A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic

Abstract Background In a new influenza pandemic, travel data such as arrival times of cases seeded by the originating country can be regarded as a combination of the epidemic size and the mobility networks of infections connecting the originating country with other regions. It can be a complete and...

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Bibliographic Details
Main Authors: Ka Chun Chong, Benny Chung Ying Zee, Maggie Haitian Wang
Format: Article
Language:English
Published: BMC 2017-02-01
Series:BMC Medical Research Methodology
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12874-017-0300-1
Description
Summary:Abstract Background In a new influenza pandemic, travel data such as arrival times of cases seeded by the originating country can be regarded as a combination of the epidemic size and the mobility networks of infections connecting the originating country with other regions. It can be a complete and timely source for estimating the basic reproduction number (R 0 ), a key indicator of disease transmissibility. Method In this study, we developed a likelihood-based method using arrival times of infected cases in different countries to estimate R 0 for influenza pandemics. A simulation was conducted to assess the performance of the proposed method. We further applied the method to the outbreak of the influenza pandemic A/H1N1 in Mexico. Results In the numerical application, the estimated R 0 was equal to 1.69 with a 95% confidence interval (1.65, 1.73). For the simulation results, the estimations were robust to the decline of travel rate and other parameter assumptions. Nevertheless, the estimates were moderately sensitive to the assumption of infectious duration. Generally, the findings were in line with other relevant studies. Conclusions Our approach as well as the estimate is potential to assist officials in planning control and prevention measures. Improved coordination to streamline or even centralize surveillance of imported cases among countries will thus be beneficial to public health.
ISSN:1471-2288