Xiaodan Sun

27 papers receiving 602 citations

Peers

Xiaodan Sun
Comparison fields: 5 of 102
  • Modeling and Simulation 312
  • Infectious Diseases 169
  • Public Health, Environmental and Occupational Health 174
  • Virology 19
  • Health, Toxicology and Mutagenesis 49
Replace King-Pan Chan with:
King-Pan Chan Hong Kong
Steven Abrams Belgium
Claudio Fronterrè United Kingdom
Sheng‐Qun Deng China
David Champredon Canada
Sushma Dahal United States
Cécile Tran Kiem France
Diana Gómez‐Barroso Spain
Megan O’Driscoll United Kingdom
Noémie Lefrancq France
Xiaodan Sun relative to King-Pan Chan Hong Kong King-Pan Chan's profile →
Citations per field
00.5×3.8×
King-Pan Chan · 1×
Citations per year

Countries citing papers authored by Xiaodan Sun

Since Specialization
Citations

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

Fields of papers citing papers by Xiaodan Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaodan Sun, 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 Xiaodan Sun Line = papers co-authored together Xiaodan Sun links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020213
2 201766
3 201438
4 202134
5 202126
6 202125
7 201724
8 201720
9 202020
10 201318
11 202016
12 202013
13 202013
14 201513
15 201610
16 201910
17 201510
18 20219
19 20188
20 20187

About Xiaodan Sun

Xiaodan Sun is a scholar working on Modeling and Simulation, Infectious Diseases, Public Health, Environmental and Occupational Health, Epidemiology and Virology, having authored 28 papers that have together received 618 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (11 papers), Mathematical and Theoretical Epidemiology and Ecology Models (6 papers), HIV/AIDS Research and Interventions (6 papers), HIV Research and Treatment (5 papers), HIV, Drug Use, Sexual Risk (4 papers), Evolution and Genetic Dynamics (3 papers), Climate Change and Health Impacts (2 papers) and Air Quality and Health Impacts (2 papers). The work is most often cited by research in Modeling and Simulation (312 citations), Infectious Diseases (169 citations), Public Health, Environmental and Occupational Health (174 citations), Virology (19 citations) and Health, Toxicology and Mutagenesis (49 citations). Xiaodan Sun has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Yanni Xiao, Sanyi Tang, Fan Xia, Nicola Luigi Bragazzi, Biao Tang, Juhua Liang, Qian Li, Xia Wang, Zhihang Peng and Hiroshi Nishiura. Their work appears in journals such as Journal of Theoretical Biology, Theoretical Biology and Medical Modelling, International Journal of Bifurcation and Chaos, BMC Public Health and Environmental Pollution.

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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