Title |
Enhancing disease surveillance with novel data streams: challenges and opportunities
|
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Published in |
EPJ Data Science, October 2015
|
DOI | 10.1140/epjds/s13688-015-0054-0 |
Pubmed ID | |
Authors |
Benjamin M Althouse, Samuel V Scarpino, Lauren Ancel Meyers, John W Ayers, Marisa Bargsten, Joan Baumbach, John S Brownstein, Lauren Castro, Hannah Clapham, Derek AT Cummings, Sara Del Valle, Stephen Eubank, Geoffrey Fairchild, Lyn Finelli, Nicholas Generous, Dylan George, David R Harper, Laurent Hébert-Dufresne, Michael A Johansson, Kevin Konty, Marc Lipsitch, Gabriel Milinovich, Joseph D Miller, Elaine O Nsoesie, Donald R Olson, Michael Paul, Philip M Polgreen, Reid Priedhorsky, Jonathan M Read, Isabel Rodríguez-Barraquer, Derek J Smith, Christian Stefansen, David L Swerdlow, Deborah Thompson, Alessandro Vespignani, Amy Wesolowski |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 16 | 41% |
Italy | 2 | 5% |
Thailand | 1 | 3% |
United Kingdom | 1 | 3% |
Indonesia | 1 | 3% |
Australia | 1 | 3% |
Unknown | 17 | 44% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 23 | 59% |
Scientists | 14 | 36% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 3% |
Spain | 2 | 1% |
United Kingdom | 1 | <1% |
Switzerland | 1 | <1% |
Unknown | 164 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 35 | 20% |
Student > Ph. D. Student | 33 | 19% |
Student > Master | 18 | 10% |
Student > Bachelor | 13 | 8% |
Student > Doctoral Student | 12 | 7% |
Other | 25 | 14% |
Unknown | 37 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 28 | 16% |
Agricultural and Biological Sciences | 22 | 13% |
Medicine and Dentistry | 13 | 8% |
Social Sciences | 12 | 7% |
Mathematics | 10 | 6% |
Other | 44 | 25% |
Unknown | 44 | 25% |