Author: Smirnova, Alexandra; Chowell, Gerardo
Title: A primer on stable parameter estimation and forecasting in epidemiology by a problem-oriented regularized least squares algorithm Document date: 2017_5_25
ID: 3fwla5ox_33
Snippet: In a similar manner, we estimated parameters and produced forecasts for the Ebola epidemics in Guinea (Fig. 4) and Liberia (Fig. 5) . Not surprisingly the model has most difficulties tracking the epidemic in Guinea due to its multi-mode nature (Fig. 4) . Since this outbreak is also the longest, we need more data (30 weeks) to forecast future incidence cases. On the other hand, the Liberia outbreak, which is 45 weeks total, can be projected from a.....
Document: In a similar manner, we estimated parameters and produced forecasts for the Ebola epidemics in Guinea (Fig. 4) and Liberia (Fig. 5) . Not surprisingly the model has most difficulties tracking the epidemic in Guinea due to its multi-mode nature (Fig. 4) . Since this outbreak is also the longest, we need more data (30 weeks) to forecast future incidence cases. On the other hand, the Liberia outbreak, which is 45 weeks total, can be projected from as little as 12 weeks of early data. This inverse modeling approach could be adapted to analyze outbreaks of other disease system, e.g., avian influenza, Middle East Respiratory Syndrome (MERS), and Zika. One could envision disease forecasts for an emerging outbreak in real time with updates every few weeks or so (depending on the disease system).
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