John W. Glasser

2.6k total citations
64 papers, 1.8k citations indexed

About

John W. Glasser is a scholar working on Epidemiology, Modeling and Simulation and Infectious Diseases. According to data from OpenAlex, John W. Glasser has authored 64 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Epidemiology, 25 papers in Modeling and Simulation and 14 papers in Infectious Diseases. Recurrent topics in John W. Glasser's work include COVID-19 epidemiological studies (25 papers), Influenza Virus Research Studies (16 papers) and Vaccine Coverage and Hesitancy (14 papers). John W. Glasser is often cited by papers focused on COVID-19 epidemiological studies (25 papers), Influenza Virus Research Studies (16 papers) and Vaccine Coverage and Hesitancy (14 papers). John W. Glasser collaborates with scholars based in United States, China and Australia. John W. Glasser's co-authors include Zhilan Feng, Albert E. Barskey, Charles W. LeBaron, John P. Mullooly, Henry R. Shinefield, Joel I. Ward, Umesh D. Parashar, William E. Barlow, Robert L. Davis and Robert S. Thompson and has published in prestigious journals such as Science, New England Journal of Medicine and PLoS ONE.

In The Last Decade

John W. Glasser

61 papers receiving 1.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John W. Glasser United States 22 725 712 468 395 236 64 1.8k
Katherine E. Atkins United Kingdom 28 588 0.8× 757 1.1× 290 0.6× 344 0.9× 193 0.8× 60 1.9k
Christine Zandotti France 30 889 1.2× 1.5k 2.1× 179 0.4× 103 0.3× 243 1.0× 105 3.1k
Shelly Bolotin Canada 22 549 0.8× 1.0k 1.4× 372 0.8× 276 0.7× 135 0.6× 70 1.6k
Liesbeth Mollema Netherlands 29 657 0.9× 1.3k 1.8× 916 2.0× 216 0.5× 146 0.6× 68 2.4k
Nobuhiko Okabe Japan 31 1.8k 2.4× 1.6k 2.3× 202 0.4× 204 0.5× 399 1.7× 180 3.3k
Anders Tegnell Sweden 23 614 0.8× 682 1.0× 242 0.5× 319 0.8× 420 1.8× 71 2.0k
Ellen Brooks‐Pollock United Kingdom 22 1.1k 1.5× 758 1.1× 133 0.3× 630 1.6× 245 1.0× 66 2.2k
Wladimir J. Alonso United States 28 1.1k 1.5× 1.8k 2.5× 111 0.2× 1.1k 2.9× 403 1.7× 58 3.3k
Giovanni Gabutti Italy 27 723 1.0× 1.7k 2.4× 559 1.2× 127 0.3× 118 0.5× 174 2.7k
Susan Hahné Netherlands 31 866 1.2× 1.7k 2.4× 1.1k 2.2× 440 1.1× 298 1.3× 112 2.6k

Countries citing papers authored by John W. Glasser

Since Specialization
Citations

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

Fields of papers citing papers by John W. Glasser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John W. Glasser. 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 John W. Glasser. The network helps show where John W. Glasser may publish in the future.

Co-authorship network of co-authors of John W. Glasser

This figure shows the co-authorship network connecting the top 25 collaborators of John W. Glasser. A scholar is included among the top collaborators of John W. Glasser based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John W. Glasser. John W. Glasser is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Glasser, John W. & Zhilan Feng. (2025). Mechanistic models are hypotheses: A perspective. Mathematical Biosciences. 383. 109419–109419.
2.
Su, Qiru, Zhilan Feng, Lixin Hao, et al.. (2021). Assessing the burden of congenital rubella syndrome in China and evaluating mitigation strategies: a metapopulation modelling study. The Lancet Infectious Diseases. 21(7). 1004–1013. 20 indexed citations
3.
Feng, Zhilan & John W. Glasser. (2019). Estimating age-specific hazard rates of infection from cross-sectional observations. PubMed. 27(1). 123–140. 1 indexed citations
4.
Feng, Zhilan, et al.. (2016). Mathematical models of Ebola—Consequences of underlying assumptions. Mathematical Biosciences. 277. 89–107. 25 indexed citations
5.
Feng, Zhilan, Andrew Hill, Aaron T. Curns, & John W. Glasser. (2016). Evaluating targeted interventions via meta-population models with multi-level mixing. Mathematical Biosciences. 287. 93–104. 19 indexed citations
6.
Feng, Zhilan, et al.. (2015). A model for the coupled disease dynamics of HIV and HSV-2 with mixing among and between genders. Mathematical Biosciences. 265. 82–100. 8 indexed citations
7.
Foster, Stanley O., Kenneth Hughes, Daniel Tarantola, & John W. Glasser. (2011). Smallpox eradication in Bangladesh, 1972–1976. Vaccine. 29. D22–D29. 5 indexed citations
8.
Glasser, John W., et al.. (2011). Mixing in age-structured population models of infectious diseases. Mathematical Biosciences. 235(1). 1–7. 44 indexed citations
9.
Glasser, John W., Zhilan Feng, Jen-Hsiang Chuang, et al.. (2010). Evaluation of Targeted Influenza Vaccination Strategies via Population Modeling. PLoS ONE. 5(9). e12777–e12777. 26 indexed citations
10.
Feng, Zhilan, Yiding Yang, Dashun Xu, et al.. (2009). Timely identification of optimal control strategies for emerging infectious diseases. Journal of Theoretical Biology. 259(1). 165–171. 20 indexed citations
11.
Best, Jennifer M., Carlos Castillo‐Solórzano, John S. Spika, et al.. (2005). Reducing the Global Burden of Congenital Rubella Syndrome: Report of the World Health Organization Steering Committee on Research Related to Measles and Rubella Vaccines and Vaccination, June 2004. The Journal of Infectious Diseases. 192(11). 1890–1897. 39 indexed citations
12.
Dayan, Gustavo H., et al.. (2005). Tracking vaccine lot lifecycles using reports to the Vaccine Adverse Event Reporting System (VAERS). Pharmacoepidemiology and Drug Safety. 14(10). 671–676. 7 indexed citations
13.
Glasser, John W.. (2004). Timely Identification of Control Strategies for Emerging Infectious Diseases. 1 indexed citations
14.
Barlow, William E., Robert L. Davis, John W. Glasser, et al.. (2001). The Risk of Seizures after Receipt of Whole-Cell Pertussis or Measles, Mumps, and Rubella Vaccine. New England Journal of Medicine. 345(9). 656–661. 240 indexed citations
15.
Black, Steven, Henry R. Shinefield, Paula Ray, et al.. (1997). Risk of hospitalization because of aseptic meningitis after measles-mumps-rubella vaccination in one- to two-year-old children: an analysis of the Vaccine Safety Datalink (VSD) Project. The Pediatric Infectious Disease Journal. 16(5). 500–503. 46 indexed citations
16.
Chen, Robert T., John W. Glasser, Philip Rhodes, et al.. (1997). Vaccine Safety Datalink Project: A New Tool for Improving Vaccine Safety Monitoring in the United States. PEDIATRICS. 99(6). 765–773. 281 indexed citations
17.
Wassilak, Steven G. F., et al.. (1995). Utility of Large‐linked Databases in Vaccine Safety, Particularly in Distinguishing Independent and Synergistic Effects. Annals of the New York Academy of Sciences. 754(1). 377–377. 35 indexed citations
18.
Glasser, John W. & Holly J. Price. (1988). Evaluating Expectations Deduced from Explicit Hypotheses about Mechanisms of Competition. Oikos. 51(1). 57–57. 16 indexed citations
19.
Glasser, John W.. (1985). Changing Oceanic Paradigms. Ecology. 66(1). 315–316. 1 indexed citations
20.
Glasser, John W.. (1979). The Role of Predation in Shaping and Maintaining the Structure of Communities. The American Naturalist. 113(5). 631–641. 34 indexed citations

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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