Matches in SemOpenAlex for { <https://semopenalex.org/work/W69453199> ?p ?o ?g. }
Showing items 1 to 76 of
76
with 100 items per page.
- W69453199 abstract "The primary objective of this dissertation is to utilise, adapt and extend current stochastic models and statistical inference techniques to describe the transmission of nosocomial pathogens, i.e. hospital-acquired pathogens, and multiply-resistant organisms within the hospital setting. The emergence of higher levels of antibiotic resistance is threatening the long term viability of current treatment options and placing greater emphasis on the use of infection control procedures. The relative importance and value of various infection control practices is often debated and there is a lack of quantitative evidence concerning their effectiveness. The methods developed in this dissertation are applied to data of methicillin-resistant Staphylococcus aureus occurrence in intensive care units to quantify the effectiveness of infection control procedures.Analysis of infectious disease or carriage data is complicated by dependencies within the data and partial observation of the transmission process. Dependencies within the data are inherent because the risk of colonisation depends on the number of other colonised individuals. The colonisation times, chain and duration are often not visible to the human eye making only partial observation of the transmission process possible. Within a hospital setting, routine surveillance monitoring permits knowledge of interval-censored colonisation times. However, consideration needs to be given to the possibility of false negative outcomes when relying on observations from routine surveillance monitoring.SI (Susceptible, Infected) models are commonly used to describe community epidemic processes and allow for any inherent dependencies. Statistical inference techniques, such as the expectation-maximisation (EM) algorithm and Markov chainMonte Carlo (MCMC) can be used to estimate the model parameters when only partial observation of the epidemic process is possible. These methods appear well suited for the analysis of hospital infectious disease data but need to be adapted for short patient stays through migration. This thesis focuses on the use of Bayesian statistics to explore the posterior distributions of the unknown parameters. MCMC techniques are introduced to overcome analytical intractability caused by partial observation of the epidemic process. Statistical issues such as model adequacy and MCMC convergence assessment are discussed throughout the thesis.The new methodology allows the quantification of the relative importance of different transmission routes and the benefits of hospital practices, in terms of changed transmission rates. Evidence-based decisions can therefore be made on the impact of infection control procedures which is otherwise difficult on the basis of clinical studies alone.The methods are applied to data describing the occurrence of methicillin-resistantStaphylococcus aureus within intensive care units in hospitals in Brisbane and London" @default.
- W69453199 created "2016-06-24" @default.
- W69453199 creator A5066837176 @default.
- W69453199 date "2006-01-01" @default.
- W69453199 modified "2023-09-26" @default.
- W69453199 title "Epidemic models and inference for the transmission of hospital pathogens" @default.
- W69453199 hasPublicationYear "2006" @default.
- W69453199 type Work @default.
- W69453199 sameAs 69453199 @default.
- W69453199 citedByCount "1" @default.
- W69453199 countsByYear W694531992017 @default.
- W69453199 crossrefType "dissertation" @default.
- W69453199 hasAuthorship W69453199A5066837176 @default.
- W69453199 hasConcept C105795698 @default.
- W69453199 hasConcept C105878827 @default.
- W69453199 hasConcept C107673813 @default.
- W69453199 hasConcept C111350023 @default.
- W69453199 hasConcept C134261354 @default.
- W69453199 hasConcept C142724271 @default.
- W69453199 hasConcept C154945302 @default.
- W69453199 hasConcept C177713679 @default.
- W69453199 hasConcept C18903297 @default.
- W69453199 hasConcept C2776214188 @default.
- W69453199 hasConcept C2776927270 @default.
- W69453199 hasConcept C32762888 @default.
- W69453199 hasConcept C33923547 @default.
- W69453199 hasConcept C41008148 @default.
- W69453199 hasConcept C71924100 @default.
- W69453199 hasConcept C761482 @default.
- W69453199 hasConcept C76155785 @default.
- W69453199 hasConcept C86803240 @default.
- W69453199 hasConceptScore W69453199C105795698 @default.
- W69453199 hasConceptScore W69453199C105878827 @default.
- W69453199 hasConceptScore W69453199C107673813 @default.
- W69453199 hasConceptScore W69453199C111350023 @default.
- W69453199 hasConceptScore W69453199C134261354 @default.
- W69453199 hasConceptScore W69453199C142724271 @default.
- W69453199 hasConceptScore W69453199C154945302 @default.
- W69453199 hasConceptScore W69453199C177713679 @default.
- W69453199 hasConceptScore W69453199C18903297 @default.
- W69453199 hasConceptScore W69453199C2776214188 @default.
- W69453199 hasConceptScore W69453199C2776927270 @default.
- W69453199 hasConceptScore W69453199C32762888 @default.
- W69453199 hasConceptScore W69453199C33923547 @default.
- W69453199 hasConceptScore W69453199C41008148 @default.
- W69453199 hasConceptScore W69453199C71924100 @default.
- W69453199 hasConceptScore W69453199C761482 @default.
- W69453199 hasConceptScore W69453199C76155785 @default.
- W69453199 hasConceptScore W69453199C86803240 @default.
- W69453199 hasLocation W694531991 @default.
- W69453199 hasOpenAccess W69453199 @default.
- W69453199 hasPrimaryLocation W694531991 @default.
- W69453199 hasRelatedWork W1539377941 @default.
- W69453199 hasRelatedWork W1988035959 @default.
- W69453199 hasRelatedWork W2041447018 @default.
- W69453199 hasRelatedWork W2074460695 @default.
- W69453199 hasRelatedWork W2083073018 @default.
- W69453199 hasRelatedWork W2091774697 @default.
- W69453199 hasRelatedWork W2094562211 @default.
- W69453199 hasRelatedWork W2099350238 @default.
- W69453199 hasRelatedWork W2115496122 @default.
- W69453199 hasRelatedWork W2137863132 @default.
- W69453199 hasRelatedWork W2166343608 @default.
- W69453199 hasRelatedWork W2169863249 @default.
- W69453199 hasRelatedWork W2170607453 @default.
- W69453199 hasRelatedWork W2239032868 @default.
- W69453199 hasRelatedWork W2335791412 @default.
- W69453199 hasRelatedWork W2680495019 @default.
- W69453199 hasRelatedWork W3038528628 @default.
- W69453199 hasRelatedWork W3103563800 @default.
- W69453199 hasRelatedWork W3107180722 @default.
- W69453199 hasRelatedWork W877723530 @default.
- W69453199 isParatext "false" @default.
- W69453199 isRetracted "false" @default.
- W69453199 magId "69453199" @default.
- W69453199 workType "dissertation" @default.