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 a 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, roč. 119, č. 15, s. "e2113561119", 12 s. ISSN 0027-8424. Dostupné z: https://dx.doi.org/10.1073/pnas.2113561119.
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Základní údaje
Originální název Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
Autoři 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 Česká republika, garant, domácí), Andrea KRAUS (703 Slovensko, domácí), 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 a NG REICH.
Vydání Proceedings of the National Academy of Sciences of the United States of America, WASHINGTON, National Academy of Sciences, 2022, 0027-8424.
Další údaje
Originální jazyk angličtina
Typ výsledku Článek v odborném periodiku
Obor 10103 Statistics and probability
Stát vydavatele Spojené státy
Utajení není předmětem státního či obchodního tajemství
WWW URL
Impakt faktor Impact factor: 11.100
Kód RIV RIV/00216224:14310/22:00126280
Organizační jednotka Přírodovědecká fakulta
Doi http://dx.doi.org/10.1073/pnas.2113561119
UT WoS 000819659900005
Klíčová slova anglicky forecasting; COVID-19; ensemble forecast; model evaluation
Štítky rivok
Příznaky Mezinárodní význam, Recenzováno
Změnil Změnila: Mgr. Marie Šípková, DiS., učo 437722. Změněno: 1. 12. 2022 17:07.
Anotace
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.
VytisknoutZobrazeno: 3. 9. 2024 04:32