Table 5.

Results of the ablation study in the three regions: Algorithm 1 with Poisson for f and identity for g, $t_{\mathrm{s}}=0$, $t_{\mathrm{i}}=5$, $t_{\mathrm{c}}=84$, $t_{\mathrm{e}}=108$ and $h=1$. We denote by wo: situation in the test period without the indicated variable and w: situation in the test period with all the explanatory variables. Ratios of wo/w are reported. Note that, for the metrics such as RMSE, MASE and MARE, a ratio lower than 1 implies that the result is good without the indicated variable. A ratio of $R_{\mathrm{COR}}^2$ higher than 1 indicates adding the variable improves the forecasts. We denote by Mcp: Malaria cases in the past.

	Variable	RMSE wo/w	MASE wo/w	MARE wo/w	${\mathit{R}}_{\mathbf{COR}}^2$ wo/w
Dakar	Mcp	1.5	1.74	2.04	0.82
	Rainfall	0.83	1.06	1.27	0.75
	Temperature	1.05	1.07	1.11	0.98
	Humidity	1.04	1.05	1.25	0.98
Fatick	Mcp	1.48	1.63	1.58	1.11
	Rainfall	0.94	0.95	1.06	0.93
	Temperature	0.96	0.98	0.96	1.01
	Humidity	0.92	1.05	1.3	0.98
Kedougou	Mcp	1.5	1.64	1.25	1.21
	Rainfall	1	0.99	0.92	1.01
	Temperature	1.02	1.02	0.92	0.97
	Humidity	1.01	1.03	1.14	0.98