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An open repository of real-time COVID-19 indicators
The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt t...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8713778/ https://www.ncbi.nlm.nih.gov/pubmed/34903654 http://dx.doi.org/10.1073/pnas.2111452118 |
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author | Reinhart, Alex Brooks, Logan Jahja, Maria Rumack, Aaron Tang, Jingjing Agrawal, Sumit Al Saeed, Wael Arnold, Taylor Basu, Amartya Bien, Jacob Cabrera, Ángel A. Chin, Andrew Chua, Eu Jing Clark, Brian Colquhoun, Sarah DeFries, Nat Farrow, David C. Forlizzi, Jodi Grabman, Jed Gratzl, Samuel Green, Alden Haff, George Han, Robin Harwood, Kate Hu, Addison J. Hyde, Raphael Hyun, Sangwon Joshi, Ananya Kim, Jimi Kuznetsov, Andrew La Motte-Kerr, Wichada Lee, Yeon Jin Lee, Kenneth Lipton, Zachary C. Liu, Michael X. Mackey, Lester Mazaitis, Kathryn McDonald, Daniel J. McGuinness, Phillip Narasimhan, Balasubramanian O’Brien, Michael P. Oliveira, Natalia L. Patil, Pratik Perer, Adam Politsch, Collin A. Rajanala, Samyak Rucker, Dawn Scott, Chris Shah, Nigam H. Shankar, Vishnu Sharpnack, James Shemetov, Dmitry Simon, Noah Smith, Benjamin Y. Srivastava, Vishakha Tan, Shuyi Tibshirani, Robert Tuzhilina, Elena Van Nortwick, Ana Karina Ventura, Valérie Wasserman, Larry Weaver, Benjamin Weiss, Jeremy C. Whitman, Spencer Williams, Kristin Rosenfeld, Roni Tibshirani, Ryan J. |
author_facet | Reinhart, Alex Brooks, Logan Jahja, Maria Rumack, Aaron Tang, Jingjing Agrawal, Sumit Al Saeed, Wael Arnold, Taylor Basu, Amartya Bien, Jacob Cabrera, Ángel A. Chin, Andrew Chua, Eu Jing Clark, Brian Colquhoun, Sarah DeFries, Nat Farrow, David C. Forlizzi, Jodi Grabman, Jed Gratzl, Samuel Green, Alden Haff, George Han, Robin Harwood, Kate Hu, Addison J. Hyde, Raphael Hyun, Sangwon Joshi, Ananya Kim, Jimi Kuznetsov, Andrew La Motte-Kerr, Wichada Lee, Yeon Jin Lee, Kenneth Lipton, Zachary C. Liu, Michael X. Mackey, Lester Mazaitis, Kathryn McDonald, Daniel J. McGuinness, Phillip Narasimhan, Balasubramanian O’Brien, Michael P. Oliveira, Natalia L. Patil, Pratik Perer, Adam Politsch, Collin A. Rajanala, Samyak Rucker, Dawn Scott, Chris Shah, Nigam H. Shankar, Vishnu Sharpnack, James Shemetov, Dmitry Simon, Noah Smith, Benjamin Y. Srivastava, Vishakha Tan, Shuyi Tibshirani, Robert Tuzhilina, Elena Van Nortwick, Ana Karina Ventura, Valérie Wasserman, Larry Weaver, Benjamin Weiss, Jeremy C. Whitman, Spencer Williams, Kristin Rosenfeld, Roni Tibshirani, Ryan J. |
author_sort | Reinhart, Alex |
collection | PubMed |
description | The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: Operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from deidentified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily. The COVIDcast API also tracks all revisions to historical data, allowing modelers to account for the frequent revisions and backfill that are common for many public health data sources. All of the data are available in a common format through the API and accompanying R and Python software packages. This paper describes the data sources and signals, and provides examples demonstrating that the auxiliary signals in the COVIDcast API present information relevant to tracking COVID activity, augmenting traditional public health reporting and empowering research and decision-making. |
format | Online Article Text |
id | pubmed-8713778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-87137782022-01-21 An open repository of real-time COVID-19 indicators Reinhart, Alex Brooks, Logan Jahja, Maria Rumack, Aaron Tang, Jingjing Agrawal, Sumit Al Saeed, Wael Arnold, Taylor Basu, Amartya Bien, Jacob Cabrera, Ángel A. Chin, Andrew Chua, Eu Jing Clark, Brian Colquhoun, Sarah DeFries, Nat Farrow, David C. Forlizzi, Jodi Grabman, Jed Gratzl, Samuel Green, Alden Haff, George Han, Robin Harwood, Kate Hu, Addison J. Hyde, Raphael Hyun, Sangwon Joshi, Ananya Kim, Jimi Kuznetsov, Andrew La Motte-Kerr, Wichada Lee, Yeon Jin Lee, Kenneth Lipton, Zachary C. Liu, Michael X. Mackey, Lester Mazaitis, Kathryn McDonald, Daniel J. McGuinness, Phillip Narasimhan, Balasubramanian O’Brien, Michael P. Oliveira, Natalia L. Patil, Pratik Perer, Adam Politsch, Collin A. Rajanala, Samyak Rucker, Dawn Scott, Chris Shah, Nigam H. Shankar, Vishnu Sharpnack, James Shemetov, Dmitry Simon, Noah Smith, Benjamin Y. Srivastava, Vishakha Tan, Shuyi Tibshirani, Robert Tuzhilina, Elena Van Nortwick, Ana Karina Ventura, Valérie Wasserman, Larry Weaver, Benjamin Weiss, Jeremy C. Whitman, Spencer Williams, Kristin Rosenfeld, Roni Tibshirani, Ryan J. Proc Natl Acad Sci U S A Biological Sciences The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: Operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from deidentified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily. The COVIDcast API also tracks all revisions to historical data, allowing modelers to account for the frequent revisions and backfill that are common for many public health data sources. All of the data are available in a common format through the API and accompanying R and Python software packages. This paper describes the data sources and signals, and provides examples demonstrating that the auxiliary signals in the COVIDcast API present information relevant to tracking COVID activity, augmenting traditional public health reporting and empowering research and decision-making. National Academy of Sciences 2021-12-13 2021-12-21 /pmc/articles/PMC8713778/ /pubmed/34903654 http://dx.doi.org/10.1073/pnas.2111452118 Text en Copyright © 2021 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Biological Sciences Reinhart, Alex Brooks, Logan Jahja, Maria Rumack, Aaron Tang, Jingjing Agrawal, Sumit Al Saeed, Wael Arnold, Taylor Basu, Amartya Bien, Jacob Cabrera, Ángel A. Chin, Andrew Chua, Eu Jing Clark, Brian Colquhoun, Sarah DeFries, Nat Farrow, David C. Forlizzi, Jodi Grabman, Jed Gratzl, Samuel Green, Alden Haff, George Han, Robin Harwood, Kate Hu, Addison J. Hyde, Raphael Hyun, Sangwon Joshi, Ananya Kim, Jimi Kuznetsov, Andrew La Motte-Kerr, Wichada Lee, Yeon Jin Lee, Kenneth Lipton, Zachary C. Liu, Michael X. Mackey, Lester Mazaitis, Kathryn McDonald, Daniel J. McGuinness, Phillip Narasimhan, Balasubramanian O’Brien, Michael P. Oliveira, Natalia L. Patil, Pratik Perer, Adam Politsch, Collin A. Rajanala, Samyak Rucker, Dawn Scott, Chris Shah, Nigam H. Shankar, Vishnu Sharpnack, James Shemetov, Dmitry Simon, Noah Smith, Benjamin Y. Srivastava, Vishakha Tan, Shuyi Tibshirani, Robert Tuzhilina, Elena Van Nortwick, Ana Karina Ventura, Valérie Wasserman, Larry Weaver, Benjamin Weiss, Jeremy C. Whitman, Spencer Williams, Kristin Rosenfeld, Roni Tibshirani, Ryan J. An open repository of real-time COVID-19 indicators |
title | An open repository of real-time COVID-19 indicators |
title_full | An open repository of real-time COVID-19 indicators |
title_fullStr | An open repository of real-time COVID-19 indicators |
title_full_unstemmed | An open repository of real-time COVID-19 indicators |
title_short | An open repository of real-time COVID-19 indicators |
title_sort | open repository of real-time covid-19 indicators |
topic | Biological Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8713778/ https://www.ncbi.nlm.nih.gov/pubmed/34903654 http://dx.doi.org/10.1073/pnas.2111452118 |
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