Chia-En Lien

408 citations
20 papers · 203 · h-index 7

Impact in

    • SARS-CoV-2 and COVID-19 Research
    • COVID-19 Clinical Research Studies
    • Viral gastroenteritis research and epidemiology
    • Vaccine Coverage and Hesitancy

Papers in

    • SARS-CoV-2 and COVID-19 Research 12
    • COVID-19 Clinical Research Studies 6
    • Vaccine Coverage and Hesitancy 7

Chia-En Lien

19 papers receiving 195 citations

Peers

Chia-En Lien
Comparison fields: 5 of 58
  • Infectious Diseases 108
  • Health 27
  • Epidemiology 87
  • Modeling and Simulation 10
  • Applied Microbiology and Biotechnology 3
Replace Michelle Morales with:
Michelle Morales United States
Barnaby Flower United Kingdom
Paul Chenoweth United States
Mia Marie Pries‐Heje Denmark
Diane Gbesemete United Kingdom
Steve G. Wassilak United States
Madison E. Weirick United States
Hannah E. Segaloff United States
Л. В. Колобухина Russia
Viktor Gasimov Pakistan
Chia-En Lien relative to Michelle Morales United States Michelle Morales's profile →
Citations per field
00.5×3.3×
Michelle Morales · 1×
Citations per year

Countries citing papers authored by Chia-En Lien

Since Specialization
Citations

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

Fields of papers citing papers by Chia-En Lien

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chia-En Lien. 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 Chia-En Lien. The network helps show where Chia-En Lien may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 200977
2 202226
3 202218
4 202315
5 202111
6 202111
7 202210
8 20225
9 20215
10 20225
11 20225
12 20233
13 20233
14 20222
15 20222
16 20222
17 20231
18 20251
19 20241
20 20240

About Chia-En Lien

Chia-En Lien is a scholar working on Infectious Diseases, Health, Public Health, Environmental and Occupational Health, Pediatrics, Perinatology and Child Health and Epidemiology, having authored 20 papers that have together received 203 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (12 papers), Vaccine Coverage and Hesitancy (7 papers), COVID-19 Clinical Research Studies (6 papers), Mosquito-borne diseases and control (5 papers), Malaria Research and Control (4 papers), Influenza Virus Research Studies (3 papers), Global Maternal and Child Health (3 papers) and Animal Virus Infections Studies (2 papers). The work is most often cited by research in Infectious Diseases (108 citations), Health (27 citations), Epidemiology (87 citations), Modeling and Simulation (10 citations) and Applied Microbiology and Biotechnology (3 citations). Chia-En Lien has collaborated with scholars based in Taiwan, United States and Paraguay. Frequent co-authors include Shan‐Chwen Chang, Hsu‐Sung Kuo, Jen-Hsiang Chuang, Hao‐Yuan Cheng, Theodore F. Tsai, Nicole Huang, Meei‐Yun Lin, Szu‐Min Hsieh, Charles Chen and Luke Tzu-Chi Liu. Their work appears in journals such as Vaccine, American Journal of Tropical Medicine and Hygiene, Vaccines, Clinical Infectious Diseases and Scientific Reports.

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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