The application of a systematic-dynamic model to study the computer simulation of severe acute respiratory syndrome transmission and the impact of control measures.
- Author:
Zhe-chun ZENG
1
;
Dong ZHAO
;
Yan LI
;
Qiang GUO
;
Peng SHI
;
Zhe LI
;
Hui-jun YIN
;
Yang LI
Author Information
- Publication Type:Journal Article
- MeSH: China; epidemiology; Computer Simulation; Disease Outbreaks; statistics & numerical data; Epidemiologic Methods; Humans; Models, Biological; Severe Acute Respiratory Syndrome; epidemiology; therapy; transmission
- From: Chinese Journal of Epidemiology 2005;26(3):159-163
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE(1) Building a macroscopical systematic-dynamic model of severe acute respiratory syndrome (SARS) transmission and disease control process. (2) To determine key variables on the control of SARS epidemic through computer simulation methodology, especially to analyze the effect of "screening for fever" practice during the epidemics. (3) To provide evidence for related decision-making.
METHODSParameters in the model were collected from local hospitals and municapal CDC through interview, questionnaire survey, literature review and case analysis. A systematic-dynamic model was built under similar studies. 'What-if' analysis was used during the simulation process.
RESULTS(1) The mean duration between disease onset and hospital admission, rate of contacts of each infectious individual as well as the rate of contacts in hospital of each infectious individual appeared to be the key variables in the process of SARS transmission. (2) Physician's alertness/sense and practice of self-protection on SARS, measures on quarantine and isolation to the patients, ventilation and disinfection process in the wards appeared to be the key variables for the control of epidemics. (3) "Screening for fever" practice on each patient at the entrance of the hospital did not seem to act as an important factor to the control of the epidemics.
CONCLUSIONThe health system in Beijing can control SARS epidemic rapidly based on current applied disease control measures and plan.