For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
32
views
52
references
 Top references
cited by
15
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      96
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Innovation in observation: a vision for early outbreak detection

      brief-report
      Author(s): 1 , 2
      Publication date (Electronic):
      Journal: Emerging Health Threats Journal
      Publisher: CoAction Publishing

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The emergence of new infections and resurgence of old ones—health threats stemming from environmental contamination or purposeful acts of bioterrorism—call for a worldwide effort in improving early outbreak detection, with the goal of ameliorating current and future risks. In some cases, the problem of outbreak detection is logistically straightforward and mathematically easy: a single case of a disease of great concern can constitute an outbreak. However, for the vast majority of maladies, a simple analytical solution does not exist. Furthermore, each step in developing reliable, sensitive, effective surveillance systems demonstrates enormous complexities in the transmission, manifestation, detection, and control of emerging health threats. In this communication, we explore potential future innovations in early outbreak detection systems that can overcome the pitfalls of current surveillance. We believe that modern advances in assembling data, techniques for collating and processing information, and technology that enables integrated analysis will facilitate a new paradigm in outbreak definition and detection. We anticipate that moving forward in this direction will provide the highly desired sensitivity and specificity in early detection required to meet the emerging challenges of global disease surveillance.

          Related collections

          Most cited references52

          • Record: found
          • Abstract: found
          • Article: not found

          Analysis of foodborne outbreak data reported internationally for source attribution.

          J.D. Greig, A Ravel (2009)
          Analysis of foodborne outbreak data is one approach to estimate the proportion of human cases of specific enteric diseases attributable to a specific food item (food attribution). Although we recognize that for a variety of reasons reported outbreaks represent only a small portion of all actual outbreaks, using outbreak data for food attribution is the only methodological approach where, theoretically, there is an actual direct link between the pathogen, its source and each infected person. The purpose of this study was to explore the usefulness of foodborne outbreak data extracted from publicly available international electronic reports and publications to provide estimates of food attribution, to derive and compare these estimates between regions, while improving the understanding of the pathogen/food vehicle combination. Electronic reports and publications of foodborne outbreaks that occurred globally since the 1980s were systematically scanned and their data were extracted and compiled in a database. A system of food categorization was developed and food vehicles assigned accordingly. The association between the aetiology and the food source was statistically described for outbreaks with both reported aetiology and incriminated food vehicle. Differences in associations between Australia and New Zealand, Canada, the European Union (EU) and the United States (US) were explored using multiple correspondence analysis and were formally tested between the EU and the US for selected pathogens and food sources. As a result, the food and aetiology cross tabulation of 4093 foodborne outbreaks that occurred globally between 1988 and 2007 is presented and discussed. For a few aetiologies and some foods the association is very specific. The lack of a specific association between the other foods and aetiologies highlights the potential roles of cross-contamination, environmental contamination and the role of the infected foodhandler along the food chain from farm to fork. Detailed analysis of the four regions highlighted some specific associations: Salmonella Enteritidis outbreaks occurred relatively often in the EU states with eggs as the most common source; Campylobacter associated outbreaks were mainly related to poultry products in the EU and to dairy products in the US; there was an association between Escherichia coli outbreaks and beef in Canada; and while Salmonella Typhiumurium outbreaks were relatively common in Australia and New Zealand, across all regions, Salmonella was associated with a variety of food groups. The value and limitations of the study are discussed, as well as the extrapolation of the food attribution estimates beyond their outbreak context.
          Article 0 comments Cited 99 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Seasonality in six enterically transmitted diseases and ambient temperature.

            A. DeMaria, Jyotsna S. Jagai, E S Naumova … (2007)
            We propose an analytical and conceptual framework for a systematic and comprehensive assessment of disease seasonality to detect changes and to quantify and compare temporal patterns. To demonstrate the proposed technique, we examined seasonal patterns of six enterically transmitted reportable diseases (EDs) in Massachusetts collected over a 10-year period (1992-2001). We quantified the timing and intensity of seasonal peaks of ED incidence and examined the synchronization in timing of these peaks with respect to ambient temperature. All EDs, except hepatitis A, exhibited well-defined seasonal patterns which clustered into two groups. The peak in daily incidence of Campylobacter and Salmonella closely followed the peak in ambient temperature with the lag of 2-14 days. Cryptosporidium, Shigella, and Giardia exhibited significant delays relative to the peak in temperature (approximately 40 days, P<0.02). The proposed approach provides a detailed quantification of seasonality that enabled us to detect significant differences in the seasonal peaks of enteric infections which would have been lost in an analysis using monthly or weekly cumulative information. This highly relevant to disease surveillance approach can be used to generate and test hypotheses related to disease seasonality and potential routes of transmission with respect to environmental factors.
            Article 0 comments Cited 93 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Web Queries as a Source for Syndromic Surveillance

              Anette Hulth, Gustaf Rydevik, Annika Linde (2009)
              In the field of syndromic surveillance, various sources are exploited for outbreak detection, monitoring and prediction. This paper describes a study on queries submitted to a medical web site, with influenza as a case study. The hypothesis of the work was that queries on influenza and influenza-like illness would provide a basis for the estimation of the timing of the peak and the intensity of the yearly influenza outbreaks that would be as good as the existing laboratory and sentinel surveillance. We calculated the occurrence of various queries related to influenza from search logs submitted to a Swedish medical web site for two influenza seasons. These figures were subsequently used to generate two models, one to estimate the number of laboratory verified influenza cases and one to estimate the proportion of patients with influenza-like illness reported by selected General Practitioners in Sweden. We applied an approach designed for highly correlated data, partial least squares regression. In our work, we found that certain web queries on influenza follow the same pattern as that obtained by the two other surveillance systems for influenza epidemics, and that they have equal power for the estimation of the influenza burden in society. Web queries give a unique access to ill individuals who are not (yet) seeking care. This paper shows the potential of web queries as an accurate, cheap and labour extensive source for syndromic surveillance.
              Article 0 comments Cited 75 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (nlm-ta): Emerg Health Threats J
                Journal ID (iso-abbrev): Emerg Health Threats J
                Journal ID (publisher-id): EHTJ
                Title: Emerging Health Threats Journal
                Publisher: CoAction Publishing
                ISSN (Electronic): 1752-8550
                Publication date (Electronic): 20 May 2010
                Publication date Collection: 2010
                Volume: 3
                Electronic Location Identifier: e6
                Affiliations
                [1 ]Department of Ecology, Evolution and Natural Resources, Rutgers University, New Brunswick, NJ, USA
                [2 ]Department of Civil and Environmental Engineering, Tufts University School of Engineering, Medford, MA, USA
                Author notes
                Correspondence Dr EN Naumova, Department of Civil and Environmental Engineering, Tufts University School of Engineering, Medford, MA, 02155, USA. E-mail: elena.naumova@ 123456tufts.edu
                Article
                Publisher ID: EHTJ-3-e6
                DOI: 10.3134/ehtj.10.006
                PMC ID: 3167656
                PubMed ID: 22460396
                SO-VID: cb0d4312-31cb-4d32-90a7-7574b61cb3f3
                Copyright © © 2010 NH Fefferman and EN Naumova; licensee Emerging Health Threats Journal
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution Licence which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 03 February 2010
                Date revision received : 14 May 2010
                Date accepted : 20 May 2010
                Categories
                Subject: Perspectives

                ScienceOpen disciplines: Public health
                Data availability:
                ScienceOpen disciplines: Public health

                Comments

                Comment on this article

                scite_

                Similar content96

                See all similar

                Cited by13

                See all cited by

                Most referenced authors381

                See all reference authors