Don Weiss
Impact in
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies
Papers in
- Microbiology 20
- Bacterial Infections and Vaccines 20
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- COVID-19 epidemiological studies 10
- Co-authors
- Richard HeffernanFarzad MostashariDebjani DasJennifer L. RakemanMarcelle LaytonAdam KarpatiSally SlavinskiAlexander Davidson
- Journals
- Emerging infectious diseases (14 papers)Clinical Infectious Diseases (8 papers)PLoS ONE (4 papers)American Journal of Public Health (3 papers)Epidemiology and Infection (2 papers)
- Partner nations
- United StatesZambiaSwitzerland
In The Last Decade
Don Weiss
78 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 148
- Modeling and Simulation 287
- Applied Microbiology and Biotechnology 109
- Infectious Diseases 948
- Microbiology 259
- Epidemiology 1.1k
Countries citing papers authored by Don Weiss
This map shows the geographic impact of Don Weiss'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 Don Weiss with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Don Weiss more than expected).
Fields of papers citing papers by Don Weiss
This network shows the impact of papers produced by Don Weiss. 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 Don Weiss. The network helps show where Don Weiss may publish in the future.
Co-authors
The 25 scholars most cited alongside Don Weiss, 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 | 2022 | 8 | |
| 2 | 2022 | 1 | |
| 3 | 2021 | 1 | |
| 4 | 2021 | 17 | |
| 5 | 2020 | 20 | |
| 6 | 2017 | 27 | |
| 7 | 2017 | 18 | |
| 8 | 2015 | 9 | |
| 9 | 2015 | 6 | |
| 10 | 2014 | 8 | |
| 11 | 2013 | 14 | |
| 12 | 2012 | 14 | |
| 13 | 2012 | 2 | |
| 14 | 2011 | 9 | |
| 15 | 2010 | 108 | |
| 16 | 2009 | 28 | |
| 17 | 2007 | 13 | |
| 18 | 2005 | 76 | |
| 19 | 2003 | 42 | |
| 20 | 2003 | 14 |
About Don Weiss
Don Weiss is a scholar working on Microbiology, Modeling and Simulation, Infectious Diseases, Microbiology and Epidemiology, having authored 78 papers that have together received 2.4k indexed citations. Recurring topics across this work include Bacterial Infections and Vaccines (20 papers), Data-Driven Disease Surveillance (15 papers), Pneumonia and Respiratory Infections (11 papers), Influenza Virus Research Studies (11 papers), COVID-19 epidemiological studies (10 papers), Mosquito-borne diseases and control (8 papers), Respiratory viral infections research (6 papers) and Syphilis Diagnosis and Treatment (5 papers). The work is most often cited by research in Modeling and Simulation (287 citations), Applied Microbiology and Biotechnology (109 citations), Infectious Diseases (948 citations), Microbiology (259 citations) and Epidemiology (1.1k citations). Don Weiss has collaborated with scholars based in United States, Zambia and Switzerland. Frequent co-authors include Richard Heffernan, Farzad Mostashari, Debjani Das, Jennifer L. Rakeman, Marcelle Layton, Adam Karpati, Sally Slavinski, Alexander Davidson, Martin Kulldorff and Michael Phillips. Their work appears in journals such as Emerging infectious diseases, Clinical Infectious Diseases, PLoS ONE, American Journal of Public Health and Epidemiology and Infection.
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.