Matt Ferrari

887 citations
10 papers · 498 indexed · 1 hit paper · h-index 9

Matt Ferrari

10 papers receiving 471 citations

Hit Papers

Progress Toward Measles Elimination — Worldwide, 2000–2022202320262024202520234080120

Peers

Matt Ferrari
Comparison fields: 5 of 59
  • Epidemiology 361
  • Health 250
  • Modeling and Simulation 145
  • Infectious Diseases 144
  • Immunology 135
Replace Claudia Steulet with:
Claudia Steulet United States
Anindya Sekhar Bose United States
Annick Dosseh Senegal
Sheilagh Smit South Africa
Sigrid Gouma United States
Elizabeth Rausch-Phung United States
Jennie S. Lavine United States
Sun B. Sowers United States
Robert J. Arciuolo United States
Ana Morice United States
Matt Ferrari relative to Claudia Steulet United States Claudia Steulet's profile →
Citations per field
00.5×
Claudia Steulet · 1×
Citations per year

Countries citing papers authored by Matt Ferrari

Since Specialization
Citations

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

Fields of papers citing papers by Matt Ferrari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matt Ferrari

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

All Works

10 of 10 papers shown
#WorkIndexed citations
1 30
2
Progress Toward Measles Elimination — Worldwide, 2000–2022breakdown →
127
3 60
4 89
5 15
6 60
7 34
8 36
9
Emergency vaccination responses during large measles outbreaks: Early intervention leads to a high proportion of averted cases
2
10 45

About Matt Ferrari

Matt Ferrari is a scholar working on Modeling and Simulation, Health and Epidemiology, having authored 10 papers that have together received 498 indexed citations. Recurring topics across this work include Virology and Viral Diseases (9 papers), Vaccine Coverage and Hesitancy (6 papers) and COVID-19 epidemiological studies (5 papers). The work is most often cited by research in Modeling and Simulation (145 citations), Health (250 citations) and Epidemiology (361 citations). Matt Ferrari has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include Marta Gacic-Dobo, Claudia Steulet, Paul A. Rota, Bryan T. Grenfell, Mick N. Mulders, Anindya Sekhar Bose, Brian Lambert, Sébastien Antoni, Allison Portnoy and Cynthia Hatcher. Their work appears in journals such as American Journal of Epidemiology, The Journal of Infectious Diseases and MMWR Morbidity and Mortality Weekly Report.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026