Nonlinear Incidence Functions

Nonlinear Incidence Functions is a mathematical model in population compartmental analysis that describes the rate of new infections in an epidemiological system as a nonlinear function of the number of susceptible and infected individuals, thereby capturing saturation effects, behavioral changes, or heterogeneous mixing patterns not accounted for by linear incidence assumptions.

140

Publications

8.2K

Citations

292

Authors

163

Institutions

Publications per year

2017–2026

59

Authors

292

  1. SD
    Salih Djilali

    Hassiba Benbouali University of Chlef, Algeria

    6 publications · 188 citations

    6

    h-index

  2. ZT
    Zhidong Teng

    Xinjiang University, China

    6 publications · 157 citations

    6

    h-index

  3. SB
    Soufiane Bentout

    Université de ain Témouchent, Algeria

    5 publications · 215 citations

    5

    h-index

  4. AK
    Abhishek Kumar

    Delhi Technological University, India

    4 publications · 101 citations

    4

    h-index

  5. AK
    Andrei Korobeinikov

    Centre de Recerca Matemàtica, Spain

    4 publications · 714 citations

    4

    h-index

1–5 of 292

Venues

  1. Applied Mathematics and Computation

    13 publications · 624 citations

    13

    h-index

  2. Chaos Solitons & Fractals

    9 publications · 282 citations

    9

    h-index

  3. Nonlinear Analysis Real World Applications

    7 publications · 560 citations

    7

    h-index

  4. Mathematical Methods in the Applied Sciences

    6 publications · 94 citations

    6

    h-index

  5. 6

    h-index

1–5