Ira M. Longini

216 papers and 19.0k indexed citations i.

About

Ira M. Longini is a scholar working on Modeling and Simulation, Epidemiology and Infectious Diseases. According to data from OpenAlex, Ira M. Longini has authored 216 papers receiving a total of 19.0k indexed citations (citations by other indexed papers that have themselves been cited), including 115 papers in Modeling and Simulation, 107 papers in Epidemiology and 88 papers in Infectious Diseases. Recurrent topics in Ira M. Longini’s work include COVID-19 epidemiological studies (115 papers), Influenza Virus Research Studies (77 papers) and Vaccine Coverage and Hesitancy (30 papers). Ira M. Longini is often cited by papers focused on COVID-19 epidemiological studies (115 papers), Influenza Virus Research Studies (77 papers) and Vaccine Coverage and Hesitancy (30 papers). Ira M. Longini collaborates with scholars based in United States, South Africa and United Kingdom. Ira M. Longini's co-authors include M. Elizabeth Halloran, James S. Koopman, Dennis L. Chao, Azhar Nizam, Alessandro Vespignani, Ana Pastore y Piontti, Natalie E. Dean, M. Elizabeth Halloran, Arnold S. Monto and Stefano Merler and has published in prestigious journals such as Nature, Science and New England Journal of Medicine.

In The Last Decade

Co-authorship network of co-authors of Ira M. Longini i

Fields of papers citing papers by Ira M. Longini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ira M. Longini. 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 Ira M. Longini. The network helps show where Ira M. Longini may publish in the future.

Countries citing papers authored by Ira M. Longini

Since Specialization
Citations

This map shows the geographic impact of Ira M. Longini'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 Ira M. Longini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ira M. Longini more than expected).

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.

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