Background: Mathematical infectious disease models available in literature, mostly take in their design that the parameters of basic reproduction number R 0 and interval serial S I as constant values during tracking the outbreak cases. In this report a new intelligent model called HH-COVID-19 is proposed, with simple design and adaptive parameters.Methods: e parameters R 0 and S I are adapted by adding three new weighting factors α, β and γ and two free parameters σ 1 and σ 2 in function of time t, thus the HH-COVID-19 become time-variant model. e parameters R 0 , S I , α, β, γ, σ 1 and σ 2 are estimated optimally based on a recent algorithm of arti cial intelligence (AI), inspired from nature called Harris Hawks Optimizer (HHO), using the data of the con rmed infected cases in Algeria country in the rst t = 55 days.Results: Parameters estimated optimally: R 0 = 1.341, S I = 5.991, α = 2.987, β = 1.566, γ = 4.998, σ 1 = −0.133 and σ 2 = 0.0324. R 0 starts on 1.341 and ends to 2.677, and S I starts on 5.991 and ends to 6.692. e estimated results are identically to the actual infected incidence in Algeria, HH-COVID-19 proved its superiority in comparison study. HH-COVID-19 predicts that in 1 May, the infected cases exceed 50 000, during May, to reach quickly the herd immunity stage at beginning of July.

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