Max S. Y. Lau
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies 15
- Infectious Diseases top 5%
- Viral Infections and Outbreaks Research 4
- Viral Infections and Vectors 3
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- Influenza Virus Research Studies 4
- Virology and Viral Diseases 3
- Data-Driven Disease Surveillance 2
- Agronomy and Crop Science top 10%
- Animal Disease Management and Epidemiology 7
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- COVID-19 Pandemic Impacts 3
- Co-authors
- Bryan T. GrenfellKristin N. NelsonSteven RileyBen LopmanBenjamin J. CowlingMichael BryanBenjamin D. DalzielAmanda McClelland
- Journals
- Proceedings of the National Academy of Sciences (3 papers)PLoS ONE (1 paper)Scientific Reports (1 paper)
- Partner nations
- United StatesUnited KingdomHong Kong
In The Last Decade
Max S. Y. Lau
19 papers receiving 623 citations
Peers
Comparison fields: 5 of 88
- Modeling and Simulation 413
- Infectious Diseases 252
- Epidemiology 186
- Agronomy and Crop Science 54
- Health 34
Countries citing papers authored by Max S. Y. Lau
This map shows the geographic impact of Max S. Y. Lau'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 Max S. Y. Lau with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Max S. Y. Lau more than expected).
Fields of papers citing papers by Max S. Y. Lau
This network shows the impact of papers produced by Max S. Y. Lau. 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 Max S. Y. Lau. The network helps show where Max S. Y. Lau may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Max S. Y. Lau, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 19 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 0 | |
| 6 | 2022 | 3 | |
| 7 | 2022 | 4 | |
| 8 | 2021 | 58 | |
| 9 | 2020 | 142 | |
| 10 | 2020 | 9 | |
| 11 | 2020 | 10 | |
| 12 | 2019 | 11 | |
| 13 | 2019 | 3 | |
| 14 | Inferring who-infected-whom-where in the 2016 Zika outbreak in Singapore: a spatio-temporal model | 2019 | 0 |
| 15 | 2018 | 27 | |
| 16 | 2017 | 17 | |
| 17 | 2015 | 43 | |
| 18 | 2015 | 48 | |
| 19 | 2011 | 21 | |
| 20 | 2010 | 80 |
About Max S. Y. Lau
Max S. Y. Lau is a scholar working on Modeling and Simulation, Agronomy and Crop Science and Infectious Diseases, having authored 23 papers that have together received 631 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (15 papers), Animal Disease Management and Epidemiology (7 papers), Influenza Virus Research Studies (4 papers), Viral Infections and Outbreaks Research (4 papers), Virology and Viral Diseases (3 papers), Viral Infections and Vectors (3 papers), COVID-19 Pandemic Impacts (3 papers) and Data-Driven Disease Surveillance (2 papers). The work is most often cited by research in Modeling and Simulation (413 citations), Infectious Diseases (252 citations) and Epidemiology (186 citations). Max S. Y. Lau has collaborated with scholars based in United States, United Kingdom and Hong Kong. Frequent co-authors include Bryan T. Grenfell, Kristin N. Nelson, Steven Riley, Ben Lopman, Benjamin J. Cowling, Michael Bryan, Benjamin D. Dalziel, Amanda McClelland, Gavin J. Gibson and George Streftaris. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS ONE 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.