Mathematical Epidemiology of Infectious Diseases
Impact in
Classified as
- Authors
- Odo Diekmann
- Journal
- Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands
In The Last Decade
doi.org/w80348282 →Countries where authors are citing Mathematical Epidemiology of Infectious Diseases
This map shows the geographic impact of Mathematical Epidemiology of Infectious Diseases. 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 Mathematical Epidemiology of Infectious Diseases with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathematical Epidemiology of Infectious Diseases more than expected).
Fields of papers citing Mathematical Epidemiology of Infectious Diseases
This network shows the impact of Mathematical Epidemiology of Infectious Diseases. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Mathematical Epidemiology of Infectious Diseases.
About Mathematical Epidemiology of Infectious Diseases
This paper, published in 1996, received 565 indexed citations . Written by Odo Diekmann covering the research area of Modeling and Simulation. It is primarily cited by scholars working on Modeling and Simulation (325 citations), Public Health, Environmental and Occupational Health (320 citations), Genetics (163 citations), Epidemiology (93 citations) and Infectious Diseases (82 citations). Published in Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands.
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.
This paper is also available at doi.org/w80348282.