Timothy M. Uyeki
- Modeling and Simulation top 0.05%
- COVID-19 epidemiological studies 26
- Infectious Diseases top 0.05%
- Viral Infections and Vectors 38
- Viral gastroenteritis research and epidemiology 32
- Viral Infections and Outbreaks Research 32
- Epidemiology top 0.05%
- Influenza Virus Research Studies 178
- Respiratory viral infections research 109
- Pneumonia and Respiratory Infections 25
- Health top 0.2%
- Agronomy and Crop Science top 0.2%
- Animal Disease Management and Epidemiology 44
- Co-authors
- David K. ShayJoseph BreseeAnthony E. FioreNancy J. CoxAlicia M. FryKaren R. BroderJohn K. IskanderGina T. Mootrey
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Timothy M. Uyeki
226 papers receiving 16.6k citations
Hit Papers
Peers
Comparison fields: 5 of 187
- Modeling and Simulation 1.9k
- Infectious Diseases 6.8k
- Epidemiology 12.1k
- Health 1.4k
- Agronomy and Crop Science 1.6k
Countries citing papers authored by Timothy M. Uyeki
This map shows the geographic impact of Timothy M. Uyeki'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 Timothy M. Uyeki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Timothy M. Uyeki more than expected).
Fields of papers citing papers by Timothy M. Uyeki
This network shows the impact of papers produced by Timothy M. Uyeki. 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 Timothy M. Uyeki. The network helps show where Timothy M. Uyeki may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Timothy M. Uyeki, 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 | 2025 | 0 | |
| 2 | Highly Pathogenic Avian Influenza A(H5N1) Virus Infection of Indoor Domestic Cats Within Dairy Industry Worker Households — Michigan, May 2024breakdown → | 2025 | 19 |
| 3 | 2025 | 1 | |
| 4 | 2025 | 0 | |
| 5 | 2025 | 0 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 1 | |
| 9 | 2023 | 5 | |
| 10 | 2023 | 3 | |
| 11 | 2022 | 3 | |
| 12 | 2021 | 10 | |
| 13 | Facemasks and Hand Hygiene to Prevent Influenza Transmission in Households | 2020 | 2 |
| 14 | Influenza-associated intensive-care unit admissions and deaths - California, September 29, 2013-January 18, 2014. | 2014 | 22 |
| 15 | 2013 | 28 | |
| 16 | 2012 | 287 | |
| 17 | 2011 | 11 | |
| 18 | 2010 | 248 | |
| 19 | Evaluation of rapid influenza diagnostic tests for detection of novel influenza A (H1N1) virus - United States, 2009. | 2009 | 231 |
| 20 | 2006 | 80 |
About Timothy M. Uyeki
Timothy M. Uyeki is a scholar working on Infectious Diseases, Modeling and Simulation and Epidemiology, having authored 235 papers that have together received 17.2k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (178 papers), Respiratory viral infections research (109 papers), Animal Disease Management and Epidemiology (44 papers), Viral Infections and Vectors (38 papers), Viral gastroenteritis research and epidemiology (32 papers), Viral Infections and Outbreaks Research (32 papers), COVID-19 epidemiological studies (26 papers) and Pneumonia and Respiratory Infections (25 papers). The work is most often cited by research in Modeling and Simulation (1.9k citations), Infectious Diseases (6.8k citations) and Epidemiology (12.1k citations). Timothy M. Uyeki has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include David K. Shay, Joseph Bresee, Anthony E. Fiore, Nancy J. Cox, Alicia M. Fry, Karen R. Broder, John K. Iskander, Gina T. Mootrey, Frederick G. Hayden and Eric J. Chow. Their work appears in journals such as Science, New England Journal of Medicine and The Lancet.
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.