Preethi Sundararaman

662 citations
6 papers · 393 indexed · 1 hit paper · h-index 4
Topics
Salmonella and Campylobacter epidemiology (5 papers)Viral gastroenteritis research and epidemiology (2 papers)Antibiotic Resistance in Bacteria (2 papers)
Partner nations
United States

In The Last Decade

Preethi Sundararaman

5 papers receiving 380 citations

Hit Papers

Geographic Differences in COVID-19 Cases, Deaths, and Inc...20202026202220242020100200300

Peers

Preethi Sundararaman
Comparison fields: 5 of 87
  • Modeling and Simulation 112
  • Infectious Diseases 102
  • Oncology 93
  • Clinical Psychology 78
  • General Health Professions 64
Replace Thi Mui Pham with:
Thi Mui Pham Netherlands
Cheng-Yin Tseng Taiwan
Amy Carter United States
Cristina Sotomayor‐Castillo Australia
Mary Eyram Ashinyo Ghana
J. Stevenson United Kingdom
Farah Husain United States
Frida Rivera‐Buendía Mexico
Lisa Domegan Ireland
Elisabeth Wilhelm United States
Preethi Sundararaman relative to Thi Mui Pham Netherlands Thi Mui Pham's profile →
Citations per field
00.5×4.8×
Thi Mui Pham · 1×
Citations per year

Countries citing papers authored by Preethi Sundararaman

Since Specialization
Citations

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

Fields of papers citing papers by Preethi Sundararaman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Preethi Sundararaman

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

All Works

6 of 6 papers shown
#WorkIndexed citations
1 0
2 10
3 13
4
Geographic Differences in COVID-19 Cases, Deaths, and Incidence — United States, February 12–April 7, 2020breakdown →
343
5 26
6 1

About Preethi Sundararaman

Preethi Sundararaman is a scholar working on Molecular Medicine, Food Science and Modeling and Simulation, having authored 6 papers that have together received 393 indexed citations. Recurring topics across this work include Salmonella and Campylobacter epidemiology (5 papers), Viral gastroenteritis research and epidemiology (2 papers) and Antibiotic Resistance in Bacteria (2 papers). The work is most often cited by research in Modeling and Simulation (112 citations), Health (47 citations) and Infectious Diseases (102 citations). Preethi Sundararaman has collaborated with scholars based in United States. Frequent co-authors include Hilary K. Whitham, Stephanie R. Bialek, Aaron T. Curns, Katherine Roguski, Benjamin J. Silk, Tamara Pilishvili, John T. Wen, Ryan Gierke, Matthew D. Ritchey and Michelle M. Hughes. Their work appears in journals such as Emerging infectious diseases, MMWR Morbidity and Mortality Weekly Report and Open Forum Infectious Diseases.

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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