Sam Abbott

26.4k citations
43 papers · 993 · h-index 14

Impact in

Papers in

Sam Abbott

41 papers receiving 969 citations

Peers

Sam Abbott
Comparison fields: 5 of 97
  • Modeling and Simulation 466
  • Virology 127
  • Infectious Diseases 368
  • Epidemiology 207
  • Public Health, Environmental and Occupational Health 155
Replace Valentina Marziano with:
Valentina Marziano Italy
Junjie Zai China
Giorgio Guzzetta Italy
Mamunur Rahman Malik Egypt
Zachary J. Madewell United States
Changcheng Wu China
Nicki Pesik United States
Ganna Rozhnova Netherlands
Edward A. Wenger United States
Seth Blumberg United States
Sam Abbott relative to Valentina Marziano Italy Valentina Marziano's profile →
Citations per field
00.5×2×3×4.2×
Valentina Marziano · 1×
Citations per year

Countries citing papers authored by Sam Abbott

Since Specialization
Citations

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

Fields of papers citing papers by Sam Abbott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sam Abbott, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sam Abbott Line = papers co-authored together Sam Abbott links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020276
2 2022118
3 2021114
4 202296
5 202051
6 202237
7 202129
8 202128
9 202326
10 202325
11 202020
12 201717
13 202215
14 202313
15 202212
16 202311
17 202310
18
Common source outbreak of relapsing fever: California.
199010
19 20239
20 20249

About Sam Abbott

Sam Abbott is a scholar working on Modeling and Simulation, Infectious Diseases, Epidemiology, Public Health, Environmental and Occupational Health and Virology, having authored 43 papers that have together received 993 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (25 papers), Influenza Virus Research Studies (8 papers), SARS-CoV-2 and COVID-19 Research (5 papers), Data-Driven Disease Surveillance (5 papers), Zoonotic diseases and public health (4 papers), COVID-19 Pandemic Impacts (4 papers), Poxvirus research and outbreaks (4 papers) and Viral Infections and Outbreaks Research (3 papers). The work is most often cited by research in Modeling and Simulation (466 citations), Virology (127 citations), Infectious Diseases (368 citations), Epidemiology (207 citations) and Public Health, Environmental and Occupational Health (155 citations). Sam Abbott has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Sebastian Funk, W. John Edmunds, Ruwan Ratnayake, Kevin van Zandvoort, Stefan Flasche, Joel Hellewell, Adam J. Kucharski, Rosalind M. Eggo, Timothy Russell and Akira Endo. Their work appears in journals such as PLoS Computational Biology, Eurosurveillance, eLife, Science and The Journal of 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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