| ORIGINAL ARTICLE |
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| Year : 2019 | Volume
: 24
| Issue : 1 | Page : 67 |
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Comparison of methods to Estimate Basic Reproduction Number (R0) of influenza, Using Canada 2009 and 2017-18 A (H1N1) Data
Roya Nikbakht1, Mohammad Reza Baneshi2, Abbas Bahrampour2, Abolfazl Hosseinnataj2
1 HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Department of Biostatistics and Epidemiology, Faculty of Health Kerman, Iran
2 Department of Biostatistics and Epidemiology, Faculty of Health, Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
Correspondence Address:
Prof. Abbas Bahrampour
Department of Biostatistics and Epidemiology, Faculty of Health, Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman
Iran
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jrms.JRMS_888_18
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Background: The basic reproduction number (R0) has a key role in epidemics and can be utilized for preventing epidemics. In this study, different methods are used for estimating R0's and their vaccination coverage to find the formula with the best performance. Materials and Methods: We estimated R0for cumulative cases count data from April 18 to July 6, 2009 and 35-2017 to 34-2018 weeks in Canada: maximum likelihood (ML), exponential growth rate (EG), time-dependent reproduction numbers (TD), attack rate (AR), gamma-distributed generation time (GT), and the final size of the epidemic. Gamma distribution with mean and standard deviation 3.6 ± 1.4 is used as GT. Results: The AR method obtained a R0 (95% confidence interval [CI]) value of 1.116 (1.1163, 1.1165) and an EG (95%CI) value of 1.46 (1.41, 1.52). The R0(95%CI) estimate was 1.42 (1.27, 1.57) for the obtained ML, 1.71 (1.12, 2.03) for the obtained TD, 1.49 (1.0, 1.97) for the gamma-distributed GT, and 1.00 (0.91, 1.09) for the final size of the epidemic. The minimum and maximum vaccination coverage were related to AR and TD methods, respectively, where the TD method has minimum mean squared error (MSE). Finally, the R0(95%CI) for 2018 data was 1.52 (1.11, 1.94) by TD method, and vaccination coverage was estimated as 34.2%. Conclusion: For the purposes of our study, the estimation of TD was the most useful tool for computing the R0, because it has the minimum MSE. The estimation R0>1 indicating that the epidemic has occurred. Thus, it is required to vaccinate at least 41.5% to prevent and control the next epidemic.
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