| A ale—9i. B._e_-—*a—« n—¥QL« ._ei' .—"§=4I;u ._e-_-fi:. ale—9i. ._eJ—' 'fi‘ n—ei' W n—Q'Zha deb. .—e—'_%‘ I481—c I—eic .—'fi. .—e—'_b n—W I—e—HE' | Thirdly, the framework produces easily interpretable probability distributions . |
| A ale—9i. B._e_-—*a—« n—¥QL« ._ei' .—"§=4I;u ._e-_-fi:. ale—9i. ._eJ—' 'fi‘ n—ei' W n—Q'Zha deb. .—e—'_%‘ I481—c I—eic .—'fi. .—e—'_b n—W I—e—HE' | We therefore argue that it is beneficial to communicate the aggregated and weighted result as easily interpretable probability distributions . |
| A ale—9i. B._e_-—*a—« n—¥QL« ._ei' .—"§=4I;u ._e-_-fi:. ale—9i. ._eJ—' 'fi‘ n—ei' W n—Q'Zha deb. .—e—'_%‘ I481—c I—eic .—'fi. .—e—'_b n—W I—e—HE' | The visual manner in which uncertainty is presented using probability distributions makes them easy to understand and communicate [62]. |
| Introduction | This approach is appealing because it provides probability distributions of quantities of interest, hence uncertainty about the projected outcomes may be provided to policy makers. |
| Multiple quantity analysis and simulated outbreaks | The multi-quantity analysis produces a probability distribution of all considered quantities, and Fig 7 further illustrates how the marginal posterior densities are located above zero for all three considered quantities. |