Daniela Schmid
Impact in
- Infectious Diseases top 2%
- Viral gastroenteritis research and epidemiology
- Clostridium difficile and Clostridium perfringens research
- SARS-CoV-2 detection and testing
- Biotechnology top 2%
- Listeria monocytogenes in Food Safety
Papers in
-
- Viral gastroenteritis research and epidemiology 22
- Clostridium difficile and Clostridium perfringens research 8
- Food Science 15
- Salmonella and Campylobacter epidemiology 13
- Co-authors
- Franz J. Allerberger (61 shared papers)I Lederer (12 shared papers)Steliana Huhulescu (9 shared papers)Werner Ruppitsch (12 shared papers)Hung-Wei Kuo (10 shared papers)Ariane Tatjana Pietzka (4 shared papers)R. Fretz (7 shared papers)Günther Wewalka (7 shared papers)
In The Last Decade
Daniela Schmid
74 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 118
- Infectious Diseases 902
- Biotechnology 258
- Food Science 341
- Modeling and Simulation 77
- Health 121
Countries citing papers authored by Daniela Schmid
This map shows the geographic impact of Daniela Schmid'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 Daniela Schmid with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Schmid more than expected).
Fields of papers citing papers by Daniela Schmid
This network shows the impact of papers produced by Daniela Schmid. 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 Daniela Schmid. The network helps show where Daniela Schmid may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniela Schmid, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 140 | |
| 2 | 2014 | 95 | |
| 3 | 2019 | 93 | |
| 4 | 1999 | 89 | |
| 5 | 2008 | 83 | |
| 6 | 2009 | 75 | |
| 7 | 2007 | 69 | |
| 8 | 2004 | 52 | |
| 9 | 2019 | 49 | |
| 10 | 2008 | 48 | |
| 11 | 2019 | 47 | |
| 12 | 2008 | 47 | |
| 13 | 2011 | 45 | |
| 14 | 2009 | 43 | |
| 15 | 2020 | 43 | |
| 16 | 2008 | 38 | |
| 17 | 2012 | 37 | |
| 18 | 2006 | 37 | |
| 19 | 2019 | 33 | |
| 20 | 2018 | 33 |
About Daniela Schmid
Daniela Schmid is a scholar working on Infectious Diseases, Food Science, Endocrinology, Epidemiology and Biotechnology, having authored 74 papers that have together received 1.9k indexed citations. Recurring topics across this work include Viral gastroenteritis research and epidemiology (22 papers), Salmonella and Campylobacter epidemiology (13 papers), Virology and Viral Diseases (11 papers), Listeria monocytogenes in Food Safety (8 papers), Clostridium difficile and Clostridium perfringens research (8 papers), Zoonotic diseases and public health (7 papers), Vaccine Coverage and Hesitancy (6 papers) and Bacteriophages and microbial interactions (5 papers). The work is most often cited by research in Infectious Diseases (902 citations), Biotechnology (258 citations), Food Science (341 citations), Modeling and Simulation (77 citations) and Health (121 citations). Daniela Schmid has collaborated with scholars based in Austria, Sweden and Germany. Frequent co-authors include Franz J. Allerberger, I Lederer, Steliana Huhulescu, Werner Ruppitsch, Hung-Wei Kuo, Ariane Tatjana Pietzka, R. Fretz, Günther Wewalka, Erica Simons and Anna Stöger. Their work appears in journals such as Eurosurveillance, Clinical Microbiology and Infection, International Journal of Infectious Diseases, Journal of Food Protection and Journal of Hospital 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.