Cargando…
Big data and analytics for infectious disease research, operations, and policy : proceedings of a workshop /
With the amount of data in the world exploding, big data could generate significant value in the field of infectious disease. The increased use of social media provides an opportunity to improve public health surveillance systems and to develop predictive models. Advances in machine learning and cro...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico Congresos, conferencias eBook |
| Idioma: | Inglés |
| Publicado: |
Washington, DC :
National Academies Press,
[2016]
|
| Colección: | Online access: NCBI NCBI Bookshelf.
Online access: National Academy of Sciences National Academies Press. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | EBOOKCENTRAL_ocn971200096 | ||
| 003 | OCoLC | ||
| 005 | 20240329122006.0 | ||
| 006 | m o d | ||
| 007 | cr cn||||||||| | ||
| 008 | 170105s2016 dcua obt 100 0 eng | ||
| 010 | |a 2016498853 | ||
| 040 | |a NLM |b eng |e rda |e pn |c NLM |d MMU |d N$T |d OCLCF |d YDX |d EBLCP |d OCLCO |d NLM |d SNK |d DKU |d AUW |d MHW |d BTN |d AGLDB |d IGB |d D6H |d OCLCA |d OCLCQ |d VTS |d VT2 |d G3B |d OCLCO |d OCLCA |d S8J |d S9I |d STF |d OCLCQ |d OCLCO |d UKAHL |d OCLCO |d OCLCQ |d OCLCA |d OCLCQ |d LVT |d OCLCO |d OCLCA |d K6U |d OCLCO |d OCLCQ |d OCL |d OCLCO |d OCLCL | ||
| 016 | 7 | |a 101699388 |2 DNLM | |
| 019 | |a 974474314 |a 974558436 |a 974697340 |a 1229351738 |a 1272923797 | ||
| 020 | |a 9780309450119 | ||
| 020 | |a 030945011X | ||
| 020 | |a 9780309450140 | ||
| 020 | |a 0309450144 | ||
| 020 | 0 | |a 9780309450126 |q (online) | |
| 020 | |a 0309450128 | ||
| 024 | 7 | |a 10.17226/23654 |2 doi | |
| 029 | 0 | |a NLM |b 101699388 | |
| 029 | 1 | |a AU@ |b 000075792160 | |
| 029 | 1 | |a AU@ |b 000075842679 | |
| 029 | 1 | |a AU@ |b 000075865926 | |
| 029 | 1 | |a AU@ |b 000075882113 | |
| 035 | |a (OCoLC)971200096 |z (OCoLC)974474314 |z (OCoLC)974558436 |z (OCoLC)974697340 |z (OCoLC)1229351738 |z (OCoLC)1272923797 | ||
| 042 | |a pcc | ||
| 050 | 4 | |a RA643 | |
| 060 | 0 | 0 | |a 2017 C-616 |
| 060 | 0 | 0 | |a WC 100 |
| 072 | 7 | |a POL |x 027000 |2 bisacsh | |
| 072 | 7 | |a POL |x 019000 |2 bisacsh | |
| 072 | 7 | |a MED |x 022090 |2 bisacsh | |
| 082 | 0 | 4 | |a 362.1969 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Alper, Joe, |e rapporteur. | |
| 245 | 1 | 0 | |a Big data and analytics for infectious disease research, operations, and policy : |b proceedings of a workshop / |c Forum on Microbial Threats, Board on Global Health, Health and Medicine Division, the National Academies of Sciences, Engineering, Medicine. |
| 264 | 1 | |a Washington, DC : |b National Academies Press, |c [2016] | |
| 300 | |a 1 online resource (1 PDF file (xvi, 81 pages)) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references. | ||
| 520 | 3 | |a With the amount of data in the world exploding, big data could generate significant value in the field of infectious disease. The increased use of social media provides an opportunity to improve public health surveillance systems and to develop predictive models. Advances in machine learning and crowdsourcing may also offer the possibility to gather information about disease dynamics, such as contact patterns and the impact of the social environment. New, rapid, point-of-care diagnostics may make it possible to capture not only diagnostic information but also other potentially epidemiologically relevant information in real time. With a wide range of data available for analysis, decision-making and policy-making processes could be improved. While there are many opportunities for big data to be used for infectious disease research, operations, and policy, many challenges remain before it is possible to capture the full potential of big data. In order to explore some of the opportunities and issues associated with the scientific, policy, and operational aspects of big data in relation to microbial threats and public health, the National Academies of Sciences, Engineering, and Medicine convened a workshop in May 2016. Participants discussed a range of topics including preventing, detecting, and responding to infectious disease threats using big data and related analytics; varieties of data (including demographic, geospatial, behavioral, syndromic, and laboratory) and their broader applications; means to improve their collection, processing, utility, and validation; and approaches that can be learned from other sectors to inform big data strategies for infectious disease research, operations, and policy. This publication summarizes the presentations and discussions from the workshop. | |
| 536 | |a This project was supported by Contract No. 200-2011-38807 (Task Order No. 38), Contract No. DJF-16-1200-P-0002127, Contract No. 1R13FD005335-01, Contract No. ICD 620644, Contract No. APA-2015-6885, Contract No. HHSN26300055, Contract No. HT9404-12-1-0009, Contract No. GHN-G-00-07-00001-00, Contract No. W81XWH14-P-0339, Contract No. HSHQDC-15-C-00043, and Contract No. VA250-16-P-1998 between the National Academy of Sciences and the Centers for Disease Control and Prevention, the Federal Bureau of Investigation, the Food and Drug Administration, Johnson & Johnson, Merck Company Foundation, the National Institute of Allergy and Infectious Diseases/National Institutes of Health, the Uniformed Services University of the Health Sciences, the U.S. Agency for International Development, the U.S. Army Medical Research and Materiel Command, the U.S. Department of Homeland Security, and the U.S. Department of Veterans Affairs, respectively, and by the American Society for Microbiology, the Infectious Diseases Society of America, Sanofi Pasteur, and the Skoll Global Threats Fund. Any opinions, findings, conclusions, or recommendations expressed in this publication do not necessarily reflect the views of any organization or agency that provided support for the project. | ||
| 588 | 0 | |a Online resource; title from PDF title page (viewed February 2, 2017). | |
| 505 | 0 | |a Introduction -- Big data and global health -- Opportunities and challenges for big data and analytics -- Case studies in big data and analysis -- Closing remarks and general discussion. | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Communicable diseases |x Epidemiology. | |
| 650 | 0 | |a Public health surveillance. | |
| 650 | 0 | |a Data sets. | |
| 650 | 0 | |a World health. | |
| 650 | 1 | 2 | |a Communicable Diseases |x epidemiology |
| 650 | 2 | 2 | |a Datasets as Topic |
| 650 | 2 | 2 | |a Global Health |
| 650 | 2 | 2 | |a Population Surveillance |
| 650 | 6 | |a Maladies infectieuses |x Épidémiologie. | |
| 650 | 6 | |a Santé publique |x Surveillance. | |
| 650 | 6 | |a Jeux de données. | |
| 650 | 6 | |a Santé mondiale. | |
| 650 | 7 | |a POLITICAL SCIENCE |x Public Policy |x Social Security. |2 bisacsh | |
| 650 | 7 | |a POLITICAL SCIENCE |x Public Policy |x Social Services & Welfare. |2 bisacsh | |
| 650 | 7 | |a MEDICAL |x Infectious Diseases. |2 bisacsh | |
| 650 | 7 | |a World health |2 fast | |
| 650 | 7 | |a Data sets |2 fast | |
| 650 | 7 | |a Communicable diseases |x Epidemiology |2 fast | |
| 650 | 7 | |a Public health surveillance |2 fast | |
| 655 | 2 | |a Congress | |
| 655 | 7 | |a proceedings (reports) |2 aat | |
| 655 | 7 | |a Conference papers and proceedings |2 fast | |
| 655 | 7 | |a Conference papers and proceedings. |2 lcgft | |
| 655 | 7 | |a Actes de congrès. |2 rvmgf | |
| 710 | 2 | |a National Academies of Sciences, Engineering, and Medicine (U.S.). |b Forum on Microbial Threats, |e issuing body. | |
| 711 | 2 | |a Workshop on Big Data and Analytics for Infectious Disease Research, Operations, and Policy |d (2016 : |c Washington, D.C.) | |
| 758 | |i has work: |a Big data and analysis for infectious disease research, operations, and policy (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGhVVyD64VYKCGfF6VDFGb |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |t Big data and analytics for infectious disease research, operations, and policy. |d Washington, D.C. : National Academies Press, 2016 |z 9780309450119 |w (OCoLC)966256622 |
| 830 | 0 | |a Online access: NCBI NCBI Bookshelf. | |
| 830 | 0 | |a Online access: National Academy of Sciences National Academies Press. | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=4833788 |z Texto completo |
| 938 | |a Askews and Holts Library Services |b ASKH |n BDZ0040574034 | ||
| 938 | |a Askews and Holts Library Services |b ASKH |n AH36618325 | ||
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL4833788 | ||
| 938 | |a EBSCOhost |b EBSC |n 1475516 | ||
| 938 | |a YBP Library Services |b YANK |n 13953243 | ||
| 938 | |a YBP Library Services |b YANK |n 13522640 | ||
| 994 | |a 92 |b IZTAP | ||