Daoling Bi

1.5k citations
15 papers · 800 indexed · h-index 13

Impact in

  • Health top 1%
    • Vaccine Coverage and Hesitancy
    • Virology and Viral Diseases
    • Respiratory viral infections research
    • Influenza Virus Research Studies
    • Pneumonia and Respiratory Infections

Papers in

    • Vaccine Coverage and Hesitancy 10
    • Virology and Viral Diseases 12
    • Influenza Virus Research Studies 4
    • Respiratory viral infections research 4
    • Pneumonia and Respiratory Infections 2

Daoling Bi

15 papers receiving 759 citations

Peers

Daoling Bi
Comparison fields: 5 of 66
  • Health 467
  • Epidemiology 647
  • Microbiology 98
  • Infectious Diseases 285
  • Modeling and Simulation 62
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Daoling Bi relative to Jennifer B. Rosen United States Jennifer B. Rosen's profile →
Citations per field
00.5×1.5×
Jennifer B. Rosen · 1×
Citations per year

Countries citing papers authored by Daoling Bi

Since Specialization
Citations

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

Fields of papers citing papers by Daoling Bi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2010227
2 200596
3 200792
4 200869
5 200957
6 201454
7 202047
8 201539
9 200529
10 200626
11 201825
12 200519
13 202013
14 20074
15 20143

About Daoling Bi

Daoling Bi is a scholar working on Health, Epidemiology, Infectious Diseases, Virology and Microbiology, having authored 15 papers that have together received 800 indexed citations. Recurring topics across this work include Virology and Viral Diseases (12 papers), Vaccine Coverage and Hesitancy (10 papers), SARS-CoV-2 and COVID-19 Research (5 papers), Influenza Virus Research Studies (4 papers), Respiratory viral infections research (4 papers), Pneumonia and Respiratory Infections (2 papers), Syphilis Diagnosis and Treatment (1 paper) and Rabies epidemiology and control (1 paper). The work is most often cited by research in Health (467 citations), Epidemiology (647 citations), Microbiology (98 citations), Infectious Diseases (285 citations) and Modeling and Simulation (62 citations). Daoling Bi has collaborated with scholars based in United States, Thailand and South Africa. Frequent co-authors include Charles W. LeBaron, Carol L. Beck, Bradley J. Sullivan, Bagher Forghani, Paul A. Rota, Maryann G. Delea, David Sugerman, Ismael R. Ortega‐Sanchez, Kimberly Ralston and Albert E. Barskey. Their work appears in journals such as The Journal of Infectious Diseases, PEDIATRICS, Clinical Infectious Diseases, Open Forum Infectious Diseases and Epidemiology and Infection.

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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