Freya M. Shearer
- Public Health, Environmental and Occupational Health top 0.5%
- Infectious Diseases top 1%
- Modeling and Simulation top 0.5%
- Genetics top 10%
- Insect Science top 2%
- Co-authors
- Simon I HayDavid M. PigottNick GoldingOliver J. BradyMoritz U. G. KraemerJane P. MessinaSarah E. RayCatherine L. Moyes
- Topics
- COVID-19 epidemiological studies (28 papers)Mosquito-borne diseases and control (14 papers)Viral Infections and Outbreaks Research (10 papers)
- Cited by
- Modeling and SimulationInfectious DiseasesPublic Health, Environmental and Occupational Health
- Journals
- Proceedings of the National Academy of SciencesThe LancetSHILAP Revista de lepidopterología
- Partner nations
- AustraliaUnited KingdomUnited States
In The Last Decade
Freya M. Shearer
50 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Public Health, Environmental and Occupational Health 1.8k
- Infectious Diseases 1.2k
- Modeling and Simulation 483
- Genetics 290
- Insect Science 244
Countries citing papers authored by Freya M. Shearer
This map shows the geographic impact of Freya M. Shearer'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 Freya M. Shearer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Freya M. Shearer more than expected).
Fields of papers citing papers by Freya M. Shearer
This network shows the impact of papers produced by Freya M. Shearer. 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 Freya M. Shearer. The network helps show where Freya M. Shearer may publish in the future.
Co-authorship network of co-authors of Freya M. Shearer
This figure shows the co-authorship network connecting the top 25 collaborators of Freya M. Shearer. A scholar is included among the top collaborators of Freya M. Shearer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Freya M. Shearer. Freya M. Shearer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 8 | |
| 6 | 5 | |
| 7 | 3 | |
| 8 | 2 | |
| 9 | 3 | |
| 10 | 6 | |
| 11 | 16 | |
| 12 | 10 | |
| 13 | 16 | |
| 14 | 5 | |
| 15 | 15 | |
| 16 | 29 | |
| 17 | 18 | |
| 18 | The current and future global distribution and population at risk of denguebreakdown → | 753 |
| 19 | 96 | |
| 20 | 97 |
About Freya M. Shearer
Freya M. Shearer is a scholar working on Modeling and Simulation, Infectious Diseases and Emergency Medical Services, having authored 52 papers that have together received 2.7k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (28 papers), Mosquito-borne diseases and control (14 papers) and Viral Infections and Outbreaks Research (10 papers). The work is most often cited by research in Modeling and Simulation (483 citations), Infectious Diseases (1.2k citations) and Public Health, Environmental and Occupational Health (1.8k citations). Freya M. Shearer has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Simon I Hay, David M. Pigott, Nick Golding, Oliver J. Brady, Moritz U. G. Kraemer, Jane P. Messina, Sarah E. Ray, Catherine L. Moyes, Joshua Longbottom and William Wint. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Lancet and SHILAP Revista de lepidopterología.
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.