Heather Wells

2.2k citations
12 papers · 485 · 1 hit paper · h-index 7

Impact in

    • SARS-CoV-2 and COVID-19 Research
    • Viral gastroenteritis research and epidemiology
    • Viral Infections and Vectors
    • COVID-19 Clinical Research Studies
    • COVID-19 epidemiological studies

Papers in

Heather Wells

9 papers receiving 475 citations

Heather Wells's Hit Papers

Global patterns in coronavirus diversity 2017 · 268 citations
2680+3+6Years since publication50100150200250

Peers

Heather Wells
Comparison fields: 5 of 70
  • Infectious Diseases 314
  • Modeling and Simulation 59
  • Animal Science and Zoology 105
  • Ecological Modeling 31
  • Virology 22
Replace Lucy Keatts with:
Lucy Keatts United States
Stefania Leopardi Italy
Maria N.B. Cajimat United States
Yan Hua China
Frank Sauvage France
David Fouchet France
François Moutou France
Oscar Rico‐Chávez Mexico
Mandev S. Gill Belgium
Anna C. Fagre United States
Heather Wells relative to Lucy Keatts United States Lucy Keatts's profile →
Citations per field
00.5×
Lucy Keatts · 1×
Citations per year

Countries citing papers authored by Heather Wells

Since Specialization
Citations

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

Fields of papers citing papers by Heather Wells

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1
Global patterns in coronavirus diversity
Hit paper breakdown →
2017268
2 202151
3 201448
4 201548
5 202333
6 202124
7 20229
8 20243
9 20161
10 20250
11 20230
12 20250

About Heather Wells

Heather Wells is a scholar working on Infectious Diseases, Molecular Biology, Epidemiology, Microbiology and Clinical Biochemistry, having authored 12 papers that have together received 485 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (5 papers), Zoonotic diseases and public health (2 papers), Gut microbiota and health (2 papers), Evolution and Genetic Dynamics (2 papers), Urinary Tract Infections Management (2 papers), Bacterial Identification and Susceptibility Testing (2 papers), Amphibian and Reptile Biology (2 papers) and CRISPR and Genetic Engineering (1 paper). The work is most often cited by research in Infectious Diseases (314 citations), Modeling and Simulation (59 citations), Animal Science and Zoology (105 citations), Ecological Modeling (31 citations) and Virology (22 citations). Heather Wells has collaborated with scholars based in United States, Uganda and Ethiopia. Frequent co-authors include Jonna A. K. Mazet, Tracey Goldstein, Simon J. Anthony, Sarah Krämer, Stephen S. Morse, Allison L. Hicks, Denise J. Greig, W. Ian Lipkin, Xiaoyu Che and Damien O. Joly. Their work appears in journals such as Open Forum Infectious Diseases, Virus Evolution, Microbiology Spectrum, Cell Host & Microbe and PLoS Pathogens.

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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