Fernando Córdova‐Lepe

458 total citations
57 papers, 304 citations indexed

About

Fernando Córdova‐Lepe is a scholar working on Public Health, Environmental and Occupational Health, Modeling and Simulation and Infectious Diseases. According to data from OpenAlex, Fernando Córdova‐Lepe has authored 57 papers receiving a total of 304 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Public Health, Environmental and Occupational Health, 22 papers in Modeling and Simulation and 15 papers in Infectious Diseases. Recurrent topics in Fernando Córdova‐Lepe's work include Mathematical and Theoretical Epidemiology and Ecology Models (21 papers), COVID-19 epidemiological studies (20 papers) and Evolution and Genetic Dynamics (10 papers). Fernando Córdova‐Lepe is often cited by papers focused on Mathematical and Theoretical Epidemiology and Ecology Models (21 papers), COVID-19 epidemiological studies (20 papers) and Evolution and Genetic Dynamics (10 papers). Fernando Córdova‐Lepe collaborates with scholars based in Chile, Colombia and United States. Fernando Córdova‐Lepe's co-authors include Eduardo González‐Olivares, Gonzalo Robledo, Manuel Pinto, María Teresa Muñoz-Quezada, Rodrigo Gutiérrez, Marco Mora, Kuo‐Shou Chiu, Alejandro Rojas‐Palma, Rodrigo Ramos‐Jiliberto and Moisés Bravo‐Gaete and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Fernando Córdova‐Lepe

50 papers receiving 299 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Fernando Córdova‐Lepe Chile 10 112 104 58 42 35 57 304
Olga Vasilieva Colombia 11 290 2.6× 78 0.8× 42 0.7× 34 0.8× 15 0.4× 48 419
Ashraf Adnan Thirthar Iraq 14 216 1.9× 170 1.6× 137 2.4× 21 0.5× 11 0.3× 31 408
Takasar Hussain Pakistan 12 185 1.7× 179 1.7× 72 1.2× 51 1.2× 12 0.3× 38 391
Parimita Roy India 10 196 1.8× 128 1.2× 126 2.2× 33 0.8× 7 0.2× 25 309
Ibrahim M. Elmojtaba Oman 11 280 2.5× 130 1.3× 114 2.0× 56 1.3× 13 0.4× 25 333
Muhammad Ozair Pakistan 13 234 2.1× 202 1.9× 102 1.8× 56 1.3× 16 0.5× 35 428
Youping Yang China 11 228 2.0× 164 1.6× 113 1.9× 43 1.0× 9 0.3× 19 318
Jeffrey J. Morgan United States 11 100 0.9× 97 0.9× 72 1.2× 39 0.9× 12 0.3× 23 292
Quentin Griette France 11 130 1.2× 175 1.7× 77 1.3× 62 1.5× 8 0.2× 24 235
Purnachandra Rao Koya Ethiopia 11 147 1.3× 124 1.2× 59 1.0× 31 0.7× 13 0.4× 59 394

Countries citing papers authored by Fernando Córdova‐Lepe

Since Specialization
Citations

This map shows the geographic impact of Fernando Córdova‐Lepe'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 Fernando Córdova‐Lepe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Córdova‐Lepe more than expected).

Fields of papers citing papers by Fernando Córdova‐Lepe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fernando Córdova‐Lepe. 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 Fernando Córdova‐Lepe. The network helps show where Fernando Córdova‐Lepe may publish in the future.

Co-authorship network of co-authors of Fernando Córdova‐Lepe

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Córdova‐Lepe. A scholar is included among the top collaborators of Fernando Córdova‐Lepe 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 Fernando Córdova‐Lepe. Fernando Córdova‐Lepe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Bravo‐Gaete, Moisés, et al.. (2024). Competition and edge effect in wildlife zoonotic agents. Ecological Modelling. 496. 110838–110838. 1 indexed citations
3.
Córdova‐Lepe, Fernando, et al.. (2024). A Dynamic Reaction-restore-type Transmission-rate Model for COVID-19. 21. 118–130. 3 indexed citations
4.
Córdova‐Lepe, Fernando, et al.. (2024). Exploring the effects of competition and predation on the success of biological invasion through mathematical modeling. Scientific Reports. 14(1). 4416–4416. 4 indexed citations
5.
Córdova‐Lepe, Fernando, et al.. (2024). A Kinematic Approach to the Classical SIR Model. Axioms. 13(10). 718–718.
6.
Marchant, Carolina, et al.. (2023). A description of the epidemiological dynamics of Chagas disease via mathematical modeling. Acta Tropica. 243. 106930–106930. 1 indexed citations
7.
Córdova‐Lepe, Fernando, et al.. (2023). A mathematical model and simulation scenarios for T and B cells immune response to severe acute respiratory syndrome-coronavirus-2. Journal of Physics Conference Series. 2516(1). 12007–12007. 1 indexed citations
8.
Bravo‐Gaete, Moisés, et al.. (2023). Concurrent dilution and amplification effects in an intraguild predation eco-epidemiological model. Scientific Reports. 13(1). 6425–6425. 7 indexed citations
9.
Córdova‐Lepe, Fernando, et al.. (2022). epcc: An R package to assess and simulate the vulnerability of ectothermic populations when facing climate change. Methods in Ecology and Evolution. 13(5). 955–962.
10.
Córdova‐Lepe, Fernando, et al.. (2022). A mathematical model for the impact of noise on population dynamics of a single species experiencing Lombard effect. Ecological Modelling. 470. 110022–110022. 1 indexed citations
11.
Córdova‐Lepe, Fernando, et al.. (2022). Adding a reaction-restoration type transmission rate dynamic-law to the basic SEIR COVID-19 model. PLoS ONE. 17(6). e0269843–e0269843. 8 indexed citations
12.
Córdova‐Lepe, Fernando, et al.. (2022). Cell lysis analysis for respiratory viruses through simulation modeling. Journal of Physics Conference Series. 2159(1). 12002–12002. 1 indexed citations
13.
Gutiérrez, Rodrigo, et al.. (2020). Model for a threshold of daily rate reduction of COVID-19 cases to avoid hospital collapse in Chile. SHILAP Revista de lepidopterología. 20(3). e7871–e7871. 7 indexed citations
14.
Córdova‐Lepe, Fernando, et al.. (2020). Distribution model of toxic agents and runoff phenomenon in flat aquatic regions. Journal of Physics Conference Series. 1514(1). 12004–12004. 1 indexed citations
15.
Córdova‐Lepe, Fernando, et al.. (2019). Susceptibility to organophosphates pesticides and the development of infectious-contagious respiratory diseases. Journal of Theoretical Biology. 488. 110133–110133. 7 indexed citations
16.
Córdova‐Lepe, Fernando, et al.. (2018). The process of connectivity loss during habitat fragmentation and their consequences on population dynamics. Ecological Modelling. 376. 68–75. 13 indexed citations
17.
Córdova‐Lepe, Fernando, et al.. (2018). Modeling the epidemiological impact of a preventive behavioral group. Medwave. 18(8). e7396–e7396. 3 indexed citations
18.
Córdova‐Lepe, Fernando, et al.. (2016). An impulsive fishery model with environmental stochasticity. Feasibility. Mathematical Biosciences. 277. 71–76. 8 indexed citations
19.
Córdova‐Lepe, Fernando, et al.. (2012). A pulse fishery model with closures as function of the catch: Conditions for sustainability. Mathematical Biosciences. 239(1). 169–177. 13 indexed citations
20.
Córdova‐Lepe, Fernando, et al.. (2011). A PULSE VACCINATION STRATEGY AT VARIABLE TIMES DEPENDING ON INCIDENCE. Journal of Biological Systems. 19(2). 329–344. 9 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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