Dynamic Modeling and Forecasting of Epidemics Incorporating Age and Vaccination Status

Nitin Kulkarni; Chunming Qiao; Alina Vereshchaka

doi:10.1007/978-3-031-43129-6_26

Dynamic Modeling and Forecasting of Epidemics Incorporating Age and Vaccination Status

Nitin Kulkarni
, Chunming Qiao
, Alina Vereshchaka

Department of Computer Science and Engineering

SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Controlling the spread of infectious diseases poses a significant challenge, necessitating a thorough understanding of the interplay between human behavior and disease transmission. This research introduces an age and vaccination stratified epidemiological model called SIHRD^a ^, ^v, which considers the differential impact of diseases on various age and vaccination groups. The model’s parameters are estimated using real-world data. We demonstrate that our model is well suited for forecasting the spread of epidemics such as COVID-19. Through the evaluation of different scenarios, we project the impact on infection rates, hospitalizations, and fatalities. These analyses and simulations provide valuable insights for effectively managing and preventing disease outbreaks.

Original language	English
Title of host publication	Social, Cultural, and Behavioral Modeling - 16th International Conference, SBP-BRiMS 2023, Proceedings
Editors	Robert Thomson, Samer Al-khateeb, Annetta Burger, Patrick Park, Aryn A. Pyke
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	263-273
Number of pages	11
ISBN (Print)	9783031431289
DOIs	https://doi.org/10.1007/978-3-031-43129-6_26
State	Published - 2023
Event	16th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2023 - Pittsburgh, United States Duration: Sep 20 2023 → Sep 22 2023

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14161 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2023
Country/Territory	United States
City	Pittsburgh
Period	09/20/23 → 09/22/23

Keywords

COVID-19
Curve fitting
Dynamic modeling
Epidemiological model
Mitigation regulations
Pandemic
SIHRD model

Access to Document

10.1007/978-3-031-43129-6_26

Cite this

Kulkarni, N., Qiao, C., & Vereshchaka, A. (2023). Dynamic Modeling and Forecasting of Epidemics Incorporating Age and Vaccination Status. In R. Thomson, S. Al-khateeb, A. Burger, P. Park, & A. A. Pyke (Eds.), Social, Cultural, and Behavioral Modeling - 16th International Conference, SBP-BRiMS 2023, Proceedings (pp. 263-273). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14161 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-43129-6_26

Kulkarni, Nitin ; Qiao, Chunming ; Vereshchaka, Alina. / Dynamic Modeling and Forecasting of Epidemics Incorporating Age and Vaccination Status. Social, Cultural, and Behavioral Modeling - 16th International Conference, SBP-BRiMS 2023, Proceedings. editor / Robert Thomson ; Samer Al-khateeb ; Annetta Burger ; Patrick Park ; Aryn A. Pyke. Springer Science and Business Media Deutschland GmbH, 2023. pp. 263-273 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Controlling the spread of infectious diseases poses a significant challenge, necessitating a thorough understanding of the interplay between human behavior and disease transmission. This research introduces an age and vaccination stratified epidemiological model called SIHRDa , v, which considers the differential impact of diseases on various age and vaccination groups. The model{\textquoteright}s parameters are estimated using real-world data. We demonstrate that our model is well suited for forecasting the spread of epidemics such as COVID-19. Through the evaluation of different scenarios, we project the impact on infection rates, hospitalizations, and fatalities. These analyses and simulations provide valuable insights for effectively managing and preventing disease outbreaks.",

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Kulkarni, N, Qiao, C & Vereshchaka, A 2023, Dynamic Modeling and Forecasting of Epidemics Incorporating Age and Vaccination Status. in R Thomson, S Al-khateeb, A Burger, P Park & A A. Pyke (eds), Social, Cultural, and Behavioral Modeling - 16th International Conference, SBP-BRiMS 2023, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14161 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 263-273, 16th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2023, Pittsburgh, United States, 09/20/23. https://doi.org/10.1007/978-3-031-43129-6_26

Dynamic Modeling and Forecasting of Epidemics Incorporating Age and Vaccination Status. / Kulkarni, Nitin; Qiao, Chunming; Vereshchaka, Alina.
Social, Cultural, and Behavioral Modeling - 16th International Conference, SBP-BRiMS 2023, Proceedings. ed. / Robert Thomson; Samer Al-khateeb; Annetta Burger; Patrick Park; Aryn A. Pyke. Springer Science and Business Media Deutschland GmbH, 2023. p. 263-273 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14161 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Kulkarni N, Qiao C, Vereshchaka A. Dynamic Modeling and Forecasting of Epidemics Incorporating Age and Vaccination Status. In Thomson R, Al-khateeb S, Burger A, Park P, A. Pyke A, editors, Social, Cultural, and Behavioral Modeling - 16th International Conference, SBP-BRiMS 2023, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. p. 263-273. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-43129-6_26