The time required to estimate the case fatality ratio of influenza using only the tip of an iceberg: joint estimation of the virulence and the transmission potential.
Estimating the case fatality ratio (CFR) of a novel strain of influenza virus during the early stage of the pandemic is one of key epidemiological tasks to be conducted as rapid research response. Past experience during the epidemics of severe acute respiratory syndrome (SARS) and influenza A (H1N1-2009) posed several technical challenges in estimating the CFR in real time. The present study aimed to develop a simple method to estimate the CFR based on readily available datasets, that is, confirmed cases and deaths, while addressing some of the known technical issues. To assess the reliability and validity of the proposed method, we examined the minimum length of time required for the assigned CFR to be included within the 95% confidence intervals and for the estimated CFR to be below a prespecified cut-off value by means of Monte Carlo simulations. Overall, the smaller the transmission potential was, the longer it took to compare the estimated CFR against the cut-off value. If policymaking and public health response have to be made based on the CFR estimate derived from the proposed method and readily available data, it should be noted that the successful estimation may take longer than a few months.
Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan.
Keisuke
K
Ejima
Ryosuke
R
Omori
Benjamin J
BJ
Cowling
Kazuyuki
K
Aihara
Hiroshi
H
Nishiura
D021821:Communicable Diseases, Emerging / Q000401:mortality / Q000635:transmission; D003198:Computer Simulation; D006801:Humans; D007251:Influenza, Human / Q000401:mortality* / Q000635:transmission* / Q000821:virology; D016013:Likelihood Functions; D008954:Models, Biological; D009010:Monte Carlo Method; D009026:Mortality; D009975:Orthomyxoviridae / Q000472:pathogenicity; D058873:Pandemics / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D013997:Time Factors; D014774:Virulence