Wan In Wei

20 papers receiving 1.4k citations

Wan In Wei's Hit Papers

Influenza vaccine uptake, COVID-19 vaccination intention and vaccine hesitancy among nurses: A survey 2020 · 501 citations
5010+2+4Years since publication100200300400500

Peers

Wan In Wei
Comparison fields: 5 of 124
  • Health 620
  • Modeling and Simulation 313
  • Infectious Diseases 391
  • Clinical Psychology 258
  • Economics and Econometrics 214
Replace Mohammad S Razai with:
Mohammad S Razai United Kingdom
Jad A. Elharake United States
Noor Alshareef Saudi Arabia
Steven Sanche Canada
Spencer Kimball United States
Deema Dababseh Jordan
Nina Gobat United Kingdom
S. M. Murshid Hasan Bangladesh
Fahad Alsohime Saudi Arabia
Gianmarco Troiano Italy
Wan In Wei relative to Mohammad S Razai United Kingdom Mohammad S Razai's profile →
Citations per field
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Mohammad S Razai · 1×
Citations per year

Countries citing papers authored by Wan In Wei

Since Specialization
Citations

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

Fields of papers citing papers by Wan In Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wan In Wei. 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 Wan In Wei. The network helps show where Wan In Wei may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Influenza vaccine uptake, COVID-19 vaccination intention and vaccine hesitancy among nurses: A survey
Hit paper breakdown →
2020501
2 2020324
3
Community Responses during Early Phase of COVID-19 Epidemic, Hong Kong
Hit paper breakdown →
2020322
4 202038
5 202138
6 202134
7 202128
8 202123
9 202222
10 202122
11 202220
12 202319
13 202210
14 20244
15 20243
16 20232
17 20082
18 20241
19 20201
20 20221

About Wan In Wei

Wan In Wei is a scholar working on Modeling and Simulation, Infectious Diseases, Health, Clinical Psychology and Sociology and Political Science, having authored 21 papers that have together received 1.4k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (8 papers), Vaccine Coverage and Hesitancy (5 papers), COVID-19 and Mental Health (4 papers), COVID-19 Clinical Research Studies (3 papers), Misinformation and Its Impacts (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Poxvirus research and outbreaks (1 paper) and Galectins and Cancer Biology (1 paper). The work is most often cited by research in Health (620 citations), Modeling and Simulation (313 citations), Infectious Diseases (391 citations), Clinical Psychology (258 citations) and Economics and Econometrics (214 citations). Wan In Wei has collaborated with scholars based in Hong Kong, China and United Kingdom. Frequent co-authors include Samuel Yeung Shan Wong, Kin On Kwok, Arthur Tang, Kin‐Kit Li, Shui Shan Lee, Julian W. Tang, Florence Lai, Yi Yuan, Valerie Wing Yu Wong and Emily Ying Yang Chan. Their work appears in journals such as Journal of Medical Internet Research, Emerging infectious diseases, Clinical Microbiology and Infection, Applied Psychology Health and Well-Being and International Journal of Nursing Studies.

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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