Liling Chaw
Impact in
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies
Papers in
-
- Tuberculosis Research and Epidemiology 6
- Viral Infections and Outbreaks Research 4
-
- Pneumocystis jirovecii pneumonia detection and treatment 2
- Influenza Virus Research Studies 2
- Co-authors
- Justin Wong (9 shared papers)Lin Naing (8 shared papers)Wee Chian Koh (4 shared papers)Mohammad Fathi Alikhan (4 shared papers)Matthew Griffith (3 shared papers)Roberta Pastore (2 shared papers)Long Chiau Ming (6 shared papers)Hitoshi Oshitani (2 shared papers)
- Journals
- PLoS ONE (4 papers)International Journal of Environmental Research and Public Health (2 papers)BMJ Open Respiratory Research (1 paper)BMJ Open (1 paper)Scientific Reports (1 paper)
- Partner nations
- BruneiMalaysiaPhilippines
In The Last Decade
Liling Chaw
27 papers receiving 510 citations
Peers
Comparison fields: 5 of 103
- Modeling and Simulation 203
- Applied Microbiology and Biotechnology 30
- Infectious Diseases 237
- Epidemiology 135
- Health 32
Countries citing papers authored by Liling Chaw
This map shows the geographic impact of Liling Chaw'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 Liling Chaw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liling Chaw more than expected).
Fields of papers citing papers by Liling Chaw
This network shows the impact of papers produced by Liling Chaw. 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 Liling Chaw. The network helps show where Liling Chaw may publish in the future.
Co-authors
The 25 scholars most cited alongside Liling Chaw, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 140 | |
| 2 | 2020 | 52 | |
| 3 | 2020 | 38 | |
| 4 | 2016 | 36 | |
| 5 | 2016 | 28 | |
| 6 | 2020 | 26 | |
| 7 | 2020 | 23 | |
| 8 | 2020 | 23 | |
| 9 | 2020 | 21 | |
| 10 | 2020 | 19 | |
| 11 | 2020 | 18 | |
| 12 | 2021 | 18 | |
| 13 | 2022 | 14 | |
| 14 | 2022 | 10 | |
| 15 | 2022 | 9 | |
| 16 | 2022 | 9 | |
| 17 | 2019 | 7 | |
| 18 | 2022 | 6 | |
| 19 | 2018 | 4 | |
| 20 | 2021 | 3 |
About Liling Chaw
Liling Chaw is a scholar working on Infectious Diseases, Epidemiology, Modeling and Simulation, Surgery and Clinical Psychology, having authored 28 papers that have together received 516 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (7 papers), Tuberculosis Research and Epidemiology (6 papers), Viral Infections and Outbreaks Research (4 papers), COVID-19 and Mental Health (4 papers), Mosquito-borne diseases and control (2 papers), Colorectal Cancer Treatments and Studies (2 papers), Pneumocystis jirovecii pneumonia detection and treatment (2 papers) and Influenza Virus Research Studies (2 papers). The work is most often cited by research in Modeling and Simulation (203 citations), Applied Microbiology and Biotechnology (30 citations), Infectious Diseases (237 citations), Epidemiology (135 citations) and Health (32 citations). Liling Chaw has collaborated with scholars based in Brunei, Malaysia and Philippines. Frequent co-authors include Justin Wong, Lin Naing, Wee Chian Koh, Mohammad Fathi Alikhan, Matthew Griffith, Roberta Pastore, Long Chiau Ming, Hitoshi Oshitani, Taro Kamigaki and David Koh. Their work appears in journals such as PLoS ONE, International Journal of Environmental Research and Public Health, BMJ Open Respiratory Research, BMJ Open and Scientific Reports.
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.