Aaron Gerding
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
-
- Data-Driven Disease Surveillance
- Influenza Virus Research Studies
Papers in
-
- COVID-19 epidemiological studies 4
-
- Forecasting Techniques and Applications 2
- Co-authors
- Nicholas G Reich (2 shared papers)Evan L. Ray (2 shared papers)Yijin Wang (1 shared paper)Ryan J. Tibshirani (1 shared paper)Estee Y. Cramer (1 shared paper)Michael A. Johansson (1 shared paper)Martha Zorn (1 shared paper)Johannes Bracher (1 shared paper)
- Journals
- Journal of the Royal Statistical Society Series A (Statistics in Society) (1 paper)Nature Communications (1 paper)Proceedings of the National Academy of Sciences (1 paper)International Journal of Forecasting (1 paper)PLoS Computational Biology (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Aaron Gerding
5 papers receiving 259 citations
Aaron Gerding's Hit Papers
Peers
Comparison fields: 5 of 43
- Modeling and Simulation 137
- Epidemiology 86
- Management Science and Operations Research 37
- Public Health, Environmental and Occupational Health 41
- Applied Microbiology and Biotechnology 2
Countries citing papers authored by Aaron Gerding
This map shows the geographic impact of Aaron Gerding'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 Aaron Gerding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aaron Gerding more than expected).
Fields of papers citing papers by Aaron Gerding
This network shows the impact of papers produced by Aaron Gerding. 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 Aaron Gerding. The network helps show where Aaron Gerding may publish in the future.
Co-authors
The 13 scholars most cited alongside Aaron Gerding, 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 | Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States Hit paper breakdown → | 2022 | 188 |
| 2 | 2022 | 36 | |
| 3 | 2024 | 31 | |
| 4 | 2024 | 15 | |
| 5 | 2024 | 2 |
About Aaron Gerding
Aaron Gerding is a scholar working on Modeling and Simulation, Management Science and Operations Research, Epidemiology, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 5 papers that have together received 272 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (4 papers), Forecasting Techniques and Applications (2 papers), Influenza Virus Research Studies (1 paper) and Data-Driven Disease Surveillance (1 paper). The work is most often cited by research in Modeling and Simulation (137 citations), Epidemiology (86 citations), Management Science and Operations Research (37 citations), Public Health, Environmental and Occupational Health (41 citations) and Applied Microbiology and Biotechnology (2 citations). Aaron Gerding has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Nicholas G Reich, Evan L. Ray, Yijin Wang, Ryan J. Tibshirani, Estee Y. Cramer, Michael A. Johansson, Martha Zorn, Johannes Bracher, Matthew Biggerstaff and Jacob Bien. Their work appears in journals such as Journal of the Royal Statistical Society Series A (Statistics in Society), Nature Communications, Proceedings of the National Academy of Sciences, International Journal of Forecasting and PLoS Computational 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.