# 2018 Ebola outbreak in the DRC

What you see below are the results of fitting a stochastic *SEIR* model to the 2018 Ebola outbreak in the Democratic Republic of Congo. This interactive visualisation attempts to replicate the results by Cristian Althaus.

The model is defined by

where $\mathbf{x}=(S,E,I)$, and

Here, $\beta(t)=\beta e^{-k(t-\tau)}$ for $t>\tau$ and $\beta(t)=\beta$ otherwise. The parameters to estimate are the base transmission rate $\beta$ and its rate of decay $k$. The remaining parameters are given by $1/\sigma=9.31\,\text{days}$, $1/\gamma=7.41\,\text{days}$, and $\tau=28\,\text{days}$.

The estimation is done from the data for cumulative incidence corresponding to $N-S(t)$, where the population size is fixed at $N=10^6$, using the linear noise approximation as described in Zimmer and Sahle (2014) and Zimmer (2015). The likelihood function is handled by `sdeparams`

.

Forecast (shaded region) is shown for the mean plus/minus std of 50 stochastic simulations run for 30 days starting from the latest data-point for any given pair of parameters.

The code for the app is available in this Github repository.