Nils Haug

7 papers receiving 966 citations

Nils Haug's Hit Papers

Ranking the effectiveness of worldwide COVID-19 government interventions 2020 · 920 citations
9200+2+4Years since publication250500750

Peers

Nils Haug
Comparison fields: 5 of 123
  • Modeling and Simulation 448
  • Health 86
  • Economics and Econometrics 246
  • Infectious Diseases 146
  • Clinical Psychology 158
Replace Elma Dervić with:
Elma Dervić Austria
Sören Mindermann United Kingdom
Mrinank Sharma United Kingdom
Luna Yue Huang United States
Trinetta Chong United States
Hannah Druckenmiller United States
Jeanette Tseng United States
Emma Krasovich United States
Kendon Bell United States
Jaecheol Lee United States
Nils Haug relative to Elma Dervić Austria Elma Dervić's profile →
Citations per field
00.5×1.5×
Elma Dervić · 1×
Citations per year

Countries citing papers authored by Nils Haug

Since Specialization
Citations

This map shows the geographic impact of Nils Haug'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 Nils Haug with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nils Haug more than expected).

Fields of papers citing papers by Nils Haug

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nils Haug. 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 Nils Haug. The network helps show where Nils Haug may publish in the future.

Co-authors

The 23 scholars most cited alongside Nils Haug, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nils Haug Line = papers co-authored together Nils Haug links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1
Ranking the effectiveness of worldwide COVID-19 government interventions
Hit paper breakdown →
2020920
2 202039
3 202112
4 202110
5 20218
6 20241
7 20241
8 20200

About Nils Haug

Nils Haug is a scholar working on Epidemiology, Economics and Econometrics, Health, Oncology and Artificial Intelligence, having authored 8 papers that have together received 991 indexed citations. Recurring topics across this work include Chronic Disease Management Strategies (2 papers), Pancreatic and Hepatic Oncology Research (1 paper), Cancer Genomics and Diagnostics (1 paper), Vaccine Coverage and Hesitancy (1 paper), COVID-19 epidemiological studies (1 paper), Diabetes Management and Education (1 paper), COVID-19 Pandemic Impacts (1 paper) and Machine Learning in Healthcare (1 paper). The work is most often cited by research in Modeling and Simulation (448 citations), Health (86 citations), Economics and Econometrics (246 citations), Infectious Diseases (146 citations) and Clinical Psychology (158 citations). Nils Haug has collaborated with scholars based in Austria, United States and Germany. Frequent co-authors include Peter Klimek, Stefan Thurner, Elma Dervić, Lukas Geyrhofer, Alessandro Londei, Amélie Desvars-Larrive, Vittorio Loreto, Beate Pinior, Alexandra Kautzky‐Willer and Carola Deischinger. Their work appears in journals such as Journal of Personalized Medicine, BMC Medicine, Frontiers in Physiology, Nature Human Behaviour and International Journal of Cancer.

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.

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