Katelynn Devinney
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
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- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
Papers in
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- COVID-19 epidemiological studies 4
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- SARS-CoV-2 and COVID-19 Research 2
- Co-authors
- Emily McGibbon (4 shared papers)Jennifer Baumgartner (4 shared papers)Corinne N. Thompson (3 shared papers)Mary Huynh (2 shared papers)Wenhui Li (1 shared paper)Hiu Tai Chan (1 shared paper)Demetre Daskalakis (1 shared paper)Kevin Konty (1 shared paper)
- Journals
- MMWR Morbidity and Mortality Weekly Report (3 papers)Journal of Artificial Societies and Social Simulation (1 paper)Journal of the American Medical Informatics Association (1 paper)Vaccine X (1 paper)Food Protection Trends (1 paper)
- Partner nations
- United States
In The Last Decade
Katelynn Devinney
9 papers receiving 206 citations
Peers
Comparison fields: 5 of 64
- Modeling and Simulation 51
- Infectious Diseases 78
- Health 25
- Oncology 65
- Health, Toxicology and Mutagenesis 23
Countries citing papers authored by Katelynn Devinney
This map shows the geographic impact of Katelynn Devinney'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 Katelynn Devinney with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Katelynn Devinney more than expected).
Fields of papers citing papers by Katelynn Devinney
This network shows the impact of papers produced by Katelynn Devinney. 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 Katelynn Devinney. The network helps show where Katelynn Devinney may publish in the future.
Co-authors
The 25 scholars most cited alongside Katelynn Devinney, 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 | 2020 | 124 | |
| 2 | 2017 | 36 | |
| 3 | 2021 | 36 | |
| 4 | 2021 | 7 | |
| 5 | 2018 | 5 | |
| 6 | 2022 | 2 | |
| 7 | 2025 | 1 | |
| 8 | 2021 | 1 | |
| 9 | 2024 | 1 |
About Katelynn Devinney
Katelynn Devinney is a scholar working on Modeling and Simulation, Infectious Diseases, Epidemiology, Endocrinology and Food Science, having authored 9 papers that have together received 213 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (4 papers), Data-Driven Disease Surveillance (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Pediatric health and respiratory diseases (1 paper), Food Supply Chain Traceability (1 paper), Salmonella and Campylobacter epidemiology (1 paper), Food Safety and Hygiene (1 paper) and Listeria monocytogenes in Food Safety (1 paper). The work is most often cited by research in Modeling and Simulation (51 citations), Infectious Diseases (78 citations), Health (25 citations), Oncology (65 citations) and Health, Toxicology and Mutagenesis (23 citations). Katelynn Devinney has collaborated with scholars based in United States. Frequent co-authors include Emily McGibbon, Jennifer Baumgartner, Corinne N. Thompson, Mary Huynh, Wenhui Li, Hiu Tai Chan, Demetre Daskalakis, Kevin Konty, Joseph Kennedy and Kevin Guerra. Their work appears in journals such as MMWR Morbidity and Mortality Weekly Report, Journal of Artificial Societies and Social Simulation, Journal of the American Medical Informatics Association, Vaccine X and Food Protection Trends.
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.