Hailing Chang
Impact in
- Infectious Diseases top 5%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- SARS-CoV-2 detection and testing
- Viral gastroenteritis research and epidemiology
- Obstetrics and Gynecology top 5%
- COVID-19 Impact on Reproduction
Papers in
-
- SARS-CoV-2 and COVID-19 Research 7
- Viral gastroenteritis research and epidemiology 6
- COVID-19 Clinical Research Studies 6
-
- Bacterial Infections and Vaccines 3
- Co-authors
- Mei Fang Zeng (17 shared papers)He Tian (9 shared papers)Jin Xu (4 shared papers)Yanling Ge (3 shared papers)Chuning Wang (5 shared papers)pengcheng liu (2 shared papers)Zhenghai Qu (1 shared paper)Lei Xu (1 shared paper)
In The Last Decade
Hailing Chang
21 papers receiving 1.1k citations
Hailing Chang's Hit Papers
Peers
Comparison fields: 5 of 89
- Infectious Diseases 666
- Obstetrics and Gynecology 172
- Modeling and Simulation 53
- Virology 50
- Molecular Medicine 39
Countries citing papers authored by Hailing Chang
This map shows the geographic impact of Hailing Chang'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 Hailing Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hailing Chang more than expected).
Fields of papers citing papers by Hailing Chang
This network shows the impact of papers produced by Hailing Chang. 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 Hailing Chang. The network helps show where Hailing Chang may publish in the future.
Co-authors
The 25 scholars most cited alongside Hailing Chang, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A Case Series of Children With 2019 Novel Coronavirus Infection: Clinical and Epidemiological Features Hit paper breakdown → | 2020 | 696 |
| 2 | 2020 | 84 | |
| 3 | 2013 | 70 | |
| 4 | 1996 | 66 | |
| 5 | 2020 | 43 | |
| 6 | 2019 | 36 | |
| 7 | 2021 | 23 | |
| 8 | 2022 | 22 | |
| 9 | 2019 | 20 | |
| 10 | 2017 | 19 | |
| 11 | 2020 | 17 | |
| 12 | 2023 | 15 | |
| 13 | 2023 | 11 | |
| 14 | 2023 | 8 | |
| 15 | 2015 | 5 | |
| 16 | 2023 | 4 | |
| 17 | 2021 | 3 | |
| 18 | 2024 | 3 | |
| 19 | 2022 | 3 | |
| 20 | 2021 | 1 |
About Hailing Chang
Hailing Chang is a scholar working on Infectious Diseases, Microbiology, Epidemiology, Obstetrics and Gynecology and Food Science, having authored 22 papers that have together received 1.1k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (7 papers), Viral gastroenteritis research and epidemiology (6 papers), COVID-19 Clinical Research Studies (6 papers), Respiratory viral infections research (4 papers), Bacterial Infections and Vaccines (3 papers), Salmonella and Campylobacter epidemiology (3 papers), COVID-19 Impact on Reproduction (2 papers) and Enterobacteriaceae and Cronobacter Research (1 paper). The work is most often cited by research in Infectious Diseases (666 citations), Obstetrics and Gynecology (172 citations), Modeling and Simulation (53 citations), Virology (50 citations) and Molecular Medicine (39 citations). Hailing Chang has collaborated with scholars based in China, France and Taiwan. Frequent co-authors include Mei Fang Zeng, He Tian, Jin Xu, Yanling Ge, Chuning Wang, pengcheng liu, Zhenghai Qu, Lei Xu, Yang Zhi and Wang Jian-she. Their work appears in journals such as The Pediatric Infectious Disease Journal, Influenza and Other Respiratory Viruses, Foodborne Pathogens and Disease, Vaccine and Journal of Microbiology Immunology and Infection.
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.