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Enhancing disease surveillance with novel data streams: challenges and opportunities.
Althouse, Benjamin M; Scarpino, Samuel V; Meyers, Lauren Ancel; Ayers, John W; Bargsten, Marisa; Baumbach, Joan; Brownstein, John S; Castro, Lauren; Clapham, Hannah; Cummings, Derek At; Del Valle, Sara; Eubank, Stephen; Fairchild, Geoffrey; Finelli, Lyn; Generous, Nicholas; George, Dylan; Harper, David R; Hébert-Dufresne, Laurent; Johansson, Michael A; Konty, Kevin; Lipsitch, Marc; Milinovich, Gabriel; Miller, Joseph D; Nsoesie, Elaine O; Olson, Donald R; Paul, Michael; Polgreen, Philip M; Priedhorsky, Reid; Read, Jonathan M; Rodríguez-Barraquer, Isabel; Smith, Derek J; Stefansen, Christian; Swerdlow, David L; Thompson, Deborah; Vespignani, Alessandro; Wesolowski, Amy.
Afiliación
  • Althouse BM; Santa Fe Institute, Santa Fe, NM, USA.
  • Scarpino SV; Santa Fe Institute, Santa Fe, NM, USA.
  • Meyers LA; Santa Fe Institute, Santa Fe, NM, USA.
  • Ayers JW; The University of Texas at Austin, Austin, TX, USA.
  • Bargsten M; San Diego State University, San Diego, CA, USA.
  • Baumbach J; New Mexico Department of Health, Santa Fe, NM, USA.
  • Brownstein JS; New Mexico Department of Health, Santa Fe, NM, USA.
  • Castro L; Children's Hospital Informatics Program, Boston Children's Hospital, Boston, MA, USA.
  • Clapham H; Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
  • Cummings DA; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada.
  • Del Valle S; Defense Systems and Analysis Division, Los Alamos National Laboratory, Los Alamos, NM, USA.
  • Eubank S; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Fairchild G; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Finelli L; Defense Systems and Analysis Division, Los Alamos National Laboratory, Los Alamos, NM, USA.
  • Generous N; Virginia BioInformatics Institute and Department of Population Health Sciences, Virginia Tech, Blacksburg, VA, USA.
  • George D; Defense Systems and Analysis Division, Los Alamos National Laboratory, Los Alamos, NM, USA.
  • Harper DR; Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Hébert-Dufresne L; Defense Systems and Analysis Division, Los Alamos National Laboratory, Los Alamos, NM, USA.
  • Johansson MA; Biomedical Advanced Research and Development Authority (BARDA), Assistant Secretary for Preparedness and Response (ASPR), Department of Health and Human Services, Washington, DC, USA.
  • Konty K; Chatham House, 10 St James's Square, London, SW1Y 4LE, UK.
  • Lipsitch M; Santa Fe Institute, Santa Fe, NM, USA.
  • Milinovich G; Division of Vector-Borne Diseases, NCEZID, Centers for Disease Control and Prevention, San Juan, PR, USA.
  • Miller JD; Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, NY, USA.
  • Nsoesie EO; Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA.
  • Olson DR; School of Population Health, The University of Queensland, Brisbane, QLD, Australia.
  • Paul M; Division of Vector-Borne Diseases, NCEZID, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Polgreen PM; Children's Hospital Informatics Program, Boston Children's Hospital, Boston, MA, USA.
  • Priedhorsky R; Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
  • Read JM; Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, NY, USA.
  • Rodríguez-Barraquer I; Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
  • Smith DJ; University of Iowa, Iowa City, IA, USA.
  • Stefansen C; Defense Systems and Analysis Division, Los Alamos National Laboratory, Los Alamos, NM, USA.
  • Swerdlow DL; Department of Epidemiology and Population Health, Institute of Infection and Global Health, University of Liverpool, Liverpool, CH64 7TE, UK.
  • Thompson D; Health Protection Research Unit in Emerging and Zoonotic Infections, NIHR, Liverpool, L69 7BE, UK.
  • Vespignani A; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Wesolowski A; Department of Zoology, University of Cambridge, Cambridge, CB2 3EJ, UK.
EPJ Data Sci ; 42015.
Article en En | MEDLINE | ID: mdl-27990325
ABSTRACT
Novel data streams (NDS), such as web search data or social media updates, hold promise for enhancing the capabilities of public health surveillance. In this paper, we outline a conceptual framework for integrating NDS into current public health surveillance. Our approach focuses on two key questions What are the opportunities for using NDS and what are the minimal tests of validity and utility that must be applied when using NDS? Identifying these opportunities will necessitate the involvement of public health authorities and an appreciation of the diversity of objectives and scales across agencies at different levels (local, state, national, international). We present the case that clearly articulating surveillance objectives and systematically evaluating NDS and comparing the performance of NDS to existing surveillance data and alternative NDS data is critical and has not sufficiently been addressed in many applications of NDS currently in the literature.
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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Screening_studies Idioma: En Revista: EPJ Data Sci Año: 2015 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Screening_studies Idioma: En Revista: EPJ Data Sci Año: 2015 Tipo del documento: Article País de afiliación: Estados Unidos