A Generalized Chain Binomial Model with Aggregated Data

In large cohort studies it can be impractical to report individual data that only summary or aggregated data are available. Using aggregated data from Bernoulli trials is expected to result in overdispersion so that a quasi-binomial approach would seem feasible. We show that when applied to aggregated data arising from cohorts of individuals according to a chain binomial model, the quasi-binomial model results in biased estimates. We propose an alternate calibration estimator and demonstrate its improved performance by simulations. The calibration method is then applied to model the probability of leaving a personal emergency link service in Hong Kong.     

Reconstruction of the Infection Curve for SARS Epidemic in Beijing,China Using a Back-Projection Method

The infection curve of Severe Acute Respiratory Syndrome (SARS) using the back-projection method was reconstructed for the SARS outbreak period (from March 1, 2003 to June 20, 2003) in Beijing to assess the effectiveness of the intervention measures. There were 2,521 confirmed SARS cases with a population size of 13 million. The SARS outbreak pattern corresponded well with the major events timeline over the SARS outbreak. Despite the limited resources with such a large population size, the intervention measures taken by the Beijing Municipal Government seemed to be effective in containing the SARS epidemic in Beijing.