Faïçal Ndaïrou

920 total citations · 1 hit paper
10 papers, 602 citations indexed

About

Faïçal Ndaïrou is a scholar working on Modeling and Simulation, Public Health, Environmental and Occupational Health and Infectious Diseases. According to data from OpenAlex, Faïçal Ndaïrou has authored 10 papers receiving a total of 602 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Modeling and Simulation, 8 papers in Public Health, Environmental and Occupational Health and 4 papers in Infectious Diseases. Recurrent topics in Faïçal Ndaïrou's work include COVID-19 epidemiological studies (8 papers), Mathematical and Theoretical Epidemiology and Ecology Models (8 papers) and Fractional Differential Equations Solutions (6 papers). Faïçal Ndaïrou is often cited by papers focused on COVID-19 epidemiological studies (8 papers), Mathematical and Theoretical Epidemiology and Ecology Models (8 papers) and Fractional Differential Equations Solutions (6 papers). Faïçal Ndaïrou collaborates with scholars based in Portugal, Spain and Finland. Faïçal Ndaïrou's co-authors include Delfim F. M. Torres, Iván Area, Juan J. Nieto, Cristiana J. Silva, Jorge Losada and Leo Lahti and has published in prestigious journals such as Chaos Solitons & Fractals, Mathematical Biosciences and Mathematical Methods in the Applied Sciences.

In The Last Decade

Faïçal Ndaïrou

8 papers receiving 584 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan

2020 469 citations Faïçal Ndaïrou, Iván Area et al. Chaos Solitons & Fractals profile →

Peers

Faïçal Ndaïrou

MS

PHEOH

ID

EE

AM

Ousmane Seydi France

Sarbaz H. A. Khoshnaw Iraq

Jayanta Mondal India

Manotosh Mandal India

Zhihua Liu France

Miriam R. Ferrández Spain

Swapan Kumar Nandi India

C. W. Chukwu South Africa

Anupam Khatua India

Amar Nath Chatterjee India

Ousmane Seydi France

Faïçal Ndaïrou

562 ×1.0

MS

253 ×0.9

PHEOH

270 ×1.4

ID

152 ×1.4

EE

13 ×0.3

AM

Citations per year, relative to Faïçal Ndaïrou Faïçal Ndaïrou (= 1×) peers Ousmane Seydi

Countries citing papers authored by Faïçal Ndaïrou

Since Specialization

Citations

This map shows the geographic impact of Faïçal Ndaïrou's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Faïçal Ndaïrou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Faïçal Ndaïrou more than expected).

Fields of papers citing papers by Faïçal Ndaïrou

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Faïçal Ndaïrou. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Faïçal Ndaïrou. The network helps show where Faïçal Ndaïrou may publish in the future.

Co-authorship network of co-authors of Faïçal Ndaïrou

This figure shows the co-authorship network connecting the top 25 collaborators of Faïçal Ndaïrou. A scholar is included among the top collaborators of Faïçal Ndaïrou based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Faïçal Ndaïrou. Faïçal Ndaïrou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

Lahti, Leo, et al.. (2025). Fractional modelling of COVID-19 transmission incorporating asymptomatic and super-spreader individuals. Mathematical Biosciences. 380. 109373–109373.

2.

Ndaïrou, Faïçal, et al.. (2024). Optimal Control Applied to Piecewise-Fractional Ebola Model. Mathematics. 12(7). 985–985. 1 indexed citations

3.

Ndaïrou, Faïçal, et al.. (2024). Epidemic transmission modeling with fractional derivatives and environmental pathogens. International Journal of Biomathematics. 2 indexed citations

4.

Ndaïrou, Faïçal, et al.. (2023). Ebola epidemic model with dynamic population and memory. Chaos Solitons & Fractals. 170. 113361–113361. 8 indexed citations

5.

Ndaïrou, Faïçal & Delfim F. M. Torres. (2023). Pontryagin Maximum Principle for Incommensurate Fractional-Orders Optimal Control Problems. Mathematics. 11(19). 4218–4218. 1 indexed citations

6.

Ndaïrou, Faïçal & Delfim F. M. Torres. (2021). Mathematical Analysis of a Fractional COVID-19 Model Applied to Wuhan, Spain and Portugal. Axioms. 10(3). 135–135. 24 indexed citations

7.

Ndaïrou, Faïçal, Iván Area, Juan J. Nieto, Cristiana J. Silva, & Delfim F. M. Torres. (2021). Fractional model of COVID-19 applied to Galicia, Spain and Portugal. Chaos Solitons & Fractals. 144. 110652–110652. 69 indexed citations

8.

Ndaïrou, Faïçal, Iván Area, Juan J. Nieto, & Delfim F. M. Torres. (2020). Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan. Chaos Solitons & Fractals. 135. 109846–109846. 469 indexed citations breakdown →

9.

Ndaïrou, Faïçal, Iván Area, & Delfim F. M. Torres. (2020). Mathematical Modeling of Japanese Encephalitis under Aquatic Environmental Effects. Mathematics. 8(11). 1880–1880. 4 indexed citations

10.

Area, Iván, et al.. (2015). Mathematical modeling of 2014 Ebola outbreak. Mathematical Methods in the Applied Sciences. 40(17). 6114–6122. 24 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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