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Why we need crowdsourced data in infectious disease surveillance
Rumi Chunara1, Mark S Smolinski, John S Brownstein
1Department of Pediatrics, Harvard Medical School, Boston, MA, USA, rumi@alum.mit.edu.
Current Infectious Disease Reports
|May 22, 2013
Summary
Crowdsourced data from internet and mobile tools can enhance infectious disease surveillance by filling gaps in traditional public health data. This approach offers a novel way to improve epidemiological models and understand disease dynamics.
Area of Science:
- Epidemiology
- Public Health
- Data Science
Background:
- Traditional infectious disease surveillance relies on public health data (environmental, hospital, census).
- These data sources have inherent limitations, including latency, cost, biases, and imprecise resolution.
- Emerging technologies offer new avenues for data collection.
Purpose of the Study:
- To explore the potential of crowdsourced data to augment current epidemiological models.
- To identify challenges and methods for utilizing novel data sources in disease surveillance.
- To enhance understanding of infectious disease dynamics through integrated data approaches.
Main Methods:
- Review of existing literature on infectious disease surveillance data.
- Analysis of the benefits and limitations of traditional versus crowdsourced data.
- Discussion of strategies for integrating diverse data streams into epidemiological frameworks.
Main Results:
- Crowdsourced data, gathered via internet and mobile tools, can provide real-time information.
- These novel data sources can complement and improve upon traditional surveillance data.
- Methods exist to overcome limitations associated with crowdsourced information.
Conclusions:
- Integrating crowdsourced data into epidemiological frameworks offers significant potential for improving infectious disease surveillance.
- Addressing data limitations is crucial for maximizing the utility of these new information sources.
- Future infectious disease dynamics research will benefit from incorporating diverse, novel data streams.
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