Don E. Willis

2.2k citations
87 papers · 1.4k indexed · 1 hit paper · h-index 20

Don E. Willis

78 papers receiving 1.4k citations

Hit Papers

COVID‐19 vaccine hesitancy: Race/ethnicity, trust, and fear256202120262022202450100150200250

Peers

Don E. Willis
Comparison fields: 5 of 101
  • Health 809
  • Modeling and Simulation 200
  • Infectious Diseases 336
  • General Health Professions 434
  • Obstetrics and Gynecology 109
Replace Mohammad S Razai with:
Mohammad S Razai United Kingdom
Alberto Giubilini United Kingdom
Ana Gama Portugal
Katharine J. Head United States
Karen Hilyard United States
Gillian K. SteelFisher United States
Rachael Piltch‐Loeb United States
Annie Wai-Ling Cheung Hong Kong
Michael Wiblishauser United States
Sadie Bell United Kingdom
Don E. Willis relative to Mohammad S Razai United Kingdom Mohammad S Razai's profile →
Citations per field
00.5×1.5×2.0×
Mohammad S Razai · 1×
Citations per year

Countries citing papers authored by Don E. Willis

Since Specialization
Citations

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

Fields of papers citing papers by Don E. Willis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Don E. Willis. 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 Don E. Willis. The network helps show where Don E. Willis may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 20232
4 20233
5 20234
6 20235
7 20232
8 20233
9 202221
10 20222
11 202213
12 20215
13 202114
14 202120
15 202166
16
COVID‐19 vaccine hesitancy: Race/ethnicity, trust, and fearbreakdown →
2021256
17 20211
18 202014
19 201913
20 20199

About Don E. Willis

Don E. Willis is a scholar working on Health, General Health Professions, Obstetrics and Gynecology, Modeling and Simulation and Clinical Psychology, having authored 87 papers that have together received 1.4k indexed citations. Recurring topics across this work include Vaccine Coverage and Hesitancy (35 papers), Food Security and Health in Diverse Populations (25 papers), Homelessness and Social Issues (12 papers), Misinformation and Its Impacts (12 papers), COVID-19 Impact on Reproduction (9 papers), Health disparities and outcomes (9 papers), SARS-CoV-2 and COVID-19 Research (8 papers) and COVID-19 Pandemic Impacts (8 papers). The work is most often cited by research in Health (809 citations), Modeling and Simulation (200 citations), Infectious Diseases (336 citations), General Health Professions (434 citations) and Obstetrics and Gynecology (109 citations). Don E. Willis has collaborated with scholars based in United States and Georgia. Frequent co-authors include Pearl A. McElfish, Kevin M. Fitzpatrick, Jennifer A. Andersen, James P. Selig, Rachel S. Purvis, Keneshia Bryant‐Moore, Ramey Moore, Holly C. Felix, Grant Drawve and Casey T. Harris. Their work appears in journals such as Vaccine, International Journal of Environmental Research and Public Health, Journal of Racial and Ethnic Health Disparities, Vaccines and Clinical and Translational Science.

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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