Susan Reed

1.1k total citations
10 papers, 629 citations indexed

About

Susan Reed is a scholar working on Epidemiology, Infectious Diseases and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Susan Reed has authored 10 papers receiving a total of 629 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Epidemiology, 3 papers in Infectious Diseases and 2 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Susan Reed's work include Influenza Virus Research Studies (8 papers), Respiratory viral infections research (7 papers) and Viral gastroenteritis research and epidemiology (2 papers). Susan Reed is often cited by papers focused on Influenza Virus Research Studies (8 papers), Respiratory viral infections research (7 papers) and Viral gastroenteritis research and epidemiology (2 papers). Susan Reed collaborates with scholars based in United States and Netherlands. Susan Reed's co-authors include Matthew J. Memoli, Rani Athota, Lindsay Czajkowski, Jeffery K. Taubenberger, Tyler Bristol, Alison Han, Richard T. Davey, Pamela A. Shaw, John H. Powers and Adriana Cervantes-Medina and has published in prestigious journals such as The Lancet, Clinical Infectious Diseases and mBio.

In The Last Decade

Susan Reed

10 papers receiving 616 citations

Peers

Susan Reed
Comparison fields: 5 of 60
  • Epidemiology 442
  • Infectious Diseases 237
  • Immunology 136
  • Molecular Biology 76
  • Modeling and Simulation 65
Replace Rani Athota with:
Rani Athota United States
Lindsay Czajkowski United States
Alison Han United States
Louise Carolan Australia
Steve Rockman Australia
Jessica Tan United States
Fabrice Bailleux France
De Jong Netherlands
Matthijs R. A. Welkers Netherlands
Annelies W. Mesman United States
Rani Athota United States View profile →
Citations per field, relative to Susan Reed
Susan Reed · 1×
Citations per year, relative to Susan Reed
Susan Reed · 1×

Countries citing papers authored by Susan Reed

Since Specialization
Citations

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

Fields of papers citing papers by Susan Reed

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Susan Reed. 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 Susan Reed. The network helps show where Susan Reed may publish in the future.

Co-authorship network of co-authors of Susan Reed

This figure shows the co-authorship network connecting the top 25 collaborators of Susan Reed. A scholar is included among the top collaborators of Susan Reed 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 Susan Reed. Susan Reed is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
# Work Indexed citations
1 9
2 45
3 9
4 36
5 40
6 1
7 42
8 68
9 272
10 107

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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