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An integrated open source web based platform for continuous chronic disease surveillance on social network channels

Award Information
Agency: Department of Health and Human Services
Branch: Centers for Disease Control and Prevention
Contract: 200-2017-M-96112
Agency Tracking Number: 200-2017-M-96112
Amount: $149,999.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: ODCDC
Solicitation Number: N/A
Solicitation Year: 2017
Award Year: 2017
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
United States
DUNS: 010926207
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Aashish Chaudhary
 (480) 275-0777
Business Contact
Phone: (518) 371-3971
Research Institution

Chronic diseases and conditions are the leading causes of death and or disability in the United States However much of the illness suffering and early death related to chronic diseases and conditions can be attributed to a few behavioral risk factors that can be mitigated by prevention programs from public health agencies To effectively prioritize plan and implement such preventive interventions public health agencies need continuous access to up to date uniformly defined surveillance information about the prevalence and impact of chronic diseases and risk factors at a county city state level We propose to develop an integrated open source web based data analytics platform for continuous chronic disease surveillance on social networking sites The platform will provide end to end capabilities ranging from tools for the compliant collection of relevant data from applicable social network channels extraction of surveillance information using machine learning and visually present this information in such a way that experts of public health agencies can derive actionable insights For this effort Kitware and SUNY Albany will work together to bring Kitware s expertise in building open source data analytics and visualization platforms with SUNY s expertise in data analytics on spatiotemporal and social media data streams

* Information listed above is at the time of submission. *

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