Jennifer Chevinsky

20 papers receiving 962 citations

Jennifer Chevinsky's Hit Papers

Underlying Medical Conditions Associated With Severe COVID-19 Illness Among Children 2021 · 233 citations
2330+1+3Years since publication50100150200

Peers

Jennifer Chevinsky
Comparison fields: 5 of 98
  • Infectious Diseases 524
  • Neurology 327
  • Critical Care and Intensive Care Medicine 84
  • Modeling and Simulation 62
  • Obstetrics and Gynecology 97
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Jennifer Chevinsky relative to Leigh Ellyn Preston United States Leigh Ellyn Preston's profile →
Citations per field
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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 →
2021233
2
Underlying Medical Conditions and Severe Illness Among 540,667 Adults Hospitalized With COVID-19, March 2020–March 2021
Hit paper breakdown →
2021203
3 2020130
4 202182
5 202167
6 201964
7 202163
8 202061
9 202126
10 202119
11 202112
12 20209
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, Clinical Psychology, Public Health, Environmental and Occupational Health and General Health Professions, having authored 20 papers that have together received 992 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (8 papers), Long-Term Effects of COVID-19 (7 papers), COVID-19 and Mental Health (5 papers), Obesity, Physical Activity, Diet (3 papers), Alcohol Consumption and Health Effects (2 papers), Nutritional Studies and Diet (2 papers), Intensive Care Unit Cognitive Disorders (2 papers) and COVID-19 and healthcare impacts (2 papers). The work is most often cited by research in Infectious Diseases (524 citations), Neurology (327 citations), Critical Care and Intensive Care Medicine (84 citations), Modeling and Simulation (62 citations) and Obstetrics and Gynecology (97 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 Melissa L. Danielson. Their work appears in journals such as MMWR Morbidity and Mortality Weekly Report, JAMA Network Open, Preventing Chronic Disease, Clinical Infectious Diseases and Vector-Borne and Zoonotic 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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