Aaron Rumack
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
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- Data-Driven Disease Surveillance
Papers in
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- COVID-19 epidemiological studies 3
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- Data-Driven Disease Surveillance 4
- Co-authors
- Siqi Liang (1 shared paper)Michael J. Meyer (1 shared paper)Juan Felipe Beltrán (1 shared paper)Robert Fragoza (1 shared paper)Jin Hua Liang (1 shared paper)Xiaomu Wei (1 shared paper)Haiyuan Yu (1 shared paper)Alex Mogilner (1 shared paper)
- Journals
- PLoS Computational Biology (3 papers)Proceedings of the National Academy of Sciences (2 papers)Nature Methods (1 paper)International Journal of Forecasting (1 paper)Epidemics (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Aaron Rumack
7 papers receiving 409 citations
Aaron Rumack's Hit Papers
Peers
Comparison fields: 5 of 78
- Modeling and Simulation 154
- Epidemiology 71
- Management Science and Operations Research 36
- Cell Biology 24
- Computational Theory and Mathematics 25
Countries citing papers authored by Aaron Rumack
This map shows the geographic impact of Aaron Rumack'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 Rumack with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aaron Rumack more than expected).
Fields of papers citing papers by Aaron Rumack
This network shows the impact of papers produced by Aaron Rumack. 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 Rumack. The network helps show where Aaron Rumack may publish in the future.
Co-authors
The 25 scholars most cited alongside Aaron Rumack, 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 | 2018 | 115 | |
| 3 | 2021 | 42 | |
| 4 | 2017 | 37 | |
| 5 | 2022 | 36 | |
| 6 | 2022 | 1 | |
| 7 | 2025 | 1 | |
| 8 | 2025 | 0 |
About Aaron Rumack
Aaron Rumack is a scholar working on Modeling and Simulation, Epidemiology, Management Science and Operations Research, Statistics and Probability and Cell Biology, having authored 8 papers that have together received 420 indexed citations. Recurring topics across this work include Data-Driven Disease Surveillance (4 papers), COVID-19 epidemiological studies (3 papers), Forecasting Techniques and Applications (2 papers), Cellular Mechanics and Interactions (1 paper), Statistical Methods in Epidemiology (1 paper) and Bioinformatics and Genomic Networks (1 paper). The work is most often cited by research in Modeling and Simulation (154 citations), Epidemiology (71 citations), Management Science and Operations Research (36 citations), Cell Biology (24 citations) and Computational Theory and Mathematics (25 citations). Aaron Rumack has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Siqi Liang, Michael J. Meyer, Juan Felipe Beltrán, Robert Fragoza, Jin Hua Liang, Xiaomu Wei, Haiyuan Yu, Alex Mogilner, Igor L. Novak and Boris M. Slepchenko. Their work appears in journals such as PLoS Computational Biology, Proceedings of the National Academy of Sciences, Nature Methods, International Journal of Forecasting and Epidemics.
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.