Algorithm 1: Forecasting Algorithm

Input: $t_{\mathrm{s}}$, $t_{\mathrm{i}}$, $t_{\mathrm{c}}$, $t_{\mathrm{e}}$ ← times of Section 2.3.1;               ℓ ← vector (Section 3.1);               h ← forecast horizon ($h\ge 1$);               $Y_{\mathrm{o}}$ ← observed malaria incidence (dependant variable);               $X=\left\{X_1,X_2,\dots ,X_k\right\}$ ← set of explanatory variables;               $f\leftarrow \mathrm{distribution}(\mathrm{Poisson}\mathrm{or}\mathrm{NB})$;               $g\leftarrow \mathrm{link}(\mathrm{identity},\log ,\mathrm{or}\mathrm{sqrt})$; Output: $\widehat{Y}$ ← the forecasted vector of malaria incidence;