FluDetWeb: an interactive web-based system for the early detection of the onset of influenza epidemics.

David Conesa, Antonio López-Quílez, Miguel Angel Martínez-Beneito, María Teresa Miralles, Francisco Verdejo
Author Information
  1. David Conesa: Departament d'Estadística i Investigació Operativa, Universitat de València, 46100 Burjassot, Valencia, Spain. david.v.conesa@uv.es

Abstract

BACKGROUND: The early identification of influenza outbreaks has became a priority in public health practice. A large variety of statistical algorithms for the automated monitoring of influenza surveillance have been proposed, but most of them require not only a lot of computational effort but also operation of sometimes not-so-friendly software.
RESULTS: In this paper, we introduce FluDetWeb, an implementation of a prospective influenza surveillance methodology based on a client-server architecture with a thin (web-based) client application design. Users can introduce and edit their own data consisting of a series of weekly influenza incidence rates. The system returns the probability of being in an epidemic phase (via e-mail if desired). When the probability is greater than 0.5, it also returns the probability of an increase in the incidence rate during the following week. The system also provides two complementary graphs. This system has been implemented using statistical free-software (R and WinBUGS), a web server environment for Java code (Tomcat) and a software module created by us (Rdp) responsible for managing internal tasks; the software package MySQL has been used to construct the database management system. The implementation is available on-line from: http://www.geeitema.org/meviepi/fludetweb/.
CONCLUSION: The ease of use of FluDetWeb and its on-line availability can make it a valuable tool for public health practitioners who want to obtain information about the probability that their system is in an epidemic phase. Moreover, the architecture described can also be useful for developers of systems based on computationally intensive methods.

References

  1. Pharmacoeconomics. 1999;16 Suppl 1:1-6 [PMID: 10623371]
  2. Public Health Rep. 1963 Jun;78(6):494-506 [PMID: 19316455]
  3. Int J Epidemiol. 2006 Oct;35(5):1314-21 [PMID: 16926216]
  4. Am J Epidemiol. 2003 Nov 15;158(10):996-1006 [PMID: 14607808]
  5. Eur J Epidemiol. 1999 May;15(5):467-73 [PMID: 10442473]
  6. Stat Med. 2008 Sep 30;27(22):4455-68 [PMID: 18618414]
  7. J Biomed Inform. 2008 Aug;41(4):544-56 [PMID: 18291726]
  8. Biom J. 2008 Feb;50(1):71-85 [PMID: 17849383]
  9. Am J Public Health. 1997 Dec;87(12):1944-50 [PMID: 9431281]
  10. Stat Med. 1999 Dec 30;18(24):3463-78 [PMID: 10611619]
  11. BMC Med Inform Decis Mak. 2007 Oct 15;7:29 [PMID: 17937786]
  12. J Biomed Inform. 2007 Aug;40(4):370-9 [PMID: 17095301]
  13. Ann Intern Med. 2004 Jun 1;140(11):910-22 [PMID: 15172906]

MeSH Term

Computer Systems
Disease Outbreaks
Humans
Influenza, Human
Internet
Population Surveillance
United States
User-Computer Interface

Word Cloud

Created with Highcharts 10.0.0systeminfluenzaalsoprobabilitysoftwarecanearlypublichealthstatisticalsurveillanceintroduceFluDetWebimplementationbasedarchitectureweb-basedincidencereturnsepidemicphaseon-lineBACKGROUND:identificationoutbreaksbecameprioritypracticelargevarietyalgorithmsautomatedmonitoringproposedrequirelotcomputationaleffortoperationsometimesnot-so-friendlyRESULTS:paperprospectivemethodologyclient-serverthinclientapplicationdesignUserseditdataconsistingseriesweeklyratesviae-maildesiredgreater05increaseratefollowingweekprovidestwocomplementarygraphsimplementedusingfree-softwareRWinBUGSwebserverenvironmentJavacodeTomcatmodulecreatedusRdpresponsiblemanaginginternaltaskspackageMySQLusedconstructdatabasemanagementavailablefrom:http://wwwgeeitemaorg/meviepi/fludetweb/CONCLUSION:easeuseavailabilitymakevaluabletoolpractitionerswantobtaininformationMoreoverdescribedusefuldeveloperssystemscomputationallyintensivemethodsFluDetWeb:interactivedetectiononsetepidemics

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