Ronald Smallenburg
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
-
- Data-Driven Disease Surveillance
- Influenza Virus Research Studies
- Respiratory viral infections research
Papers in
-
- Data-Driven Disease Surveillance 4
- Influenza Virus Research Studies 3
- Respiratory viral infections research 1
- Health 2
- Vaccine Coverage and Hesitancy 1
- Social Media in Health Education 1
- Co-authors
- Carl Koppeschaar (5 shared papers)Vittoria Colizza (3 shared papers)AnnaSara Carnahan (3 shared papers)Ken Eames (3 shared papers)Moa Rehn (3 shared papers)Daniela Paolotti (3 shared papers)Alessandro Vespignani (3 shared papers)Clément Turbelin (2 shared papers)
- Journals
- Vaccine (2 papers)Clinical Microbiology and Infection (1 paper)Journal of Medical Internet Research (1 paper)PLoS ONE (1 paper)
- Partner nations
- PortugalUnited KingdomUnited States
In The Last Decade
Ronald Smallenburg
5 papers receiving 250 citations
Peers
Comparison fields: 5 of 60
- Modeling and Simulation 83
- Epidemiology 201
- Health 40
- Applied Psychology 9
- Ecological Modeling 6
Countries citing papers authored by Ronald Smallenburg
This map shows the geographic impact of Ronald Smallenburg'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 Ronald Smallenburg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ronald Smallenburg more than expected).
Fields of papers citing papers by Ronald Smallenburg
This network shows the impact of papers produced by Ronald Smallenburg. 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 Ronald Smallenburg. The network helps show where Ronald Smallenburg may publish in the future.
Co-authors
The 25 scholars most cited alongside Ronald Smallenburg, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 120 | |
| 2 | 2009 | 72 | |
| 3 | 2014 | 34 | |
| 4 | 2014 | 32 | |
| 5 | 2016 | 2 |
About Ronald Smallenburg
Ronald Smallenburg is a scholar working on Epidemiology, Health, Sociology and Political Science, Physiology and Modeling and Simulation, having authored 5 papers that have together received 260 indexed citations. Recurring topics across this work include Data-Driven Disease Surveillance (4 papers), Influenza Virus Research Studies (3 papers), Smoking Behavior and Cessation (1 paper), COVID-19 epidemiological studies (1 paper), Survey Methodology and Nonresponse (1 paper), Respiratory viral infections research (1 paper), Vaccine Coverage and Hesitancy (1 paper) and Social Media in Health Education (1 paper). The work is most often cited by research in Modeling and Simulation (83 citations), Epidemiology (201 citations), Health (40 citations), Applied Psychology (9 citations) and Ecological Modeling (6 citations). Ronald Smallenburg has collaborated with scholars based in Portugal, United Kingdom and United States. Frequent co-authors include Carl Koppeschaar, Vittoria Colizza, AnnaSara Carnahan, Ken Eames, Moa Rehn, Daniela Paolotti, Alessandro Vespignani, Clément Turbelin, John Edmunds and M. Gabriela M. Gomes. Their work appears in journals such as Vaccine, Clinical Microbiology and Infection, Journal of Medical Internet Research and PLoS ONE.
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.