Kylie E. C. Ainslie

15.8k citations
35 papers · 950 indexed · 1 hit paper · h-index 14
Topics
COVID-19 epidemiological studies (19 papers)SARS-CoV-2 and COVID-19 Research (14 papers)Influenza Virus Research Studies (11 papers)

In The Last Decade

Kylie E. C. Ainslie

34 papers receiving 928 citations

Hit Papers

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

Peers

Kylie E. C. Ainslie
Comparison fields: 5 of 98
  • Infectious Diseases 530
  • Modeling and Simulation 478
  • Epidemiology 225
  • Economics and Econometrics 157
  • Health 136
Replace Cécile Tran Kiem with:
Cécile Tran Kiem France
Alessio Andronico France
Valentina Marziano Italy
Shanlu Zhao China
Nana Owusu‐Boaitey United States
Noémie Lefrancq France
Tiffany Leung United States
Thomas N. Vilches Canada
Kylie E. C. Ainslie relative to Cécile Tran Kiem France Cécile Tran Kiem's profile →
Citations per field
00.5×1.6×
Cécile Tran Kiem · 1×
Citations per year

Countries citing papers authored by Kylie E. C. Ainslie

Since Specialization
Citations

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

Fields of papers citing papers by Kylie E. C. Ainslie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kylie E. C. Ainslie. 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 Kylie E. C. Ainslie. The network helps show where Kylie E. C. Ainslie may publish in the future.

Co-authorship network of co-authors of Kylie E. C. Ainslie

This figure shows the co-authorship network connecting the top 25 collaborators of Kylie E. C. Ainslie. A scholar is included among the top collaborators of Kylie E. C. Ainslie 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 Kylie E. C. Ainslie. Kylie E. C. Ainslie 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
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5 6
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11 17
12 14
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14 18
15 110
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17 65
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About Kylie E. C. Ainslie

Kylie E. C. Ainslie is a scholar working on Modeling and Simulation, Health and Infectious Diseases, having authored 35 papers that have together received 950 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (19 papers), SARS-CoV-2 and COVID-19 Research (14 papers) and Influenza Virus Research Studies (11 papers). The work is most often cited by research in Modeling and Simulation (478 citations), Infectious Diseases (530 citations) and Health (136 citations). Kylie E. C. Ainslie has collaborated with scholars based in United Kingdom, Netherlands and United States. Frequent co-authors include Michael Haber, Christl A. Donnelly, Steven Riley, Helen Ward, William Barclay, Graham Cooke, Deborah Ashby, Christina Atchison, Paul Elliott and Ara Darzi. Their work appears in journals such as Science, Nucleic Acids Research and Nature Communications.

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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