David Benkeser

5.7k total citations · 1 hit paper
66 papers, 1.8k citations indexed

About

David Benkeser is a scholar working on Statistics and Probability, Infectious Diseases and Epidemiology. According to data from OpenAlex, David Benkeser has authored 66 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Statistics and Probability, 20 papers in Infectious Diseases and 17 papers in Epidemiology. Recurrent topics in David Benkeser's work include Advanced Causal Inference Techniques (16 papers), Statistical Methods and Inference (15 papers) and Statistical Methods and Bayesian Inference (9 papers). David Benkeser is often cited by papers focused on Advanced Causal Inference Techniques (16 papers), Statistical Methods and Inference (15 papers) and Statistical Methods and Bayesian Inference (9 papers). David Benkeser collaborates with scholars based in United States, Georgia and Kenya. David Benkeser's co-authors include Patrick S. Sullivan, Elise Lankiewicz, Leandro Mena, Austin Jones, Jennifer Sherwood, Brian Honermann, Chris Beyrer, Stefan Baral, Gregorio A. Millett and Jeffrey S. Crowley and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

David Benkeser

60 papers receiving 1.8k citations

Hit Papers

Assessing differential impacts of COVID-19 on black commu... 2020 2026 2022 2024 2020 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Assessing differential impacts of COVID-19 on black communities
    2020 821 citations David Benkeser, Patrick S. Sullivan et al. profile →

Peers

David Benkeser
Eric Tchetgen Tchetgen United States
Laina D. Mercer United States
Andrew Anglemyer United States
Michael L. Pennell United States
Stanley Xu United States
Karla Díaz-Ordaz United Kingdom
Kwok Fai Lam Hong Kong
Catherine R. Lesko United States
Ruth H. Keogh United Kingdom
Peter Doshi United States
Eric Tchetgen Tchetgen United States
David Benkeser
Citations per year, relative to David Benkeser David Benkeser (= 1×) peers Eric Tchetgen Tchetgen

Countries citing papers authored by David Benkeser

Since Specialization
Citations

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

Fields of papers citing papers by David Benkeser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Benkeser

This figure shows the co-authorship network connecting the top 25 collaborators of David Benkeser. A scholar is included among the top collaborators of David Benkeser 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 David Benkeser. David Benkeser 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.
Kim, Sara, Patricia B. Pavlinac, Karim Manji, et al.. (2025). Personalized azithromycin treatment rules for children with watery diarrhea using machine learning. Nature Communications. 16(1). 5968–5968.
2.
Liu, Chang, Qin Hui, Quinn S. Wells, et al.. (2024). A Multivariable Mendelian Randomization Study of Systolic and Diastolic Blood Pressure, Lipid Profile, and Heart Failure Subtypes. Genes. 15(9). 1126–1126. 1 indexed citations
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Hejazi, Nima S., Xiaoying Shen, Lindsay N. Carpp, et al.. (2023). Stochastic interventional approach to assessing immune correlates of protection: Application to the COVE messenger RNA-1273 vaccine trial. International Journal of Infectious Diseases. 137. 28–39. 2 indexed citations
6.
Benkeser, David, et al.. (2022). Authorship trends in infectious diseases society of America affiliated journal articles conducted in low-income countries, 1998–2018. SHILAP Revista de lepidopterología. 2(6). e0000275–e0000275. 10 indexed citations
7.
Laan, Mark J. van der, David Benkeser, & Weixin Cai. (2022). Efficient estimation of pathwise differentiable target parameters with the undersmoothed highly adaptive lasso. The International Journal of Biostatistics. 19(1). 261–289. 4 indexed citations
8.
Nebel, Mary Beth, Daniel E. Lidstone, Liwei Wang, et al.. (2022). Accounting for motion in resting-state fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?. NeuroImage. 257. 119296–119296. 22 indexed citations
9.
Benkeser, David, et al.. (2021). Nonparametric inference for interventional effects with multiple mediators. SHILAP Revista de lepidopterología. 10 indexed citations
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Benkeser, David, Iván Díaz, Alex Luedtke, et al.. (2020). Improving precision and power in randomized trials for COVID‐19 treatments using covariate adjustment, for binary, ordinal, and time‐to‐event outcomes. Biometrics. 77(4). 1467–1481. 42 indexed citations
12.
Reback, Cathy J., Joshua A. Rusow, Demetria Cain, et al.. (2020). Technology-Based Stepped Care to Stem Transgender Adolescent Risk Transmission: Protocol for a Randomized Controlled Trial (TechStep). JMIR Research Protocols. 9(8). e18326–e18326. 11 indexed citations
13.
Hejazi, Nima S., Mark J. van der Laan, Holly Janes, Peter B. Gilbert, & David Benkeser. (2020). Efficient nonparametric inference on the effects of stochastic interventions under two‐phase sampling, with applications to vaccine efficacy trials. Biometrics. 77(4). 1241–1253. 17 indexed citations
14.
Benkeser, David, Keith J. Horvath, Cathy J. Reback, Joshua A. Rusow, & Michael G. Hudgens. (2020). Design and Analysis Considerations for a Sequentially Randomized HIV Prevention Trial. Statistics in Biosciences. 12(3). 446–467. 4 indexed citations
15.
Magaret, Craig A., David Benkeser, Brian D. Williamson, et al.. (2019). Prediction of VRC01 neutralization sensitivity by HIV-1 gp160 sequence features. PLoS Computational Biology. 15(4). e1006952–e1006952. 27 indexed citations
16.
Juraska, Michal, Craig A. Magaret, Jason Shao, et al.. (2018). Viral genetic diversity and protective efficacy of a tetravalent dengue vaccine in two phase 3 trials. Proceedings of the National Academy of Sciences. 115(36). 48 indexed citations
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18.
Koelman, Diederik L H, David Benkeser, Joshua P. Klein, & Farrah J. Mateen. (2017). Acute disseminated encephalomyelitis: prognostic value of early follow-up brain MRI. Journal of Neurology. 264(8). 1754–1762. 8 indexed citations
19.
Khandelwal, Nita, Ruth A. Engelberg, David Benkeser, Norma B. Coe, & J. Randall Curtis. (2014). End-of-Life Expenditure in the ICU and Perceived Quality of Dying. CHEST Journal. 146(6). 1594–1603. 14 indexed citations
20.
Kizer, Jorge R., David Benkeser, Alice M. Arnold, et al.. (2012). Total and High-Molecular-Weight Adiponectin and Risk of Coronary Heart Disease and Ischemic Stroke in Older Adults. The Journal of Clinical Endocrinology & Metabolism. 98(1). 255–263. 39 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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