Leonardo Clemente
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
Papers in
-
- COVID-19 epidemiological studies 6
-
- Data-Driven Disease Surveillance 5
- Influenza Virus Research Studies 1
- Co-authors
- Mauricio Santillana (8 shared papers)Fred Lu (4 shared papers)Dianbo Liu (2 shared papers)Canelle Poirier (2 shared papers)Alessandro Vespignani (2 shared papers)Jessica T. Davis (2 shared papers)Matteo Chinazzi (2 shared papers)Sarah F. McGough (1 shared paper)
- Journals
- Journal of Medical Internet Research (2 papers)npj Digital Medicine (1 paper)Journal of The Royal Society Interface (1 paper)PLoS neglected tropical diseases (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United StatesMexicoItaly
In The Last Decade
Leonardo Clemente
9 papers receiving 142 citations
Peers
Comparison fields: 5 of 43
- Modeling and Simulation 67
- Health Informatics 4
- Epidemiology 45
- Public Health, Environmental and Occupational Health 35
- Health Information Management 5
Countries citing papers authored by Leonardo Clemente
This map shows the geographic impact of Leonardo Clemente'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 Leonardo Clemente with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leonardo Clemente more than expected).
Fields of papers citing papers by Leonardo Clemente
This network shows the impact of papers produced by Leonardo Clemente. 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 Leonardo Clemente. The network helps show where Leonardo Clemente may publish in the future.
Co-authors
The 14 scholars most cited alongside Leonardo Clemente, 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 | 2020 | 45 | |
| 2 | 2021 | 33 | |
| 3 | 2020 | 28 | |
| 4 | 2019 | 21 | |
| 5 | 2022 | 10 | |
| 6 | 2025 | 3 | |
| 7 | 2025 | 2 | |
| 8 | 2020 | 2 | |
| 9 | 2025 | 1 |
About Leonardo Clemente
Leonardo Clemente is a scholar working on Modeling and Simulation, Epidemiology, Public Health, Environmental and Occupational Health, Economics and Econometrics and Infectious Diseases, having authored 9 papers that have together received 145 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (6 papers), Data-Driven Disease Surveillance (5 papers), Mosquito-borne diseases and control (3 papers), COVID-19 Pandemic Impacts (2 papers), Spectroscopy and Chemometric Analyses (1 paper), Influenza Virus Research Studies (1 paper), Fault Detection and Control Systems (1 paper) and Species Distribution and Climate Change (1 paper). The work is most often cited by research in Modeling and Simulation (67 citations), Health Informatics (4 citations), Epidemiology (45 citations), Public Health, Environmental and Occupational Health (35 citations) and Health Information Management (5 citations). Leonardo Clemente has collaborated with scholars based in United States, Mexico and Italy. Frequent co-authors include Mauricio Santillana, Fred Lu, Dianbo Liu, Canelle Poirier, Alessandro Vespignani, Jessica T. Davis, Matteo Chinazzi, Sarah F. McGough, J. Nathan Kutz and Caroline O. Buckee. Their work appears in journals such as Journal of Medical Internet Research, npj Digital Medicine, Journal of The Royal Society Interface, PLoS neglected tropical diseases and Proceedings of the National Academy of Sciences.
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.