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Outputs (18)

Estimating disease transmission in a closed population under repeated testing (2024)
Journal Article
Wascher, M., Schnell, P. M., Khuda Bukhsh, W. R., Quam, M. B. M., Tien, J. H., & Rempała, G. A. (2024). Estimating disease transmission in a closed population under repeated testing. Journal of the Royal Statistical Society: Series C, https://doi.org/10.1093/jrsssc/qlae021

The article presents a novel statistical framework for COVID-19 transmission monitoring and control, which was developed and deployed at The Ohio State University main campus in Columbus during the Autumn term of 2020. Our approach effectively handle... Read More about Estimating disease transmission in a closed population under repeated testing.

Towards Inferring Network Properties from Epidemic Data (2023)
Journal Article
Kiss, I. Z., Berthouze, L., & KhudaBukhsh, W. R. (2024). Towards Inferring Network Properties from Epidemic Data. Bulletin of Mathematical Biology, 86(1), Article 6. https://doi.org/10.1007/s11538-023-01235-3

Epidemic propagation on networks represents an important departure from traditional mass-action models. However, the high-dimensionality of the exact models poses a challenge to both mathematical analysis and parameter inference. By using mean-field... Read More about Towards Inferring Network Properties from Epidemic Data.

Dynamical Survival Analysis for Epidemic Modeling (2023)
Book Chapter
Rempała, G. A., & KhudaBukhsh, W. R. (2023). Dynamical Survival Analysis for Epidemic Modeling. In Handbook of Visual, Experimental and Computational Mathematics: Bridges through Data (1-17). Springer. https://doi.org/10.1007/978-3-030-93954-0_31-1

This chapter describes the dynamical survival analysis (DSA) method for modeling infectious diseases. This method provides a powerful framework for analyzing compartmental models of large epidemics, such as the popular susceptible-infected-recovered... Read More about Dynamical Survival Analysis for Epidemic Modeling.

COVID-19 dynamics in an Ohio prison (2023)
Journal Article
KhudaBukhsh, W. R., Khalsa, S. K., Kenah, E., Rempała, G. A., & Tien, J. H. (2023). COVID-19 dynamics in an Ohio prison. Frontiers in Public Health, 11, Article 1087698. https://doi.org/10.3389/fpubh.2023.1087698

Incarcerated individuals are a highly vulnerable population for infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Understanding the transmission of respiratory infections within prisons and between prisons and surrounding c... Read More about COVID-19 dynamics in an Ohio prison.

Projecting COVID-19 cases and hospital burden in Ohio (2023)
Journal Article
KhudaBukhsh, W. R., Bastian, C. D., Wascher, M., Klaus, C., Sahai, S. Y., Weir, M. H., …Rempała, G. A. (2023). Projecting COVID-19 cases and hospital burden in Ohio. Journal of Theoretical Biology, 561, Article 111404. https://doi.org/10.1016/j.jtbi.2022.111404

As the Coronavirus 2019 disease (COVID-19) started to spread rapidly in the state of Ohio, the Ecology, Epidemiology and Population Health (EEPH) program within the Infectious Diseases Institute (IDI) at The Ohio State University (OSU) took the initi... Read More about Projecting COVID-19 cases and hospital burden in Ohio.

Likelihood-Free Dynamical Survival Analysis applied to the COVID-19 epidemic in Ohio (2022)
Journal Article
Klaus, C., Wascher, M., KhudaBukhsh, W. R., & Rempała, G. A. (2023). Likelihood-Free Dynamical Survival Analysis applied to the COVID-19 epidemic in Ohio. Mathematical Biosciences and Engineering, 20(2), 4103-4127. https://doi.org/10.3934/mbe.2023192

The Dynamical Survival Analysis (DSA) is a framework for modeling epidemics based on mean field dynamics applied to individual (agent) level history of infection and recovery. Recently, the DSA method has been shown to be an effective tool in analyzi... Read More about Likelihood-Free Dynamical Survival Analysis applied to the COVID-19 epidemic in Ohio.

Hypergraphon mean field games (2022)
Journal Article
Cui, K., KhudaBukhsh, W. R., & Koeppl, H. (2022). Hypergraphon mean field games. Chaos, 32(11), Article 113129. https://doi.org/10.1063/5.0093758

We propose an approach to modeling large-scale multi-agent dynamical systems allowing interactions among more than just pairs of agents using the theory of mean field games and the notion of hypergraphons, which are obtained as limits of large hyperg... Read More about Hypergraphon mean field games.

A functional central limit theorem for SI processes on configuration model graphs (2022)
Journal Article
KhudaBukhsh, W. R., Woroszylo, C., Rempała, G. A., & Koeppl, H. (2022). A functional central limit theorem for SI processes on configuration model graphs. Advances in Applied Probability, 54(3), 880-912. https://doi.org/10.1017/apr.2022.52

We study a stochastic compartmental susceptible–infected (SI) epidemic process on a configuration model random graph with a given degree distribution over a finite time interval. We split the population of graph vertices into two compartments, namely... Read More about A functional central limit theorem for SI processes on configuration model graphs.

Dynamic survival analysis for non-Markovian epidemic models (2022)
Journal Article
Di Lauro, F., KhudaBukhsh, W. R., Kiss, I. Z., Kenah, E., Jensen, M., & Rempała, G. A. (2022). Dynamic survival analysis for non-Markovian epidemic models. Journal of the Royal Society. Interface, 19(191), Article 20220124. https://doi.org/10.1098/rsif.2022.0124

We present a new method for analysing stochastic epidemic models under minimal assumptions. The method, dubbed dynamic survival analysis (DSA), is based on a simple yet powerful observation, namely that population-level mean-field trajectories descri... Read More about Dynamic survival analysis for non-Markovian epidemic models.

Motif-based mean-field approximation of interacting particles on clustered networks (2022)
Journal Article
Cui, K., Khudabukhsh, W. R., & Koeppl, H. (2022). Motif-based mean-field approximation of interacting particles on clustered networks. Physical Review E, 105(4), Article L042301. https://doi.org/10.1103/PhysRevE.105.L042301

Interacting particles on graphs are routinely used to study magnetic behavior in physics, disease spread in epidemiology, and opinion dynamics in social sciences. The literature on mean-field approximations of such systems for large graphs typically... Read More about Motif-based mean-field approximation of interacting particles on clustered networks.

Analysis of individual-level data from 2018–2020 Ebola outbreak in Democratic Republic of the Congo (2022)
Journal Article
Vossler, H., Akilimali, P., Pan, Y., KhudaBukhsh, W. R., Kenah, E., & Rempała, G. A. (2022). Analysis of individual-level data from 2018–2020 Ebola outbreak in Democratic Republic of the Congo. Scientific Reports, 12, Article 5534. https://doi.org/10.1038/s41598-022-09564-4

The 2018–2020 Ebola virus disease epidemic in Democratic Republic of the Congo (DRC) resulted in 3481 cases (probable and confirmed) and 2299 deaths. In this paper, we use a novel statistical method to analyze the individual-level incidence and hospi... Read More about Analysis of individual-level data from 2018–2020 Ebola outbreak in Democratic Republic of the Congo.

Quantifying the Population-Level Effect of the COVID-19 Mass Vaccination Campaign in Israel: A Modeling Study (2022)
Journal Article
Somekh, I., Khudabukhsh, W. R., Root, E. D., Boker, L. K., Rempala, G., Simões, E. A., & Somekh, E. (2022). Quantifying the Population-Level Effect of the COVID-19 Mass Vaccination Campaign in Israel: A Modeling Study. Open Forum Infectious Diseases, 9(5), Article ofac087. https://doi.org/10.1093/ofid/ofac087

Background: Estimating real-world vaccine effectiveness is challenging as a variety of population factors can impact vaccine effectiveness. We aimed to assess the population-level reduction in cumulative severe acute respiratory syndrome coronavirus... Read More about Quantifying the Population-Level Effect of the COVID-19 Mass Vaccination Campaign in Israel: A Modeling Study.

Incorporating age and delay into models for biophysical systems (2020)
Journal Article
KhudaBukhsh, W. R., Kang, H.-W., Kenah, E., & Rempała, G. A. (2021). Incorporating age and delay into models for biophysical systems. Physical Biology, 18(1), Article 015002. https://doi.org/10.1088/1478-3975/abc2ab

In many biological systems, chemical reactions or changes in a physical state are assumed to occur instantaneously. For describing the dynamics of those systems, Markov models that require exponentially distributed inter-event times have been used wi... Read More about Incorporating age and delay into models for biophysical systems.

Generalized Cost-Based Job Scheduling in Very Large Heterogeneous Cluster Systems (2020)
Journal Article
KhudaBukhsh, W. R., Kar, S., Alt, B., Rizk, A., & Koeppl, H. (2020). Generalized Cost-Based Job Scheduling in Very Large Heterogeneous Cluster Systems. IEEE Transactions on Parallel and Distributed Systems, 31(11), 2594-2604. https://doi.org/10.1109/tpds.2020.2997771

We study job assignment in large, heterogeneous resource-sharing clusters of servers with finite buffers. This load balancing problem arises naturally in today's communication and big data systems, such as Amazon Web Services, Network Service Functio... Read More about Generalized Cost-Based Job Scheduling in Very Large Heterogeneous Cluster Systems.

Survival dynamical systems: individual-level survival analysis from population-level epidemic models (2019)
Journal Article
KhudaBukhsh, W. R., Choi, B., Kenah, E., & Rempała, G. A. (2020). Survival dynamical systems: individual-level survival analysis from population-level epidemic models. Interface Focus, 10(1), Article 20190048. https://doi.org/10.1098/rsfs.2019.0048

In this paper, we show that solutions to ordinary differential equations describing the large-population limits of Markovian stochastic epidemic models can be interpreted as survival or cumulative hazard functions when analysing data on individuals s... Read More about Survival dynamical systems: individual-level survival analysis from population-level epidemic models.

Transitions: A Protocol-Independent View of the Future Internet (2019)
Journal Article
Alt, B., Weckesser, M., Becker, C., Hollick, M., Kar, S., Klein, A., …Steinmetz, R. (2019). Transitions: A Protocol-Independent View of the Future Internet. Proceedings of the IEEE, 107(4), 835-846. https://doi.org/10.1109/JPROC.2019.2895964

Countless novel approaches to communication protocols, overlay networks, and distributed middleware are published every year, yet the adoption of such novel findings in the global Internet landscape progresses at a slow pace. Many of such new communi... Read More about Transitions: A Protocol-Independent View of the Future Internet.

Quasi-Steady-State Approximations Derived from the Stochastic Model of Enzyme Kinetics (2019)
Journal Article
Kang, H., KhudaBukhsh, W. R., Koeppl, H., & Rempała, G. A. (2019). Quasi-Steady-State Approximations Derived from the Stochastic Model of Enzyme Kinetics. Bulletin of Mathematical Biology, 81(5), 1303-1336. https://doi.org/10.1007/s11538-019-00574-4

The paper outlines a general approach to deriving quasi-steady-state approximations (QSSAs) of the stochastic reaction networks describing the Michaelis–Menten enzyme kinetics. In particular, it explains how different sets of assumptions about chemic... Read More about Quasi-Steady-State Approximations Derived from the Stochastic Model of Enzyme Kinetics.