Jennifer Chevinsky

20 papers receiving 985 citations

Jennifer Chevinsky's Hit Papers

Underlying Medical Conditions Associated With Severe COVID-19 Illness Among Children 2021 · 238 citations
2380+1+3Years since publication50100150200

Peers

Jennifer Chevinsky
Comparison fields: 5 of 97
  • Infectious Diseases 349
  • Neurology 220
  • Modeling and Simulation 44
  • Critical Care and Intensive Care Medicine 38
  • Obstetrics and Gynecology 52
Replace Erin K. Stokes with:
Erin K. Stokes United States
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Pranav Ish India
Reshma Golamari United States
Tope Oyelade United Kingdom
Devyani Ramgobin United States
Julien Poissy France
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Citations per field
00.5×3.4×
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Citations per year

Countries citing papers authored by Jennifer Chevinsky

Since Specialization
Citations

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

Fields of papers citing papers by Jennifer Chevinsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1
Underlying Medical Conditions Associated With Severe COVID-19 Illness Among Children
Hit paper breakdown →
2021238
2
Underlying Medical Conditions and Severe Illness Among 540,667 Adults Hospitalized With COVID-19, March 2020–March 2021
Hit paper breakdown →
2021209
3 2020131
4 202182
5 202168
6 201967
7 202064
8 202164
9 202126
10 202119
11 202113
12 202010
13 20226
14 20206
15 20205
16 20212
17 20221
18 20141
19 20231
20 20201

About Jennifer Chevinsky

Jennifer Chevinsky is a scholar working on Infectious Diseases, Neurology, Public Health, Environmental and Occupational Health, Surgery and Critical Care and Intensive Care Medicine, having authored 20 papers that have together received 1.0k indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (6 papers), Long-Term Effects of COVID-19 (5 papers), Obesity, Physical Activity, Diet (2 papers), Intensive Care Unit Cognitive Disorders (2 papers), COVID-19 and Mental Health (2 papers), COVID-19 epidemiological studies (1 paper), Mosquito-borne diseases and control (1 paper) and Diet, Metabolism, and Disease (1 paper). The work is most often cited by research in Infectious Diseases (349 citations), Neurology (220 citations), Modeling and Simulation (44 citations), Critical Care and Intensive Care Medicine (38 citations) and Obstetrics and Gynecology (52 citations). Jennifer Chevinsky has collaborated with scholars based in United States and France. Frequent co-authors include Alyson B. Goodman, Lyudmyla Kompaniyets, Tegan K. Boehmer, Leigh Ellyn Preston, William R. Mac Kenzie, Adi V. Gundlapalli, Audrey F. Pennington, Amy M. Lavery, Jean Y. Ko and Lyna Z. Schieber. Their work appears in journals such as MMWR Morbidity and Mortality Weekly Report, Preventing Chronic Disease, JAMA Network Open, Current Developments in Nutrition and American Journal of Health Promotion.

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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