Matthew Griffith

1.2k citations
22 papers · 938 · h-index 11

Impact in

Papers in

Matthew Griffith

20 papers receiving 873 citations

Peers

Matthew Griffith
Comparison fields: 5 of 84
  • Modeling and Simulation 152
  • General Health Professions 409
  • Microbiology 96
  • Applied Microbiology and Biotechnology 19
  • Infectious Diseases 128
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M. Allison Arwady United States
Tammy A. Santibanez United States
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Citations per field
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Citations per year

Countries citing papers authored by Matthew Griffith

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Griffith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012287
2 2010209
3 2020169
4 201252
5 201242
6 202040
7 201234
8 200324
9 201820
10 201712
11 201611
12 200710
13 20239
14 20227
15
The assessment of health risks with feedback: Results of a systematic review
20084
16 20184
17
Clinical Profile and Outcomes of Severe Scrub Typhus Infection Requiring Intensive Care Management
20091
18 20181
19 20241
20 20241

About Matthew Griffith

Matthew Griffith is a scholar working on Modeling and Simulation, Microbiology, General Health Professions, Public Health, Environmental and Occupational Health and Infectious Diseases, having authored 22 papers that have together received 938 indexed citations. Recurring topics across this work include Bacterial Infections and Vaccines (4 papers), COVID-19 epidemiological studies (4 papers), Innovations in Medical Education (3 papers), Health and Medical Education (3 papers), Public Health Policies and Education (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Health Promotion and Cardiovascular Prevention (2 papers) and Workplace Health and Well-being (1 paper). The work is most often cited by research in Modeling and Simulation (152 citations), General Health Professions (409 citations), Microbiology (96 citations), Applied Microbiology and Biotechnology (19 citations) and Infectious Diseases (128 citations). Matthew Griffith has collaborated with scholars based in Japan, United States and Australia. Frequent co-authors include Lin Naing, Justin Wong, Liling Chaw, Jeffrey H. Herbst, Seth M. Noar, Sajal K. Chattopadhyay, Holly R. Wethington, Shawna L. Mercer, Robert L. Johnson and Verughese Jacob. Their work appears in journals such as Western Pacific surveillance response journal, Vaccine, American Journal of Preventive Medicine, Clinical Infectious Diseases and BMJ Open.

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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