Center for Disease Dynamics, Economics & Policy
Impact in
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- Antibiotic Use and Resistance
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies
Papers in
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- COVID-19 epidemiological studies 280
- Top scholars
- Edward C. HolmesMarc LipsitchBryan T. GrenfellRamanan LaxminarayanMatthew B. ThomasAndrew F. ReadPeter J. HudsonMarcel Salathé
- Journals
- Proceedings of the National Academy of Sciences (82 papers)PLoS ONE (81 papers)Journal of Virology (63 papers)Scientific Reports (58 papers)PLoS Pathogens (46 papers)
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
Center for Disease Dynamics, Economics & Policy
2.0k papers receiving 132.3k citations
Peers
Comparison fields: 5 of 240
- Applied Microbiology and Biotechnology 6.6k
- Modeling and Simulation 12.4k
- Infectious Diseases 28.5k
- Molecular Medicine 7.8k
- Endocrinology 5.5k
Countries citing scholars working at Center for Disease Dynamics, Economics & Policy
This map shows the geographic impact of research produced by authors working at Center for Disease Dynamics, Economics & Policy. 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 papers produced at Center for Disease Dynamics, Economics & Policy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Center for Disease Dynamics, Economics & Policy more than expected).
Fields of papers published by authors at Center for Disease Dynamics, Economics & Policy
This network shows the impact of papers affiliated with Center for Disease Dynamics, Economics & Policy at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Center for Disease Dynamics, Economics & Policy at the time of their publication.
About Center for Disease Dynamics, Economics & Policy
In recent decades, authors affiliated with Center for Disease Dynamics, Economics & Policy have published 2.2k papers, which have received a total of 143.3k indexed citations . Scholars at this organization have produced 281 papers in Modeling and Simulation, 90 papers in Applied Microbiology and Biotechnology, 505 papers in Infectious Diseases, 92 papers in Molecular Medicine and 467 papers in Public Health, Environmental and Occupational Health on the topics of COVID-19 epidemiological studies (280 papers), Mosquito-borne diseases and control (231 papers), Malaria Research and Control (198 papers), Influenza Virus Research Studies (183 papers), Viral Infections and Vectors (160 papers), Evolution and Genetic Dynamics (155 papers), Animal Disease Management and Epidemiology (123 papers) and Insect symbiosis and bacterial influences (110 papers). Their work is cited by papers focused on Applied Microbiology and Biotechnology (6.6k citations), Modeling and Simulation (12.4k citations), Infectious Diseases (28.5k citations), Molecular Medicine (7.8k citations) and Endocrinology (5.5k citations). Authors at Center for Disease Dynamics, Economics & Policy collaborate with scholars in United States, United Kingdom and Australia and have published in prestigious journals including Proceedings of the National Academy of Sciences, PLoS ONE, Journal of Virology, Scientific Reports and PLoS Pathogens. Some of Center for Disease Dynamics, Economics & Policy's most productive authors include Edward C. Holmes, Marc Lipsitch, Bryan T. Grenfell, Ramanan Laxminarayan, Matthew B. Thomas, Andrew F. Read, Peter J. Hudson, Marcel Salathé, Marilyn J. Roossinck and Ramanan Laxminarayan.
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.