المؤلفون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L, Reich, Nicholas G, Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H, Barbarossa, Maria Vittoria, Leithäuser, Neele, Mohring, Jan, Schneider, Johanna, Włazło, Jaroslaw, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajíček, Milan, Pérez Álvarez, Cesar, Reina, Borja, Bosse, Nikos I, Meakin, Sophie R, Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerová, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsimas, Li, Michael Lingzhi, Saksham, Soni, Dehning, Jonas, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Hotz, Thomas, Singh, David E, Guzman-Merino, Miguel, Aznarte, Jose L, Moriña, David, Alonso, Sergio, Álvarez, Enric, López, Daniel, Prats, Clara, Burgard, Jan Pablo, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Català, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Bartolucci, Francesco, Jona Lasinio, Giovanna, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav, Porebski, Przemyslaw, Venkatramanan, Srinivasan, Bartczuk, Rafal P, Dreger, Filip, Gambin, Anna, Gogolewski, Krzysztof, Gruziel-Słomka, Magdalena, Krupa, Bartosz, Moszyński, Antoni, Niedzielewski, Karol, Nowosielski, Jedrzej, Radwan, Maciej, Rakowski, Franciszek, Semeniuk, Marcin, Szczurek, Ewa, Zieliński, Jakub, Kisielewski, Jan, Pabjan, Barbara, Kirsten, Holger, Kheifetz, Yuri, Scholz, Markus, Biecek, Przemyslaw, Bodych, Marcin, Filinski, Maciej, Idzikowski, Radoslaw, Krueger, Tyll, Ozanski, Tomasz, Bracher, Johannes, Funk, Sebastian

المساهمون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L, Reich, Nicholas G, Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H, Barbarossa, Maria Vittoria, Leithäuser, Neele, Mohring, Jan, Schneider, Johanna, Włazło, Jaroslaw, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajíček, Milan, Pérez Álvarez, Cesar, Reina, Borja, Bosse, Nikos I, Meakin, Sophie R, Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerová, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsima, Li, Michael Lingzhi, Saksham, Soni, Dehning, Jona, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Hotz, Thoma, Singh, David E, Guzman-Merino, Miguel, Aznarte, Jose L, Moriña, David, Alonso, Sergio, Álvarez, Enric, López, Daniel, Prats, Clara, Burgard, Jan Pablo, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Català, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Bartolucci, Francesco, Jona Lasinio, Giovanna, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav

مصطلحات موضوعية: epidemiology, global health, none

الوصف: Background: Short-term forecasts of infectious disease contribute to situational awareness and capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise forecasts' predictive performance by combining independent models into an ensemble. Here we report the performance of ensemble predictions of COVID-19 cases and deaths across Europe from March 2021 to March 2022. Methods: We created the European COVID-19 Forecast Hub, an online open-access platform where modellers upload weekly forecasts for 32 countries with results publicly visualised and evaluated. We created a weekly ensemble forecast from the equally-weighted average across individual models' predictive quantiles. We measured forecast accuracy using a baseline and relative Weighted Interval Score (rWIS). We retrospectively explored ensemble methods, including weighting by past performance. Results: We collected weekly forecasts from 48 models, of which we evaluated 29 models alongside the ensemble model. The ensemble had a consistently strong performance across countries over time, performing better on rWIS than 91% of forecasts for deaths (N=763 predictions from 20 models), and 83% forecasts for cases (N=886 predictions from 23 models). Performance remained stable over a 4-week horizon for death forecasts but declined with longer horizons for cases. Among ensemble methods, the most influential choice came from using a median average instead of the mean, regardless of weighting component models. Conclusions: Our results support combining independent models into an ensemble forecast to improve epidemiological predictions, and suggest that median averages yield better performance than methods based on means. We highlight that forecast consumers should place more weight on incident death forecasts than case forecasts at horizons greater than two weeks. Funding: European Commission, Ministerio de Ciencia, Innovación y Universidades, FEDER; Agència de Qualitat i Avaluació Sanitàries ...

وصف الملف: ELETTRONICO

العلاقة: info:eu-repo/semantics/altIdentifier/pmid/37083521; info:eu-repo/semantics/altIdentifier/wos/WOS:001009734700001; volume:12; firstpage:1; lastpage:23; numberofpages:23; journal:ELIFE; https://hdl.handle.net/11311/1236163Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85158061738

الإتاحة: https://doi.org/10.7554/eLife.81916Test
https://hdl.handle.net/11311/1236163Test

المؤلفون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L., Reich, Nicholas G., Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H., Barbarossa, Maria Vittoria, Leithäuser, Neele, Mohring, Jan, Schneider, Johanna, Wlazło, Jarosław, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajíček, Milan, Pérez Álvarez, Cesar, Reina, Borja, Bosse, Nikos I., Meakin, Sophie R., Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerová, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsimas, Li, Michael Lingzhi, Saksham, Soni, Dehning, Jonas, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar Haro, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Hotz, Thomas, Singh, David E., Guzman-Merino, Miguel, Aznarte, Jose L., Moriña, David, Alonso, Sergio, Álvarez, Enric, López, Daniel, Prats, Clara, Burgard, Jan Pablo, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Català, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Bartolucci, Francesco, Jona Lasinio, Giovanna, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav, Porebski, Przemyslaw, Venkatramanan, Srinivasan, Bartczuk, Rafal P., Dreger, Filip, Gambin, Anna, Gogolewski, Krzysztof, Gruziel-Słomka, Magdalena, Krupa, Bartosz, Moszyński, Antoni, Niedzielewski, Karol, Nowosielski, Jedrzej, Radwan, Maciej, Rakowski, Franciszek, Semeniuk, Marcin, Szczurek, Ewa, Zieliński, Jakub, Kisielewski, Jan, Pabjan, Barbara, Kirsten, Holger, Kheifetz, Yuri, Scholz, Markus, Biecek, Przemysław, Bodych, Marcin, Filinski, Maciej, Idzikowski, Radoslaw, Krueger, Tyll, Ozanski, Tomasz, Bracher, Johannes, Funk, Sebastian

مصطلحات موضوعية: ddc:610

الوصف: Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for ...

وصف الملف: application/pdf

العلاقة: http://dx.doi.org/10.25673/103473Test; https://opendata.uni-halle.de//handle/1981185920/105425Test

الإتاحة: https://doi.org/10.25673/103473Test
https://opendata.uni-halle.de//handle/1981185920/105425Test

المؤلفون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L., Reich, Nicholas G., Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, E., Krymova, Ekaterina, Meinke, Jan H., Barbarossa, Maria Vittoria, Leithäuser, Neele, Mohring, Jan, Schneider, Johanna, Włazło, Jaroslaw, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajíček, Milan, Pérez Álvarez, Cesar, Reina, Borja, Bosse, Nikos I., Meakin, Sophie R., Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerová, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsimas, Li, Michael Lingzhi, Saksham, Soni, Dehning, Jonas, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Hotz, Thomas, Singh, David E., Guzman-Merino, Miguel, Aznarte, Jose L., Moriña, David, Alonso, Sergio, Álvarez, Enric, López, Daniel, Prats, Clara, Burgard, Jan Pablo, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Català, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Bartolucci, Francesco, Jona Lasinio, Giovanna, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav, Porebski, Przemyslaw, Venkatramanan, Srinivasan, Bartczuk, Rafal P., Dreger, Filip, Gambin, Anna, Gogolewski, Krzysztof, Gruziel-Słomka, Magdalena, Krupa, Bartosz, Moszyński, Antoni, Niedzielewski, Karol, Nowosielski, Jedrzej, Radwan, Maciej, Rakowski, Franciszek, Semeniuk, Marcin, Szczurek, Ewa, Zieliński, Jakub, Kisielewski, Jan, Pabjan, Barbara, Kirsten, Holger, Kheifetz, Yuri, Scholz, Markus, Biecek, Przemyslaw, Bodych, Marcin, Filinski, Maciej, Idzikowski, Radoslaw, Krueger, Tyll, Ozanski, T., Ozanski, Tomasz, Bracher, Johannes

المصدر: eLife, 12, Art.-Nr.: e81916 ; ISSN: 2050-084X

مصطلحات موضوعية: ddc:330, Economics, info:eu-repo/classification/ddc/330

الوصف: Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for ...

العلاقة: info:eu-repo/semantics/altIdentifier/wos/001009734700001; info:eu-repo/semantics/altIdentifier/issn/2050-084X; https://publikationen.bibliothek.kit.edu/1000159071Test

الإتاحة: https://doi.org/10.7554/eLife.81916Test
https://publikationen.bibliothek.kit.edu/1000159071Test

المؤلفون: Sherratt, Katharine, Gruson, Hugo, Ullrich, Alexander, Porebski, Przemyslaw, Venkatramanan, Srinivasan, Bartczuk, Rafal P, Dreger, Filip, Gambin, Anna, Gogolewski, Krzysztof, Gruziel-Slomka, Magdalena, Krupa, Bartosz, Moszyński, Antoni, Niedzielewski, Karol, Gibson, Graham, Nowosielski, Jedrzej, Radwan, Maciej, Rakowski, Franciszek, Semeniuk, Marcin, Szczurek, Ewa, Zielinski, Jakub, Kisielewski, Jan, Pabjan, Barbara, Holger, Kirsten, Kheifetz, Yuri, Ray, Evan L, Scholz, Markus, Przemyslaw, Biecek, Bodych, Marcin, Filinski, Maciej, Idzikowski, Radoslaw, Krueger, Tyll, Ozanski, Tomasz, Bracher, Johannes, Funk, Sebastian, Reich, Nicholas G, Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Grah, Rok, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H, Barbarossa, Maria Vittoria, Leithauser, Neele, Mohring, Jan, Schneider, Johanna, Wlazlo, Jaroslaw, Johnson, Helen, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Niehus, Rene, Tucek, Vit, Smid, Martin, Zajicek, Milan, Perez Alvarez, Cesar, Reina, Borja, Bosse, Nikos I, Meakin, Sophie R, Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Prasse, Bastian, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerova, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsimas, Li, Michael Lingzhi, Saksham, Soni, Sandmann, Frank, Dehning, Jonas, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Deuschel, Jannik, Hotz, Thomas, Singh, David E, Guzman-Merino, Miguel, Aznarte, Jose L, Morina, David, Alonso, Sergio, Alvarez, Enric, Lopez, Daniel, Prats, Clara, Burgard, Jan Pablo, Wolffram, Daniel, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Catala, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Abbott, Sam, Bartolucci, Francesco, Jona Lasinio, Giovanna, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav

المصدر: eLife 12, e81916 (2023). doi:10.7554/eLife.81916

مصطلحات موضوعية: info:eu-repo/classification/ddc/600

جغرافية الموضوع: DE

الوصف: Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022.Methods:We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance.Results:Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident ...

العلاقة: info:eu-repo/semantics/altIdentifier/wos/WOS:001009734700001; info:eu-repo/semantics/altIdentifier/pmid/37083521; info:eu-repo/semantics/altIdentifier/issn/2050-084X; https://juser.fz-juelich.de/record/1009058Test; https://juser.fz-juelich.de/search?p=id:%22FZJ-2023-02606%22Test

الإتاحة: https://doi.org/10.7554/eLife.81916Test
https://doi.org/10.34734/FZJ-2023-02606Test
https://juser.fz-juelich.de/record/1009058Test
https://juser.fz-juelich.de/search?p=id:%22FZJ-2023-02606%22Test

المؤلفون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L, Reich, Nicholas G, Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H, Barbarossa, Maria Vittoria, Leithauser, Neele, Mohring, Jan, Schneider, Johanna, Wlazlo, Jaroslaw, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajicek, Milan, Perez Alvarez, Cesar, Reina, Borja, Bosse, Nikos I, Meakin, Sophie R, Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerova, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsimas, Li, Michael Lingzhi, Saksham, Soni, Dehning, Jonas, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Hotz, Thomas, Singh, David E, Guzman- Merino, Miguel, Aznarte, Jose L, Morina, David, Alonso, Sergio, Alvarez, Enric, Lopez, Daniel, Prats, Clara, Burgard, Jan Pablo, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Catala, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Bartolucci, Francesco, Lasinio, Giovanna Jona, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav, Porebski, Przemyslaw, Venkatramanan, Srinivasan, Bartczuk, Rafal P, Dreger, Filip, Gambin, Anna, Gogolewski, Krzysztof, Gruziel-Slomka, Magdalena, Krupa, Bartosz, Moszyński, Antoni, Niedzielewski, Karol, Nowosielski, Jedrzej, Radwan, Maciej, Rakowski, Franciszek, Semeniuk, Marcin, Szczurek, Ewa, Zielinski, Jakub, Kisielewski, Jan, Pabjan, Barbara, Holger, Kirsten, Kheifetz, Yuri, Scholz, Markus, Biecek, Przemyslaw, Bodych, Marcin, Filinski, Maciej, Idzikowski, Radoslaw, Krueger, Tyll, Ozanski, Tomasz, Bracher, Johannes, Funk, Sebastian

المساهمون: London School of Hygiene & Tropical Medicine, London, United Kingdom, European Centre for Disease Prevention and Control (ECDC), Stockholm, Sweden, Karlsruhe Institute of Technology, Karlsruhe, Germany, Robert Koch Institute, Berlin, Germany, University of Massachusetts Amherst, Amherst, United States, Boston Children’s Hospital and Harvard Medical School, Boston, United States, Third Faculty of Medicine, Charles University, Prague, Czech Republic, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland, Éducation nationale, Valbonne, France, Eidgenossische Technische Hochschule, Zurich, Switzerland, Forschungszentrum Jülich GmbH, Jülich, Germany, Frankfurt Institute for Advanced Studies, Frankfurt, Germany, raunhofer Institute for Industrial Mathematics, Kaiserslautern, Germany, Heidelberg University, Heidelberg, Germany, Helmholtz Centre for Infection Research, Braunschweig, Germany, IEM, Inc, Bel Air, United States, IEM, Inc, Baton Rouge, United States, Institut d’Investigacions Biomèdiques August Pi i Sunyer, Universitat Pompeu Fabra, Barcelona, Spain, Institute of Computer Science of the CAS, Prague, Czech Republic, Institute of Information Theory and Automation of the CAS, Prague, Czech Republic, Inverence, Madrid, Spain, Los Alamos National Laboratory, Los Alamos, United States, LUMSA University, Rome, Italy, Masaryk University, Brno, Czech Republic, Massachusetts Institute of Technology, Cambridge, United States, Max-Planck-Institut für Dynamik und Selbstorganisation, Göttingen, Germany, Medical University of Gdansk, Gdańsk, Poland, Paul Scherrer Institute, Villigen, Switzerland, Politecnico di Milano, Milan, Italy, Technical University of Kaiserlautern, Kaiserslautern, Germany, Technische Universität Ilmenau, Ilmenau, Germany, Universidad Carlos III de Madrid, Leganes, Spain, Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain, Universitat de Barcelona, Barcelona, Spain, Universitat Politècnica de Catalunya, Barcelona, Spain, Universitat Trier, Trier, Germany, University of Cologne, Cologne, Germany, University of Halle, Halle, Germany, University of Ljubljana, Ljubljana, Slovenia, University of Milano-Bicocca, Milano, Italy, University of Molise, Pesche, Italy, University of Oxford, Oxford, United Kingdom, University of Palermo, Palermo, Italy, University of Pavia, Pavia, Italy, University of Perugia, Perugia, Italy, University of Rome "La Sapienza", Rome, Italy, University of Rome "Tor Vergata", Rome, Italy, University of Southern California, Los Angeles, United States, University of Sydney, Sydney, Australia, University of Virginia, Charlottesville, United States, Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, University of Bialystok, Poland, University of Wroclaw, Wroclaw, Poland, Universtät Leipzig, Leipzig, Germany, Warsaw University of Technology, Warsaw, Poland, Wroclaw University of Science and Technology, Wroclaw, Poland

مصطلحات موضوعية: COVID-19, Europe, ensemble, epidemiology, forecast, global health, modelling, none, prediction

الوصف: Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for ...

وصف الملف: application/pdf

العلاقة: Sherratt K, Gruson H, Grah R, Johnson H, Niehus R, Prasse B, Sandmann F, Deuschel J, Wolffram D, Abbott S, Ullrich A, Gibson G, Ray EL, Reich NG, Sheldon D, Wang Y, Wattanachit N, Wang L, Trnka J, Obozinski G, Sun T, Thanou D, Pottier L, Krymova E, Meinke JH, Barbarossa MV, Leithauser N, Mohring J, Schneider J, Wlazlo J, Fuhrmann J, Lange B, Rodiah I, Baccam P, Gurung H, Stage S, Suchoski B, Budzinski J, Walraven R, Villanueva I, Tucek V, Smid M, Zajicek M, Perez Alvarez C, Reina B, Bosse NI, Meakin SR, Castro L, Fairchild G, Michaud I, Osthus D, Alaimo Di Loro P, Maruotti A, Eclerova V, Kraus A, Kraus D, Pribylova L, Dimitris B, Li ML, Saksham S, Dehning J, Mohr S, Priesemann V, Redlarski G, Bejar B, Ardenghi G, Parolini N, Ziarelli G, Bock W, Heyder S, Hotz T, Singh DE, Guzman-Merino M, Aznarte JL, Morina D, Alonso S, Alvarez E, Lopez D, Prats C, Burgard JP, Rodloff A, Zimmermann T, Kuhlmann A, Zibert J, Pennoni F, Divino F, Catala M, Lovison G, Giudici P, Tarantino B, Bartolucci F, Jona Lasinio G, Mingione M, Farcomeni A, Srivastava A, Montero-Manso P, Adiga A, Hurt B, Lewis B, Marathe M, Porebski P, Venkatramanan S, Bartczuk RP, Dreger F, Gambin A, Gogolewski K, Gruziel-Slomka M, Krupa B, Moszyński A, Niedzielewski K, Nowosielski J, Radwan M, Rakowski F, Semeniuk M, Szczurek E, Zielinski J, Kisielewski J, Pabjan B, Holger K, Kheifetz Y, Scholz M, Przemyslaw B, Bodych M, Filinski M, Idzikowski R, Krueger T, Ozanski T, Bracher J, Funk S. Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations. Elife. 2023 Apr 21;12:e81916. doi:10.7554/eLife.81916.; https://depot.ceon.pl/handle/123456789/22761Test

الإتاحة: https://doi.org/10.7554/eLife.81916Test
https://depot.ceon.pl/handle/123456789/22761Test

المؤلفون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L, Reich, Nicholas G, Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H, Barbarossa, Maria Vittoria, Leithauser, Neele, Mohring, Jan, Schneider, Johanna, Wlazlo, Jaroslaw, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajicek, Milan, Perez Alvarez, Cesar, Reina, Borja, Bosse, Nikos I, Meakin, Sophie R, Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac

المساهمون: Netzwerk Universitätsmedizin, FISR, Agència de Qualitat i Avaluació Sanitàries de Catalunya, European Centre for Disease Prevention and Control, European Commission, Bundesministerium für Bildung und Forschung, Health Protection Research Unit, InPresa, Los Alamos National Laboratory, MUNI, Ministerio de Sanidad, Ministry of Science and Higher Education of Poland, National Institute of General Medical Sciences, National Institutes of Health, Virginia Department of Health, Narodowe Centrum Badań i Rozwoju, Horizon 2020, German Free State of Saxony, Spanish Ministry of Health, Social Policy and Equality, Wellcome Trust, RECETOX Přírodovědecké Fakulty Masarykovy Univerzity, CETOCOEN EXCELLENCEC, RECETOX RI project

المصدر: eLife ; volume 12 ; ISSN 2050-084X

الوصف: Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for ...

الإتاحة: https://doi.org/10.7554/elife.81916Test
https://cdn.elifesciences.org/articles/81916/elife-81916-v2.pdfTest
https://cdn.elifesciences.org/articles/81916/elife-81916-v2.xmlTest
https://elifesciences.org/articles/81916Test

المؤلفون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L, Reich, Nicholas G, Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H, Barbarossa, Maria Vittoria, Leithauser, Neele, Mohring, Jan, Schneider, Johanna, Wlazlo, Jaroslaw, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajicek, Milan, Perez Alvarez, Cesar, Reina, Borja, Bosse, Nikos I, Meakin, Sophie R, Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerova, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsimas, Li, Michael Lingzhi, Saksham, Soni, Dehning, Jonas, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Hotz, Thomas, Singh, David E, Guzman-Merino, Miguel, Aznarte, Jose L, Morina, David, Alonso, Sergio, Alvarez, Enric, Lopez, Daniel, Prats, Clara, Burgard, Jan Pablo, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Catala, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Bartolucci, Francesco, Jona Lasinio, Giovanna, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav, Porebski, Przemyslaw, Venkatramanan, Srinivasan, Bartczuk, Rafal P, Dreger, Filip, Gambin, Anna, Gogolewski, Krzysztof, Gruziel-Slomka, Magdalena, Krupa, Bartosz, Moszyński, Antoni, Niedzielewski, Karol, Nowosielski, Jedrzej, Radwan, Maciej, Rakowski, Franciszek, Semeniuk, Marcin, Szczurek, Ewa, Zielinski, Jakub, Kisielewski, Jan, Pabjan, Barbara, Holger, Kirsten, Kheifetz, Yuri, Scholz, Markus, Przemyslaw, Biecek, Bodych, Marcin, Filinski, Maciej, Idzikowski, Radoslaw, Krueger, Tyll, Ozanski, Tomasz, Bracher, Johannes, Funk, Sebastian

المساهمون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L, Reich, Nicholas G, Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H, Barbarossa, Maria Vittoria, Leithauser, Neele, Mohring, Jan, Schneider, Johanna, Wlazlo, Jaroslaw, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajicek, Milan, Perez Alvarez, Cesar, Reina, Borja, Bosse, Nikos I, Meakin, Sophie R, Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerova, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsima, Li, Michael Lingzhi, Saksham, Soni, Dehning, Jona, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Hotz, Thoma, Singh, David E, Guzman-Merino, Miguel, Aznarte, Jose L, Morina, David, Alonso, Sergio, Alvarez, Enric, Lopez, Daniel, Prats, Clara, Burgard, Jan Pablo, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Catala, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Bartolucci, Francesco, Jona Lasinio, Giovanna, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav

مصطلحات موضوعية: COVID-19, Europe, ensemble, epidemiology, forecast, global health, modelling, none, prediction

الوصف: Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022.Methods:We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1-4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models' predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models' forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models' past predictive performance.Results:Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models' forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models' forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models' forecasts of deaths (N=763 predictions from 20 models). Across a 1-4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident ...

العلاقة: info:eu-repo/semantics/altIdentifier/wos/WOS:001009734700001; volume:12; journal:ELIFE; https://hdl.handle.net/11590/451048Test

الإتاحة: https://doi.org/10.7554/eLife.81916Test
https://hdl.handle.net/11590/451048Test

المؤلفون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L, Reich, Nicholas G, Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H, Barbarossa, Maria Vittoria, Leithäuser, Neele, Mohring, Jan, Schneider, Johanna, Włazło, Jaroslaw, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajíček, Milan, Pérez Álvarez, Cesar, Reina, Borja, Bosse, Nikos I, Meakin, Sophie R, Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerová, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsimas, Li, Michael Lingzhi, Saksham, Soni, Dehning, Jonas, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Hotz, Thomas, Singh, David E, Guzman-Merino, Miguel, Aznarte, Jose L, Moriña, David, Alonso, Sergio, Álvarez, Enric, López, Daniel, Prats, Clara, Burgard, Jan Pablo, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Català, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Bartolucci, Francesco, Jona Lasinio, Giovanna, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav, Porebski, Przemyslaw, Venkatramanan, Srinivasan, Bartczuk, Rafal P, Dreger, Filip, Gambin, Anna, Gogolewski, Krzysztof, Gruziel-Słomka, Magdalena, Krupa, Bartosz, Moszyński, Antoni, Niedzielewski, Karol, Nowosielski, Jedrzej, Radwan, Maciej, Rakowski, Franciszek, Semeniuk, Marcin, Szczurek, Ewa, Zieliński, Jakub, Kisielewski, Jan, Pabjan, Barbara, Kirsten, Holger, Kheifetz, Yuri, Scholz, Markus, Biecek, Przemyslaw, Bodych, Marcin, Filinski, Maciej, Idzikowski, Radoslaw, Krueger, Tyll, Ozanski, Tomasz, Bracher, Johannes, Funk, Sebastian

المساهمون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L, Reich, Nicholas G, Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H, Barbarossa, Maria Vittoria, Leithäuser, Neele, Mohring, Jan, Schneider, Johanna, Włazło, Jaroslaw, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajíček, Milan, Pérez Álvarez, Cesar, Reina, Borja, Bosse, Nikos I, Meakin, Sophie R, Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerová, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsima, Li, Michael Lingzhi, Saksham, Soni, Dehning, Jona, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Hotz, Thoma, Singh, David E, Guzman-Merino, Miguel, Aznarte, Jose L, Moriña, David, Alonso, Sergio, Álvarez, Enric, López, Daniel, Prats, Clara, Burgard, Jan Pablo, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Català, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Bartolucci, Francesco, Jona Lasinio, Giovanna, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav

العلاقة: volume:12; journal:ELIFE; https://hdl.handle.net/11391/1546793Test

الإتاحة: https://doi.org/10.7554/eLife.81916Test
https://hdl.handle.net/11391/1546793Test

المؤلفون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L, Reich, Nicholas G, Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H, Barbarossa, Maria Vittoria, Leithäuser, Neele, Mohring, Jan, Schneider, Johanna, Włazło, Jaroslaw, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajíček, Milan, Pérez Álvarez, Cesar, Reina, Borja, Bosse, Nikos I, Meakin, Sophie R, Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerová, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsimas, Li, Michael Lingzhi, Saksham, Soni, Dehning, Jonas, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Hotz, Thomas, Singh, David E, Guzman-Merino, Miguel, Aznarte, Jose L, Moriña, David, Alonso, Sergio, Álvarez, Enric, López, Daniel, Prats, Clara, Burgard, Jan Pablo, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Català, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Bartolucci, Francesco, Jona Lasinio, Giovanna, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav, Porebski, Przemyslaw, Venkatramanan, Srinivasan, Bartczuk, Rafal P, Dreger, Filip, Gambin, Anna, Gogolewski, Krzysztof, Gruziel-Słomka, Magdalena, Krupa, Bartosz, Moszyński, Antoni, Niedzielewski, Karol, Nowosielski, Jedrzej, Radwan, Maciej, Rakowski, Franciszek, Semeniuk, Marcin, Szczurek, Ewa, Zieliński, Jakub, Kisielewski, Jan, Pabjan, Barbara, Kirsten, Holger, Kheifetz, Yuri, Scholz, Markus, Biecek, Przemyslaw, Bodych, Marcin, Filinski, Maciej, Idzikowski, Radoslaw, Krueger, Tyll, Ozanski, Tomasz, Bracher, Johannes, Funk, Sebastian

المساهمون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L, Reich, Nicholas G, Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H, Barbarossa, Maria Vittoria, Leithäuser, Neele, Mohring, Jan, Schneider, Johanna, Włazło, Jaroslaw, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajíček, Milan, Pérez Álvarez, Cesar, Reina, Borja, Bosse, Nikos I, Meakin, Sophie R, Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerová, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsima, Li, Michael Lingzhi, Saksham, Soni, Dehning, Jona, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Hotz, Thoma, Singh, David E, Guzman-Merino, Miguel, Aznarte, Jose L, Moriña, David, Alonso, Sergio, Álvarez, Enric, López, Daniel, Prats, Clara, Burgard, Jan Pablo, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Català, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Bartolucci, Francesco, Jona Lasinio, Giovanna, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav

مصطلحات موضوعية: epidemiology, global health, none

الوصف: Background: Short-term forecasts of infectious disease contribute to situational awareness and capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise forecasts' predictive performance by combining independent models into an ensemble. Here we report the performance of ensemble predictions of COVID-19 cases and deaths across Europe from March 2021 to March 2022. Methods: We created the European COVID-19 Forecast Hub, an online open-access platform where modellers upload weekly forecasts for 32 countries with results publicly visualised and evaluated. We created a weekly ensemble forecast from the equally-weighted average across individual models' predictive quantiles. We measured forecast accuracy using a baseline and relative Weighted Interval Score (rWIS). We retrospectively explored ensemble methods, including weighting by past performance. Results: We collected weekly forecasts from 48 models, of which we evaluated 29 models alongside the ensemble model. The ensemble had a consistently strong performance across countries over time, performing better on rWIS than 91% of forecasts for deaths (N=763 predictions from 20 models), and 83% forecasts for cases (N=886 predictions from 23 models). Performance remained stable over a 4-week horizon for death forecasts but declined with longer horizons for cases. Among ensemble methods, the most influential choice came from using a median average instead of the mean, regardless of weighting component models. Conclusions: Our results support combining independent models into an ensemble forecast to improve epidemiological predictions, and suggest that median averages yield better performance than methods based on means. We highlight that forecast consumers should place more weight on incident death forecasts than case forecasts at horizons greater than two weeks. Funding: European Commission, Ministerio de Ciencia, Innovación y Universidades, FEDER; Agència de Qualitat i Avaluació Sanitàries de ...

العلاقة: volume:12; journal:ELIFE; https://hdl.handle.net/11695/119387Test; https://elifesciences.org/articles/81916Test

الإتاحة: https://doi.org/10.7554/eLife.81916Test
https://hdl.handle.net/11695/119387Test
https://elifesciences.org/articles/81916Test

المؤلفون: Sherratt, Katharine, Gruson, Hugo, Grah, Rok, Johnson, Helen, Niehus, Rene, Prasse, Bastian, Sandmann, Frank, Deuschel, Jannik, Wolffram, Daniel, Abbott, Sam, Ullrich, Alexander, Gibson, Graham, Ray, Evan L, Reich, Nicholas G, Sheldon, Daniel, Wang, Yijin, Wattanachit, Nutcha, Wang, Lijing, Trnka, Jan, Obozinski, Guillaume, Sun, Tao, Thanou, Dorina, Pottier, Loic, Krymova, Ekaterina, Meinke, Jan H, Barbarossa, Maria Vittoria, Leithauser, Neele, Mohring, Jan, Schneider, Johanna, Wlazlo, Jaroslaw, Fuhrmann, Jan, Lange, Berit, Rodiah, Isti, Baccam, Prasith, Gurung, Heidi, Stage, Steven, Suchoski, Bradley, Budzinski, Jozef, Walraven, Robert, Villanueva, Inmaculada, Tucek, Vit, Smid, Martin, Zajicek, Milan, Perez Alvarez, Cesar, Reina, Borja, Bosse, Nikos I, Meakin, Sophie R, Castro, Lauren, Fairchild, Geoffrey, Michaud, Isaac, Osthus, Dave, Alaimo Di Loro, Pierfrancesco, Maruotti, Antonello, Eclerova, Veronika, Kraus, Andrea, Kraus, David, Pribylova, Lenka, Dimitris, Bertsimas, Li, Michael Lingzhi, Saksham, Soni, Dehning, Jonas, Mohr, Sebastian, Priesemann, Viola, Redlarski, Grzegorz, Bejar, Benjamin, Ardenghi, Giovanni, Parolini, Nicola, Ziarelli, Giovanni, Bock, Wolfgang, Heyder, Stefan, Hotz, Thomas, Singh, David E, Guzman-Merino, Miguel, Aznarte, Jose L, Morina, David, Alonso, Sergio, Alvarez, Enric, Lopez, Daniel, Prats, Clara, Burgard, Jan Pablo, Rodloff, Arne, Zimmermann, Tom, Kuhlmann, Alexander, Zibert, Janez, Pennoni, Fulvia, Divino, Fabio, Catala, Marti, Lovison, Gianfranco, Giudici, Paolo, Tarantino, Barbara, Bartolucci, Francesco, Jona Lasinio, Giovanna, Mingione, Marco, Farcomeni, Alessio, Srivastava, Ajitesh, Montero-Manso, Pablo, Adiga, Aniruddha, Hurt, Benjamin, Lewis, Bryan, Marathe, Madhav, Porebski, Przemyslaw, Venkatramanan, Srinivasan, Bartczuk, Rafal P, Dreger, Filip, Gambin, Anna, Gogolewski, Krzysztof, Gruziel-Slomka, Magdalena, Krupa, Bartosz, Moszyński, Antoni, Niedzielewski, Karol, Nowosielski, Jedrzej, Radwan, Maciej, Rakowski, Franciszek, Semeniuk, Marcin, Szczurek, Ewa, Zielinski, Jakub, Kisielewski, Jan, Pabjan, Barbara, Holger, Kirsten, Kheifetz, Yuri, Scholz, Markus, Przemyslaw, Biecek, Bodych, Marcin, Filinski, Maciej, Idzikowski, Radoslaw, Krueger, Tyll, Ozanski, Tomasz, Bracher, Johannes, Funk, Sebastian

المصدر: Elife ; ISSN:2050-084X ; Volume:12

مصطلحات موضوعية: COVID-19, Europe, ensemble, epidemiology, forecast, global health, modelling, none, prediction

الوصف: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022.

العلاقة: https://doi.org/10.7554/eLife.81916Test; https://pubmed.ncbi.nlm.nih.gov/37083521Test; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238088Test/

الإتاحة: https://doi.org/10.7554/eLife.81916Test
https://pubmed.ncbi.nlm.nih.gov/37083521Test
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238088Test/