Moritz U. G. Kraemer
- Modeling and Simulation top 0.02%
- Public Health, Environmental and Occupational Health top 0.2%
- Infectious Diseases top 0.2%
- Economics and Econometrics top 0.5%
- Epidemiology top 2%
- Co-authors
- David M. PigottJohn S. BrownsteinKamran KhanSimon I HayBernardo GutiérrezOliver J. BradyIsaac I. BogochAlexander Watts
- Topics
- COVID-19 epidemiological studies (55 papers)Mosquito-borne diseases and control (44 papers)Viral Infections and Vectors (30 papers)
- Cited by
- Modeling and SimulationInfectious DiseasesPublic Health, Environmental and Occupational Health
- Partner nations
- United KingdomUnited StatesCanada
In The Last Decade
Moritz U. G. Kraemer
97 papers receiving 9.0k citations
Hit Papers
Peers
Comparison fields: 5 of 193
- Modeling and Simulation 3.9k
- Public Health, Environmental and Occupational Health 3.6k
- Infectious Diseases 3.5k
- Economics and Econometrics 1.5k
- Epidemiology 1.3k
Countries citing papers authored by Moritz U. G. Kraemer
This map shows the geographic impact of Moritz U. G. Kraemer'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 Moritz U. G. Kraemer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Moritz U. G. Kraemer more than expected).
Fields of papers citing papers by Moritz U. G. Kraemer
This network shows the impact of papers produced by Moritz U. G. Kraemer. 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 Moritz U. G. Kraemer. The network helps show where Moritz U. G. Kraemer may publish in the future.
Co-authorship network of co-authors of Moritz U. G. Kraemer
This figure shows the co-authorship network connecting the top 25 collaborators of Moritz U. G. Kraemer. A scholar is included among the top collaborators of Moritz U. G. Kraemer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Moritz U. G. Kraemer. Moritz U. G. Kraemer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 34 | |
| 4 | 6 | |
| 5 | 0 | |
| 6 | 14 | |
| 7 | 11 | |
| 8 | 3 | |
| 9 | 6 | |
| 10 | 23 | |
| 11 | 15 | |
| 12 | 5 | |
| 13 | 50 | |
| 14 | 37 | |
| 15 | 83 | |
| 16 | 101 | |
| 17 | The effect of human mobility and control measures on the COVID-19 epidemic in Chinabreakdown → | 1934 |
| 18 | 40 | |
| 19 | 141 | |
| 20 | 275 |
About Moritz U. G. Kraemer
Moritz U. G. Kraemer is a scholar working on Modeling and Simulation, Infectious Diseases and Public Health, Environmental and Occupational Health, having authored 101 papers that have together received 9.2k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (55 papers), Mosquito-borne diseases and control (44 papers) and Viral Infections and Vectors (30 papers). The work is most often cited by research in Modeling and Simulation (3.9k citations), Infectious Diseases (3.5k citations) and Public Health, Environmental and Occupational Health (3.6k citations). Moritz U. G. Kraemer has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include David M. Pigott, John S. Brownstein, Kamran Khan, Simon I Hay, Bernardo Gutiérrez, Oliver J. Brady, Isaac I. Bogoch, Alexander Watts, Samuel V. Scarpino and Oliver G. Pybus. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and The Lancet.
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.