COVID-19 Modeling and Forecasting

In response to the ongoing COVID-19 outbreak, we extended the Global Epidemic and Mobility model (GLEAM) to incorporate the effects of travel restrictions, non-pharmaceutical interventions, age-structured contact patterns, and vaccination campaigns to study, project, and forecast the evolution of the COVID-19 pandemic.

In early 2020, we studied the effect of travel restrictions on the spread of SARS-CoV-2 and we provided some of the early estimates on the basic reproduction number for SARS-CoV-2 and of the estimated risk of sustained community transmission outside Mainland China. Later on, we focused on producing projection scenarios and forecasts on the evolution of the COVID-19 pandemic and the diffusion of different SARS-CoV-2 variants in different countries, while also showing the effects of non-pharmaceutical interventions (business/school closures, testing strategies, mask mandates, etc..), alternative vaccine campaign strategies, and eviction moratoria on future COVID-19 cases, hospitalizations, and deaths.


Online dashboards:


Papers and Research Reports:

  • Klein, B., Generous, N., Chinazzi, M., Bhadricha, Z., Gunashekar, R., Kori, P., Li, B., McCabe, S., Green, J., Lazer, D., Marsicano, C., Scarpino, S.V., & Vespignani, A. (2021). Higher education responses to COVID-19 in the United States: Evidence for the impacts of university policy. medRxiv: 2021.10.07.21264419.
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  • Wu, D., Gao, L., Xiong, X., Chinazzi, M., Vespignani, A., Ma, Y.A., & Yu, R. Quantifying Uncertainty in Deep Spatiotemporal Forecasting (2021). ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021.
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  • Adjodah, D., Dinakar, K., Chinazzi, M., Fraiberger, S.P., Pentland, A., Bates, S., Staller, K., Vespignani, A., & Bhatt, D.L. (2021). Association between COVID-19 outcomes and mask mandates, adherence, and attitudes. PLOS ONE, 16(6), e0252315.
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  • Lu, F. S., Nguyen, A. T., Link, N. B., Molina, M., Davis, J.T., Chinazzi, M., Xiong, X., Vespignani, A., Lipsitch, M., & Santillana, M. (2021). Estimating the cumulative incidence of COVID-19 in the United States using influenza surveillance, virologic testing, and mortality data: four complementary approaches. PLOS Computational Biology, 17(6), e1008994.
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  • Borchering, R. K., Viboud, C., Howerton, E., Smith, C. P., Truelove, S., Runge, M. C., Reich, N.G., Contamin, L., Levander, J., Salerno, J., van Panhuis, W., Kinsey, M., Tallaksen, K., Obrecht, R.F., Asher, L., Costello, C., Kelbaugh, M., Wilson, S., Shin, L., Gallagher, M.E., Mullany, L.C., Rainwater-Lovett, K., Lemaitre, J.C., Dent, J., Grantz, K.H., Kaminsky, J., Lauer, S.A., Lee, E.C., Meredith, H.R., Perez-Saez, J., Keegan, L.T., Karlen, D., Chinazzi, M., Davis, J.T., Mu, K., Xiong, X., Pastore y Piontti, A., Vespignani, V., Srivastava, A., Porebski, P., Venkatramanan, S., Adiga, A., Lewis, B., Klahn, B., Outten, J., Schlitt, J., Corbett, P., Telionis, P.A., Wang, L., Peddireddy, A.S., Hurt, B., Chen, J., Vullikanti, A., Marathe, M., Healy, J.M., Slayton, R.B., Biggerstaff, M., Johansson, M.A., Shea, K., & Lessler, J. (2021). Modeling of future COVID-19 cases, hospitalizations, and deaths, by vaccination rates and nonpharmaceutical intervention scenarios—United States, April–September 2021. Morbidity and Mortality Weekly Report, 70(19), 719.
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  • Gozzi, N., Tizzoni, M., Chinazzi, M., Ferres, L., Vespignani, A., & Perra, N. (2021). Estimating the effect of social inequalities on the mitigation of COVID-19 across communities in Santiago de Chile. Nature communications, 12(1), 1-9.
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  • Nande, A., Sheen, J., Walters, E.L., Klein, B., Chinazzi, M., Gheorghe, A., Adlam, B., Shinnick, J., Tejeda, M.F., Scarpino, S.V., Vespignani, A., Greenlee, A.J., Schneider, D., Levy, M. Z., & Hill, A.L. (2021). The effect of eviction moratoria on the transmission of SARS-CoV-2. Nature Communications, 12, 2274.
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  • Kogan, N.E., Clemente, L., Liautaud, P., Kaashoek, J., Link, N.B., Nguyen, A.T., Lu, F.S., Huybers P., Resch B., Havas C., Petutschnig A., Davis J.T., Chinazzi, M., Mustafa, B., Hanage, W.P., Vespignani, A., & Santillana, M. (2021). An early warning approach to monitor COVID-19 activity with multiple digital traces in near real-time. Science Advances, 7(10), eabd6989.
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  • Du, Z., Pandey, A., Bai, Y., C Fitzpatrick, M., Chinazzi, M., Pastore y Piontti, A., Lachmann, M., Vespignani, A., Cowling, B.J., Galvani, A.P., & Meyers, L.A. (2021) Comparative cost-effectiveness of SARS-CoV-2 testing strategies in the USA: a modelling study. The Lancet Public Health, 6(3), e184-e191.
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  • Mistry, D., Litvinova, M., Patore y Piontti, A., Chinazzi, M., Fumanelli, L., Gomes, M.F., Haque, S.A., Liu, Q-H., Mu, K., Xiong, X., Halloran, M.E., Longini, I.M., Merler, S., Ajelli, M., & Vespignani, A. (2021). Inferring high-resolution human mixing patterns for disease modeling. Nature Communications, 12, 323.
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  • Poirier, C., Liu, D., Clemente, L., Ding, X., Chinazzi, M., Davis, J.T., Vespignani, A., & Santillana, M. (2020). Real-time forecasting of the COVID-19 outbreak in Chinese provinces: machine learning approach using novel digital data and estimates from mechanistic models. Journal of Medical Internet Research, 22(8), e20285.
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  • Aleta, A., Martin-Corral, D., Pastore y Piontti, A., Ajelli, M., Litvinova, M., Chinazzi, M., Dean, N.E., Halloran, M.E., Longini, I.M., Merler, S., Pentland, A., Vespignani, A., Moro, E., & Moreno, Y. (2020). Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19. Nature Human Behaviour, 4(9), 964-971.
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  • Chinazzi, M., Davis, J.T., Ajelli, M., Gioannini, C., Litvinova, M., Merler, S., Pastore y Piontti, A., Mu, K., Rossi, L., Sun, K., Viboud, C., Xiong, X., Yu, H., Halloran, M.E., Longini, I.M., & Vespignani, A. (2020). The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak. Science, 368(6489), 395-400.
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  • Chinazzi, M., Pastore y Piontti, A., Davis, J.T., Mu, K., Gozzi, N., Perra, N., Ajelli, M., & Vespignani, A. (2021). The path to dominance: geographical heterogeneity in the establishment of the alpha variant in the US. Working paper.
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  • Wu, D., Chinazzi, M., Vespignani, A., Ma, Y. A., & Yu, R. (2021). Accelerating Stochastic Simulation with Interactive Neural Processes. arXiv preprint arXiv:2106.02770.
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  • Davis, J. T., Chinazzi, M., Perra, N., Mu, K., y Piontti, A. P., Ajelli, M., Dean, N.E., Gioannini, C., Litvinova, M., Merler, S., Rossi, L., Sun, K., Xiong, X., Halloran, M.E., Longini, I.M., Viboud, C., & Vespignani, A. (2021). Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave in Europe and the United States. medRxiv 2021.03.24.21254199.
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  • Gozzi, N., Chinazzi, M., Davis, J. T., Mu, K., Pastore y Piontti, A., Ajelli, M., Perra, N., & Vespignani, A. (2021). Estimating the spreading and dominance of SARS-CoV-2 VOC 202012/01 (lineage B.1.1.7) across Europe. medRxiv 2021.02.22.21252235.
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  • Wu, D., Gao, L., Xiong, X., Chinazzi, M., Vespignani, A., Ma, Y., & Yu, R. (2021). DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting. arXiv preprint arXiv:2102.06684.
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  • Cramer, E., Ray, E., Lopez, V., Bracher, J., Brennen, A., Rivadeneira, A., Gerding, A., Gneiting, T., House, K., Huang, Y., Jayawardena, D., Kanji, A., Khandelwal, A., Le, K., Mühlemann, A., Niemi, J., Shah, A., Stark, A., Wang, Y., Wattanachit, N., Zorn, M., Gu, Y., Jain, S., Bannur, N., Deva, A., Kulkarni, M., Merugu, S., Raval, A., Shingi, S., Tiwari, A., White, J., Woody, S., Dahan, M., Fox, S., Gaither, K., Lachmann, M., Meyers, L., Scott, J., Tec, M., Srivastava, A., George, G., Cegan, J., Dettwiller, I., England, W., Farthing, M., Hunter, R., Lafferty, B., Linkov, I., Mayo, M., Parno, M., Rowland, M., Trump, B., Corsetti, S., Baer, T., Eisenberg, M., Falb, K., Huang, Y., Martin, E., McCauley, E., Myers, R., Schwarz, T., Sheldon, D., Gibson, G., Yu, R., Gao, L., Ma, Y., Wu, D., Yan, X., Jin, X., Wang, Y.X., Chen, Y., Guo, L., Zhao, Y., Gu, Q., Chen, J., Wang, L., Xu, P., Zhang, W., Zou, D., Biegel, H., Lega, J., Snyder, T., Wilson, D., McConnell, S., Walraven, R., Shi, Y., Ban, X., Hong, Q.J., Kong, S., Turtle, J., Ben-Nun, M., Riley, P., Riley, S., Koyluoglu, U., DesRoches, D., Hamory, B., Kyriakides, C., Leis, H., Milliken, J., Moloney, M., Morgan, J., Ozcan, G., Schrader, C., Shakhnovich, E., Siegel, D., Spatz, R., Stiefeling, C., Wilkinson, B., Wong, A., Gao, Z., Bian, J., Cao, W., Ferres, J., Li, C., Liu, T.Y., Xie, X., Zhang, S., Zheng, S., Vespignani, A., Chinazzi, M., Davis, J.T., Mu, K., Pastore y Piontti, A., Xiong, X., Zheng, A., Baek, J., Farias, V., Georgescu, A., Levi, R., Sinha, D., Wilde, J., Penna, N., Celi, L., Sundar, S., Cavany, S., Espana, G., Moore, S., Oidtman, R., Perkins, A., Osthus, D., Castro, L., Fairchild, G., Michaud, I., Karlen, D., Lee, E., Dent, J., Grantz, K., Kaminsky, J., Kaminsky, K., Keegan, L., Lauer, S., Lemaitre, J., Lessler, J., Meredith, H., Perez-Saez, J., Shah, S., Smith, C., Truelove, S., Wills, J., Kinsey, M., Obrecht, R., Tallaksen, K., Burant, J., Wang, L., Gao, L., Gu, Z., Kim, M., Li, X., Wang, G., Wang, Y., Yu, S., Reiner, R., Barber, R., Gaikedu, E., Hay, S., Lim, S., Murray, C., Pigott, D., Prakash, B., Adhikari, B., Cui, J., Rodriguez, A., Tabassum, A., Xie, J., Keskinocak, P., Asplund, J., Baxter, A., Oruc, B., Serban, N., Arik, S., Dusenberry, M., Epshteyn, A., Kanal, E., Le, L., Li, C.L., Pfister, T., Sava, D., Sinha, R., Tsai, T., Yoder, N., Yoon, J., Zhang, L., Abbott, S., Bosse, N., Funk, S., Hellewel, J., Meakin, S., Munday, J., Sherratt, K., Zhou, M., Kalantari, R., Yamana, T., Pei, S., Shaman, J., Ayer, T., Adee, M., Chhatwal, J., Dalgic, O., Ladd, M., Linas, B., Mueller, P., Xiao, J., Li, M., Bertsimas, D., Lami, O., Soni, S., Bouardi, H., Wang, Y., Wang, Q., Xie, S., Zeng, D., Green, A., Bien, J., Hu, A., Jahja, M., Narasimhan, B., Rajanala, S., Rumack, A., Simon, N., Tibshirani, R., Tibshirani, R., Ventura, V., Wasserman, L., O’Dea, E., Drake, J., Pagano, R., Walker, J., Slayton, R., Johansson, M., Biggerstaff, M., & Reich, N. (2021). Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US. medRxiv 2021.02.03.21250974v2.
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  • Aleta, A., Martín-Corral, D., Bakker, M. A., Pastore y Piontti, A., Ajelli, M., Litvinova, M., Chinazzi, M., Dean, N.E., Halloran, M.E., Longini, I.M., Pentland, A., Vespignani, A., Moreno, Y., & Moro, E. (2020). Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas. medRxiv 2020.12.15.20248273.
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  • Davis, J.T., Chinazzi, M., Perra, N., Mu, K., Pastore y Piontti, A., Ajelli, M., Dean, N.E., Gioannini, C., Litvinova, M., Merler, S., Rossi, L., Sun, K., Xiong, X., Halloran, M.E., Longini, I.M., Viboud, C., & Vespignani, A. (2020). Estimating the establishment of local transmission and the cryptic phase of the COVID-19 pandemic in the USA. medRxiv 2020.07.06.20140285.
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  • Shah, C., Dehmamy, N., Perra, N., Chinazzi, M., Barabási, A. L., Vespignani, A., & Yu, R. (2020). Finding Patient Zero: Learning Contagion Source with Graph Neural Networks. arXiv preprint arXiv:2006.11913.
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  • Chinazzi, M., Davis, J. T., Mu, K., Pastore y Piontti, A., Perra, N., Scarpino, S.V., & Vespignani, A. (2020). Preliminary estimates of the international spreading risk associated with the SARS-CoV-2 VUI 202012/01. Northeastern University, Laboratory for the Modeling of Biological and Socio-technical Systems research report, December 26th, 2020. Available online at https://www.mobs-lab.org/2019ncov.html.

  • Klein, B., LaRock, T., McCabe, S., Torres, L., Friedland, L., Privitera, F., Lake, B., Kraemer, M.U.G., Brownstein, J.S., Lazer, D., Eliassi-Rad, T., Scarpino, S.V., Vespignani, A., & Chinazzi, M. (2020). Reshaping a nation: Mobility, commuting, and contact patterns during the COVID-19 outbreak. Northeastern University, Network Science Institute research report, May 11th, 2020. Available online at https://www.mobs-lab.org/2019ncov.html.

  • Klein, B., LaRock, T., McCabe, S., Torres, L., Privitera, F., Lake, B., Kraemer, M.U.G., Brownstein, J.S., Lazer, D., Eliassi-Rad, T., Scarpino, S.V., Chinazzi, M. & Vespignani, A. (2020). Assessing changes in commuting and individual mobility in major metropolitan areas in the United States during the COVID-19 outbreak. Northeastern University, Network Science Institute research report, March 31st, 2020. Available online at https://www.mobs-lab.org/2019ncov.html.

  • Ray, E. L., Wattanachit, N., Niemi, J., Kanji, A. H., House, K., Cramer, E. Y., Bracher, J., Zheng, A., Yamana, T.K., Xiong, X., Woody, S., Wang, Y., Wang, L., Walraven, R.L., Tomar, V., Sherratt, K., Sheldon, D., Reiner, R.C., Prakash, B.A., Osthus, D., Li, M.L., Lee, E.C., Koyluoglu, U., Keskinocak, P., Gu, Y., Gu, Q., George, G.E., España, G., Corsetti, S., Chhatwal, J., Cavany, S., Biegel, H., Ben-Nun, M., Walker, J., Slayton, R., Lopez, V., Biggerstaff, M., Johansson, M.A., Reich, N.G., & COVID-19 Forecast Hub Consortium. (2020). Ensemble Forecasts of Coronavirus Disease 2019 (COVID-19) in the us. medRxiv 2020.08.19.20177493.
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  • MOBS Laboratory. Estimating the onset of local transmission of the COVID-19 epidemic in African countries (Report V1.0). Northeastern University, Laboratory for the Modeling of Biological and Socio-technical Systems research report, March 17th, 2020. Available online at https://www.mobs-lab.org/2019ncov.html.

  • Chinazzi, M., Davis, J.T., Mu, K., Pastore y Piontti, A., Ajelli, M., Dean, N.E., Gioannini, C., Litvinova, M., Merler, S., Rossi, L., Sun, K., Viboud, C., Halloran, M.E., Longini, I.M., & Vespignani, A. (2020). Estimating the risk of sustained community transmission of COVID-19 outside Mainland China. Northeastern University, Laboratory for the Modeling of Biological and Socio-technical Systems research report, March 11th, 2020. Available online at https://www.mobs-lab.org/2019ncov.html.

  • Chinazzi, M., Davis, J. T., Gioannini, C., Litvinova, M., Pastore y Piontti, A., Rossi, L., Xiong, X., Halloran, M.E., Longini, I.M., & Vespignani, A. (2020). Preliminary assessment of the International Spreading Risk Associated with the 2019 novel Coronavirus (2019-nCoV) outbreak in Wuhan City. Northeastern University, Laboratory for the Modeling of Biological and Socio-technical Systems research report. 8 reports between January 17th and January 29th, 2020. Available online at https://www.mobs-lab.org/2019ncov.html.