Using Routine Surveillance Data to Estimate the Epidemic Potential of Emerging Zoonoses: Application to the Emergence of US Swine Origin Influenza A H3N2v Virus

Cauchemez, Simon; Epperson, Scott; Biggerstaff, Matthew; Swerdlow, David; Finelli, Lyn; Ferguson, Neil M.

If the source of infection is unknown for a subset of cases, different options are available. If data are believed to be missing at random, these cases can simply be excluded from the analysis. However, it is possible that certain sources of infection are more likely to generate missing data. In such a scenario, upper bounds for R can be obtained by assuming that all cases with missing data were due to human-to-human transmission and lower bounds by assuming the reverse. If human-to-human cases are prone to be classified as reservoir-to-human transmission, R may be underestimated. If the source of infection is uncertain, the analysis of detailed outbreak data [11, 24] might allow estimation of the probability that the case was infected by the reservoir, which could then be used to estimate F and R using our methods. Phylogenetic analysis might also help resolve uncertainties about the source of infection. Clearly, our approach will start to break down if the proportion of cases with missing data becomes too large or if the classification of cases is too unreliable. We note that other methods, for instance based on contact tracing, would also struggle in these situations.