A. Danielle Iuliano

8.1k citations
77 papers · 2.0k indexed · 3 hit papers · h-index 22

A. Danielle Iuliano

71 papers receiving 2.0k citations

Hit Papers

Use of At-Home COVID-19 Tests — United States, Au...1212019202620212023100200300400

Peers

A. Danielle Iuliano
Comparison fields: 5 of 137
  • Modeling and Simulation 430
  • Infectious Diseases 816
  • Epidemiology 1.1k
  • Health 235
  • Applied Microbiology and Biotechnology 36
Replace Byung Chul Chun with:
Byung Chul Chun South Korea
Jim McMenamin United Kingdom
John Paget Netherlands
Laurie Kamimoto United States
Sarah A. Buchan Canada
Clément Turbelin France
W J Paget Netherlands
Jessie R. Chung United States
Ayman Chit Canada
Manjusha Gaglani United States
A. Danielle Iuliano relative to Byung Chul Chun South Korea Byung Chul Chun's profile →
Citations per field
00.5×1.5×2.1×
Byung Chul Chun · 1×
Citations per year

Countries citing papers authored by A. Danielle Iuliano

Since Specialization
Citations

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

Fields of papers citing papers by A. Danielle Iuliano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20252
4 20243
5 20243
6 20242
7 20241
8 20233
9 202213
10
Use of At-Home COVID-19 Tests — United States, August 23, 2021–March 12, 2022breakdown →
2022121
11 202144
12 20216
13 20202
14
Estimated incidence of COVID-19 illness and hospitalization - United States, February-September, 2020.
202015
15 20191
16 20185
17 201810
18 201722
19 20176
20 200615

About A. Danielle Iuliano

A. Danielle Iuliano is a scholar working on Modeling and Simulation, Epidemiology and Infectious Diseases, having authored 77 papers that have together received 2.0k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (51 papers), Respiratory viral infections research (31 papers), COVID-19 epidemiological studies (26 papers), Pneumonia and Respiratory Infections (9 papers), Animal Disease Management and Epidemiology (8 papers), Viral Infections and Outbreaks Research (7 papers), Viral Infections and Vectors (7 papers) and Data-Driven Disease Surveillance (7 papers). The work is most often cited by research in Modeling and Simulation (430 citations), Infectious Diseases (816 citations) and Epidemiology (1.1k citations). A. Danielle Iuliano has collaborated with scholars based in United States, China and Bangladesh. Frequent co-authors include Cécile Viboud, John Paget, Peter Spreeuwenberg, Lone Simonsen, Robert J. Taylor, Joseph Bresee, Vivek Charu, Carrie Reed, Alicia M. Fry and Neha Patel. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Clinical 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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