An artificially simulated outbreak of a respiratory infectious disease.

ABSTRACT: BACKGROUND:Outbreaks of respiratory infectious diseases often occur in crowded places. To understand the pattern of spread of an outbreak of a respiratory infectious disease and provide a theoretical basis for targeted implementation of scientific prevention and control, we attempted to establish a stochastic model to simulate an outbreak of a respiratory infectious disease at a military camp. This model fits the general pattern of disease transmission and further enriches theories on the transmission dynamics of infectious diseases. METHODS:We established an enclosed system of 500 people exposed to adenovirus type 7 (ADV 7) in a military camp. During the infection period, the patients transmitted the virus randomly to susceptible people. The spread of the epidemic under militarized management mode was simulated using a computer model named "the random collision model", and the effects of factors such as the basic reproductive number (R0), time of isolation of the patients (TOI), interval between onset and isolation (IOI), and immunization rates (IR) on the developmental trend of the epidemic were quantitatively analysed. RESULTS:Once the R0 exceeded 1.5, the median attack rate increased sharply; when R0?=?3, with a delay in the TOI, the attack rate increased gradually and eventually remained stable. When the IOI exceeded 2.3?days, the median attack rate also increased dramatically. When the IR exceeded 0.5, the median attack rate approached zero. The median generation time was 8.26?days, (95% confidence interval [CI]: 7.84-8.69?days). The partial rank correlation coefficients between the attack rate of the epidemic and R0, TOI, IOI, and IR were 0.61, 0.17, 0.45, and?-?0.27, respectively. CONCLUSIONS:The random collision model not only simulates how an epidemic spreads with superior precision but also allows greater flexibility in setting the activities of the exposure population and different types of infectious diseases, which is conducive to furthering exploration of the epidemiological characteristics of epidemic outbreaks.

SUBMITTER: Guo Z 

PROVIDER: S-EPMC6993344 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature