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For: Li J, Giabbanelli P. Returning to a Normal Life via COVID-19 Vaccines in the United States: A Large-scale Agent-Based Simulation Study. JMIR Med Inform 2021;9:e27419. [PMID: 33872188 DOI: 10.2196/27419] [Cited by in Crossref: 29] [Cited by in F6Publishing: 32] [Article Influence: 29.0] [Reference Citation Analysis]
Number Citing Articles
1 Beerman JT, Beaumont GG, Giabbanelli PJ. A Scoping Review of Three Dimensions for Long-Term COVID-19 Vaccination Models: Hybrid Immunity, Individual Drivers of Vaccinal Choice, and Human Errors. Vaccines (Basel) 2022;10:1716. [PMID: 36298581 DOI: 10.3390/vaccines10101716] [Reference Citation Analysis]
2 Mukherjee UK, Seshadri S. Epidemic Modeling, Prediction, and Control. Tutorials in Operations Research: Emerging and Impactful Topics in Operations 2022. [DOI: 10.1287/educ.2022.0241] [Reference Citation Analysis]
3 Bushaj S, Yin X, Beqiri A, Andrews D, Büyüktahtakın İE. A simulation-deep reinforcement learning (SiRL) approach for epidemic control optimization. Ann Oper Res. [DOI: 10.1007/s10479-022-04926-7] [Reference Citation Analysis]
4 Soto-ferrari M, Carrasco-pena A, Prieto D. AGGFORCLUS: A hybrid methodology integrating forecasting with clustering to assess mitigation plans and contagion risk in pandemic outbreaks: the COVID-19 Case Study. Journal of Business Analytics 2022. [DOI: 10.1080/2573234x.2022.2122881] [Reference Citation Analysis]
5 Streilein W, Finklea L, Schuldt D, Schiefelbein MC, Yahalom R, Ali H, Norige A. Evaluating COVID-19 Exposure Notification Effectiveness With SimAEN: A Simulation Tool Designed for Public Health Decision Making. Public Health Rep 2022;:333549221116361. [PMID: 36039558 DOI: 10.1177/00333549221116361] [Reference Citation Analysis]
6 Rykovanov GN, Lebedev SN, Zatsepin OV, Kaminskii GD, Karamov EV, Romanyukha AA, Feigin AM, Chetverushkin BN. Agent-Based Simulation of the COVID-19 Epidemic in Russia. Her Russ Acad Sci 2022;92:479-487. [DOI: 10.1134/s1019331622040219] [Reference Citation Analysis]
7 Cattaneo A, Vitali A, Mazzoleni M, Previdi F. An agent-based model to assess large-scale COVID-19 vaccination campaigns for the Italian territory: The case study of Lombardy region. Comput Methods Programs Biomed 2022;224:107029. [PMID: 35908330 DOI: 10.1016/j.cmpb.2022.107029] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Liu S, Wei C(, Kalgotra P, Cobanoglu C. Seeing is believing? Data mining to create a choice-based conjoint approach for restaurant mobile marketing. International Journal of Hospitality Management 2022;104:103248. [DOI: 10.1016/j.ijhm.2022.103248] [Reference Citation Analysis]
9 Lee S, Zabinsky ZB, Wasserheit JN, Ross JM, Chen S, Liu S. COVID-19 Endemic Plan: Impact of Vaccination and Non-pharmaceutical Interventions with Viral Variants and Waning Immunity Using an Agent-Based Simulation.. [DOI: 10.1101/2022.06.03.22275834] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
10 Nie Z, Xu L, Zhang H, Cao Y, Zhang C, Pan J, Zhang J. Crowding and vaccination: Tourist's two-sided perception on crowding and the moderating effect of vaccination status during COVID-19 pandemic. Journal of Destination Marketing & Management 2022;24:100705. [DOI: 10.1016/j.jdmm.2022.100705] [Reference Citation Analysis]
11 Sun J, Sarfraz M, Khawaja KF, Ozturk I, Raza MA. The Perils of the Pandemic for the Tourism and Hospitality Industries: Envisaging the Combined Effect of COVID-19 Fear and Job Insecurity on Employees’ Job Performance in Pakistan. PRBM 2022;Volume 15:1325-46. [DOI: 10.2147/prbm.s365972] [Cited by in Crossref: 4] [Cited by in F6Publishing: 6] [Article Influence: 4.0] [Reference Citation Analysis]
12 Bianchin G, Dall'Anese E, Poveda JI, Jacobson D, Carlton EJ, Buchwald AG. Novel use of online optimization in a mathematical model of COVID-19 to guide the relaxation of pandemic mitigation measures. Sci Rep 2022;12:4731. [PMID: 35304511 DOI: 10.1038/s41598-022-08389-5] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
13 Daghriri T, Proctor M, Matthews S. Evolution of Select Epidemiological Modeling and the Rise of Population Sentiment Analysis: A Literature Review and COVID-19 Sentiment Illustration. Int J Environ Res Public Health 2022;19:3230. [PMID: 35328916 DOI: 10.3390/ijerph19063230] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
14 Katoto PDMC, Parker S, Coulson N, Pillay N, Cooper S, Jaca A, Mavundza E, Houston G, Groenewald C, Essack Z, Simmonds J, Shandu LD, Couch M, Khuzwayo N, Ncube N, Bhengu P, Rooyen HV, Wiysonge CS. Predictors of COVID-19 Vaccine Hesitancy in South African Local Communities: The VaxScenes Study. Vaccines 2022;10:353. [DOI: 10.3390/vaccines10030353] [Cited by in Crossref: 11] [Cited by in F6Publishing: 11] [Article Influence: 11.0] [Reference Citation Analysis]
15 Lutz CB, Giabbanelli PJ. When Do We Need Massive Computations to Perform Detailed COVID-19 Simulations? Adv Theory Simul 2022;5:2100343. [PMID: 35441122 DOI: 10.1002/adts.202100343] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
16 Ekinci Y, Gursoy D, Can AS, Williams NL. Does travel desire influence COVID-19 vaccination intentions? Journal of Hospitality Marketing & Management. [DOI: 10.1080/19368623.2022.2020701] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
17 Eryarsoy E, Shahmanzari M, Tanrisever F. Models for government intervention during a pandemic. European Journal of Operational Research 2022. [DOI: 10.1016/j.ejor.2021.12.036] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
18 Capris T, Takagi Y, Figueiredo D, Henriques J, Pires IM. A Convolutional Neural Network-enabled IoT framework to verify COVID-19 hygiene conditions and authorize access to facilities. Procedia Computer Science 2022;203:727-732. [DOI: 10.1016/j.procs.2022.07.108] [Reference Citation Analysis]
19 Omae Y, Kakimoto Y, Sasaki M, Toyotani J, Hara K, Gon Y, Takahashi H. SIRVVD model-based verification of the effect of first and second doses of COVID-19/SARS-CoV-2 vaccination in Japan. Math Biosci Eng 2022;19:1026-40. [PMID: 34903024 DOI: 10.3934/mbe.2022047] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
20 Omae Y, Sasaki M, Toyotani J, Hara K, Takahashi H. Theoretical Analysis of the SIRVVD Model for Insights Into the Target Rate of COVID-19/SARS-CoV-2 Vaccination in Japan. IEEE Access 2022;10:43044-54. [DOI: 10.1109/access.2022.3168985] [Reference Citation Analysis]
21 Thompson J, Wattam S. Estimating the impact of interventions against COVID-19: From lockdown to vaccination. PLoS One 2021;16:e0261330. [PMID: 34919576 DOI: 10.1371/journal.pone.0261330] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 4.0] [Reference Citation Analysis]
22 Suppan M, Stuby L, Harbarth S, Fehlmann CA, Achab S, Abbas M, Suppan L. Nationwide Deployment of a Serious Game Designed to Improve COVID-19 Infection Prevention Practices in Switzerland: Prospective Web-Based Study. JMIR Serious Games 2021;9:e33003. [PMID: 34635472 DOI: 10.2196/33003] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
23 Kosinski RJ. The Failures of an Ideal COVID-19 Vaccine: A Simulation Study.. [DOI: 10.1101/2021.11.22.21266669] [Reference Citation Analysis]
24 Kumar N, Oke J, Nahmias-Biran BH. Activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas. Sci Rep 2021;11:22665. [PMID: 34811414 DOI: 10.1038/s41598-021-01522-w] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
25 Song F, Bachmann MO. Vaccination against COVID-19 and society's return to normality in England: a modelling study of impacts of different types of naturally acquired and vaccine-induced immunity. BMJ Open 2021;11:e053507. [PMID: 34785556 DOI: 10.1136/bmjopen-2021-053507] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
26 Maehashi R, Nagaoka R, Nigoshi Y, Hayashi Y, Moriguchi R, Kakimoto Y, Toyotani J, Hara K, Takahashi H, Omae Y. Mathematical Model Considering Effect of COVID-19 Contact-Confirming Application (COCOA) and “GoTo Travel Campaign”. J Phys : Conf Ser 2021;2090:012022. [DOI: 10.1088/1742-6596/2090/1/012022] [Reference Citation Analysis]
27 Jemmali M. Intelligent algorithms and complex system for a smart parking for vaccine delivery center of COVID-19. Complex Intell Systems 2021;:1-13. [PMID: 34777982 DOI: 10.1007/s40747-021-00524-5] [Cited by in Crossref: 10] [Cited by in F6Publishing: 4] [Article Influence: 10.0] [Reference Citation Analysis]
28 Lutz CB, Giabbanelli PJ. When do we need massive computations to perform detailed COVID-19 simulations?. [DOI: 10.1101/2021.08.26.21262694] [Reference Citation Analysis]
29 Suppan M, Stuby L, Harbarth S, Fehlmann CA, Achab S, Abbas M, Suppan L. Nationwide Deployment of a Serious Game Designed to Improve COVID-19 Infection Prevention Practices in Switzerland: Prospective Web-Based Study (Preprint).. [DOI: 10.2196/preprints.33003] [Reference Citation Analysis]
30 Gursoy D, Can AS, Williams N, Ekinci Y. Evolving impacts of COVID-19 vaccination intentions on travel intentions. The Service Industries Journal 2021;41:719-33. [DOI: 10.1080/02642069.2021.1938555] [Cited by in Crossref: 28] [Cited by in F6Publishing: 20] [Article Influence: 28.0] [Reference Citation Analysis]
31 Thompson J, Wattam S. Estimating the impact of interventions against COVID-19: from lockdown to vaccination.. [DOI: 10.1101/2021.03.21.21254049] [Reference Citation Analysis]
32 Li J, Giabbanelli PJ. Identifying Synergistic Interventions to Address COVID-19 Using a Large Scale Agent-Based Model. Computational Science – ICCS 2021 2021. [DOI: 10.1007/978-3-030-77967-2_54] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]