CRAMER, EY, EL RAY, VK LOPEZ, J. BRACHER, A. BRENNEN, AJC RIVADENEIRA, A. GERDING, T. GNEITING, KH HOUSE, YX HUANG, D. JAYAWARDENA, AH KANJI, A. KHANDELWAL, K. LE, A. MUHLEMANN, J. NIEMI, A. SHAH, A. STARK, YJ WANG, N. WATTANACHIT, MW ZORN, Gu YY, S. JAIN, N. BANNUR, A. DEVA, M. KULKARNI, S. MERUGU, A. RAVAL, S. SHINGI, A. TIWARI, J. WHITE, NF ABERNETHY, S. WOODY, M. DAHAN, S. FOX, K. GAITHER, M. LACHMANN, LA MEYERS, JG SCOTT, M. TEC, A. SRIVASTAVA, GE GEORGE, JC CEGAN, ID DETTWILLER, WP ENGLAND, MW FARTHING, RH HUNTER, B. LAFFERTY, I. LINKOV, ML MAYO, MD PARNO, MA ROWLAND, BD TRUMP, Y. ZHANG-JAMES, S. CHEN, SV FARAONE, J. HESS, CP MORLEY, A. SALEKIN, DL WANG, SM CORSETTI, TM BAER, MC EISENBERG, K. FALB, YT HUANG, Martin ET, E. MCCAULEY, RL MYERS, T. SCHWARZ, D. SHELDON, GC GIBSON, R. YU, LY GAO, Y. MA, DX WU, XF YAN, XY JIN, YX WANG, YQ CHEN, LH GUO, YT ZHAO, QQ GU, JH CHEN, LX WANG, P. XU, WT ZHANG, DF ZOU, H. BIEGEL, J. LEGA, S. MCCONNELL, VP NAGRAJ, SL GUERTIN, C. HULME-LOWE, SD TURNER, YF SHI, XG BAN, R. WALRAVEN, QJ HONG, S. KONG, A. VAN DE WALLE, JA TURTLE, M. BEN-NUN, S. RILEY, P. RILEY, U. KOYLUOGLU, D. DESROCHES, P. FORLI, B. HAMORY, C. KYRIAKIDES, H. LEIS, J. MILLIKEN, M. MOLONEY, J. MORGAN, N. NIRGUDKAR, G. OZCAN, N. PIWONKA, M. RAVI, C. SCHRADER, E. SHAKHNOVICH, D. SIEGEL, R. SPATZ, C. STIEFELING, B. WILKINSON, A. WONG, S. CAVANY, G. ESPANA, S. MOORE, R. OIDTMAN, A. PERKINS, David KRAUS, Andrea KRAUS, ZF GAO, J. BIAN, W. CAO, JL FERRES, CZ LI, TY LIU, X. XIE, S. ZHANG, S. ZHENG, A. VESPIGNANI, M. CHINAZZI, JT DAVIS, K. MU, APY PIONTTI, XY XIONG, A. ZHENG, J. BAEK, V. FARIAS, A. GEORGESCU, R. LEVI, D. SINHA, J. WILDE, G. PERAKIS, MA BENNOUNA, D. NZE-NDONG, D. SINGHVI, I. SPANTIDAKIS, L. THAYAPARAN, A. TSIOURVAS, A. SARKER, A. JADBABAIE, D. SHAH, N. DELLA PENNA, LA CELI, S. SUNDAR, R. WOLFINGER, D. OSTHUS, L. CASTRO, G. FAIRCHILD, I. MICHAUD, D. KARLEN, M. KINSEY, LC MULLANY, K. RAINWATER-LOVETT, L. SHIN, K. TALLAKSEN, S. WILSON, EC LEE, J. DENT, KH GRANTZ, AL HILL, J. KAMINSKY, K. KAMINSKY, LT KEEGAN, SA LAUER, JC LEMAITRE, J. LESSLER, HR MEREDITH, J. PEREZ-SAEZ, S. SHAH, CP SMITH, SA TRUELOVE, J. WILLS, M. MARSHALL, L. GARDNER, K. NIXON, JC BURANT, L. WANG, L. GAO, Gu ZL, M. KIM, XY LI, GN WANG, YY WANG, S. YU, RC REINER, R. BARBER, E. GAKIDOU, Hay SI, S. LIM, C. MURRAY, D. PIGOTT, HL GURUNG, P. BACCAM, SA STAGE, BT SUCHOSKI, BA PRAKASH, B. ADHIKARI, JM CUI, A. RODRIGUEZ, A. TABASSUM, JJ XIE, P. KESKINOCAK, J. ASPLUND, A. BAXTER, BE ORUC, N. SERBAN, SO ARIK, M. DUSENBERRY, A. EPSHTEYN, E. KANAL, Le LT, CL LI, T. PFISTER, D. SAVA, R. SINHA, T. TSAI, N. YODER, J. YOON, LY ZHANG, S. ABBOTT, NI BOSSE, S. FUNK, J. HELLEWELL, SR MEAKIN, K. SHERRATT, MY ZHOU, R. KALANTARI, TK YAMANA, S. PEI, J. SHAMAN, ML LI, D. BERTSIMAS, OS LAMI, S. SONI, HT BOUARDI, T. AYER, M. ADEE, J. CHHATWAL, OO DALGIC, MA LADD, BP LINAS, P. MUELLER, J. XIAO, YJ WANG, QX WANG, SH XIE, DL ZENG, A. GREEN, J. BIEN, L. BROOKS, AJ HU, M. JAHJA, D. MCDONALD, B. NARASIMHAN, C. POLITSCH, S. RAJANALA, A. RUMACK, N. SIMON, RJ TIBSHIRANI, R. TIBSHIRANI, V. VENTURA, L. WASSERMAN, EB O'DEA, JM DRAKE, R. PAGANO, QT TRAN, LST HO, H. HUYNH, JW WALKER, RB SLAYTON, MA JOHANSSON, M. BIGGERSTAFF and NG REICH. Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States. Proceedings of the National Academy of Sciences of the United States of America. WASHINGTON: National Academy of Sciences, 2022, vol. 119, No 15, p. "e2113561119", 12 pp. ISSN 0027-8424. Available from: https://dx.doi.org/10.1073/pnas.2113561119.
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Basic information
Original name Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
Authors CRAMER, EY, EL RAY, VK LOPEZ, J. BRACHER, A. BRENNEN, AJC RIVADENEIRA, A. GERDING, T. GNEITING, KH HOUSE, YX HUANG, D. JAYAWARDENA, AH KANJI, A. KHANDELWAL, K. LE, A. MUHLEMANN, J. NIEMI, A. SHAH, A. STARK, YJ WANG, N. WATTANACHIT, MW ZORN, Gu YY, S. JAIN, N. BANNUR, A. DEVA, M. KULKARNI, S. MERUGU, A. RAVAL, S. SHINGI, A. TIWARI, J. WHITE, NF ABERNETHY, S. WOODY, M. DAHAN, S. FOX, K. GAITHER, M. LACHMANN, LA MEYERS, JG SCOTT, M. TEC, A. SRIVASTAVA, GE GEORGE, JC CEGAN, ID DETTWILLER, WP ENGLAND, MW FARTHING, RH HUNTER, B. LAFFERTY, I. LINKOV, ML MAYO, MD PARNO, MA ROWLAND, BD TRUMP, Y. ZHANG-JAMES, S. CHEN, SV FARAONE, J. HESS, CP MORLEY, A. SALEKIN, DL WANG, SM CORSETTI, TM BAER, MC EISENBERG, K. FALB, YT HUANG, Martin ET, E. MCCAULEY, RL MYERS, T. SCHWARZ, D. SHELDON, GC GIBSON, R. YU, LY GAO, Y. MA, DX WU, XF YAN, XY JIN, YX WANG, YQ CHEN, LH GUO, YT ZHAO, QQ GU, JH CHEN, LX WANG, P. XU, WT ZHANG, DF ZOU, H. BIEGEL, J. LEGA, S. MCCONNELL, VP NAGRAJ, SL GUERTIN, C. HULME-LOWE, SD TURNER, YF SHI, XG BAN, R. WALRAVEN, QJ HONG, S. KONG, A. VAN DE WALLE, JA TURTLE, M. BEN-NUN, S. RILEY, P. RILEY, U. KOYLUOGLU, D. DESROCHES, P. FORLI, B. HAMORY, C. KYRIAKIDES, H. LEIS, J. MILLIKEN, M. MOLONEY, J. MORGAN, N. NIRGUDKAR, G. OZCAN, N. PIWONKA, M. RAVI, C. SCHRADER, E. SHAKHNOVICH, D. SIEGEL, R. SPATZ, C. STIEFELING, B. WILKINSON, A. WONG, S. CAVANY, G. ESPANA, S. MOORE, R. OIDTMAN, A. PERKINS, David KRAUS (203 Czech Republic, guarantor, belonging to the institution), Andrea KRAUS (703 Slovakia, belonging to the institution), ZF GAO, J. BIAN, W. CAO, JL FERRES, CZ LI, TY LIU, X. XIE, S. ZHANG, S. ZHENG, A. VESPIGNANI, M. CHINAZZI, JT DAVIS, K. MU, APY PIONTTI, XY XIONG, A. ZHENG, J. BAEK, V. FARIAS, A. GEORGESCU, R. LEVI, D. SINHA, J. WILDE, G. PERAKIS, MA BENNOUNA, D. NZE-NDONG, D. SINGHVI, I. SPANTIDAKIS, L. THAYAPARAN, A. TSIOURVAS, A. SARKER, A. JADBABAIE, D. SHAH, N. DELLA PENNA, LA CELI, S. SUNDAR, R. WOLFINGER, D. OSTHUS, L. CASTRO, G. FAIRCHILD, I. MICHAUD, D. KARLEN, M. KINSEY, LC MULLANY, K. RAINWATER-LOVETT, L. SHIN, K. TALLAKSEN, S. WILSON, EC LEE, J. DENT, KH GRANTZ, AL HILL, J. KAMINSKY, K. KAMINSKY, LT KEEGAN, SA LAUER, JC LEMAITRE, J. LESSLER, HR MEREDITH, J. PEREZ-SAEZ, S. SHAH, CP SMITH, SA TRUELOVE, J. WILLS, M. MARSHALL, L. GARDNER, K. NIXON, JC BURANT, L. WANG, L. GAO, Gu ZL, M. KIM, XY LI, GN WANG, YY WANG, S. YU, RC REINER, R. BARBER, E. GAKIDOU, Hay SI, S. LIM, C. MURRAY, D. PIGOTT, HL GURUNG, P. BACCAM, SA STAGE, BT SUCHOSKI, BA PRAKASH, B. ADHIKARI, JM CUI, A. RODRIGUEZ, A. TABASSUM, JJ XIE, P. KESKINOCAK, J. ASPLUND, A. BAXTER, BE ORUC, N. SERBAN, SO ARIK, M. DUSENBERRY, A. EPSHTEYN, E. KANAL, Le LT, CL LI, T. PFISTER, D. SAVA, R. SINHA, T. TSAI, N. YODER, J. YOON, LY ZHANG, S. ABBOTT, NI BOSSE, S. FUNK, J. HELLEWELL, SR MEAKIN, K. SHERRATT, MY ZHOU, R. KALANTARI, TK YAMANA, S. PEI, J. SHAMAN, ML LI, D. BERTSIMAS, OS LAMI, S. SONI, HT BOUARDI, T. AYER, M. ADEE, J. CHHATWAL, OO DALGIC, MA LADD, BP LINAS, P. MUELLER, J. XIAO, YJ WANG, QX WANG, SH XIE, DL ZENG, A. GREEN, J. BIEN, L. BROOKS, AJ HU, M. JAHJA, D. MCDONALD, B. NARASIMHAN, C. POLITSCH, S. RAJANALA, A. RUMACK, N. SIMON, RJ TIBSHIRANI, R. TIBSHIRANI, V. VENTURA, L. WASSERMAN, EB O'DEA, JM DRAKE, R. PAGANO, QT TRAN, LST HO, H. HUYNH, JW WALKER, RB SLAYTON, MA JOHANSSON, M. BIGGERSTAFF and NG REICH.
Edition Proceedings of the National Academy of Sciences of the United States of America, WASHINGTON, National Academy of Sciences, 2022, 0027-8424.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10103 Statistics and probability
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 11.100
RIV identification code RIV/00216224:14310/22:00126280
Organization unit Faculty of Science
Doi http://dx.doi.org/10.1073/pnas.2113561119
UT WoS 000819659900005
Keywords in English forecasting; COVID-19; ensemble forecast; model evaluation
Tags rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Marie Šípková, DiS., učo 437722. Changed: 1/12/2022 17:07.
Abstract
Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https:// covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naive baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.
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