Preliminary analysis of the transmission dynamics of nosocomial infections: stochastic and management effects.
A simple mathematical model is developed for the spread of hand-borne nosocomial pathogens such as Staphylococcus aureus within a general medical-surgical ward. In contrast to previous models a stochastic approach is used. Computer simulations are used to explore the properties of the model, and the...
| Main Authors: | , , |
|---|---|
| Format: | Journal article |
| Language: | English |
| Published: |
1999
|
| _version_ | 1826296015238463488 |
|---|---|
| author | Cooper, B Medley, G Scott, G |
| author_facet | Cooper, B Medley, G Scott, G |
| author_sort | Cooper, B |
| collection | OXFORD |
| description | A simple mathematical model is developed for the spread of hand-borne nosocomial pathogens such as Staphylococcus aureus within a general medical-surgical ward. In contrast to previous models a stochastic approach is used. Computer simulations are used to explore the properties of the model, and the results are presented in terms of the pathogen's successful introduction rate, ward-level prevalence, and colonized patient-days, emphasizing the general effects of changes in management of patients and carers. Small changes in the transmissibility of the organism resulted in large changes in all three measures. Even small increases in the frequency of effective handwashes were enough to bring endemic organisms under control. Reducing the number of colonized patients admitted to the ward was also an effective control measure across a wide range of different situations. Increasing surveillance activities had little effect on the successful introduction rate but gave an almost linear reduction in colonized patient-days and ward-level prevalence. Shorter lengths of patient stay were accompanied by higher successful introduction rates, but had little effect on the other measures unless the mean time before detection of a colonized individual was large compared to the mean length of stay. We conclude that chance effects are likely to be amongst the most important factors in determining the course of an outbreak. Mathematical models can provide valuable insights into the non-linear interactions between a small number of processes, but for the very small populations found in hospital wards, a stochastic approach is essential. |
| first_indexed | 2024-03-07T04:09:51Z |
| format | Journal article |
| id | oxford-uuid:c77656f9-1d74-498c-9b4d-f1d06976a0e3 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:09:51Z |
| publishDate | 1999 |
| record_format | dspace |
| spelling | oxford-uuid:c77656f9-1d74-498c-9b4d-f1d06976a0e32022-03-27T06:45:09ZPreliminary analysis of the transmission dynamics of nosocomial infections: stochastic and management effects.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:c77656f9-1d74-498c-9b4d-f1d06976a0e3EnglishSymplectic Elements at Oxford1999Cooper, BMedley, GScott, GA simple mathematical model is developed for the spread of hand-borne nosocomial pathogens such as Staphylococcus aureus within a general medical-surgical ward. In contrast to previous models a stochastic approach is used. Computer simulations are used to explore the properties of the model, and the results are presented in terms of the pathogen's successful introduction rate, ward-level prevalence, and colonized patient-days, emphasizing the general effects of changes in management of patients and carers. Small changes in the transmissibility of the organism resulted in large changes in all three measures. Even small increases in the frequency of effective handwashes were enough to bring endemic organisms under control. Reducing the number of colonized patients admitted to the ward was also an effective control measure across a wide range of different situations. Increasing surveillance activities had little effect on the successful introduction rate but gave an almost linear reduction in colonized patient-days and ward-level prevalence. Shorter lengths of patient stay were accompanied by higher successful introduction rates, but had little effect on the other measures unless the mean time before detection of a colonized individual was large compared to the mean length of stay. We conclude that chance effects are likely to be amongst the most important factors in determining the course of an outbreak. Mathematical models can provide valuable insights into the non-linear interactions between a small number of processes, but for the very small populations found in hospital wards, a stochastic approach is essential. |
| spellingShingle | Cooper, B Medley, G Scott, G Preliminary analysis of the transmission dynamics of nosocomial infections: stochastic and management effects. |
| title | Preliminary analysis of the transmission dynamics of nosocomial infections: stochastic and management effects. |
| title_full | Preliminary analysis of the transmission dynamics of nosocomial infections: stochastic and management effects. |
| title_fullStr | Preliminary analysis of the transmission dynamics of nosocomial infections: stochastic and management effects. |
| title_full_unstemmed | Preliminary analysis of the transmission dynamics of nosocomial infections: stochastic and management effects. |
| title_short | Preliminary analysis of the transmission dynamics of nosocomial infections: stochastic and management effects. |
| title_sort | preliminary analysis of the transmission dynamics of nosocomial infections stochastic and management effects |
| work_keys_str_mv | AT cooperb preliminaryanalysisofthetransmissiondynamicsofnosocomialinfectionsstochasticandmanagementeffects AT medleyg preliminaryanalysisofthetransmissiondynamicsofnosocomialinfectionsstochasticandmanagementeffects AT scottg preliminaryanalysisofthetransmissiondynamicsofnosocomialinfectionsstochasticandmanagementeffects |