Jon Brassey

1.4k citations
42 papers · 850 · h-index 17

Impact in

Papers in

Jon Brassey

40 papers receiving 827 citations

Peers

Jon Brassey
Comparison fields: 5 of 110
  • Modeling and Simulation 112
  • Infectious Diseases 353
  • General Dentistry 21
  • Statistics, Probability and Uncertainty 47
  • Pulmonary and Respiratory Medicine 163
Replace Michelle O’Neill with:
Michelle O’Neill Ireland
Jessica J Bartoszko Canada
Hira Imeri Switzerland
Stefanie Hossmann Switzerland
Tom Jefferson United Kingdom
Eric A. Meyerowitz United States
Bonnie Arquilla United States
Wee Hoe Gan Singapore
Daniel Bekele Ketema Ethiopia
Amy Zheng United States
Jon Brassey relative to Michelle O’Neill Ireland Michelle O’Neill's profile →
Citations per field
00.5×4.7×
Michelle O’Neill · 1×
Citations per year

Countries citing papers authored by Jon Brassey

Since Specialization
Citations

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

Fields of papers citing papers by Jon Brassey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020175
2 201868
3 201858
4 202157
5 200156
6 202048
7 202138
8 202135
9 200733
10 202130
11 202128
12 202128
13 202125
14 201024
15 202218
16 202117
17 202216
18 201915
19
SARS-CoV-2 viral load and the severity of COVID-19
202013
20 202111

About Jon Brassey

Jon Brassey is a scholar working on Infectious Diseases, Modeling and Simulation, Pulmonary and Respiratory Medicine, General Health Professions and Artificial Intelligence, having authored 42 papers that have together received 850 indexed citations. Recurring topics across this work include SARS-CoV-2 detection and testing (15 papers), SARS-CoV-2 and COVID-19 Research (13 papers), COVID-19 epidemiological studies (10 papers), Infection Control and Ventilation (9 papers), COVID-19 Clinical Research Studies (5 papers), Health Sciences Research and Education (4 papers), Meta-analysis and systematic reviews (4 papers) and COVID-19 and healthcare impacts (3 papers). The work is most often cited by research in Modeling and Simulation (112 citations), Infectious Diseases (353 citations), General Dentistry (21 citations), Statistics, Probability and Uncertainty (47 citations) and Pulmonary and Respiratory Medicine (163 citations). Jon Brassey has collaborated with scholars based in United Kingdom, Canada and Slovakia. Frequent co-authors include Elizabeth Spencer, Carl Heneghan, Tom Jefferson, Annette Plüddemann, Igho Onakpoya, David H. Evans, John Conly, Kamal R Mahtani, Paul Glasziou and Iain Marshall. Their work appears in journals such as F1000Research, BMJ evidence-based medicine, Journal of Hospital Infection, BMC Medical Research Methodology and New Review of Information Networking.

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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