Mark D. Gallivan

17 papers receiving 822 citations

Mark D. Gallivan's Hit Papers

Pandemics: Risks, Impacts, and Mitigation 2017 · 347 citations
3470+3+6Years since publication100200300

Peers

Mark D. Gallivan
Comparison fields: 5 of 133
  • Modeling and Simulation 136
  • Infectious Diseases 161
  • Health 54
  • Economics and Econometrics 177
  • General Health Professions 145
Replace Nita K. Madhav with:
Nita K. Madhav United States
Arush Lal United Kingdom
Matthew M. Kavanagh United States
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Nirmal Kandel Switzerland
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Mark D. Gallivan relative to Nita K. Madhav United States Nita K. Madhav's profile →
Citations per field
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Nita K. Madhav · 1×
Citations per year

Countries citing papers authored by Mark D. Gallivan

Since Specialization
Citations

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

Fields of papers citing papers by Mark D. Gallivan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1
Pandemics: Risks, Impacts, and Mitigation
Hit paper breakdown →
2017347
2 2017168
3 2019163
4 201797
5 201541
6 201617
7 202116
8 201912
9 202211
10
Physician offices invade clinical laboratory market.
19855
11 20135
12 20174
13 20234
14 20152
15
Self-insurance wave continues.
19861
16
Technology planning: an imperative, not an option.
19861
17
Inpatient use declines: persistent but slower.
19871
18 20250

About Mark D. Gallivan

Mark D. Gallivan is a scholar working on Modeling and Simulation, Ophthalmology, Infectious Diseases, Public Health, Environmental and Occupational Health and Medical Laboratory Technology, having authored 18 papers that have together received 895 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (3 papers), Infectious Diseases and Tuberculosis (3 papers), Retinal Diseases and Treatments (3 papers), Zoonotic diseases and public health (2 papers), Tuberculosis Research and Epidemiology (2 papers), Viral Infections and Outbreaks Research (2 papers), Global Health Care Issues (2 papers) and Retinal Imaging and Analysis (1 paper). The work is most often cited by research in Modeling and Simulation (136 citations), Infectious Diseases (161 citations), Health (54 citations), Economics and Econometrics (177 citations) and General Health Professions (145 citations). Mark D. Gallivan has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Ben Oppenheim, Nita K. Madhav, NATHAN D. WOLFE, Prime M. Mulembakani, Edward A. Rubin, Patrick Ayscue, Neha Shah, Jennifer Flood, Theodore Leng and Linda M. O’Keeffe. Their work appears in journals such as Open Forum Infectious Diseases, The Lancet, Ophthalmic surgery, lasers & imaging retina, Journal of Public Health Management and Practice and BMJ Global Health.

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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