Ruth Studley
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
Papers in
-
- SARS-CoV-2 and COVID-19 Research 3
- COVID-19 Clinical Research Studies 1
- SARS-CoV-2 detection and testing 1
-
- COVID-19 epidemiological studies 3
- Co-authors
- Karina-Doris Vihta (6 shared papers)Nicole Stoesser (6 shared papers)Ian Diamond (6 shared papers)David W. Eyre (6 shared papers)Emma Pritchard (6 shared papers)Thomas House (5 shared papers)Koen B. Pouwels (6 shared papers)Philippa C. Matthews (6 shared papers)
- Journals
- Nature Medicine (2 papers)Clinical Infectious Diseases (1 paper)The Lancet Microbe (1 paper)American Journal of Epidemiology (1 paper)eLife (1 paper)
- Partner nations
- United KingdomAustraliaCanada
In The Last Decade
Ruth Studley
7 papers receiving 666 citations
Ruth Studley's Hit Papers
Peers
Comparison fields: 5 of 76
- Modeling and Simulation 153
- Infectious Diseases 491
- Health 143
- Sensory Systems 25
- Neurology 43
Countries citing papers authored by Ruth Studley
This map shows the geographic impact of Ruth Studley'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 Ruth Studley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruth Studley more than expected).
Fields of papers citing papers by Ruth Studley
This network shows the impact of papers produced by Ruth Studley. 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 Ruth Studley. The network helps show where Ruth Studley may publish in the future.
Co-authors
The 25 scholars most cited alongside Ruth Studley, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Effect of Delta variant on viral burden and vaccine effectiveness against new SARS-CoV-2 infections in the UK Hit paper breakdown → | 2021 | 335 |
| 2 | 2021 | 185 | |
| 3 | 2021 | 68 | |
| 4 | 2022 | 66 | |
| 5 | 2021 | 11 | |
| 6 | 2022 | 6 | |
| 7 | 2024 | 2 | |
| 8 | 2025 | 0 |
About Ruth Studley
Ruth Studley is a scholar working on Infectious Diseases, Modeling and Simulation, Health, Epidemiology and Organic Chemistry, having authored 8 papers that have together received 673 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (3 papers), COVID-19 epidemiological studies (3 papers), COVID-19 Clinical Research Studies (1 paper), Vaccine Coverage and Hesitancy (1 paper), SARS-CoV-2 detection and testing (1 paper) and Data-Driven Disease Surveillance (1 paper). The work is most often cited by research in Modeling and Simulation (153 citations), Infectious Diseases (491 citations), Health (143 citations), Sensory Systems (25 citations) and Neurology (43 citations). Ruth Studley has collaborated with scholars based in United Kingdom, Australia and Canada. Frequent co-authors include Karina-Doris Vihta, Nicole Stoesser, Ian Diamond, David W. Eyre, Emma Pritchard, Thomas House, Koen B. Pouwels, Philippa C. Matthews, Emma Rourke and John I. Bell. Their work appears in journals such as Nature Medicine, Clinical Infectious Diseases, The Lancet Microbe, American Journal of Epidemiology and eLife.
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.