AN ANALYSIS OF INFECTIOUS DISEASE SPREAD AND PREVENTION BASED ON MICROSCOPIC STRUCTURE OF SCHOOL POPULATION: ‘BACK MONTE CARLO' DATA APPROACH
Method: The daily reported data of cases of swine flu and the dates of closure in each class of schools collected from September 2009 to March 2010 in a city in Japan were analyzed based on stochastic mathematical model of infectious disease spread considering each class as a unit. Totally 21,253 cases were reported out of 51,871 students in 134 schools (elementary schools, junior high schools, high schools and kindergartens). To construct accurate model, infected numbers must be estimated from case report data taking latent period into account, which is deterministically impossible. To resolve this difficulty, we stochastically estimated and obtained data of infected numbers by ‘Back Monte Carlo’ calculation and used in the analysis. The analysis was mainly carried out using data during September up to December to avoid the influence of vacations.
Result: The rates of transmission within class were calculated by maximum likelihood method in addition to those within whole school and community (all schools). The rate within class was much larger (more than 10 times larger) than other rates. Among 2 to 5 day duration of school closure, the duration of 3 day seemed to be the best under most likely assumptions. Simulation of the model failed to reproduce very rapid spread of infection in the last ten days in October but such a rapid spread was reasonably attributable to a specific episode.
Conclusion: Back Monte Carlo data approach was found useful in determining most effective preventive strategy against infectious disease based on microscopic class based model of infectious disease spread in schools.