Improving early epidemiological assessment of emerging Aedes-transmitted epidemics using historical data

Julien Riou; Chiara Poletto; Pierre-Yves Boëlle

Epidemiological parameters and predictive distribution of future incidence The posterior distributions of the parameters built up dierently as data accrued for R 0,Z and ρ Z . For all three choices of prior distributions, the posterior distributions of R 0,Z quickly overlaid after a few points of incidence data were observed (Fig. 5A) . In sharp contrast, the posterior distributions of ρ Z could remain aected by the choice of prior distributions (Fig. 5B) . In Martinique and Saint-Martin, ρ Z remained essentially unidentied with the NI priors for the entire duration of the epidemic, with 95% credible intervals ranging approximately from 20 to 80%, even though the posterior mean was close to the estimates obtained with the more informative priors (around 25% at the end). Informative priors allowed for a more precise estimation of ρ Z , and this remained the 6 . CC-BY-NC 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder.