We afforded our framework the flexibility to achieve this by designing it as a sequence of five steps, with alternative assumptions possible at each step. To address this objective, we first developed a new framework for modeling the burden of yellow fever that was conducive to exploring alternative assumptions about the two issues of primary interest.
Combined with estimates that most infections go unreported (range of 95% credible intervals, 99.65 to 99.99%), our results suggest that yellow fever’s burden will remain highly uncertain without major improvements in surveillance. Even so, statistical uncertainty was even greater than uncertainty due to modeling assumptions, accounting for a total of 87% of variance in burden estimates.
#Eye of the beholder 3 version 1.0 driver#
Uncertainty about the vaccination status of serological study participants was the primary driver of this uncertainty. We found that alternative interpretations of serological data resulted in a nearly 20-fold difference in burden estimates (range of central estimates, 8.4 × 10 4 to 1.5 × 10 6 deaths in 2021–2030).
We developed a framework for estimating the burden of yellow fever in Africa and evaluated its sensitivity to modeling assumptions that are often overlooked. These estimates involve numerous modeling assumptions, whose uncertainties are not always well described. Estimates of disease burden are important for setting public health priorities.
0 kommentar(er)
