Enhancing disease surveillance with novel data streams: challenges and opportunities
dc.contributor | Virginia Tech | en |
dc.contributor.author | Althouse, Benjamin M. | en |
dc.contributor.author | Scarpino, Samuel V. | en |
dc.contributor.author | Meyers, Lauren Ancel | en |
dc.contributor.author | Ayers, John W. | en |
dc.contributor.author | Bargsten, Marisa | en |
dc.contributor.author | Baumbach, Joan | en |
dc.contributor.author | Brownstein, John S. | en |
dc.contributor.author | Castro, Lauren | en |
dc.contributor.author | Clapham, Hannah | en |
dc.contributor.author | Cummings, Derek A. T. | en |
dc.contributor.author | Del Valle, Sara | en |
dc.contributor.author | Eubank, Stephen | en |
dc.contributor.author | Fairchild, Geoffrey | en |
dc.contributor.author | Finelli, Lyn | en |
dc.contributor.author | Generous, Nicholas | en |
dc.contributor.author | George, Dylan | en |
dc.contributor.author | Harper, David R. | en |
dc.contributor.author | Hebert-Dufresne, Laurent | en |
dc.contributor.author | Johansson, Michael A. | en |
dc.contributor.author | Konty, Kevin | en |
dc.contributor.author | Lipsitch, Marc | en |
dc.contributor.author | Millinovich, Gabriel | en |
dc.contributor.author | Miller, Joseph D. | en |
dc.contributor.author | Nsoesie, Elaine O. | en |
dc.contributor.author | Olson, Donald R. | en |
dc.contributor.author | Paul, Michael | en |
dc.contributor.author | Priedhorsky, Reid | en |
dc.contributor.author | Read, Jonathan M. | en |
dc.contributor.author | Rodriguez-Barraquer, Isabel | en |
dc.contributor.author | Smith, Derek J. | en |
dc.contributor.author | Stefansen, Christian | en |
dc.contributor.author | Swerdlow, David L. | en |
dc.contributor.author | Thompson, Deborah | en |
dc.contributor.author | Vespignani, Alessandro | en |
dc.contributor.author | Wesolowski, Amy | en |
dc.contributor.author | Polgreen, Philip M. | en |
dc.date.accessioned | 2017-10-27T17:45:21Z | en |
dc.date.available | 2017-10-27T17:45:21Z | en |
dc.date.issued | 2015 | en |
dc.description.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. | en |
dc.description.sponsorship | We also gratefully acknowledge funding from the Santa Fe Institute, the NIH MIDAS Center of Excellence at the Harvard Center for Communicable Disease Dynamics, William Sick, Mike Frumkin and the Frumkin Falco Family Foundation. BMA and SVS also acknowledge support from the Santa Fe Institute and the Omidyar Group. | en |
dc.description.version | Published version | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.doi | https://doi.org/10.1140/epjds/s13688-015-0054-0 | en |
dc.identifier.issue | 17 | en |
dc.identifier.uri | http://hdl.handle.net/10919/79827 | en |
dc.identifier.volume | 4 | en |
dc.language.iso | en | en |
dc.publisher | Springer | en |
dc.rights | Creative Commons Attribution 4.0 International | en |
dc.rights.holder | The Author(s) | en |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en |
dc.subject | disease surveillance | en |
dc.subject | novel data streams | en |
dc.subject | digital surveillance | en |
dc.title | Enhancing disease surveillance with novel data streams: challenges and opportunities | en |
dc.title.serial | EJP Data Science | en |
dc.type | Article - Refereed | en |
dc.type.dcmitype | Text | en |
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