Udo Goetsch
Impact in
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Tuberculosis Research and Epidemiology
- SARS-CoV-2 detection and testing
- Viral Infections and Outbreaks Research
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
Papers in
-
- SARS-CoV-2 and COVID-19 Research 6
- Tuberculosis Research and Epidemiology 5
- COVID-19 Clinical Research Studies 3
- SARS-CoV-2 detection and testing 2
- Viral Infections and Outbreaks Research 2
-
- Mosquito-borne diseases and control 2
- Malaria Research and Control 2
- Co-authors
- René Gottschalk (9 shared papers)Timo Wolf (8 shared papers)Sebastian Hoehl (6 shared papers)Sandra Ciesek (8 shared papers)Christiane Pallas (5 shared papers)Marek Widera (6 shared papers)Alexander Wilhelm (4 shared papers)Niko Kohmer (5 shared papers)
In The Last Decade
Udo Goetsch
20 papers receiving 593 citations
Peers
Comparison fields: 5 of 64
- Infectious Diseases 477
- Modeling and Simulation 59
- Animal Science and Zoology 30
- Health 21
- Epidemiology 86
Countries citing papers authored by Udo Goetsch
This map shows the geographic impact of Udo Goetsch'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 Udo Goetsch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Udo Goetsch more than expected).
Fields of papers citing papers by Udo Goetsch
This network shows the impact of papers produced by Udo Goetsch. 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 Udo Goetsch. The network helps show where Udo Goetsch may publish in the future.
Co-authors
The 25 scholars most cited alongside Udo Goetsch, 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 | 118 | |
| 2 | 2022 | 109 | |
| 3 | 2008 | 81 | |
| 4 | 2021 | 59 | |
| 5 | 2020 | 44 | |
| 6 | 2021 | 43 | |
| 7 | 2020 | 30 | |
| 8 | 2016 | 25 | |
| 9 | 2009 | 25 | |
| 10 | 2012 | 20 | |
| 11 | 2019 | 12 | |
| 12 | 2012 | 9 | |
| 13 | 2021 | 8 | |
| 14 | 2022 | 5 | |
| 15 | 2024 | 4 | |
| 16 | 2025 | 4 | |
| 17 | 2013 | 4 | |
| 18 | 2022 | 3 | |
| 19 | 2023 | 1 | |
| 20 | 2023 | 1 |
About Udo Goetsch
Udo Goetsch is a scholar working on Infectious Diseases, Public Health, Environmental and Occupational Health, Economics and Econometrics, Modeling and Simulation and Molecular Biology, having authored 20 papers that have together received 605 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (6 papers), Tuberculosis Research and Epidemiology (5 papers), COVID-19 Clinical Research Studies (3 papers), SARS-CoV-2 detection and testing (2 papers), Mosquito-borne diseases and control (2 papers), COVID-19 epidemiological studies (2 papers), Viral Infections and Outbreaks Research (2 papers) and Malaria Research and Control (2 papers). The work is most often cited by research in Infectious Diseases (477 citations), Modeling and Simulation (59 citations), Animal Science and Zoology (30 citations), Health (21 citations) and Epidemiology (86 citations). Udo Goetsch has collaborated with scholars based in Germany, Ireland and Italy. Frequent co-authors include René Gottschalk, Timo Wolf, Sebastian Hoehl, Sandra Ciesek, Christiane Pallas, Marek Widera, Alexander Wilhelm, Niko Kohmer, Tuna Toptan and Katharina Grikscheit. Their work appears in journals such as Infection, Eurosurveillance, International Journal of Infectious Diseases, Science Immunology and Journal of Travel Medicine.
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.