Massimo Lombardo
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
Papers in
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- SARS-CoV-2 and COVID-19 Research 6
- COVID-19 Clinical Research Studies 3
-
- COVID-19 epidemiological studies 3
- Co-authors
- Danilo Cereda (3 shared papers)Alessandro Ferrari (1 shared paper)Raffaele Bruno (1 shared paper)Fausto Baldanti (1 shared paper)Pietro Bisagni (1 shared paper)Irene Cassaniti (1 shared paper)Antonio Capone (2 shared papers)Paola Isernia (1 shared paper)
In The Last Decade
Massimo Lombardo
17 papers receiving 494 citations
Peers
Comparison fields: 5 of 98
- Modeling and Simulation 98
- Infectious Diseases 188
- Health 27
- Obstetrics and Gynecology 17
- Oncology 59
Countries citing papers authored by Massimo Lombardo
This map shows the geographic impact of Massimo Lombardo'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 Massimo Lombardo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Lombardo more than expected).
Fields of papers citing papers by Massimo Lombardo
This network shows the impact of papers produced by Massimo Lombardo. 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 Massimo Lombardo. The network helps show where Massimo Lombardo may publish in the future.
Co-authors
The 25 scholars most cited alongside Massimo Lombardo, 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 | 142 | |
| 2 | 2021 | 105 | |
| 3 | 2020 | 84 | |
| 4 | 2018 | 33 | |
| 5 | 2022 | 27 | |
| 6 | 2006 | 25 | |
| 7 | 2020 | 23 | |
| 8 | 2022 | 14 | |
| 9 | 2020 | 13 | |
| 10 | 2023 | 11 | |
| 11 | 2021 | 9 | |
| 12 | 2022 | 4 | |
| 13 | 2024 | 3 | |
| 14 | 2023 | 2 | |
| 15 | 2025 | 2 | |
| 16 | 2025 | 2 | |
| 17 | 2025 | 1 | |
| 18 | 2025 | 0 |
About Massimo Lombardo
Massimo Lombardo is a scholar working on Infectious Diseases, Modeling and Simulation, Oncology, Emergency Medicine and Epidemiology, having authored 18 papers that have together received 500 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (6 papers), COVID-19 Clinical Research Studies (3 papers), COVID-19 epidemiological studies (3 papers), Data-Driven Disease Surveillance (2 papers), COVID-19 and healthcare impacts (2 papers), vaccines and immunoinformatics approaches (1 paper), Lipid Membrane Structure and Behavior (1 paper) and Cholesterol and Lipid Metabolism (1 paper). The work is most often cited by research in Modeling and Simulation (98 citations), Infectious Diseases (188 citations), Health (27 citations), Obstetrics and Gynecology (17 citations) and Oncology (59 citations). Massimo Lombardo has collaborated with scholars based in Italy, Australia and Slovakia. Frequent co-authors include Danilo Cereda, Alessandro Ferrari, Raffaele Bruno, Fausto Baldanti, Pietro Bisagni, Irene Cassaniti, Antonio Capone, Paola Isernia, Roberta Maserati and Giuseppe Marongiu. Their work appears in journals such as Vaccines, Geriatric Orthopaedic Surgery & Rehabilitation, International Journal of Pharmaceutics, Epidemics and International Journal of Gynecology & Obstetrics.
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.