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The perfect storm of information: combining traditional and non-traditional data sources for public health situational awareness during hurricane response.
Bennett, Kelly J; Olsen, Jennifer M; Harris, Sara; Mekaru, Sumiko; Livinski, Alicia A; Brownstein, John S.
Afiliação
  • Bennett KJ; Office of Emergency Management, Division of Fusion, U.S. Department of Health and Human Services, Washington, DC, USA.
  • Olsen JM; Office of Emergency Management, U.S. Department of Health and Human Services, Washington, DC, USA.
  • Harris S; Office of Emergency Management, Division of Fusion, U.S. Department of Health and Human Services, Washington, DC, USA.
  • Mekaru S; Boston Children's Hospital, Emergency Medicine, Boston, MA, USA.
  • Livinski AA; Office of Administration, National Institutes of Health, Division of Library Services, Bethesda, MD, USA.
  • Brownstein JS; Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
PLoS Curr ; 52013 12 16.
Article em En | MEDLINE | ID: mdl-24459610
BACKGROUND: Hurricane Isaac made landfall in southeastern Louisiana in late August 2012, resulting in extensive storm surge and inland flooding. As the lead federal agency responsible for medical and public health response and recovery coordination, the Department of Health and Human Services (HHS) must have situational awareness to prepare for and address state and local requests for assistance following hurricanes. Both traditional and non-traditional data have been used to improve situational awareness in fields like disease surveillance and seismology. This study investigated whether non-traditional data (i.e., tweets and news reports) fill a void in traditional data reporting during hurricane response, as well as whether non-traditional data improve the timeliness for reporting identified HHS Essential Elements of Information (EEI). METHODS: HHS EEIs provided the information collection guidance, and when the information indicated there was a potential public health threat, an event was identified and categorized within the larger scope of overall Hurricane Issac situational awareness. Tweets, news reports, press releases, and federal situation reports during Hurricane Isaac response were analyzed for information about EEIs. Data that pertained to the same EEI were linked together and given a unique event identification number to enable more detailed analysis of source content. Reports of sixteen unique events were examined for types of data sources reporting on the event and timeliness of the reports. RESULTS: Of these sixteen unique events identified, six were reported by only a single data source, four were reported by two data sources, four were reported by three data sources, and two were reported by four or more data sources. For five of the events where news tweets were one of multiple sources of information about an event, the tweet occurred prior to the news report, press release, local government\emergency management tweet, and federal situation report. In all circumstances where citizens were reporting along with other sources, the citizen tweet was the earliest notification of the event. CONCLUSION: Critical information is being shared by citizens, news organizations, and local government representatives. To have situational awareness for providing timely, life-saving public health and medical response following a hurricane, this study shows that non-traditional data sources should augment traditional data sources and can fill some of the gaps in traditional reporting. During a hurricane response where early event detection can save lives and reduce morbidity, tweets can provide a source of information for early warning. In times of limited budgets, investing technical and personnel resources to efficiently and effectively gather, curate, and analyze non-traditional data for improved situational awareness can yield a high return on investment.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2013 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2013 Tipo de documento: Article