| Title: |
The United States COVID-19 Forecast Hub dataset |
| Authors: |
Cramer, Estee Y.; Huang, Yuxin; Wang, Yijin; Ray, Evan L.; Cornell, Matthew; Bracher, Johannes; Brennen, Andrea; Rivadeneira, Alvaro J.Castro; Gerding, Aaron; House, Katie; Jayawardena, Dasuni; Sinha, Rajarishi; Tsai, Thomas; Yoder, Nate; Yoon, Jinsung; Zhang, Leyou; Wang, Liqiang; Wilson, Daniel; Belov, Artur A.; Chow, Carson C.; Zhang, Shun; Lauer, Stephen A.; Shrivastav, Monika; Gerkin, Richard C.; Yogurtcu, Osman N.; Ibrahim, Mark; Lacroix, Timothee; Le, Matthew; Liao, Jason; Zhang, Shunpu; Nickel, Maximilian; Sagun, Levent; Lee, Elizabeth C.; Wattanchit, Nutcha; Abbott, Sam; Bosse, Nikos I.; You, Jialu; Funk, Sebastian; Hellewell, Joel; Meakin, Sophie R.; Sherratt, Katharine; Kalantari, Rahi; Zou, Zihang; Lemaitre, Joseph C.; Zhou, Mingyuan; Guo, Lihong; Karimzadeh, Morteza; Lucas, Benjamin; Ngo, Thoai; Zoraghein, Hamidreza; Bannur, Nayana; Vahedi, Behzad; Wang, Zhongying; Sen Pei; Lessler, Justin; Shaman, Jeffrey; Biegel, Hannah; Zheng, Shun; Yamana, Teresa K.; Bertsimas, Dimitris; Li, Michael L.; Soni, Saksham; Bouardi, Hamza Tazi; Adee, Madeline; Deva, Ayush; Meredith, Hannah R.; Ayer, Turgay; Chhatwal, Jagpreet; Dalgic, Ozden O.; Chinazzi, Matteo; Lega, Joceline; Ladd, Mary A.; Linas, Benjamin P.; Mueller, Peter; Xiao, Jade; Bosch, Jurgen; Chintanippu, Krishna; Wilson, Austin; Zimmerman, Peter; Jain, Sansiddh; Wang, Qinxia; Vespignani, Alessandro; Wang, Yuanjia; Hussain, Fazle; Xie, Shanghong; Zeng, Donglin; Bien, Jacob; Perez-Saez, Javier; Brooks, Logan; Green, Alden; Hu, Addison J.; Jahja, Maria; McDonald, Daniel; Xiong, Xinyue; Kulkarni, Mihir; Narasimhan, Balasubramanian; Khandelwal, Ayush; Politsch, Collin; Shah, Sam; Rajanala, Samyak; Rumack, Aaron; Simon, Noah; Tibshirani, Ryan J.; Tibshirani, Rob; Ventura, Valerie; Davis, Jessica T.; Wasserman, Larry; Drake, John M.; Merugu, Srujana; Smith, Claire P.; Khan, Zeina; O’Dea, Eamon B.; Abu-Mostafa, Yaser; Bathwal, Rahil; Chang, Nicholas A.; Chitta, Pavan; Erickson, Anne; Mu, Kunpeng; Goel, Sumit; Gowda, Jethin; Chattopadhyay, Ishanu; Jin, Qixuan; Jo, Hyeong Chan; Van Bussel, Frank; Raval, Alpan; Kim, Juhyun; Kulkarni, Pranav; Lushtak, Samuel M.; Mann, Ethan; Piontti, Ana Pastore y.; Popken, Max; Kraus, David; Soohoo, Connor; Tirumala, Kushal; Tseng, Albert; Varadarajan, Vignesh; McConnell, Steve; Vytheeswaran, Jagath; Shingi, Siddhant; Wang, Christopher; Yeluri, Akshay; Baek, Jackie; Truelove, Shaun A.; Yurk, Dominic; Zhang, Michael; Zlokapa, Alexander; Pagano, Robert; Jain, Chandini; Tomar, Vishal; Guertin, Stephanie L.; Ho, Lam; Huynh, Huong; Tiwari, Avtansh; Wills, Josh; Farias, Vivek; Tran, Quoc; Lopez, Velma K.; Walker, Jo W.; Slayton, Rachel B.; Johansson, Michael A.; Biggerstaff, Matthew; Reich, Nicholas G.; Hulme-Lowe, Christopher; White, Jerome; Gardner, Lauren; Adiga, Aniruddha; Georgescu, Andreea; Hurt, Benjamin; Lewis, Bryan; Marathe, Madhav; Peddireddy, Akhil Sai; Porebski, Przemyslaw; Venkatramanan, Srinivasan; Wang, Lijing; Dahan, Maytal; Marshall, Maximilian; Nagraj, V. P.; Fox, Spencer; Zhao, Yanting; Gaither, Kelly; Lachmann, Michael; Meyers, Lauren Ancel; Scott, James G.; Tec, Mauricio; Woody, Spencer; Srivastava, Ajitesh; Nixon, Kristen; Xu, Tianjian; Cegan, Jeffrey C.; Turner, Stephen D.; Zorn, Martha W.; Dettwiller, Ian D.; England, William P.; Farthing, Matthew W.; George, Glover E.; Hunter, Robert H.; Lafferty, Brandon; Burant, John C.; Linkov, Igor; Mayo, Michael L.; Parno, Matthew D.; Rowland, Michael A.; Levi, Retsef; Bejar, Benjamín; Trump, Benjamin D.; Chen, Samuel; Faraone, Stephen V.; Hess, Jonathan; Budzinski, Jozef; Morley, Christopher P.; Salekin, Asif; Wang, Dongliang; Zhang-James, Yanli; Baer, Thomas M.; Sinha, Deeksha; Corsetti, Sabrina M.; Choirat, Christine; Eisenberg, Marisa C.; Falb, Karl; Jivane, Viresh; Huang, Yitao; Martin, Emily T.; McCauley, Ella; Myers, Robert L.; Schwarz, Tom; Gibson, Graham Casey; Wilde, Joshua; Sheldon, Daniel; Gao, Liyao; Flahault, Antoine; Chiang, Wen Hao; Ma, Yian; Wu, Dongxia; Yu, Rose; Jin, Xiaoyong; Wang, Yu Xiang; Yan, Xifeng; Chen, Yang Quan; Zheng, Andrew; Le, Khoa; Krymova, Ekaterina; Mohler, George; Lee, Gavin; Manetti, Elisa; Namigai, Kristen; Obozinski, Guillaume; Sun, Tao; Thanou, Dorina; Ban, Xuegang; Shi, Yunfeng; Lami, Omar Skali; Walraven, Robert; Bian, Jiang; Mody, Vidhi; Hong, Qi Jun; van de Walle, Axel; Ben-Nun, Michal; Riley, Steven; Riley, Pete; Turtle, James; Cao, Duy; Galasso, Joseph; Bennouna, Amine; Huang, Yi; Cho, Jae H.; Jo, Areum; Mody, Vrushti; DesRoches, David; Forli, Pedro; Hamory, Bruce; Koyluoglu, Ugur; Kyriakides, Christina; Leis, Helen; Milliken, John; Gao, Junyi; Ndong, David Nze; Moloney, Michael; Morgan, James; Nirgudkar, Ninad; Niemi, Jarad; Ozcan, Gokce; Piwonka, Noah; Ravi, Matt; Schrader, Chris; Shakhnovich, Elizabeth; Glass, Lucas; Siegel, Daniel; Perakis, Georgia; Spatz, Ryan; Stiefeling, Chris; Wilkinson, Barrie; Wong, Alexander; Stark, Ariane; Cavany, Sean; España, Guido; Moore, Sean; Qian, Cheng; Oidtman, Rachel; Perkins, Alex; Singhvi, Divya; Ivy, Julie S.; Mayorga, Maria E.; Mele, Jessica; Rosenstrom, Erik T.; Swann, Julie L.; Shah, Apurv; Kraus, Andrea; Romberg, Justin; Chen, Jinghui; Spantidakis, Ioannis; Thayaparan, Leann; Tsiourvas, Asterios; Weisberg, Shane; Jadbabaie, Ali; Sarker, Arnab; Shah, Devavrat; Celi, Leo A.; Sharma, Rakshith; Penna, Nicolas D.; Gu, Quanquan; Sundar, Saketh; Berlin, Abraham; Gneiting, Tilmann; Gandhi, Parth D.; McAndrew, Thomas; Piriya, Matthew; Chen, Ye; Hlavacek, William; Spaeder, Jeffrey; Lin, Yen Ting; Mallela, Abhishek; Wang, Lingxiao; Miller, Ely; Neumann, Jacob; Posner, Richard; Mühlemann, Anja; Wolfinger, Russ; Castro, Lauren; Fairchild, Geoffrey; Sun, Jimeng; Michaud, Isaac; Osthus, Dave; Wolffram, Daniel; Xu, Pan; Karlen, Dean; Panaggio, Mark J.; Kinsey, Matt; Mullany, Luke C.; Gu, Youyang; Rainwater-Lovett, Kaitlin; Xiao, Cao; Shin, Lauren; Tallaksen, Katharine; Wilson, Shelby; Brenner, Michael; Zhang, Weitong; Coram, Marc; Edwards, Jessie K.; Joshi, Keya; Klein, Ellen; Hulse, Juan Dent; Khurana, Ankita; Chen, Yixian; Grantz, Kyra H.; Hill, Alison L.; Kaminsky, Kathryn; Kaminsky, Joshua; Zou, Difan; Keegan, Lindsay T.; Cao, Wei; Gao, Lei; Kanji, Abdul Hannan; Gu, Zhiling; Kim, Myungjin; Li, Xinyi; Wang, Yueying; Wang, Guannan; Wang, Lily; Yu, Shan; Jain, Chaman; Gao, Zhifeng; Bhatia, Sangeeta; Kumar, Ajay; Lu, Guoqing; Nouvellet, Pierre; Barber, Ryan; Gaikedu, Emmanuela; Hay, Simon; Lim, Steve; Murray, Chris; Pigott, David; Ferres, Juan Lavista; Reiner, Robert C.; Baccam, Prasith; Gurung, Heidi L.; Pfeiffer, Ruth; Lakhani, Anshul; Stage, Steven A.; Suchoski, Bradley T.; Fong, Chung Yan; Yeung, Dit Yan; Adhikari, Bijaya; Li, Chaozhuo; Cui, Jiaming; Prakash, B. Aditya; Rodríguez, Alexander; Tabassum, Anika; Sumner, Timothy; Xie, Jiajia; Mehrotra, Prakhar; Asplund, John; Baxter, Arden; Keskinocak, Pinar; Liu, Tie Yan; Oruc, Buse Eylul; Serban, Nicoleta; Arik, Sercan O.; Dusenberry, Mike; Epshteyn, Arkady; Wang, Dongdong; Kanal, Elli; Le, Long T.; Pasumarty, Sujitha; Li, Chun Liang; Xie, Xing; Pfister, Tomas |
| Publication Year: |
2022 |
| Collection: |
University of Hong Kong: HKU Scholars Hub |
| Description: |
Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages. ; published_or_final_version |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
Scientific Data; Scientific Data, 2022, v. 9, n. 1, article no. 462; article no. 462; WOS:000834818500002; PMC9342845; https://hub.hku.hk/handle/10722/316669 |
| DOI: |
10.1038/s41597-022-01517-w |
| Availability: |
https://hub.hku.hk/handle/10722/316669; https://doi.org/10.1038/s41597-022-01517-w |
| Rights: |
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
| Accession Number: |
edsbas.3B76AA39 |
| Database: |
BASE |