Mingwang Shen

2.8k citations
81 papers · 1.5k indexed · 1 hit paper · h-index 22

Mingwang Shen

77 papers receiving 1.5k citations

Hit Papers

Projected rapid growth in diabetes disease burden and eco...1052023202620242025255075100

Peers

Mingwang Shen
Comparison fields: 5 of 146
  • Modeling and Simulation 516
  • Infectious Diseases 526
  • Virology 78
  • Health Informatics 21
  • Health 113
Replace David Benkeser with:
David Benkeser United States
Patricia Harrington Ireland
Junxiong Pang Singapore
Chorh Chuan Tan Singapore
Omid Dadras Iran
Jen-Hsiang Chuang Taiwan
Jason Zucker United States
Sanjat Kanjilal United States
Mingwang Shen relative to David Benkeser United States David Benkeser's profile →
Citations per field
00.5×4.2×
David Benkeser · 1×
Citations per year

Countries citing papers authored by Mingwang Shen

Since Specialization
Citations

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

Fields of papers citing papers by Mingwang Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Mingwang Shen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mingwang Shen Line = papers co-authored together Mingwang Shen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 202423
4 20241
5 20242
6 20236
7 20235
8
Projected rapid growth in diabetes disease burden and economic burden in China: a spatio-temporal study from 2020 to 2030breakdown →
2023105
9 20239
10 20236
11 202322
12 202338
13 20231
14 202241
15 202114
16 20215
17 20201
18 20205
19 202015
20 201714

About Mingwang Shen

Mingwang Shen is a scholar working on Modeling and Simulation, Virology, Infectious Diseases, Health and Hepatology, having authored 81 papers that have together received 1.5k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (24 papers), SARS-CoV-2 and COVID-19 Research (12 papers), HIV/AIDS Research and Interventions (12 papers), HIV, Drug Use, Sexual Risk (11 papers), HIV Research and Treatment (10 papers), COVID-19 Pandemic Impacts (9 papers), Hepatitis B Virus Studies (9 papers) and Vaccine Coverage and Hesitancy (8 papers). The work is most often cited by research in Modeling and Simulation (516 citations), Infectious Diseases (526 citations), Virology (78 citations), Health Informatics (21 citations) and Health (113 citations). Mingwang Shen has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Yanni Xiao, Lei Zhang, Libin Rong, Guihua Zhuang, Zhihang Peng, Christopher K. Fairley, Yan Li, Jinli Liu, Hua Qiang and Jun Lyu. Their work appears in journals such as International Journal of Infectious Diseases, BMC Public Health, The Lancet Regional Health - Western Pacific, Vaccine and The Innovation.

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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