OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Identifying Synergistic Interventions to Address COVID-19 Using a Large Scale Agent-Based Model
Junjiang Li, Philippe J. Giabbanelli
Lecture notes in computer science (2021), pp. 655-662
Closed Access | Times Cited: 12

Showing 12 citing articles:

Comparative effectiveness of contact tracing interventions in the context of the COVID-19 pandemic: a systematic review
Francisco Pozo-Martin, Miguel Beltrán, Sophie Alice Müller, et al.
European Journal of Epidemiology (2023) Vol. 38, Iss. 3, pp. 243-266
Open Access | Times Cited: 31

Modified EDAS Method for MAGDM Based on MSM Operators with 2-Tuple Linguistic T -Spherical Fuzzy Sets
Sumera Naz, Muhammad Akram, G. Muhiuddin, et al.
Mathematical Problems in Engineering (2022) Vol. 2022, pp. 1-34
Open Access | Times Cited: 21

Simulation-based what-if analysis for controlling the spread of Covid-19 in universities
Navid Ghaffarzadegan
PLoS ONE (2021) Vol. 16, Iss. 2, pp. e0246323-e0246323
Open Access | Times Cited: 26

Open data for COVID-19 policy analysis and mapping
Rebecca Katz, Kate Toole, Hailey Robertson, et al.
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 4

Experimental evaluation of a machine learning approach to improve the reproducibility of network simulations
Luke Liang, Hieu Phan, Philippe J. Giabbanelli
SIMULATION (2024) Vol. 100, Iss. 6, pp. 545-561
Closed Access | Times Cited: 1

When Do We Need Massive Computations to Perform Detailed COVID‐19 Simulations?
Christopher B. Lutz, Philippe J. Giabbanelli
Advanced Theory and Simulations (2021) Vol. 5, Iss. 2
Open Access | Times Cited: 9

Modelling the SARS-CoV-2 outbreak: Assessing the usefulness of protective measures to reduce the pandemic at population level
M. Àngels Colomer, Antoni Margalida, Francesc Alòs, et al.
The Science of The Total Environment (2021) Vol. 789, pp. 147816-147816
Open Access | Times Cited: 7

Opportunities and Challenges in Developing COVID-19 Simulation Models: Lessons from Six Funded Projects
Philippe J. Giabbanelli, Jennifer Badham, Brian Castellani, et al.
(2021)
Open Access | Times Cited: 7

COVID AMP: An Open Access Dataset of COVID-19 Response Policies
Rebecca Katz, Kate Toole, Hailey Robertson, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 1

Towards Reusable Building Blocks to Develop COVID-19 Simulation Models
S. Andrew Schroeder, Christopher Vendome, Philippe J. Giabbanelli, et al.
2018 Winter Simulation Conference (WSC) (2022), pp. 569-580
Closed Access | Times Cited: 2

When do we need massive computations to perform detailed COVID-19 simulations?
Christopher B. Lutz, Philippe J. Giabbanelli
medRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 1

Computational Science – ICCS 2021
Maciej Paszyński, Dieter Kranzlmüller, Valeria V. Krzhizhanovskaya, et al.
Lecture notes in computer science (2021)
Closed Access | Times Cited: 1

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