The Domestic and International Impacts of the 2009-H1N1 Influenza A Pandemic Global Challenges, Global Solutions: Workshop Summary (2010) / Chapter Skim
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A6 Estimation of the Reproductive Number and the Serial Interval in Early Phase of the 2009 Influenza AH1N1 Pandemic in the USA
A6 Estimation of the Reproductive Number and the Serial Interval in Early Phase of the 2009 Influenza AH1N1 Pandemic in the USA
Pages 191-207
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From page 191... ...
Virus Investigation Team, 2009) , a number of uncertainties remain about the severity of this virus on a per-case basis; moreover, higher-than normal attack rates expected from an antigenically novel virus may lead to substantial population-level severe morbidity and mortality even if the case-fatality ratio remains low (Lipsitch et al., 2009)
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From page 192... ...
Estimates of these quantities characterize the rates of epidemic growth and inform recommendations for control measures; ongoing estimates of the reproductive number as control measures are introduced can be used to estimate the impact of control measures. Previous modeling work has stated that a reproductive number exceeding two for influenza would make it unlikely that even stringent control measures could halt the growth of an influenza pandemic (Hallroan et al., 2008)
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From page 193... ...
. This method is well suited for estimation of the basic reproductive number, R0, and the serial interval in real time with observed aggregated daily counts of new cases, denoted by N = {N0, N1,…, NT}, where T is the last day of observation and N0 are the initial number of seed cases that begin the outbreak.
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From page 194... ...
We only consider Mt such that the augmented data represents no more than 95% of the imputed reported value. Adjustment for changes in reporting fraction Further, we report on the impact of changes in reporting.
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From page 195... ...
Figure A6-1 R01627 an increase in the rate of ascertainment, i.e., the average severity of infections was uneditable bitmapped image not decreasing. Rather, the proportion of cases being ascertained was increasing text replaced with more mild cases being ascertained.
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From page 196... ...
. Interquartile ranges for the estimates were obtained by using a parametric bootstrap; 1000 simulated datasets were generated using the parameter estimates and constrained to have a total epidemic size within 2% of the actual epidemic size.
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From page 197... ...
On the basis of these results, we set k to four since the log likelihood values for the varying values of k are nearly indistinguishable and in all cases the major mass (on average 88% for the original data and 93% for the augmented data) of the serial interval lies in the first 3 days.
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From page 198... ...
We further A6-3 in the final pane of Figure A6-4 the dependence between the estimates. R01627 from simulated outbreaks, we Using data estimate the bivariate density of the basic reproductive number and the mean of uneditable bitmapped image the serial interval using a bivariate kernel density estimator.
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From page 199... ...
Italicized results reflect results accounting for an 11% per day increase in reporting fraction starting April 13.
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are all shown using data with onset date no later than the value in the x-axis. Augmented data estimates are not shown after April 30, 2009 since less than 5% of the data is original data.
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From page 201... ...
from maximum likelihood estimation, though slightly higher than the estimated mean serial interval. This suggests that the estimated values for serial intervals are based on regularities in deviations from the trend in the epidemiological curve.
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These estimates were similarly sensitive to assumptions on the initial reporting fraction and its rate of change starting April 13. For values of the initial reporting fraction from 0.01 to 0.20 for the imputed data on April 27, the estimate of R0 will range between 3.03 and 2.70 for the Cowling serial interval and 2.03 and 1.81 for the Fraser serial interval.
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From page 203... ...
1.87 (1.85, 2.08) Num cases Original data 275 392 529 681 Imputed data 282 435 689 940 Augmented data 295.0 471.3 786.3 1130.6 Italicized results reflect results accounting for an 11% per day increase in reporting fraction starting April 13.
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From page 204... ...
In all analyses of such data, the statistical confidence intervals obtained should not be interpreted as measuring all of the uncertainty in estimates; additional uncertainty comes from unmeasured changes in reporting. We have also noted the impact of the assumed reporting distribution on the estimates with a sensitivity analysis.
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From page 205... ...
. It is clear that more precise estimates of the serial interval in various contexts for this virus are essential to reduce the uncertainty of estimates of the reproductive number; similarly, it is essential to estimate growth rates in a variety of contexts where reporting fractions can be better understood, possibly at local levels where a single reporting system is used.
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Proc Natl Acad Sci USA 2008; 105(12)
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APPENDIX A 207 Surveillance Group for New Influenza A (H1N1) Virus Investigation and Control in Spain.
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