Aye Moa
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Epidemiology top 10%
- Influenza Virus Research Studies
- Respiratory viral infections research
- Pneumonia and Respiratory Infections
Papers in
- Epidemiology 30
- Influenza Virus Research Studies 19
- Respiratory viral infections research 11
- Data-Driven Disease Surveillance 5
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- Viral Infections and Outbreaks Research 7
- SARS-CoV-2 and COVID-19 Research 6
- Co-authors
- C. Raina MacIntyre (44 shared papers)Michelle Barnes (2 shared papers)Abela Mahimbo (1 shared paper)Abrar Ahmad Chughtai (16 shared papers)Valerie Beral (2 shared papers)Karen Canfell (2 shared papers)David Muscatello (4 shared papers)Emily Banks (1 shared paper)
- Journals
- Vaccine (6 papers)Influenza and Other Respiratory Viruses (5 papers)PLoS ONE (3 papers)International Journal of Cardiology (2 papers)Public Health (2 papers)
- Partner nations
- AustraliaUnited StatesChina
In The Last Decade
Aye Moa
47 papers receiving 736 citations
Peers
Comparison fields: 5 of 111
- Modeling and Simulation 82
- Epidemiology 363
- Infectious Diseases 162
- Health 50
- Oncology 152
Countries citing papers authored by Aye Moa
This map shows the geographic impact of Aye Moa'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 Aye Moa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aye Moa more than expected).
Fields of papers citing papers by Aye Moa
This network shows the impact of papers produced by Aye Moa. 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 Aye Moa. The network helps show where Aye Moa may publish in the future.
Co-authors
The 25 scholars most cited alongside Aye Moa, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 104 | |
| 2 | 2008 | 95 | |
| 3 | 2016 | 66 | |
| 4 | 2014 | 63 | |
| 5 | 2013 | 61 | |
| 6 | 2013 | 44 | |
| 7 | 2014 | 29 | |
| 8 | 2016 | 29 | |
| 9 | 2023 | 24 | |
| 10 | 2016 | 21 | |
| 11 | 2017 | 20 | |
| 12 | 2020 | 17 | |
| 13 | 2013 | 12 | |
| 14 | 2020 | 12 | |
| 15 | 2021 | 11 | |
| 16 | 2019 | 11 | |
| 17 | 2023 | 10 | |
| 18 | 2021 | 10 | |
| 19 | 2019 | 10 | |
| 20 | 2019 | 10 |
About Aye Moa
Aye Moa is a scholar working on Epidemiology, Infectious Diseases, Modeling and Simulation, Surgery and Pulmonary and Respiratory Medicine, having authored 54 papers that have together received 762 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (19 papers), COVID-19 epidemiological studies (12 papers), Respiratory viral infections research (11 papers), Viral Infections and Outbreaks Research (7 papers), SARS-CoV-2 and COVID-19 Research (6 papers), Vaccine Coverage and Hesitancy (5 papers), Data-Driven Disease Surveillance (5 papers) and Infection Control and Ventilation (4 papers). The work is most often cited by research in Modeling and Simulation (82 citations), Epidemiology (363 citations), Infectious Diseases (162 citations), Health (50 citations) and Oncology (152 citations). Aye Moa has collaborated with scholars based in Australia, United States and China. Frequent co-authors include C. Raina MacIntyre, Michelle Barnes, Abela Mahimbo, Abrar Ahmad Chughtai, Valerie Beral, Karen Canfell, David Muscatello, Emily Banks, Robin Turner and Holly Seale. Their work appears in journals such as Vaccine, Influenza and Other Respiratory Viruses, PLoS ONE, International Journal of Cardiology and Public Health.
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.