Alexander Gutfraind

999 total citations
32 papers, 575 citations indexed

About

Alexander Gutfraind is a scholar working on Epidemiology, Hepatology and Statistical and Nonlinear Physics. According to data from OpenAlex, Alexander Gutfraind has authored 32 papers receiving a total of 575 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Epidemiology, 9 papers in Hepatology and 7 papers in Statistical and Nonlinear Physics. Recurrent topics in Alexander Gutfraind's work include Hepatitis C virus research (9 papers), HIV, Drug Use, Sexual Risk (7 papers) and Complex Network Analysis Techniques (6 papers). Alexander Gutfraind is often cited by papers focused on Hepatitis C virus research (9 papers), HIV, Drug Use, Sexual Risk (7 papers) and Complex Network Analysis Techniques (6 papers). Alexander Gutfraind collaborates with scholars based in United States, Israel and Australia. Alexander Gutfraind's co-authors include Lauren Ancel Meyers, Alexander A. Ganin, Jeffrey M. Keisler, Alexander Kott, Rami Mangoubi, Igor Linkov, Emanuele Massaro, Basmattee Boodram, Harel Dahari and Alison P. Galvani and has published in prestigious journals such as PLoS ONE, Scientific Reports and European Journal of Operational Research.

In The Last Decade

Alexander Gutfraind

31 papers receiving 560 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alexander Gutfraind United States 13 157 155 105 78 70 32 575
John A. Sokolowski United States 12 80 0.5× 212 1.4× 95 0.9× 14 0.2× 27 0.4× 56 749
Dionne M. Aleman Canada 21 40 0.3× 64 0.4× 23 0.2× 26 0.3× 95 1.4× 75 1.0k
Francesco Gargiulo Italy 16 24 0.2× 187 1.2× 24 0.2× 197 2.5× 5 0.1× 64 935
Rajendra Kulkarni United States 10 29 0.2× 36 0.2× 47 0.4× 11 0.1× 40 0.6× 54 514
Douglas R. Bish United States 16 99 0.6× 50 0.3× 47 0.4× 11 0.1× 2 0.0× 41 771
Trevor J. Sweeting United Kingdom 17 57 0.4× 86 0.6× 18 0.2× 5 0.1× 28 0.4× 59 1.3k
Ariel Cintrón-Arias United States 6 5 0.0× 55 0.4× 122 1.2× 10 0.1× 189 2.7× 11 511
Zhenzhen Lu China 12 16 0.1× 62 0.4× 7 0.1× 6 0.1× 38 0.5× 29 1.1k
Vishwajeet Kumar India 15 7 0.0× 123 0.8× 8 0.1× 23 0.3× 19 0.3× 58 842
Mehdi Jalalpour United States 14 362 2.3× 216 1.4× 52 0.5× 18 0.3× 24 839

Countries citing papers authored by Alexander Gutfraind

Since Specialization
Citations

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

Fields of papers citing papers by Alexander Gutfraind

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alexander Gutfraind. 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 Alexander Gutfraind. The network helps show where Alexander Gutfraind may publish in the future.

Co-authorship network of co-authors of Alexander Gutfraind

This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Gutfraind. A scholar is included among the top collaborators of Alexander Gutfraind 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 Alexander Gutfraind. Alexander Gutfraind 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.
2.
Mackesy‐Amiti, Mary Ellen, Alexander Gutfraind, Eric Tatara, et al.. (2024). Modeling of randomized hepatitis C vaccine trials: Bridging the gap between controlled human infection models and real-word testing. PNAS Nexus. 4(1). pgae564–pgae564. 1 indexed citations
3.
Gutfraind, Alexander, et al.. (2023). Victims of human trafficking and exploitation in the healthcare system: a retrospective study using a large multi-state dataset and ICD-10 codes. Frontiers in Public Health. 11. 1243413–1243413. 3 indexed citations
4.
Gutfraind, Alexander, et al.. (2021). Effectiveness of isolation policies in schools: evidence from a mathematical model of influenza and COVID-19. PeerJ. 9. e11211–e11211. 4 indexed citations
5.
Tatara, Eric, Nicholson Collier, Jonathan Ozik, et al.. (2019). Multi-Objective Model Exploration of Hepatitis C Elimination in an Agent-Based Model of People who Inject Drugs. PubMed. 13. 1008–1019. 8 indexed citations
6.
Gutfraind, Alexander, Basmattee Boodram, Jennifer E. Layden, et al.. (2019). Modeling indicates efficient vaccine-based interventions for the elimination of hepatitis C virus among persons who inject drugs in metropolitan Chicago. Vaccine. 37(19). 2608–2616. 9 indexed citations
7.
Gutfraind, Alexander, Jennifer K. Peterson, Erica Billig Rose, et al.. (2018). Integrating evidence, models and maps to enhance Chagas disease vector surveillance. PLoS neglected tropical diseases. 12(11). e0006883–e0006883. 9 indexed citations
8.
Major, Marian, Alexander Gutfraind, Louis Shekhtman, et al.. (2018). Modeling of patient virus titers suggests that availability of a vaccine could reduce hepatitis C virus transmission among injecting drug users. Science Translational Medicine. 10(449). 35 indexed citations
9.
Boodram, Basmattee, Anna Hotton, Louis Shekhtman, Alexander Gutfraind, & Harel Dahari. (2017). High-Risk Geographic Mobility Patterns among Young Urban and Suburban Persons who Inject Drugs and their Injection Network Members. Journal of Urban Health. 95(1). 71–82. 16 indexed citations
10.
Gutfraind, Alexander, et al.. (2017). Modeling vaccine and DAA treatment scale up effect on hepatitis C prevalence among persons who inject drugs in metropolitan Chicago. Journal of Hepatology. 66(1). S505–S506. 2 indexed citations
11.
Staudt, Christian, et al.. (2017). Generating realistic scaled complex networks. Applied Network Science. 2(1). 36–36. 14 indexed citations
12.
Ganin, Alexander A., Emanuele Massaro, Alexander Gutfraind, et al.. (2016). Operational resilience: concepts, design and analysis. Scientific Reports. 6(1). 19540–19540. 197 indexed citations
13.
Fu, Rui, Alexander Gutfraind, & Margaret L. Brandeau. (2016). Modeling a dynamic bi-layer contact network of injection drug users and the spread of blood-borne infections. Mathematical Biosciences. 273. 102–113. 9 indexed citations
14.
15.
Gutfraind, Alexander & Lauren Ancel Meyers. (2015). Evaluating Large-scale Blood Transfusion Therapy for the Current Ebola Epidemic in Liberia. The Journal of Infectious Diseases. 211(8). 1262–1267. 18 indexed citations
16.
Gutfraind, Alexander, Basmattee Boodram, Marian Major, et al.. (2015). Mathematical Modeling of Hepatitis C Prevalence Reduction with Antiviral Treatment Scale-Up in Persons Who Inject Drugs in Metropolitan Chicago. PLoS ONE. 10(8). e0135901–e0135901. 24 indexed citations
17.
Johnson, Matthew, et al.. (2013). Evader interdiction: algorithms, complexity and collateral damage. Annals of Operations Research. 222(1). 341–359. 6 indexed citations
18.
Gutfraind, Alexander. (2010). Optimizing Topological Cascade Resilience Based on the Structure of Terrorist Networks. PLoS ONE. 5(11). e13448–e13448. 24 indexed citations
19.
Gutfraind, Alexander. (2009). Understanding Terrorist Organizations with a Dynamic Model. Studies in Conflict and Terrorism. 32(1). 45–59. 17 indexed citations
20.
Gutfraind, Alexander & Achim Kempf. (2007). Error-reducing Structure of the Genetic Code Indicates Code Origin in Non-thermophile Organisms. Origins of Life and Evolution of Biospheres. 38(1). 75–85. 8 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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