Erik Volz
Impact in
- Modeling and Simulation top 0.2%
- COVID-19 epidemiological studies
- Virology top 1%
- HIV Research and Treatment
Papers in
-
- HIV/AIDS Research and Interventions 21
- SARS-CoV-2 and COVID-19 Research 8
- Virology 20
- HIV Research and Treatment 20
- Co-authors
- Lauren Ancel Meyers (7 shared papers)Simon D. W. Frost (13 shared papers)Douglas D. Heckathorn (1 shared paper)Joel C. Miller (5 shared papers)Katia Koelle (2 shared papers)Trevor Bedford (1 shared paper)Antonio Páez (3 shared papers)Anja C. Slim (1 shared paper)
- Journals
- PLoS Computational Biology (7 papers)Epidemics (5 papers)Virus Evolution (4 papers)Journal of The Royal Society Interface (4 papers)Systematic Biology (3 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Erik Volz
71 papers receiving 3.7k citations
Peers
Comparison fields: 5 of 150
- Modeling and Simulation 834
- Virology 532
- Infectious Diseases 1.3k
- Statistical and Nonlinear Physics 832
- Epidemiology 1.1k
Countries citing papers authored by Erik Volz
This map shows the geographic impact of Erik Volz'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 Erik Volz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erik Volz more than expected).
Fields of papers citing papers by Erik Volz
This network shows the impact of papers produced by Erik Volz. 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 Erik Volz. The network helps show where Erik Volz may publish in the future.
Co-authors
The 25 scholars most cited alongside Erik Volz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Probability based estimation theory for respondent driven sampling | 2008 | 424 |
| 2 | 2013 | 266 | |
| 3 | 2007 | 230 | |
| 4 | 2007 | 187 | |
| 5 | 2011 | 180 | |
| 6 | 2009 | 160 | |
| 7 | 2012 | 133 | |
| 8 | 2011 | 132 | |
| 9 | 2008 | 121 | |
| 10 | 2010 | 110 | |
| 11 | 2010 | 107 | |
| 12 | 2011 | 104 | |
| 13 | 2008 | 103 | |
| 14 | 2013 | 92 | |
| 15 | 2013 | 81 | |
| 16 | 2012 | 80 | |
| 17 | 2009 | 77 | |
| 18 | 2017 | 72 | |
| 19 | 2014 | 66 | |
| 20 | 2004 | 63 |
About Erik Volz
Erik Volz is a scholar working on Infectious Diseases, Virology, Epidemiology, Public Health, Environmental and Occupational Health and Modeling and Simulation, having authored 71 papers that have together received 3.8k indexed citations. Recurring topics across this work include HIV/AIDS Research and Interventions (21 papers), HIV Research and Treatment (20 papers), COVID-19 epidemiological studies (16 papers), HIV, Drug Use, Sexual Risk (14 papers), Evolution and Genetic Dynamics (12 papers), Mathematical and Theoretical Epidemiology and Ecology Models (11 papers), Complex Network Analysis Techniques (10 papers) and SARS-CoV-2 and COVID-19 Research (8 papers). The work is most often cited by research in Modeling and Simulation (834 citations), Virology (532 citations), Infectious Diseases (1.3k citations), Statistical and Nonlinear Physics (832 citations) and Epidemiology (1.1k citations). Erik Volz has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Lauren Ancel Meyers, Simon D. W. Frost, Douglas D. Heckathorn, Joel C. Miller, Katia Koelle, Trevor Bedford, Antonio Páez, Anja C. Slim, Sergei L. Kosakovsky Pond and Melissa J. Ward. Their work appears in journals such as PLoS Computational Biology, Epidemics, Virus Evolution, Journal of The Royal Society Interface and Systematic Biology.
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.