Quantifying uncertainty about future antimicrobial resistance with structured expert judgment

Research output: Contribution to conferenceAbstract

Abstract

Antibiotic resistance is a major global concern. Although many countries collect resistance surveillance data, the large number of factors that influence the emergence and spread of resistance makes it extremely difficult to translate historical data into future predictions. To bridge the gap between existing surveillance data and the needs of decision makers, we use Cooke’s classical model of structured expert judgment to quantify uncertainty about future resistance rates for select pathogen-antibiotic pairs in several European countries.
Original languageEnglish
Number of pages1
Publication statusPublished - 28 Jul 2017
EventINFORMS Healthcare 2017 - Rotterdam, Netherlands
Duration: 26 Jul 201728 Jul 2017
http://meetings2.informs.org/wordpress/healthcare2017/

Conference

ConferenceINFORMS Healthcare 2017
CountryNetherlands
CityRotterdam
Period26/07/1728/07/17
Internet address

Keywords

  • antibiotic resistance
  • resistance surveillance data
  • future resistance rates

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    Research Output

    Quantifying uncertainty about future antimicrobial resistance: comparing structured expert judgment and statistical forecasting methods

    Colson, A. R., Megiddo, I., Alvarez-Uria, G., Gandra, S., Bedford, T., Morton, A., Cooke, R. M. & Laxminarayan, R., 5 Jul 2019, In : PLOS One. 14, 7, p. e0219190 18 p., e0219190.

    Research output: Contribution to journalArticle

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    Cite this

    Colson, A. (2017). Quantifying uncertainty about future antimicrobial resistance with structured expert judgment. Abstract from INFORMS Healthcare 2017, Rotterdam, Netherlands.