Sara Chaothai

514 citations
6 papers · 187 · 1 hit paper · h-index 4

Impact in

    • SARS-CoV-2 and COVID-19 Research
    • COVID-19 Clinical Research Studies
    • SARS-CoV-2 detection and testing
    • Viral gastroenteritis research and epidemiology
    • COVID-19 epidemiological studies

Papers in

Sara Chaothai

6 papers receiving 185 citations

Sara Chaothai's Hit Papers

Real-world COVID-19 vaccine effectiveness against the Omicron BA.2 variant in a SARS-CoV-2 infection-naive population 2023 · 116 citations
1160+1+2Years since publication255075100

Peers

Sara Chaothai
Comparison fields: 5 of 44
  • Infectious Diseases 160
  • Modeling and Simulation 39
  • Health 37
  • Animal Science and Zoology 22
  • Obstetrics and Gynecology 10
Replace Bosco Lam with:
Bosco Lam Hong Kong
Ivan Fan Ngai Hung Hong Kong
Kelvin K. H. Kwan Hong Kong
Leo L. H. Luk Hong Kong
Biliana Nestorova United States
Jianhui Nie China
Kwok Yung Yuen Hong Kong
Cameron Bissett United Kingdom
Qiaoli Peng China
Gabriele Pagani Italy
Sara Chaothai relative to Bosco Lam Hong Kong Bosco Lam's profile →
Citations per field
00.5×
Bosco Lam · 1×
Citations per year

Countries citing papers authored by Sara Chaothai

Since Specialization
Citations

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

Fields of papers citing papers by Sara Chaothai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

6 of 6 papers shown
#Work
1
Real-world COVID-19 vaccine effectiveness against the Omicron BA.2 variant in a SARS-CoV-2 infection-naive population
Hit paper breakdown →
2023116
2 202144
3 202213
4 202210
5 20233
6 20211

About Sara Chaothai

Sara Chaothai is a scholar working on Infectious Diseases, Animal Science and Zoology, Health, Cardiology and Cardiovascular Medicine and Organic Chemistry, having authored 6 papers that have together received 187 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (6 papers), COVID-19 Clinical Research Studies (5 papers), Animal Virus Infections Studies (3 papers), Vaccine Coverage and Hesitancy (1 paper), SARS-CoV-2 detection and testing (1 paper) and Viral Infections and Immunology Research (1 paper). The work is most often cited by research in Infectious Diseases (160 citations), Modeling and Simulation (39 citations), Health (37 citations), Animal Science and Zoology (22 citations) and Obstetrics and Gynecology (10 citations). Sara Chaothai has collaborated with scholars based in Hong Kong, China and Australia. Frequent co-authors include Samuel M. S. Cheng, Malik Peiris, Eric H. Y. Lau, David S.C. Hui, GM Leung, Kelvin K. H. Kwan, Joseph T. Wu, Kathy Leung, Cheuk Kwong Lee and Chao Wu. Their work appears in journals such as Clinical Infectious Diseases, Nature Medicine, EClinicalMedicine, Vaccine and Journal of Clinical Virology.

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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