Literature DB >> 14667012

Conceptual foundations for infectious disease surveillance.

Mark C Thurmond1.   

Abstract

The purpose of this report is to offer concepts for consideration in developing infectious disease surveillance systems, defined here as active, formal, and systematic processes intentionally directed to rapidly seek out and identify infectious disease agents or disease. Performance of surveillance systems can be judged by their accuracy (sensitivity and specificity), precision (repeatability), timeliness, multiple utility, and value. Surveillance system operation and function necessary to achieve high performance are defined in part by characteristics of the specific infectious disease, including disease transition state dynamics, that define probabilities of being in the latent, infectious, or clinical phase of disease. Two key components of surveillance are the sampling scheme, which is intended to maximize the probability of capturing an infected animal or specimen as soon as possible after the herd has been exposed, and the diagnostic assays, which should maximize the probability of detecting the agent, or evidence of the agent, if it is present in the specimen, while minimizing the likelihood of a false-positive result. Proportional risk sampling, targeted sampling, and repeated sampling are strategies that can improve overall surveillance system accuracy and particularly the temporal sensitivity related to early detection. Hierarchical sampling schemes and multiplexed assays can maximize efficiency and improve utility by serving multiple surveillance systems and purposes. Development of the surveillance systems needed to address emerging and foreign animal diseases will necessarily require design and architecture that are highly probability-driven to maximize surveillance sensitivity and specificity and to minimize cost.

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Year:  2003        PMID: 14667012     DOI: 10.1177/104063870301500601

Source DB:  PubMed          Journal:  J Vet Diagn Invest        ISSN: 1040-6387            Impact factor:   1.279


  13 in total

1.  Bayesian spatiotemporal analysis of foot-and-mouth disease data from the Republic of Turkey.

Authors:  A J Branscum; A M Perez; W O Johnson; M C Thurmond
Journal:  Epidemiol Infect       Date:  2007-07-05       Impact factor: 2.451

Review 2.  Systematic review of surveillance systems and methods for early detection of exotic, new and re-emerging diseases in animal populations.

Authors:  V Rodríguez-Prieto; M Vicente-Rubiano; A Sánchez-Matamoros; C Rubio-Guerri; M Melero; B Martínez-López; M Martínez-Avilés; L Hoinville; T Vergne; A Comin; B Schauer; F Dórea; D U Pfeiffer; J M Sánchez-Vizcaíno
Journal:  Epidemiol Infect       Date:  2014-09-12       Impact factor: 4.434

3.  Concepts for risk-based surveillance in the field of veterinary medicine and veterinary public health: review of current approaches.

Authors:  Katharina D C Stärk; Gertraud Regula; Jorge Hernandez; Lea Knopf; Klemens Fuchs; Roger S Morris; Peter Davies
Journal:  BMC Health Serv Res       Date:  2006-02-28       Impact factor: 2.655

4.  Evaluation of temporal surveillance system sensitivity and freedom from bovine viral diarrhea in Danish dairy herds using scenario tree modelling.

Authors:  Alessandro Foddai; Anders Stockmarr; Anette Boklund
Journal:  BMC Vet Res       Date:  2016-06-21       Impact factor: 2.741

5.  Low-pathogenic notifiable avian influenza serosurveillance and the risk of infection in poultry - a critical review of the European Union active surveillance programme (2005-2007).

Authors:  J L Gonzales; A R W Elbers; A Bouma; G Koch; J J de Wit; J A Stegeman
Journal:  Influenza Other Respir Viruses       Date:  2010-03       Impact factor: 4.380

6.  Comparison of Alternative Meat Inspection Regimes for Pigs From Non-Controlled Housing - Considering the Cost of Error.

Authors:  Rikke Koch Hansen; Lisbeth Harm Nielsen; Mahmoud El Tholth; Barbara Haesler; Alessandro Foddai; Lis Alban
Journal:  Front Vet Sci       Date:  2018-06-05

7.  Sepsis surveillance from administrative data in the absence of a perfect verification.

Authors:  S Reza Jafarzadeh; Benjamin S Thomas; Jeff Gill; Victoria J Fraser; Jonas Marschall; David K Warren
Journal:  Ann Epidemiol       Date:  2016-08-20       Impact factor: 3.797

8.  Using mixed methods to investigate factors influencing reporting of livestock diseases: a case study among smallholders in Bolivia.

Authors:  Georgina Limon; Elisa G Lewis; Yu-Mei Chang; Hugo Ruiz; Maria Elba Balanza; Javier Guitian
Journal:  Prev Vet Med       Date:  2013-11-16       Impact factor: 2.670

9.  Surveillance for emerging biodiversity diseases of wildlife.

Authors:  Laura F Grogan; Lee Berger; Karrie Rose; Victoria Grillo; Scott D Cashins; Lee F Skerratt
Journal:  PLoS Pathog       Date:  2014-05-29       Impact factor: 6.823

10.  Challenges in Identifying and Determining the Impacts of Infection with Pestiviruses on the Herd Health of Free Ranging Cervid Populations.

Authors:  Julia F Ridpath; John D Neill
Journal:  Front Microbiol       Date:  2016-06-17       Impact factor: 5.640

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