Maya Monroe
Impact in
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
-
- Influenza Virus Research Studies
- Respiratory viral infections research
- Pneumonia and Respiratory Infections
Papers in ⓘ
- Epidemiology 12
- Influenza Virus Research Studies 11
- Respiratory viral infections research 8
-
- COVID-19 epidemiological studies 3
- Co-authors
- Ann Thomas (10 shared papers)Nancy M. Bennett (9 shared papers)William Schaffner (9 shared papers)Evan J. Anderson (10 shared papers)Ruth Lynfield (7 shared papers)Laurie M. Billing (4 shared papers)Shikha Garg (8 shared papers)Jan Baumbach (4 shared papers)
- Journals
- Open Forum Infectious Diseases (6 papers)Clinical Infectious Diseases (2 papers)The Journal of Infectious Diseases (1 paper)Annals of Internal Medicine (1 paper)Influenza and Other Respiratory Viruses (1 paper)
- Partner nations
- United StatesKenyaCanada
In The Last Decade
Maya Monroe
11 papers receiving 200 citations
Peers
Comparison fields: 5 of 44
- Modeling and Simulation 24
- Epidemiology 168
- Infectious Diseases 58
- Health 26
- Cardiology and Cardiovascular Medicine 20
Countries citing papers authored by Maya Monroe
This map shows the geographic impact of Maya Monroe'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 Maya Monroe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya Monroe more than expected).
Fields of papers citing papers by Maya Monroe
This network shows the impact of papers produced by Maya Monroe. 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 Maya Monroe. The network helps show where Maya Monroe may publish in the future.
Co-authors
The 25 scholars most cited alongside Maya Monroe, 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 | 86 | |
| 2 | 2015 | 52 | |
| 3 | 2016 | 27 | |
| 4 | 2022 | 14 | |
| 5 | 2018 | 12 | |
| 6 | 2013 | 7 | |
| 7 | 2020 | 2 | |
| 8 | 2016 | 2 | |
| 9 | 2017 | 1 | |
| 10 | 2017 | 1 | |
| 11 | 2020 | 1 | |
| 12 | 2017 | 0 |
About Maya Monroe
Maya Monroe is a scholar working on Epidemiology, Modeling and Simulation, Genetics, Infectious Diseases and Health, having authored 12 papers that have together received 205 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (11 papers), Respiratory viral infections research (8 papers), COVID-19 epidemiological studies (3 papers), Diabetes and associated disorders (2 papers), Smoking Behavior and Cessation (1 paper), Animal Disease Management and Epidemiology (1 paper), Cardiovascular Effects of Exercise (1 paper) and Vaccine Coverage and Hesitancy (1 paper). The work is most often cited by research in Modeling and Simulation (24 citations), Epidemiology (168 citations), Infectious Diseases (58 citations), Health (26 citations) and Cardiology and Cardiovascular Medicine (20 citations). Maya Monroe has collaborated with scholars based in United States, Kenya and Canada. Frequent co-authors include Ann Thomas, Nancy M. Bennett, William Schaffner, Evan J. Anderson, Ruth Lynfield, Laurie M. Billing, Shikha Garg, Jan Baumbach, Rachel Herlihy and Sue Kim. Their work appears in journals such as Open Forum Infectious Diseases, Clinical Infectious Diseases, The Journal of Infectious Diseases, Annals of Internal Medicine and Influenza and Other Respiratory Viruses.
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.