Eva A. Enns

3.6k total citations
69 papers, 1.2k citations indexed

About

Eva A. Enns is a scholar working on Infectious Diseases, General Health Professions and Epidemiology. According to data from OpenAlex, Eva A. Enns has authored 69 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Infectious Diseases, 22 papers in General Health Professions and 21 papers in Epidemiology. Recurrent topics in Eva A. Enns's work include HIV/AIDS Research and Interventions (17 papers), COVID-19 epidemiological studies (14 papers) and Adolescent Sexual and Reproductive Health (13 papers). Eva A. Enns is often cited by papers focused on HIV/AIDS Research and Interventions (17 papers), COVID-19 epidemiological studies (14 papers) and Adolescent Sexual and Reproductive Health (13 papers). Eva A. Enns collaborates with scholars based in United States, Canada and Netherlands. Eva A. Enns's co-authors include Fernando Alarid‐Escudero, Hawre Jalal, Eline Krijkamp, Petros Pechlivanoglou, Jessie Juusola, Alan M. Garber, Crystal Smith-Spangler, M. G. Myriam Hunink, Margaret L. Brandeau and Meggan E. Craft and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Annals of Internal Medicine and PLoS ONE.

In The Last Decade

Eva A. Enns

66 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eva A. Enns United States 18 251 240 199 168 139 69 1.2k
Faisal Shuaib Nigeria 21 340 1.4× 290 1.2× 654 3.3× 63 0.4× 187 1.3× 85 1.8k
Raymundo Soares Azevedo Brazil 25 284 1.1× 685 2.9× 430 2.2× 39 0.2× 179 1.3× 104 1.8k
Louis Coupal Canada 20 181 0.7× 196 0.8× 167 0.8× 379 2.3× 119 0.9× 61 1.8k
Kofi Nyarko Ghana 20 247 1.0× 488 2.0× 189 0.9× 69 0.4× 89 0.6× 78 1.2k
Zhihang Peng China 25 347 1.4× 622 2.6× 788 4.0× 226 1.3× 135 1.0× 143 2.0k
Tao Shen China 21 174 0.7× 514 2.1× 312 1.6× 23 0.1× 36 0.3× 88 1.6k
Sudipta Bhat India 9 126 0.5× 100 0.4× 943 4.7× 132 0.8× 102 0.7× 14 1.7k
Mac W. Otten United States 17 902 3.6× 310 1.3× 342 1.7× 83 0.5× 251 1.8× 25 1.8k
Reiko Tsuyuoka Japan 21 488 1.9× 128 0.5× 181 0.9× 72 0.4× 23 0.2× 40 1.2k
Kung‐Jong Lui United States 19 118 0.5× 577 2.4× 362 1.8× 150 0.9× 100 0.7× 146 2.2k

Countries citing papers authored by Eva A. Enns

Since Specialization
Citations

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

Fields of papers citing papers by Eva A. Enns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eva A. Enns. 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 Eva A. Enns. The network helps show where Eva A. Enns may publish in the future.

Co-authorship network of co-authors of Eva A. Enns

This figure shows the co-authorship network connecting the top 25 collaborators of Eva A. Enns. A scholar is included among the top collaborators of Eva A. Enns 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 Eva A. Enns. Eva A. Enns 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.
Mink, Pamela J., et al.. (2023). Adaptive COVID-19 Mitigation Strategies: Tradeoffs between Trigger Thresholds, Response Timing, and Effectiveness. MDM Policy & Practice. 8(2). 107949468–107949468. 1 indexed citations
2.
Smith, Matthew J., Eva A. Enns, Lauren A. White, Marie L. J. Gilbertson, & Meggan E. Craft. (2023). The illusion of personal health decisions for infectious disease management: disease spread in social contact networks. Royal Society Open Science. 10(3). 221122–221122. 1 indexed citations
3.
Dorélien, Audrey, et al.. (2023). Quantifying social contact patterns in Minnesota during stay-at-home social distancing order. BMC Infectious Diseases. 23(1). 324–324. 5 indexed citations
4.
Wheatley, Margo M., et al.. (2023). Barriers, opportunities, and potential costs of expanding HIV support services. AIDS Care. 35(8). 1083–1090.
5.
Jenness, Samuel M., Cynthia M. Lyles, Kyle T. Bernstein, et al.. (2022). The Role of HIV Partner Services in the Modern Biomedical HIV Prevention Era: A Network Modeling Study. Sexually Transmitted Diseases. 49(12). 801–807. 3 indexed citations
6.
Jenness, Samuel M., Dawn K. Smith, Julia L. Marcus, et al.. (2021). A decision analytics model to optimize investment in interventions targeting the HIV preexposure prophylaxis cascade of care. AIDS. 35(9). 1479–1489. 4 indexed citations
7.
Enns, Eva A., et al.. (2021). Network connectivity of Minnesota waterbodies and implications for aquatic invasive species prevention. Biological Invasions. 23(10). 3231–3242. 18 indexed citations
8.
Alarid‐Escudero, Fernando, Eline Krijkamp, Eva A. Enns, et al.. (2021). A Tutorial on Time-Dependent Cohort State-Transition Models in R using a Cost-Effectiveness Analysis Example. arXiv (Cornell University). 11 indexed citations
9.
10.
Krijkamp, Eline, Fernando Alarid‐Escudero, Eva A. Enns, et al.. (2020). A Multidimensional Array Representation of State-Transition Model Dynamics. Medical Decision Making. 40(2). 242–248. 9 indexed citations
11.
Rajasingham, Radha, Eva A. Enns, Alexander Khoruts, & Byron P. Vaughn. (2019). Cost-effectiveness of Treatment Regimens for Clostridioides difficile Infection: An Evaluation of the 2018 Infectious Diseases Society of America Guidelines. Clinical Infectious Diseases. 70(5). 754–762. 43 indexed citations
12.
Alarid‐Escudero, Fernando, Eva A. Enns, Karen M. Kuntz, Tzeyu L. Michaud, & Hawre Jalal. (2019). “Time Traveling Is Just Too Dangerous” but Some Methods Are Worth Revisiting: The Advantages of Expected Loss Curves Over Cost-Effectiveness Acceptability Curves and Frontier. Value in Health. 22(5). 611–618. 30 indexed citations
13.
Alarid‐Escudero, Fernando, et al.. (2019). A Need for Change! A Coding Framework for Improving Transparency in Decision Modeling. PharmacoEconomics. 37(11). 1329–1339. 33 indexed citations
14.
VanderWaal, Kimberly, Eva A. Enns, Meggan E. Craft, et al.. (2018). Modeling cost-effectiveness of risk-based bovine tuberculosis surveillance in Minnesota. Preventive Veterinary Medicine. 159. 1–11. 12 indexed citations
15.
Lee, Kyueun, Dimitri Drekonja, & Eva A. Enns. (2017). Cost-Effectiveness of Antibiotic Prophylaxis Strategies for Transrectal Prostate Biopsy in an Era of Increasing Antimicrobial Resistance. Value in Health. 21(3). 310–317. 8 indexed citations
16.
VanderWaal, Kimberly, Eva A. Enns, Catalina Picasso‐Risso, et al.. (2017). Optimal surveillance strategies for bovine tuberculosis in a low-prevalence country. Scientific Reports. 7(1). 4140–4140. 30 indexed citations
17.
Enns, Eva A., Cavan Reilly, Beth A Virnig, et al.. (2016). Potential Impact of Integrating HIV Surveillance and Clinic Data on Retention-in-Care Estimates and Re-Engagement Efforts. AIDS Patient Care and STDs. 30(9). 409–415. 14 indexed citations
18.
Alarid‐Escudero, Fernando, et al.. (2015). Calibration of Piecewise Markov Models Using a Change-Point Analysis Through an Iterative Convex Optimization Algorithm. Value in Health. 18(7). A814–A814. 1 indexed citations
19.
Enns, Eva A.. (2012). CALIBRATION METHODS FOR INFERRING TRANSITION PROBABILITIES FROM CROSS-SECTIONAL STUDIES. 1 indexed citations
20.
Smith-Spangler, Crystal, Jessie Juusola, Eva A. Enns, et al.. (2010). Desalination of the American Diet: Population Strategies to Decrease Sodium Intake and the Burden of Cardiovascular Disease. Annals of Internal Medicine. 1 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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