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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.
|Number of pages||1|
|Publication status||Published - 28 Jul 2017|
|Event||INFORMS Healthcare 2017 - Rotterdam, Netherlands|
Duration: 26 Jul 2017 → 28 Jul 2017
|Conference||INFORMS Healthcare 2017|
|Period||26/07/17 → 28/07/17|
- antibiotic resistance
- resistance surveillance data
- future resistance rates
Quantifying uncertainty about future antimicrobial resistance: comparing structured expert judgment and statistical forecasting methodsColson, 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 journal › Article › peer-reviewOpen AccessFile4 Citations (Scopus)4 Downloads (Pure)