi, M., et al., A two-step vaccination technique to limit COVID-19 spread using mobile data. 2021. 70: p. 102886.

     [15]      Sun, X., et al. Targeted vaccination based on a wireless sensor system. in 2015 IEEE International Conference on Pervasive Computing and Communications (PerCom). 2015. IEEE.

     [16]      Salvamani, S., et al., Understanding the dynamics of COVID-19; implications for therapeutic intervention, vaccine development and movement control. 2020. 77(4): p. 168-184.

     [17]      Wilder-Smith, A. and D.O.J.J.o.t.m. Freedman, Isolation, quarantine, social distancing and community containment: pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak. 2020.

     [18]      Behdinian, A., et al., An integrating Machine learning algorithm and simulation method for improving Software Project Management: A real case study. Journal of Quality Engineering and Production Optimization, 2022.

     [19]      Amani, M.A. and F. Marinello, A Deep Learning-Based Model to Reduce Costs and Increase Productivity in the Case of Small Datasets: A Case Study in Cotton Cultivation. Agriculture, 2022. 12(2): p. 267.

     [20]      Rahman, M., et al., Machine Learning on the COVID-19 Pandemic, Human Mobility and Air Quality: A Review. 2021.

     [21]      Al Zobbi, M., et al., Measurement Method for Evaluating the Lockdown Policies during the COVID-19 Pandemic. 2020. 17(15): p. 5574.

     [22]      Asad, S.M., et al. Travelers-Tracing and Mobility Profiling Using Machine Learning in Railway Systems. in 2020 International Conference on UK-China Emerging Technologies (UCET). 2020. IEEE.

     [23]      Hosseini, M.S. and A.M. Gittler. Factors Influencing Human Mobility During The COVID-19 Pandemic in Selected Countries of Europe and North America. in 2020 IEEE International Conference on Big Data (Big Data). 2020. IEEE.

     [24]      Ahmadi, M.R. and R.S. Shahabi, Cutoff grade optimization in open pit mines using genetic algorithm. Resources Policy, 2018. 55: p. 184-191.

     [25]      Amani, M.A., et al., A machine learning-based model for the estimation of the temperature-dependent moduli of graphene oxide reinforced nanocomposites and its application in a thermally affected buckling analysis. Engineering with Computers, 2021. 37(3): p. 2245-2255.

     [26]      Lan, T., et al., A comparative study of decision tree, random forest, and convolutional neural network for spread-F identification. Advances in Space Research, 2020. 65(8): p. 2052-2061.

     [27]      Joshi, T., et al., An improved ant colony optimization with correlation and Gini importance for feature selection, in Communication and Intelligent Systems. 2021, Springer. p. 629-641.