Baojun Song

3.2k total citations · 1 hit paper
27 papers, 2.1k citations indexed

About

Baojun Song is a scholar working on Public Health, Environmental and Occupational Health, Modeling and Simulation and Genetics. According to data from OpenAlex, Baojun Song has authored 27 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Public Health, Environmental and Occupational Health, 15 papers in Modeling and Simulation and 12 papers in Genetics. Recurrent topics in Baojun Song's work include Mathematical and Theoretical Epidemiology and Ecology Models (19 papers), COVID-19 epidemiological studies (14 papers) and Evolution and Genetic Dynamics (12 papers). Baojun Song is often cited by papers focused on Mathematical and Theoretical Epidemiology and Ecology Models (19 papers), COVID-19 epidemiological studies (14 papers) and Evolution and Genetic Dynamics (12 papers). Baojun Song collaborates with scholars based in United States, China and Canada. Baojun Song's co-authors include Carlos Castillo‐Chávez, Abba B. Gumel, Chandra Nath Podder, Oluwaseun Sharomi, Juan Pablo Aparicio, Sanling Yuan, Faina Berezovskaya, Georgy P. Karev, Jia Li and Xiaohong Wang and has published in prestigious journals such as Journal of Theoretical Biology, Journal of the Franklin Institute and Chaos Solitons & Fractals.

In The Last Decade

Baojun Song

25 papers receiving 2.0k citations

Hit Papers

Dynamical Models of Tuberculosis and Their Applications 2004 2026 2011 2018 2004 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Baojun Song United States 12 1.7k 1.2k 897 396 190 27 2.1k
Jean M. Tchuenche Tanzania 29 1.6k 0.9× 1.4k 1.2× 552 0.6× 538 1.4× 216 1.1× 101 2.3k
Yicang Zhou China 22 1.4k 0.8× 1.1k 0.9× 823 0.9× 253 0.6× 222 1.2× 66 1.9k
Nicolas Bacaër France 20 1.1k 0.6× 745 0.6× 625 0.7× 367 0.9× 226 1.2× 37 1.6k
Andrei Korobeinikov Spain 21 2.3k 1.4× 1.7k 1.4× 1.5k 1.7× 227 0.6× 163 0.9× 74 2.9k
Soovoojeet Jana India 23 1.2k 0.7× 1.1k 0.9× 630 0.7× 207 0.5× 96 0.5× 76 1.7k
Julien Arino Canada 23 1.4k 0.8× 1.6k 1.3× 655 0.7× 542 1.4× 445 2.3× 64 2.3k
Kazeem O. Okosun South Africa 25 1.4k 0.9× 1.0k 0.8× 437 0.5× 438 1.1× 146 0.8× 58 1.9k
Winston Garira Zimbabwe 23 994 0.6× 662 0.5× 497 0.6× 348 0.9× 183 1.0× 55 1.5k
C. Connell McCluskey Canada 22 2.0k 1.2× 1.7k 1.3× 1.3k 1.5× 173 0.4× 124 0.7× 35 2.3k
Maia Martcheva United States 31 2.7k 1.6× 2.2k 1.8× 1.4k 1.6× 617 1.6× 508 2.7× 139 3.7k

Countries citing papers authored by Baojun Song

Since Specialization
Citations

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

Fields of papers citing papers by Baojun Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Baojun Song. 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 Baojun Song. The network helps show where Baojun Song may publish in the future.

Co-authorship network of co-authors of Baojun Song

This figure shows the co-authorship network connecting the top 25 collaborators of Baojun Song. A scholar is included among the top collaborators of Baojun Song 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 Baojun Song. Baojun Song 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.
Yuan, Sanling, et al.. (2023). Threshold behavior and exponential ergodicity of an sir epidemic model: the impact of random jamming and hospital capacity. Journal of Mathematical Biology. 88(1). 2–2. 4 indexed citations
2.
Song, Baojun, et al.. (2022). Epidemic threshold and ergodicity of an SEIR model with vertical transmission under the telegraph noise. Chaos Solitons & Fractals. 167. 113017–113017. 20 indexed citations
3.
Li, Meili, et al.. (2021). Estimating the quarantine failure rate for COVID-19. Infectious Disease Modelling. 6. 924–929. 2 indexed citations
4.
Wei, Yingying, Baojun Song, & Sanling Yuan. (2021). Dynamics of a ratio-dependent population model for Green Sea Turtle with age structure. Journal of Theoretical Biology. 516. 110614–110614. 5 indexed citations
5.
Song, Baojun. (2021). Basic reinfection number and backward bifurcation. Mathematical Biosciences & Engineering. 18(6). 8064–8083. 9 indexed citations
6.
Wei, Yingying, et al.. (2020). The Impact of Temperature-Dependent Sex Determination on the Population Dynamics of Green Sea Turtles (Chelonia mydas). Bionatura. 5(1). 1029–1038. 1 indexed citations
7.
Song, Baojun, et al.. (2020). Noise-induced transitions in a non-smooth SIS epidemic model with media alert. Mathematical Biosciences & Engineering. 18(1). 745–763. 13 indexed citations
8.
Yuan, Sanling, et al.. (2018). A Mathematical Study to Gout Symptoms. Journal of Applied Mathematics and Physics. 6(12). 2579–2588. 1 indexed citations
9.
Kheiri, Hossein, et al.. (2016). A two-strain TB model with multiple latent stages. Mathematical Biosciences & Engineering. 13(4). 741–785. 18 indexed citations
10.
Song, Baojun, et al.. (2015). A symmetric intraguild predation model for the invasive lionfish and native grouper. Communications in Mathematical Biology and Neuroscience. 2015. 6 indexed citations
11.
Lou, Jie, et al.. (2015). THE COUPLED WITHIN-AND BETWEEN-HOST DYNAMICS IN THE EVOLUTION OF HIV/AIDS IN CHINA. Journal of Applied Analysis & Computation. 5(4). 731–750. 7 indexed citations
12.
Cao, Hui, Yicang Zhou, & Baojun Song. (2011). Complex Dynamics of Discrete SEIS Models with Simple Demography. Discrete Dynamics in Nature and Society. 2011(1). 9 indexed citations
13.
Song, Baojun, et al.. (2011). Epidemic spread of influenza viruses: The impact of transient populations on disease dynamics. Mathematical Biosciences & Engineering. 8(1). 199–222. 8 indexed citations
14.
Sharomi, Oluwaseun, Chandra Nath Podder, Abba B. Gumel, & Baojun Song. (2008). Mathematical analysis of the transmission dynamics of HIV/TB coinfection in the presence of treatment. Mathematical Biosciences & Engineering. 5(1). 145–174. 172 indexed citations
15.
Song, Baojun, et al.. (2006). Raves, clubs and ecstasy: the impact of peer pressure. Mathematical Biosciences & Engineering. 3(1). 249–266. 42 indexed citations
16.
Song, Baojun & Diana M. Thomas. (2006). Dynamics of starvation in humans. Journal of Mathematical Biology. 54(1). 27–43. 23 indexed citations
17.
Berezovskaya, Faina, Georgy P. Karev, Baojun Song, & Carlos Castillo‐Chávez. (2005). A Simple Epidemic Model with Surprising Dynamics. Mathematical Biosciences & Engineering. 2(1). 133–152. 65 indexed citations
18.
Castillo‐Chávez, Carlos & Baojun Song. (2004). Dynamical Models of Tuberculosis and Their Applications. Mathematical Biosciences & Engineering. 1(2). 361–404. 1485 indexed citations breakdown →
19.
Song, Baojun, Carlos Castillo‐Chávez, & Juan Pablo Aparicio. (2002). Tuberculosis models with fast and slow dynamics: the role of close and casual contacts. Mathematical Biosciences. 180(1-2). 187–205. 109 indexed citations
20.
Song, Baojun, Carlos Castillo‐Chávez, & Juan Pablo Aparicio. (2001). Global Dynamics of TB Models with Density Dependent Demography. eCommons (Cornell University).

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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