Danielle Eddy

1.4k citations
7 papers · 915 · 2 hit papers · h-index 6

Impact in

Papers in

    • COVID-19 Clinical Research Studies 3
    • SARS-CoV-2 and COVID-19 Research 3
    • SARS-CoV-2 detection and testing 1
    • Long-Term Effects of COVID-19 1

Danielle Eddy

7 papers receiving 898 citations

Danielle Eddy's Hit Papers

T cell response to SARS-CoV-2 infection in humans: A systematic review 2021 · 258 citations
2580+2+4Years since publication50100150200250

Peers

Danielle Eddy
Comparison fields: 5 of 82
  • Infectious Diseases 545
  • Modeling and Simulation 70
  • Obstetrics and Gynecology 80
  • Health 49
  • Neurology 81
Replace Paula Byrne with:
Paula Byrne Ireland
Michael Jahn Germany
Nathan Post United Kingdom
David Leeman United Kingdom
Madhumita Shrotri United Kingdom
Yangyang Deng United States
Ollie Lloyd United Kingdom
Rubén Manrique Colombia
Tal Gonen Israel
Danielle Eddy relative to Paula Byrne Ireland Paula Byrne's profile →
Citations per field
00.5×4.7×
Paula Byrne · 1×
Citations per year

Countries citing papers authored by Danielle Eddy

Since Specialization
Citations

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

Fields of papers citing papers by Danielle Eddy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Danielle Eddy, 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 Danielle Eddy Line = papers co-authored together Danielle Eddy links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1
SARS-CoV-2 (COVID-19): What Do We Know About Children? A Systematic Review
Hit paper breakdown →
2020258
2
T cell response to SARS-CoV-2 infection in humans: A systematic review
Hit paper breakdown →
2021258
3 2020234
4 202079
5 201451
6 202031
7 20204

About Danielle Eddy

Danielle Eddy is a scholar working on Infectious Diseases, Neurology, Speech and Hearing, Epidemiology and Obstetrics and Gynecology, having authored 7 papers that have together received 915 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Diabetes Management and Research (1 paper), Long-Term Effects of COVID-19 (1 paper), Adolescent and Pediatric Healthcare (1 paper), SARS-CoV-2 detection and testing (1 paper), Diabetes and associated disorders (1 paper) and COVID-19 Impact on Reproduction (1 paper). The work is most often cited by research in Infectious Diseases (545 citations), Modeling and Simulation (70 citations), Obstetrics and Gynecology (80 citations), Health (49 citations) and Neurology (81 citations). Danielle Eddy has collaborated with scholars based in United Kingdom and Singapore. Frequent co-authors include Adrian Shields, Madhumita Shrotri, Nathan Post, Sharif Ismail, Paul Kellam, David Leeman, May CI van Schalkwyk, Gayatri Amirthalingam, Catherine Huntley and Samuel Rigby. Their work appears in journals such as PLoS ONE, Clinical Infectious Diseases, Journal of Pediatric Nursing, medRxiv and SSRN Electronic Journal.

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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