Brett Sutton

28 papers receiving 446 citations

Peers

Brett Sutton
Comparison fields: 5 of 87
  • Parasitology 94
  • Modeling and Simulation 58
  • Endocrinology 45
  • Infectious Diseases 127
  • Health 47
Replace Vincent Pommier de Santi with:
Vincent Pommier de Santi France
Tomás Aragón United States
J C Desenclos France
Sapha Barkati Canada
R. Migliani France
Pauline Han United States
Maja Sočan Slovenia
Aroop Mohanty India
Stefan Hagmann United States
P Kreidl Austria
Brett Sutton relative to Vincent Pommier de Santi France Vincent Pommier de Santi's profile →
Citations per field
00.5×1.5×
Vincent Pommier de Santi · 1×
Citations per year

Countries citing papers authored by Brett Sutton

Since Specialization
Citations

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

Fields of papers citing papers by Brett Sutton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201568
2 202156
3 201739
4 201138
5 201936
6 201529
7 201426
8 202022
9 202119
10 201718
11 200118
12 201814
13 202312
14 202310
15 202410
16 20209
17 20226
18 20235
19 20205
20 20144

About Brett Sutton

Brett Sutton is a scholar working on Infectious Diseases, Epidemiology, Modeling and Simulation, Public Health, Environmental and Occupational Health and Health, having authored 31 papers that have together received 461 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (8 papers), Influenza Virus Research Studies (5 papers), Vaccine Coverage and Hesitancy (3 papers), Vector-Borne Animal Diseases (3 papers), Vector-borne infectious diseases (3 papers), COVID-19 and Mental Health (3 papers), Zoonotic diseases and public health (2 papers) and Viral gastroenteritis research and epidemiology (2 papers). The work is most often cited by research in Parasitology (94 citations), Modeling and Simulation (58 citations), Endocrinology (45 citations), Infectious Diseases (127 citations) and Health (47 citations). Brett Sutton has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Katherine Bond, Simon M. Firestone, Lucinda Franklin, Andrew A. Lover, Annelies Wilder‐Smith, Nicola Stephens, Mary Valcanis, Allen Cheng, Richard A. Powell and Mila Petrova. Their work appears in journals such as The Medical Journal of Australia, Clinical Infectious Diseases, BMC Public Health, The Lancet Regional Health - Western Pacific and PLoS Currents.

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.

Explore authors with similar magnitude of impact