List of COVID-19 simulation models

Last updated

COVID-19 simulation models are mathematical infectious disease models for the spread of COVID-19. [1] The list should not be confused with COVID-19 apps used mainly for digital contact tracing.

Contents

Note that some of the applications listed are website-only models or simulators, and some of those rely on (or use) real-time data from other sources.

Models with the most scientific backing

The sub-list contains simulators that are based on theoretical models. Due to the high number of pre-print research created and driving by the COVID-19 pandemic, [2] especially newer models should only be considered with further scientific rigor. [3] [4]

Simulations and models

Genome databases

Several of these models make use of genome databases, including the following:

Consortia, research clusters, other collections

Vaccination monitors, models or dashboards

Note: The following (additional) resources are mostly based on actual data, not simulation. They might include predictive features, e. g. vaccination rate estimation, but in general are not based on theoretical or modeling grounds as the main list of this article. Nonetheless, forecasting remains important. [64] (See for example the COVID-19 Forecast Hub) [65]

Models with less scientific backing

The following models are purely for educational purposes only.

Trainings and other resources

See also

Related Research Articles

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References

  1. ↑ Adam D (April 2020). "Special report: The simulations driving the world's response to COVID-19". Nature. 580 (7803): 316–318. Bibcode:2020Natur.580..316A. doi:10.1038/d41586-020-01003-6. PMID   32242115. S2CID   256820433.
  2. ↑ Brierley L. "The role of research preprints in the academic response to the COVID-19 epidemic". Authorea Preprints. doi: 10.22541/au.158516578.89167184 .
  3. ↑ "Another 178,000 deaths? Scientists' latest virus projection is a warning". NBC News. 24 September 2020. Retrieved 2021-02-22.
  4. ↑ Tufekci Z (2020-04-02). "Don't Believe the COVID-19 Models". The Atlantic. Retrieved 2021-02-22.
  5. ↑ Chen TM, Rui J, Wang QP, Zhao ZY, Cui JA, Yin L (February 2020). "A mathematical model for simulating the phase-based transmissibility of a novel coronavirus". Infectious Diseases of Poverty. 9 (1): 24. doi: 10.1186/s40249-020-00640-3 . PMC   7047374 . PMID   32111262.
  6. ↑ "CoSim Online". shiny.covid-simulator.com. Retrieved 14 December 2023.
  7. ↑ "COVID-19 Mobility Network Modeling". covid-mobility.stanford.edu. Retrieved 14 December 2023.
  8. ↑ Chang S, Pierson E, Koh PW, Gerardin J, Redbird B, Grusky D, Leskovec J (January 2021). "Mobility network models of COVID-19 explain inequities and inform reopening". Nature. 589 (7840): 82–87. Bibcode:2021Natur.589...82C. doi: 10.1038/s41586-020-2923-3 . PMID   33171481.
  9. ↑ "Home - COVID-19 Simulator". covid19sim.org. Retrieved 14 December 2023.
  10. ↑ "Policy Simulator Methodology". COVID-19 Simulator. Retrieved 2021-02-21.
  11. ↑ "Healthcare Workers". Centers for Disease Control and Prevention. 11 February 2020. Retrieved 14 December 2023.
  12. ↑ CDC (2020-02-11). "Healthcare Workers". Centers for Disease Control and Prevention. Retrieved 2021-02-22.
  13. ↑ Ng MK. "SEIRS-based COVID-19 Simulation Package". markusng.com. Retrieved 14 December 2023.
  14. ↑ "Research project - CovidSim - Modeling and simulation of covid infection spread in crowds in system relevant infrastructures - HM Hochschule München University of Applied Sciences". Hochschule München. Retrieved 14 December 2023.
  15. ↑ Ng M (24 September 2023). "COVIDSim — SEIRS-based COVID-19 Simulation Package". GitHub . Retrieved 14 December 2023.
  16. ↑ Ng M (2020-12-23), nkymark/COVIDSim , retrieved 2021-03-09
  17. ↑ Ng KY, Gui MM (October 2020). "COVID-19: Development of a robust mathematical model and simulation package with consideration for ageing population and time delay for control action and resusceptibility". Physica D: Nonlinear Phenomena. 411: 132599. arXiv: 2004.01974 . Bibcode:2020PhyD..41132599N. doi:10.1016/j.physd.2020.132599. PMC   7282799 . PMID   32536738.
  18. ↑ "CovidSIM". covidsim.eu. Retrieved 2021-03-13.
  19. ↑ Schneider KA, Ngwa GA, Schwehm M, Eichner L, Eichner M (November 2020). "The COVID-19 pandemic preparedness simulation tool: CovidSIM". BMC Infectious Diseases. 20 (1): 859. doi: 10.1186/s12879-020-05566-7 . PMC   7675392 . PMID   33213360.
  20. ↑ "CovRadar". covradar.net. Retrieved 14 December 2023.
  21. ↑ Wittig A, Miranda F, Hölzer M, Altenburg T, Bartoszewicz JM, Dieckmann MA, et al. (2021-04-06). "CovRadar: Continuously tracking and filtering SARS-CoV-2 mutations for molecular surveillance". bioRxiv   10.1101/2021.02.03.429146v2 .
  22. ↑ "Molecular surveillance of SARS-CoV-2 spike protein mutations using CovRadar". News-Medical.net. 2021-02-07. Retrieved 2021-04-25.
  23. ↑ De-Leon H, Pederiva F (August 2020). "Particle modeling of the spreading of coronavirus disease (COVID-19)". Physics of Fluids. 32 (8): 087113. arXiv: 2005.10357 . Bibcode:2020PhFl...32h7113D. doi:10.1063/5.0020565. PMC   7441410 . PMID   32848352.
  24. ↑ De-Leon H, Pederiva F (July 2021). "Statistical mechanics study of the introduction of a vaccine against COVID-19 disease". Physical Review E. 104 (1): 014132. arXiv: 2012.07306 . Bibcode:2021PhRvE.104a4132D. doi:10.1103/PhysRevE.104.014132. PMID   34412259. S2CID   229155979.
  25. ↑ "Dr. Ghaffarzadegan's model - Simulate your university's covid-19 cases". forio.com. Retrieved 2 May 2021.
  26. ↑ Ghaffarzadegan N (2021-02-01). "Simulation-based what-if analysis for controlling the spread of Covid-19 in universities". PLOS ONE. 16 (2): e0246323. Bibcode:2021PLoSO..1646323G. doi: 10.1371/journal.pone.0246323 . PMC   7850497 . PMID   33524045.
  27. ↑ "COVID-19 simulation model creates scenarios". www.vtnews.vt.edu. Archived from the original on 2021-03-06. Retrieved 2021-02-21.
  28. ↑ "Event Horizon - COVID-19". rocs.hu-berlin.de. Retrieved 14 December 2023.
  29. ↑ Maier BF, Brockmann D (May 2020). "Effective containment explains subexponential growth in recent confirmed COVID-19 cases in China". Science. 368 (6492): 742–746. arXiv: 2002.07572 . Bibcode:2020Sci...368..742M. doi: 10.1126/science.abb4557 . PMC   7164388 . PMID   32269067.
  30. ↑ "Evolutionary AI". evolution.ml. Retrieved 14 December 2023.
  31. ↑ "Evolutionary AI". evolution.ml. Retrieved 2021-04-26.
  32. ↑ Miikkulainen R, Francon O, Meyerson E, Qiu X, Sargent D, Canzani E, Hodjat B (2020-08-01). "From Prediction to Prescription: Evolutionary Optimization of Non-Pharmaceutical Interventions in the COVID-19 Pandemic". arXiv: 2005.13766 [cs.NE].
  33. 1 2 "Can Computer Models Select the Best Public Health Interventions for COVID-19?". IEEE Spectrum: Technology, Engineering, and Science News. 5 January 2021. Retrieved 2021-04-26.
  34. ↑ Siwiak M, Szczesny P, Siwiak M (2020-07-10). "From the index case to global spread: the global mobility based modelling of the COVID-19 pandemic implies higher infection rate and lower detection ratio than current estimates". PeerJ. 8: e9548. doi: 10.7717/peerj.9548 . ISSN   2167-8359. PMC   7357567 . PMID   32728498.
  35. ↑ Abele D, Kühn MJ, Koslow W, Rack K, Siggel M, Kleinert J, et al. (2022-01-01). "MEmilio - a high performance Modular EpideMIcs simuLatIOn software". GitHub.
  36. ↑ Kühn MJ, Abele D, Mitra T, Koslow W, Abedi M, Rack K, et al. (September 2021). "Assessment of effective mitigation and prediction of the spread of SARS-CoV-2 in Germany using demographic information and spatial resolution". Mathematical Biosciences. 339: 108648. doi:10.1016/j.mbs.2021.108648. PMC   8243656 . PMID   34216635.
  37. ↑ Kühn MJ, Abele D, Binder S, Rack K, Klitz M, Kleinert J, Gilg J, Spataro L, Koslow W, Siggel M, Meyer-Hermann M, Basermann A (2022). "Regional opening strategies with commuter testing and containment of new SARS-CoV-2 variants in Germany". BMC Infectious Diseases. 22 (1): 333. doi: 10.1186/s12879-022-07302-9 . ISSN   1471-2334. medRxiv   10.1101/2021.04.23.21255995 . PMC   8978163 . PMID   35379190.
  38. ↑ Koslow W, Kühn MJ, Binder S, Klitz M, Abele D, Basermann A, Meyer-Hermann M (2022-05-16). "Appropriate relaxation of non-pharmaceutical interventions minimizes the risk of a resurgence in SARS-CoV-2 infections in spite of the Delta variant". PLOS Computational Biology. 18 (5): e1010054. Bibcode:2022PLSCB..18E0054K. doi: 10.1371/journal.pcbi.1010054 . ISSN   1553-7358. medRxiv   10.1101/2021.07.09.21260257 . PMC   9135349 . PMID   35576211.
  39. ↑ Shattock AJ, Le Rutte EA, Dünner RP, Sen S, Kelly SL, Chitnis N, Penny MA (March 2022). "Impact of vaccination and non-pharmaceutical interventions on SARS-CoV-2 dynamics in Switzerland". Epidemics. 38 (7): 100535. Bibcode:2021PLSCB..17E9146H. doi:10.1016/j.epidem.2021.100535. PMC   8669952 . PMID   34923396.
  40. ↑ "Git-repository with open access source-code for OpenCOVID". GitHub. Swiss TPH. 2022-01-31. Retrieved 2022-02-15.
  41. ↑ "COVID-19 Government Response Tracker". www.bsg.ox.ac.uk. 18 March 2020. Retrieved 14 December 2023.
  42. ↑ "COVID-19 Government Response Tracker". www.bsg.ox.ac.uk. 18 March 2020. Retrieved 2021-04-26.
  43. ↑ "sc-cosmo – Stanford-CIDE COronavirus Simulation MOdel" . Retrieved 14 December 2023.
  44. ↑ "SDL PAND - Mapa global". pand.sdlps.com. Retrieved 2023-05-20.
  45. ↑ Khailaie S, Mitra T, Bandyopadhyay A, Schips M, Mascheroni P, Vanella P, Lange B, Binder SC, Meyer-Hermann M (2021). "Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures". BMC Medicine. 19 (1): 32. doi: 10.1186/s12916-020-01884-4 . ISSN   1741-7015. medRxiv   10.1101/2020.04.04.20053637 . PMC   7840427 . PMID   33504336.
  46. ↑ "simm / covid19 / SECIR". GitLab. Retrieved 2021-07-05.
  47. ↑ "Report · Wiki · simm / covid19 / SECIR". GitLab. Retrieved 2021-07-05.
  48. ↑ "Our research". Helmholtz Centre for Infection Research. Retrieved 2021-07-05.
  49. ↑ Syga S, David-Rus D, Schälte Y, Hatzikirou H, Deutsch A (November 2021). "Inferring the effect of interventions on COVID-19 transmission networks". Scientific Reports. 11 (1): 21913. arXiv: 2012.03846 . Bibcode:2021NatSR..1121913S. doi:10.1038/s41598-021-01407-y. PMC   8578219 . PMID   34754025.
  50. ↑ "Epidemiology Collection". epubs.siam.org.
  51. ↑ Kastalskiy IA, Pankratova EV, Mirkes EM, Kazantsev VB, Gorban AN (November 2021). "Social stress drives the multi-wave dynamics of COVID-19 outbreaks". Scientific Reports. 11 (1): 22497. arXiv: 2106.08966 . Bibcode:2021NatSR..1122497K. doi: 10.1038/s41598-021-01317-z . PMC   8602246 . PMID   34795311.
  52. ↑ "COVID-19 Simulation Tool". corona-lab.ch. Retrieved 28 April 2021.
  53. ↑ Gorji H, Arnoldini M, Jenny DF, Hardt WD, Jenny P (2021-05-04). "Dynamic modelling to identify mitigation strategies for the COVID-19 pandemic". Swiss Medical Weekly . 151 (1718): w20487. doi:10.4414/smw.2021.20487. hdl: 20.500.11850/484250 . ISSN   1424-3997. medRxiv   10.1101/2020.11.30.20239566 . PMID   33945149.
  54. ↑ "CDC list of Forecast Inclusion and Assumptions". www.cdc.gov/coronavirus.
  55. ↑ "CORESMA". CORESMA. Retrieved 2021-07-05.
  56. ↑ "Home - COVID 19 forecast hub". covid19forecasthub.org. Retrieved 14 December 2023.
  57. ↑ Best R, Boice J (2020-05-01). "Where The Latest COVID-19 Models Think We're Headed — And Why They Disagree". FiveThirtyEight. Retrieved 2021-02-21.
  58. ↑ "Home - COVID 19 forecast hub". covid19forecasthub.org. Retrieved 2021-02-21.
  59. ↑ "Nextstrain". nextstrain.org. Retrieved 2021-04-26.
  60. ↑ "Nextstrain". nextstrain.org. Retrieved 14 December 2023.
  61. ↑ "SIMID – Simulation Models of Infectious Diseases" . Retrieved 14 December 2023.
  62. ↑ "Rapid Assistance in Modelling the Pandemic: RAMP | Royal Society". royalsociety.org. Retrieved 2021-03-09.
  63. ↑ "UT COVID-19 Modeling Consortium". covid-19.tacc.utexas.edu. Retrieved 14 December 2023.
  64. ↑ CDC (2020-02-11). "Coronavirus Disease 2019 (COVID-19) - COVID-19 Forecasting: Background Information". Centers for Disease Control and Prevention. Retrieved 2021-10-03.
  65. ↑ "About the Hub - COVID 19 forecast hub". covid19forecasthub.org. Retrieved 2021-10-03.
  66. ↑ "COVID-19 Map". Johns Hopkins Coronavirus Resource Center. Retrieved 14 December 2023.
  67. ↑ "COVID-19 Map". Johns Hopkins Coronavirus Resource Center. Retrieved 2021-04-26.
  68. ↑ Dong E, Du H, Gardner L (May 2020). "An interactive web-based dashboard to track COVID-19 in real time". The Lancet. Infectious Diseases. 20 (5): 533–534. doi:10.1016/S1473-3099(20)30120-1. PMC   7159018 . PMID   32087114.
  69. ↑ "COVIDVaxView | CDC". www.cdc.gov. 2021-09-23. Retrieved 2021-10-03.
  70. ↑ Datopian, Open Knowledge International. "Novel Coronavirus 2019". DataHub.io. Retrieved 2021-05-02.
  71. ↑ datasets/covid-19, Data Packaged Core Datasets at GitHub, 2021-05-02, retrieved 2021-05-02
  72. ↑ Bundesministerium für Gesundheit. "Das offizielle Dashboard zur Impfkampagne der Bundesrepublik Deutschland". impfdashboard.de (in German). Retrieved 2021-06-07.
  73. ↑ "Simulation der COVID19-Impfkampagne". www.zidatasciencelab.de. Retrieved 14 December 2023.
  74. ↑ "IHME | COVID-19 Projections". Institute for Health Metrics and Evaluation. Retrieved 14 December 2023.
  75. ↑ "Cellular Defense Automata model". thememeticist.github.io.
  76. ↑ "CoVariants (CoVariants] - Overview of SARS-CoV-2 variants and mutations that are of interest)". covariants.org. Retrieved 14 December 2023.
  77. ↑ "Covid-19 Simulator". www.coronasimulator.com. Retrieved 28 April 2021.
  78. ↑ Prabowo A (3 May 2020). "COVID19: Top 7 online interactive simulations, curated". Medium. Retrieved 2021-02-21.
  79. ↑ "Build software better, together (topics/covid-19)". GitHub. Retrieved 14 December 2023.
  80. ↑ "COVID-19 Simulator". exchange.iseesystems.com. Retrieved 14 December 2023.
  81. ↑ "Coronavirus Dashboard". ncov2019.live. Retrieved 14 December 2023.
  82. ↑ "cov19.cc" . Retrieved 18 August 2023.
  83. ↑ "COVID-19 Simulation Resources" . Retrieved 2020-02-21.
  84. ↑ "Simulating coronavirus with the SIR model". fatiherikli.github.io. Archived from the original on 2021-04-19. Retrieved 2021-02-21.
  85. ↑ "Covid-19 Spread Simulation". c19model.com. Retrieved 14 December 2023.
  86. ↑ "CAS COVID-19 Resources". CAS. Retrieved 2021-06-02.
  87. ↑ "COVID Data Tracker". Centers for Disease Control and Prevention. 28 March 2020. Retrieved 14 December 2023.
  88. ↑ "Full, live, global, COVID-19 Status Report for 251 locales & 71 Ships". civilsocietysolidarityagainstcovid19.com. Retrieved 2021-07-01.
  89. ↑ Bohan J. "LibGuides: Cornell Institute for Social & Economic Research (CISER): COVID-19 Data Sources". guides.library.cornell.edu. Retrieved 14 December 2023.
  90. ↑ Dbouk T, Drikakis D (January 2021). "On airborne virus transmission in elevators and confined spaces". Physics of Fluids. 33 (1): 011905. Bibcode:2021PhFl...33a1905D. doi:10.1063/5.0038180. PMC   7984422 . PMID   33790526.
  91. ↑ Larsen JR, Martin MR, Martin JD, Kuhn P, Hicks JB (2020). "Modeling the Onset of Symptoms of COVID-19". Frontiers in Public Health. 8: 473. doi: 10.3389/fpubh.2020.00473 . PMC   7438535 . PMID   32903584.
  92. ↑ Mathieu E, Ritchie H, Rodés-Guirao L, Appel C, Giattino C, Hasell J, Macdonald B, Dattani S, Beltekian D, Ortiz-Ospina E, Roser M (5 March 2020). "Coronavirus Pandemic (COVID-19)". Our World in Data. Retrieved 14 December 2023.
  93. ↑ "The COVID Tracking Project". The COVID Tracking Project. Retrieved 14 December 2023.
  94. ↑ "Vadere – Open Source Framework for Pedestrian and Crowd Simulation". www.vadere.org. Retrieved 14 December 2023.
  95. ↑ "WHO Coronavirus (COVID-19) Dashboard". covid19.who.int. Retrieved 2021-07-01.

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