Qu Cheng
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Infectious Diseases top 10%
- Viral Infections and Vectors
Papers in
-
- Viral Infections and Vectors 9
- Viral Infections and Outbreaks Research 3
-
- Mosquito-borne diseases and control 8
- Malaria Research and Control 3
- Co-authors
- Peng Gong (4 shared papers)Justin V. Remais (9 shared papers)Song Liang (7 shared papers)Robert C. Spear (5 shared papers)John M. Marshall (2 shared papers)Zhicong Yang (2 shared papers)Qinlong Jing (3 shared papers)Baoguo Jiang (1 shared paper)
- Journals
- PLoS neglected tropical diseases (4 papers)PLoS Computational Biology (2 papers)BMC Infectious Diseases (2 papers)Environmental Research (1 paper)Frontiers in Public Health (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Qu Cheng
33 papers receiving 676 citations
Peers
Comparison fields: 5 of 129
- Modeling and Simulation 72
- Infectious Diseases 154
- Transportation 48
- Ecological Modeling 29
- Global and Planetary Change 127
Countries citing papers authored by Qu Cheng
This map shows the geographic impact of Qu Cheng'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 Qu Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qu Cheng more than expected).
Fields of papers citing papers by Qu Cheng
This network shows the impact of papers produced by Qu Cheng. 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 Qu Cheng. The network helps show where Qu Cheng may publish in the future.
Co-authors
The 25 scholars most cited alongside Qu Cheng, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 168 | |
| 2 | 2017 | 123 | |
| 3 | 2016 | 80 | |
| 4 | 2019 | 40 | |
| 5 | 2020 | 32 | |
| 6 | 2017 | 27 | |
| 7 | 2019 | 27 | |
| 8 | 2022 | 24 | |
| 9 | 2021 | 21 | |
| 10 | 2024 | 16 | |
| 11 | 2020 | 13 | |
| 12 | 2008 | 12 | |
| 13 | 2020 | 12 | |
| 14 | 2021 | 11 | |
| 15 | 2019 | 11 | |
| 16 | 2021 | 10 | |
| 17 | 2021 | 10 | |
| 18 | 2023 | 9 | |
| 19 | 2021 | 8 | |
| 20 | 2020 | 5 |
About Qu Cheng
Qu Cheng is a scholar working on Infectious Diseases, Public Health, Environmental and Occupational Health, Modeling and Simulation, Civil and Structural Engineering and Epidemiology, having authored 37 papers that have together received 694 indexed citations. Recurring topics across this work include Viral Infections and Vectors (9 papers), Mosquito-borne diseases and control (8 papers), COVID-19 epidemiological studies (6 papers), Data-Driven Disease Surveillance (3 papers), Air Quality and Health Impacts (3 papers), Malaria Research and Control (3 papers), Viral Infections and Outbreaks Research (3 papers) and Climate Change and Health Impacts (3 papers). The work is most often cited by research in Modeling and Simulation (72 citations), Infectious Diseases (154 citations), Transportation (48 citations), Ecological Modeling (29 citations) and Global and Planetary Change (127 citations). Qu Cheng has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Peng Gong, Justin V. Remais, Song Liang, Robert C. Spear, John M. Marshall, Zhicong Yang, Qinlong Jing, Baoguo Jiang, Tianbing Wang and Haozhe Cong. Their work appears in journals such as PLoS neglected tropical diseases, PLoS Computational Biology, BMC Infectious Diseases, Environmental Research and Frontiers in Public Health.
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.