Kris V. Parag

11.5k citations
38 papers · 726 indexed · 1 hit paper · h-index 14
Topics
COVID-19 epidemiological studies (25 papers)Data-Driven Disease Surveillance (12 papers)Influenza Virus Research Studies (10 papers)

In The Last Decade

Kris V. Parag

35 papers receiving 707 citations

Hit Papers

Estimating the effects of non-pharmaceutical intervention...20202026202220242020100200300

Peers

Kris V. Parag
Comparison fields: 5 of 98
  • Modeling and Simulation 460
  • Infectious Diseases 237
  • Epidemiology 190
  • Economics and Econometrics 139
  • Public Health, Environmental and Occupational Health 114
Replace Sam Abbott with:
Sam Abbott United Kingdom
Nathanaël Hozé France
Jon Parker United States
King-Pan Chan Hong Kong
Laura Fumanelli Italy
Xiaodan Sun China
Caitlin Rivers United States
Ana I. Bento United States
Spencer J. Fox United States
Áine B. Collins Ireland
Kris V. Parag relative to Sam Abbott United Kingdom Sam Abbott's profile →
Citations per field
00.5×
Sam Abbott · 1×
Citations per year

Countries citing papers authored by Kris V. Parag

Since Specialization
Citations

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

Fields of papers citing papers by Kris V. Parag

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kris V. Parag. 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 Kris V. Parag. The network helps show where Kris V. Parag may publish in the future.

Co-authorship network of co-authors of Kris V. Parag

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 20
4 6
5 6
6 2
7 8
8 6
9 14
10 1
11 4
12 32
13 7
14 7
15 21
16 15
17 23
18 16
19 4
20 8

About Kris V. Parag

Kris V. Parag is a scholar working on Modeling and Simulation, Epidemiology and Infectious Diseases, having authored 38 papers that have together received 726 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (25 papers), Data-Driven Disease Surveillance (12 papers) and Influenza Virus Research Studies (10 papers). The work is most often cited by research in Modeling and Simulation (460 citations), Infectious Diseases (237 citations) and Epidemiology (190 citations). Kris V. Parag has collaborated with scholars based in United Kingdom, Hong Kong and Brazil. Frequent co-authors include Christl A. Donnelly, Oliver G. Pybus, Robin N. Thompson, Benjamin J. Cowling, Louis du Plessis, Glenn Vinnicombe, Alexander E. Zarebski, Caroline E. Walters, Kylie E. C. Ainslie and H. Juliette T. Unwin. Their work appears in journals such as Nature Communications, Bioinformatics and American Journal of Epidemiology.

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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