Matthew Feaster
Impact in
- Infectious Diseases top 10%
- SARS-CoV-2 detection and testing
- SARS-CoV-2 and COVID-19 Research
- HIV/AIDS Research and Interventions
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
Papers in
-
- SARS-CoV-2 detection and testing 6
- SARS-CoV-2 and COVID-19 Research 5
-
- Workplace Health and Well-being 2
- Co-authors
- Ying-Ying Goh (8 shared papers)Niklas Krause (2 shared papers)Alexander Viloria Winnett (6 shared papers)Rustem F. Ismagilov (6 shared papers)Reid Akana (4 shared papers)Anna E. Romano (4 shared papers)Jacob T. Barlow (2 shared papers)Serena Rajabiun (1 shared paper)
- Journals
- American Journal of Industrial Medicine (2 papers)Microbiology Spectrum (2 papers)MMWR Morbidity and Mortality Weekly Report (1 paper)Vaccine (1 paper)Journal of Clinical Microbiology (1 paper)
- Partner nations
- United StatesThailand
In The Last Decade
Matthew Feaster
13 papers receiving 208 citations
Peers
Comparison fields: 5 of 56
- Infectious Diseases 131
- Modeling and Simulation 27
- General Dentistry 5
- General Health Professions 61
- Health 11
Countries citing papers authored by Matthew Feaster
This map shows the geographic impact of Matthew Feaster'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 Matthew Feaster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Feaster more than expected).
Fields of papers citing papers by Matthew Feaster
This network shows the impact of papers produced by Matthew Feaster. 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 Matthew Feaster. The network helps show where Matthew Feaster may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew Feaster, 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 | 2021 | 59 | |
| 2 | 2020 | 47 | |
| 3 | 2018 | 39 | |
| 4 | 2018 | 14 | |
| 5 | 2023 | 13 | |
| 6 | 2019 | 9 | |
| 7 | 2023 | 8 | |
| 8 | 2023 | 8 | |
| 9 | 2022 | 7 | |
| 10 | 2023 | 4 | |
| 11 | 2025 | 2 | |
| 12 | 2024 | 1 | |
| 13 | 2025 | 1 | |
| 14 | 2025 | 0 |
About Matthew Feaster
Matthew Feaster is a scholar working on Infectious Diseases, General Health Professions, Radiology, Nuclear Medicine and Imaging, Epidemiology and Public Health, Environmental and Occupational Health, having authored 14 papers that have together received 212 indexed citations. Recurring topics across this work include SARS-CoV-2 detection and testing (6 papers), SARS-CoV-2 and COVID-19 Research (5 papers), COVID-19 diagnosis using AI (3 papers), Workplace Health and Well-being (2 papers), Vector-borne infectious diseases (2 papers), Mosquito-borne diseases and control (2 papers), Infection Control and Ventilation (1 paper) and Yersinia bacterium, plague, ectoparasites research (1 paper). The work is most often cited by research in Infectious Diseases (131 citations), Modeling and Simulation (27 citations), General Dentistry (5 citations), General Health Professions (61 citations) and Health (11 citations). Matthew Feaster has collaborated with scholars based in United States and Thailand. Frequent co-authors include Ying-Ying Goh, Niklas Krause, Alexander Viloria Winnett, Rustem F. Ismagilov, Reid Akana, Anna E. Romano, Jacob T. Barlow, Serena Rajabiun, Howard Cabral and Amy Pan. Their work appears in journals such as American Journal of Industrial Medicine, Microbiology Spectrum, MMWR Morbidity and Mortality Weekly Report, Vaccine and Journal of Clinical Microbiology.
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.