Author: Ni, Michael Y; Chan, Brandford H Y; Leung, Gabriel M; Lau, Eric H Y; Pang, Herbert
Title: Transmissibility of the Ice Bucket Challenge among globally influential celebrities: retrospective cohort study Document date: 2014_12_16
ID: pun1l9bt_8
Snippet: We used fully observed nomination chains to estimate the R0, a measure of transmissibility, for a celebrities based cohort, up to the fifth generation seeded from each index case (the first generation). R0 was estimated as the product of the mean number of nominations (n) and the probability of successful nomination (p), assuming a branching process in which each participant of the Ice Bucket Challenge generates a random number of next generation.....
Document: We used fully observed nomination chains to estimate the R0, a measure of transmissibility, for a celebrities based cohort, up to the fifth generation seeded from each index case (the first generation). R0 was estimated as the product of the mean number of nominations (n) and the probability of successful nomination (p), assuming a branching process in which each participant of the Ice Bucket Challenge generates a random number of next generation participants. To account for the fact that the challenge had already taken off in early August 2014,15 we excluded nominees in the calculation of p who had previously completed the challenge (that is, were “immune†from future participation) but included them in the calculation of n so that the estimated R0 would reflect the transmissibility in a fully “susceptible†population. We obtained 95% confidence intervals of the R0 estimate by bootstrap with 1000 replications. Mean serial interval was calculated by assuming at least a half day delay in accepting the challenge, based on all nominator-nominee pairs in our dataset. We used multivariable ordinal logistic regression to examine the association between number of successful nominations and personal factors (age, sex, occupation, and net worth) or popularity (number of likes on Facebook and number of followers on Twitter). To handle missing data we carried out sensitivity analysis with multiple imputation. All analyses were done using R version 3.0.2 and SAS university edition, 2014.
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