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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:

Quantifying the information in noisy epidemic curves
Kris V. Parag, Christl A. Donnelly, Alexander E. Zarebski
Nature Computational Science (2022) Vol. 2, Iss. 9, pp. 584-594
Open Access | Times Cited: 24

Showing 24 citing articles:

Effectiveness assessment of non-pharmaceutical interventions: lessons learned from the COVID-19 pandemic
Adrian Lison, Nicolas Banholzer, Mrinank Sharma, et al.
The Lancet Public Health (2023) Vol. 8, Iss. 4, pp. e311-e317
Open Access | Times Cited: 32
Resurgence of Omicron BA.2 in SARS-CoV-2 infection-naive Hong Kong
Ruopeng Xie, Kimberly M. Edwards, Dillon C. Adam, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 23
Generative Bayesian modeling to nowcast the effective reproduction number from line list data with missing symptom onset dates
Adrian Lison, Sam Abbott, Jana S. Huisman, et al.
PLoS Computational Biology (2024) Vol. 20, Iss. 4, pp. e1012021-e1012021
Open Access | Times Cited: 8
Asymmetric limits on timely interventions from noisy epidemic data
Kris V. Parag, Ben Lambert, Christl A. Donnelly, et al.
medRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Optimal algorithms for controlling infectious diseases in real time using noisy infection data
Sándor Beregi, Kris V. Parag
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 3
Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand
Leighton M. Watson, Michael J. Plank, Bridget Armstrong, et al.
Communications Medicine (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 2
Risk averse reproduction numbers improve resurgence detection
Kris V. Parag, Uri Obolski
PLoS Computational Biology (2023) Vol. 19, Iss. 7, pp. e1011332-e1011332
Open Access | Times Cited: 4
Angular reproduction numbers improve estimates of transmissibility when disease generation times are misspecified or time-varying
Kris V. Parag, Benjamin J. Cowling, Ben Lambert
Proceedings of the Royal Society B Biological Sciences (2023) Vol. 290, Iss. 2007
Open Access | Times Cited: 4
Host behaviour driven by awareness of infection risk amplifies the chance of superspreading events
Kris V. Parag, Robin N. Thompson
Journal of The Royal Society Interface (2024) Vol. 21, Iss. 216
Open Access | Times Cited: 1
How to Measure the Controllability of an Infectious Disease?
Kris V. Parag
Physical Review X (2024) Vol. 14, Iss. 3
Open Access | Times Cited: 1
Improving estimates of epidemiological quantities by combining reported cases with wastewater data: a statistical framework with applications to COVID-19 in Aotearoa New Zealand
Leighton M. Watson, Michael J. Plank, Bridget Armstrong, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
How to measure the controllability of an infectious disease?
Kris V. Parag
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
EpidemicKabu a new method to identify epidemic waves and their peaks and valleys
Lina Marcela Ruiz Galvis, Anderson Alexis Ruales Barbosa, Oscar Ignacio Mendoza Cardozo, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Interpreting epidemiological surveillance data: A modelling study from Pune City
Prathith Bhargav, Soumil Kelkar, Joy Merwin Monteiro, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Information Theory in a Darwinian Evolution Population Dynamics Model
Eddy Kwessi
Symmetry (2024) Vol. 16, Iss. 11, pp. 1522-1522
Open Access
Towards Improved Uncertainty Quantification of Stochastic Epidemic Models Using Sequential Monte Carlo
Arindam Fadikar, Abby Stevens, Nicholson Collier, et al.
2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (2024), pp. 843-852
Open Access
Deep learning-informed Bayesian model-based analysis to estimate superspreading events in epidemic outbreaks
Arianna Tasciotti, F. Urban, Federica De Dea, et al.
IEEE Access (2024) Vol. 12, pp. 161375-161400
Open Access
Machine learning mathematical models for incidence estimation during pandemics
Oscar Fajardo-Fontiveros, Mattia Mattei, Giulio Burgio, et al.
PLoS Computational Biology (2024) Vol. 20, Iss. 12, pp. e1012687-e1012687
Open Access
The Difference-of-Log-Normals Distribution is Fundamental in Nature
Robert Parham
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
Host behaviour driven by awareness of infection risk amplifies the chance of superspreading events
Kris V. Parag, Robin N. Thompson
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 1
Estimation of the Time-Varying Effective Reproductive Number of COVID-19 Based on Multivariate Time Series of Severe Health Outcomes
Benjamin R. Young, Faith Ho, Yun Lin, et al.
The Journal of Infectious Diseases (2023) Vol. 229, Iss. 2, pp. 502-506
Open Access | Times Cited: 1
Angular reproduction numbers improve estimates of transmissibility when disease generation times are misspecified or time-varying
Kris V. Parag, Benjamin J. Cowling, Ben Lambert
medRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 1
Risk averse reproduction numbers improve resurgence detection
Kris V. Parag, Uri Obolski
medRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access
Getting the most out of noisy surveillance data
Lauren McGough
Nature Computational Science (2022) Vol. 2, Iss. 9, pp. 559-560
Open Access
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