Sheikh Taslim Ali

3.8k citations
46 papers · 2.1k indexed · 1 hit paper · h-index 21

Sheikh Taslim Ali

43 papers receiving 2.0k citations

Hit Papers

Impact assessment of non-pharmaceutical interventions aga...8682020202620222024250500750

Peers

Sheikh Taslim Ali
Comparison fields: 5 of 123
  • Modeling and Simulation 1.3k
  • Infectious Diseases 890
  • Health 181
  • Epidemiology 633
  • Clinical Psychology 323
Replace Kenji Mizumoto with:
Kenji Mizumoto Japan
Tim K. Tsang Hong Kong
Mike Yat Wah Kwan Hong Kong
Kiesha Prem United Kingdom
Rebecca Katz United States
Xiangjun Du China
Juliette Paireau France
Borame Sue Lee Dickens Singapore
Chad R. Wells United States
Sheikh Taslim Ali relative to Kenji Mizumoto Japan Kenji Mizumoto's profile →
Citations per field
00.5×4.6×
Kenji Mizumoto · 1×
Citations per year

Countries citing papers authored by Sheikh Taslim Ali

Since Specialization
Citations

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

Fields of papers citing papers by Sheikh Taslim Ali

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sheikh Taslim Ali. 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 Sheikh Taslim Ali. The network helps show where Sheikh Taslim Ali may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 20242
4 202310
5 20226
6 202222
7 202218
8 202225
9 20224
10 202266
11 202257
12 202111
13 202156
14 202137
15 2020217
16 202017
17 20205
18
Stochastic Modelling: An Approach to Quantify the Transmission Intensity of Pandemic Influenza (H1N1) in Maharashtra
20130
19 201329
20 20110

About Sheikh Taslim Ali

Sheikh Taslim Ali is a scholar working on Modeling and Simulation, Infectious Diseases and Health, having authored 46 papers that have together received 2.1k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (36 papers), SARS-CoV-2 and COVID-19 Research (13 papers), Influenza Virus Research Studies (13 papers), Respiratory viral infections research (7 papers), Viral Infections and Outbreaks Research (7 papers), COVID-19 Pandemic Impacts (7 papers), SARS-CoV-2 detection and testing (7 papers) and Animal Disease Management and Epidemiology (5 papers). The work is most often cited by research in Modeling and Simulation (1.3k citations), Infectious Diseases (890 citations) and Health (181 citations). Sheikh Taslim Ali has collaborated with scholars based in Hong Kong, China and South Korea. Frequent co-authors include Benjamin J. Cowling, GM Leung, Peng Wu, Eric H. Y. Lau, Tim K. Tsang, Qiuyan Liao, Susan S. Chiu, Min Whui Fong, Joseph T. Wu and Mike Yat Wah Kwan. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

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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