Kaiyi Han

407 citations
17 papers · 320 · h-index 10

Impact in

Papers in

    • Vaccine Coverage and Hesitancy 11
    • Influenza Virus Research Studies 9
    • Respiratory viral infections research 6

Kaiyi Han

17 papers receiving 314 citations

Peers

Kaiyi Han
Comparison fields: 5 of 74
  • Health 197
  • Modeling and Simulation 67
  • Infectious Diseases 118
  • Epidemiology 103
  • Health, Toxicology and Mutagenesis 34
Replace Nadia A. Charania with:
Nadia A. Charania New Zealand
Chuchu Ye China
Zhoubin Zhang China
Chunna Ma China
Amy Carter United States
Muli Zhang China
Katherine Min Jia Hong Kong
Mabel Sheau Fong Low Singapore
Joey Sin Taiwan
J. Bresee United States
Kaiyi Han relative to Nadia A. Charania New Zealand Nadia A. Charania's profile →
Citations per field
00.5×4.5×
Nadia A. Charania · 1×
Citations per year

Countries citing papers authored by Kaiyi Han

Since Specialization
Citations

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

Fields of papers citing papers by Kaiyi Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 202065
2 201445
3 202144
4 201534
5 202124
6 202017
7 202117
8 202114
9 201713
10 202410
11 19998
12 20227
13 20225
14 20225
15 20225
16
[Relationship between risk of childhood acute leukemia and children's and parents' lifestyles and household environment exposure].
20154
17 20233

About Kaiyi Han

Kaiyi Han is a scholar working on Health, Epidemiology, Modeling and Simulation, Infectious Diseases and Pediatrics, Perinatology and Child Health, having authored 17 papers that have together received 320 indexed citations. Recurring topics across this work include Vaccine Coverage and Hesitancy (11 papers), Influenza Virus Research Studies (9 papers), Respiratory viral infections research (6 papers), COVID-19 epidemiological studies (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Acute Lymphoblastic Leukemia research (2 papers), Childhood Cancer Survivors' Quality of Life (2 papers) and Cardiovascular Health and Risk Factors (1 paper). The work is most often cited by research in Health (197 citations), Modeling and Simulation (67 citations), Infectious Diseases (118 citations), Epidemiology (103 citations) and Health, Toxicology and Mutagenesis (34 citations). Kaiyi Han has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Mark R. Francis, Zhiyuan Hou, Tracey Chantler, Heidi J. Larson, Lance E. Rodewald, Fanxing Du, Hongjie Yu, Xuan Zhang, Qian Wang and Bingyi Yang. Their work appears in journals such as Vaccines, Vaccine, Human Vaccines & Immunotherapeutics, Buildings and Global Health Research and Policy.

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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