Jinren Pan

635 citations
31 papers · 410 · h-index 13

Impact in

Papers in

    • Respiratory viral infections research 8
    • Virology and Viral Diseases 6
    • Influenza Virus Research Studies 3
    • SARS-CoV-2 and COVID-19 Research 3
    • Viral Infections and Vectors 3

Jinren Pan

29 papers receiving 403 citations

Peers

Jinren Pan
Comparison fields: 5 of 76
  • Modeling and Simulation 108
  • Infectious Diseases 152
  • Health 60
  • Microbiology 44
  • Endocrinology 30
Replace Emilia Lupulescu with:
Emilia Lupulescu Romania
Adrienne Guignard Belgium
Hester E. de Melker Netherlands
John Carnie Australia
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Takuri Takahashi Japan
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Citations per field
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Citations per year

Countries citing papers authored by Jinren Pan

Since Specialization
Citations

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

Fields of papers citing papers by Jinren Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jinren Pan, 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 Jinren Pan Line = papers co-authored together Jinren Pan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202149
2 202040
3 201234
4 201532
5 201629
6 201826
7 201425
8 201621
9 202020
10 201817
11 201416
12 202113
13 202012
14 201411
15 201511
16 202210
17 201510
18 20225
19 20225
20
A cross-sectional survey to evaluate knowledge, attitude and practice (KAP) regarding measles vaccination among ethnic minorities.
20155

About Jinren Pan

Jinren Pan is a scholar working on Epidemiology, Infectious Diseases, Modeling and Simulation, Public Health, Environmental and Occupational Health and Microbiology, having authored 31 papers that have together received 410 indexed citations. Recurring topics across this work include Respiratory viral infections research (8 papers), COVID-19 epidemiological studies (7 papers), Virology and Viral Diseases (6 papers), Influenza Virus Research Studies (3 papers), Vaccine Coverage and Hesitancy (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Bacterial Infections and Vaccines (3 papers) and Viral Infections and Vectors (3 papers). The work is most often cited by research in Modeling and Simulation (108 citations), Infectious Diseases (152 citations), Health (60 citations), Microbiology (44 citations) and Endocrinology (30 citations). Jinren Pan has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Enfu Chen, Hanqing He, Ling Feng, Yang Zhou, Wanwan Sun, Shuyun Xie, Pingping Yao, Shelan Liu, Rui Yan and Qian Li. Their work appears in journals such as Vaccine, Epidemiology and Infection, International Journal of Infectious Diseases, Open Forum Infectious Diseases and Frontiers in Public Health.

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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