Weiming Wang

10.5k total citations · 4 hit papers
200 papers, 6.8k citations indexed

About

Weiming Wang is a scholar working on Public Health, Environmental and Occupational Health, Genetics and Modeling and Simulation. According to data from OpenAlex, Weiming Wang has authored 200 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 126 papers in Public Health, Environmental and Occupational Health, 70 papers in Genetics and 68 papers in Modeling and Simulation. Recurrent topics in Weiming Wang's work include Mathematical and Theoretical Epidemiology and Ecology Models (91 papers), Evolution and Genetic Dynamics (69 papers) and COVID-19 epidemiological studies (50 papers). Weiming Wang is often cited by papers focused on Mathematical and Theoretical Epidemiology and Ecology Models (91 papers), Evolution and Genetic Dynamics (69 papers) and COVID-19 epidemiological studies (50 papers). Weiming Wang collaborates with scholars based in China, Hong Kong and United States. Weiming Wang's co-authors include Yongli Cai, Daihai He, Shi Zhao, Yijun Lou, Lin Yang, Daozhou Gao, Maggie Haitian Wang, Salihu S. Musa, Yun Kang and Jinjun Ran and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Ethnopharmacology.

In The Last Decade

Weiming Wang

194 papers receiving 6.5k citations

Hit Papers

Preliminary estimation of the basic reproductio... 2015 2026 2018 2022 2020 2020 2015 2019 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Weiming Wang China 36 3.8k 3.4k 2.1k 1.2k 730 200 6.8k
Sanyi Tang China 44 4.1k 1.1× 3.4k 1.0× 1.8k 0.9× 1.4k 1.1× 491 0.7× 240 7.4k
Yanni Xiao China 39 3.2k 0.8× 3.7k 1.1× 1.5k 0.7× 1.7k 1.4× 191 0.3× 180 6.4k
Zhen Jin China 54 5.2k 1.4× 3.7k 1.1× 2.7k 1.3× 1.0k 0.8× 1.2k 1.7× 474 10.8k
Gui‐Quan Sun China 48 3.5k 0.9× 2.2k 0.7× 1.9k 0.9× 605 0.5× 1.1k 1.5× 214 6.3k
Fred Brauer Canada 37 4.5k 1.2× 4.3k 1.3× 2.2k 1.0× 1.1k 0.9× 470 0.6× 142 8.1k
Wendi Wang China 41 5.5k 1.4× 3.8k 1.1× 3.6k 1.7× 751 0.6× 402 0.6× 170 7.1k
David J. D. Earn Canada 40 2.2k 0.6× 3.4k 1.0× 1.7k 0.8× 1.4k 1.1× 192 0.3× 104 7.7k
Linda J. S. Allen United States 37 3.1k 0.8× 2.3k 0.7× 1.9k 0.9× 704 0.6× 199 0.3× 128 5.2k
Glenn F. Webb United States 46 3.1k 0.8× 3.2k 0.9× 1.4k 0.7× 1.0k 0.8× 202 0.3× 184 8.4k
Yang Kuang United States 48 5.5k 1.4× 2.8k 0.8× 3.6k 1.7× 366 0.3× 1.1k 1.5× 202 8.6k

Countries citing papers authored by Weiming Wang

Since Specialization
Citations

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

Fields of papers citing papers by Weiming Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weiming Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Weiming Wang. A scholar is included among the top collaborators of Weiming Wang 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 Weiming Wang. Weiming Wang 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.
Zhang, Ciliu, Zhong-Liang Zhang, Xiaole Wang, et al.. (2025). Gene therapy with covalently closed-end AAV vector for spinal muscular atrophy. Molecular Therapy. 33(10). 4848–4857.
2.
Zhao, Shi, Zihao Guo, Kai Wang, et al.. (2025). modelSSE: An R Package for Characterizing Infectious Disease Superspreading from Contact Tracing Data. Bulletin of Mathematical Biology. 87(4). 47–47. 1 indexed citations
3.
Zeng, Ting, Yaoqin Lu, Zihao Guo, et al.. (2023). Effectiveness of the booster dose of inactivated COVID-19 vaccine against Omicron BA.5 infection: a matched cohort study of adult close contacts. Respiratory Research. 24(1). 246–246. 9 indexed citations
4.
Cai, Yongli, et al.. (2023). Global stability of a fractional order SIS epidemic model. Journal of Differential Equations. 352. 221–248. 28 indexed citations
5.
Zhao, Shi, Yu Zhao, Biao Tang, et al.. (2021). Shrinkage in serial intervals across transmission generations of COVID-19. Journal of Theoretical Biology. 529. 110861–110861. 1 indexed citations
6.
Liu, Ying, Weidong Ji, Zhengrong Yang, et al.. (2021). An analysis on the trend of AIDS/HIV incidence in Chongqing and Shenzhen, China from 2005–2015 based on Age-Period-Cohort model. Mathematical Biosciences & Engineering. 18(5). 6961–6977. 7 indexed citations
7.
Zhao, Shi, Salihu S. Musa, Qianying Lin, et al.. (2020). Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak. Journal of Clinical Medicine. 9(2). 388–388. 302 indexed citations
8.
Zhao, Shi, Zian Zhuang, Peihua Cao, et al.. (2020). Quantifying the association between domestic travel and the exportation of novel coronavirus (2019-nCoV) cases from Wuhan, China in 2020: a correlational analysis. Journal of Travel Medicine. 27(2). 66 indexed citations
10.
Ji, Weidong, Na Xie, Daihai He, et al.. (2019). Age-Period-Cohort Analysis on the Time Trend of Hepatitis B Incidence in Four Prefectures of Southern Xinjiang, China from 2005 to 2017. International Journal of Environmental Research and Public Health. 16(20). 3886–3886. 11 indexed citations
11.
Zhou, Huayun, Weiming Wang, Guoding Zhu, et al.. (2018). [Epidemiological analysis of malaria prevalence in Jiangsu Province in 2016].. PubMed. 30(1). 32–36. 5 indexed citations
12.
Cai, Yongli, et al.. (2017). Turing patterns in a reaction–diffusion epidemic model. International Journal of Biomathematics. 11(2). 1850025–1850025. 7 indexed citations
13.
Cao, Yuanyuan, Huayun Zhou, Guoding Zhu, et al.. (2016). [Analysis of channels of going abroad of imported malaria patients in Jiangsu Province, China].. PubMed. 28(6). 653–656. 2 indexed citations
14.
Wang, Weiming, et al.. (2013). Allee-Effect-Induced Instability in a Reaction-Diffusion Predator-Prey Model. Abstract and Applied Analysis. 2013. 1–10. 9 indexed citations
15.
Wang, Weiming, et al.. (2013). Dynamical complexity induced by Allee effect in a predator–prey model. Nonlinear Analysis Real World Applications. 16. 103–119. 47 indexed citations
16.
Gao, Qi, et al.. (2010). Sample related factors affecting short-term culture of erythrocytic Plasmodium vivax in vitro.. 22(1). 56–58. 2 indexed citations
17.
Pei, Hong, et al.. (2010). Prevalence and control of malaria in Sihong County from 1997 to 2007.. 22(1). 84–86. 2 indexed citations
18.
Wang, Weiming. (2010). The Amplitude Equations of an Epidemic Model. Science Technology and Engineering. 5 indexed citations
19.
Cao, Jun, et al.. (2009). Epidemic and control of malaria in Jiangsu Province.. 21(6). 503–506. 6 indexed citations
20.
Wang, Weiming, et al.. (2009). Analysis of malaria situation in Nantong City.. 21(6). 555–556. 1 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026