Laina D. Mercer

3.6k citations
43 papers · 2.2k indexed · 1 hit paper · h-index 20

Impact in

Papers in

Laina D. Mercer

42 papers receiving 2.2k citations

Hit Papers

Assessing differential impacts of COVID-19 on black communities 2020 · 821 citations
8212020202620222024250500750

Peers

Laina D. Mercer
Comparison fields: 5 of 155
  • Applied Psychology 293
  • Modeling and Simulation 198
  • Health 295
  • Infectious Diseases 372
  • General Health Professions 487
Replace Shiva Raj Mishra with:
Shiva Raj Mishra Nepal
Roger E. Thomas Canada
Cyrille Delpierre France
Eleanor J. Murray United States
Alessandra Buja Italy
L. Miriam Dickinson United States
Adriana Pérez United States
Monica Webb Hooper United States
Silvia Stringhini Switzerland
Muhammad Aziz Rahman Australia
Laina D. Mercer relative to Shiva Raj Mishra Nepal Shiva Raj Mishra's profile →
Citations per field
00.5×4.9×
Shiva Raj Mishra · 1×
Citations per year

Countries citing papers authored by Laina D. Mercer

Since Specialization
Citations

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

Fields of papers citing papers by Laina D. Mercer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Laina D. Mercer. 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 Laina D. Mercer. The network helps show where Laina D. Mercer may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20249
3 20222
4 202210
5 20217
6 20205
7 202017
8 201826
9 201718
10 201620
11 201481
12 201471
13 2014273
14 201412
15 201422
16 201379
17 201344
18 201369
19 201212
20 201114

About Laina D. Mercer

Laina D. Mercer is a scholar working on Applied Psychology, Modeling and Simulation, Infectious Diseases, Statistics and Probability and Cardiology and Cardiovascular Medicine, having authored 43 papers that have together received 2.2k indexed citations. Recurring topics across this work include Viral gastroenteritis research and epidemiology (9 papers), Viral Infections and Immunology Research (9 papers), Smoking Behavior and Cessation (6 papers), Behavioral Health and Interventions (6 papers), Animal Virus Infections Studies (3 papers), Statistical Methods and Bayesian Inference (3 papers), COVID-19 epidemiological studies (3 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). The work is most often cited by research in Applied Psychology (293 citations), Modeling and Simulation (198 citations), Health (295 citations), Infectious Diseases (372 citations) and General Health Professions (487 citations). Laina D. Mercer has collaborated with scholars based in United States, South Africa and United Kingdom. Frequent co-authors include Jaimee L. Heffner, Jonathan B. Bricker, Elise Lankiewicz, David Benkeser, Chris Beyrer, Stefan Baral, Gregorio A. Millett, Jeffrey S. Crowley, Leandro Mena and Austin Jones. Their work appears in journals such as Vaccine, BMC Medicine, The Lancet Infectious Diseases, npj Vaccines and PLoS neglected tropical 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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