Matthew Whitaker

3.4k citations
31 papers · 1.4k · 1 hit paper · h-index 18

Impact in

Papers in

    • COVID-19 Clinical Research Studies 10
    • SARS-CoV-2 and COVID-19 Research 8
    • SARS-CoV-2 detection and testing 3
    • Long-Term Effects of COVID-19 6

Matthew Whitaker

30 papers receiving 1.3k citations

Matthew Whitaker's Hit Papers

Persistent COVID-19 symptoms in a community study of 606,434 people in England 2022 · 246 citations
2460+1+2Years since publication50100150200

Peers

Matthew Whitaker
Comparison fields: 5 of 121
  • Modeling and Simulation 152
  • Infectious Diseases 450
  • Neurology 317
  • Critical Care and Intensive Care Medicine 43
  • Health 51
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Matthew Whitaker relative to Joshua Elliott United Kingdom Joshua Elliott's profile →
Citations per field
00.5×1.5×
Joshua Elliott · 1×
Citations per year

Countries citing papers authored by Matthew Whitaker

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Whitaker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Persistent COVID-19 symptoms in a community study of 606,434 people in England
Hit paper breakdown →
2022246
2 2021111
3 202292
4 202287
5 202085
6 202174
7 202271
8 202167
9 202066
10 202165
11 202161
12 201451
13 202348
14 202044
15 201734
16 202129
17 202228
18 202318
19 202316
20 202313

About Matthew Whitaker

Matthew Whitaker is a scholar working on Infectious Diseases, Neurology, General Health Professions, Clinical Psychology and Epidemiology, having authored 31 papers that have together received 1.4k indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (10 papers), SARS-CoV-2 and COVID-19 Research (8 papers), Long-Term Effects of COVID-19 (6 papers), SARS-CoV-2 detection and testing (3 papers), COVID-19 and Mental Health (3 papers), COVID-19 epidemiological studies (2 papers), Healthcare professionals’ stress and burnout (1 paper) and Medical and Biological Sciences (1 paper). The work is most often cited by research in Modeling and Simulation (152 citations), Infectious Diseases (450 citations), Neurology (317 citations), Critical Care and Intensive Care Medicine (43 citations) and Health (51 citations). Matthew Whitaker has collaborated with scholars based in United Kingdom, Greece and France. Frequent co-authors include Paul Elliott, Joshua Elliott, Graham Cooke, Helen Ward, Marc Chadeau‐Hyam, Ara Darzi, Steven Riley, Barbara Bodinier, Christl A. Donnelly and William Barclay. Their work appears in journals such as Nature Communications, American Journal of Public Health, International Journal of Epidemiology, EClinicalMedicine and European Journal of Epidemiology.

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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