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Article ; Online: Modelling disease mitigation at mass gatherings: A case study of COVID-19 at the 2022 FIFA World Cup.

Grunnill, Martin / Arino, Julien / McCarthy, Zachary / Bragazzi, Nicola Luigi / Coudeville, Laurent / Thommes, Edward W / Amiche, Amine / Ghasemi, Abbas / Bourouiba, Lydia / Tofighi, Mohammadali / Asgary, Ali / Baky-Haskuee, Mortaza / Wu, Jianhong

PLoS computational biology

2024 Volume 20, Issue 1, Page(s) e1011018

Abstract: The 2022 FIFA World Cup was the first major multi-continental sporting Mass Gathering Event (MGE) of the post COVID-19 era to allow foreign spectators. Such large-scale MGEs can potentially lead to outbreaks of infectious disease and contribute to the ... ...

Abstract	The 2022 FIFA World Cup was the first major multi-continental sporting Mass Gathering Event (MGE) of the post COVID-19 era to allow foreign spectators. Such large-scale MGEs can potentially lead to outbreaks of infectious disease and contribute to the global dissemination of such pathogens. Here we adapt previous work and create a generalisable model framework for assessing the use of disease control strategies at such events, in terms of reducing infections and hospitalisations. This framework utilises a combination of meta-populations based on clusters of people and their vaccination status, Ordinary Differential Equation integration between fixed time events, and Latin Hypercube sampling. We use the FIFA 2022 World Cup as a case study for this framework (modelling each match as independent 7 day MGEs). Pre-travel screenings of visitors were found to have little effect in reducing COVID-19 infections and hospitalisations. With pre-match screenings of spectators and match staff being more effective. Rapid Antigen (RA) screenings 0.5 days before match day performed similarly to RT-PCR screenings 1.5 days before match day. Combinations of pre-travel and pre-match testing led to improvements. However, a policy of ensuring that all visitors had a COVID-19 vaccination (second or booster dose) within a few months before departure proved to be much more efficacious. The State of Qatar abandoned all COVID-19 related travel testing and vaccination requirements over the period of the World Cup. Our work suggests that the State of Qatar may have been correct in abandoning the pre-travel testing of visitors. However, there was a spike in COVID-19 cases and hospitalisations within Qatar over the World Cup. Given our findings and the spike in cases, we suggest a policy requiring visitors to have had a recent COVID-19 vaccination should have been in place to reduce cases and hospitalisations.
MeSH term(s)	Humans ; Mass Gatherings ; COVID-19 Vaccines ; COVID-19/epidemiology ; COVID-19/prevention & control ; Soccer ; Sports
Chemical Substances	COVID-19 Vaccines
Language	English
Publishing date	2024-01-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1011018
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Generating Simulation-Based Contacts Matrices for Disease Transmission Modelling at Special Settings

Najafabadi, Mahdi M. / Asgary, Ali / Tofighi, Mohammadali / Tofighi, Ghassem

2021

Abstract: Since a significant amount of disease transmission occurs through human-to-human or social contact, understanding who interacts with whom in time and space is essential for disease transmission modeling, prediction, and assessment of prevention ... ...

Abstract	Since a significant amount of disease transmission occurs through human-to-human or social contact, understanding who interacts with whom in time and space is essential for disease transmission modeling, prediction, and assessment of prevention strategies in different environments and special settings. Thus, measuring contact mixing patterns, often in the form of a contacts matrix, has been a key component of heterogeneous disease transmission modeling research. Several data collection techniques estimate or calculate a contacts matrix at different geographical scales and population mixes based on surveys and sensors. This paper presents a methodology for generating a contacts matrix by using high fidelity simulations which mimic actual workflow and movements of individuals in time and space. Results of this study show that such simulations can be a feasible, flexible, and reasonable alternative method for estimating social contacts and generating contacts mixing matrices for various settings under different conditions.
Keywords	Electrical Engineering and Systems Science - Systems and Control
Publishing date	2021-01-25
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Complex adaptive systems-based framework for modeling the health impacts of climate change.

Talukder, Byomkesh / Schubert, Jochen E / Tofighi, Mohammadali / Likongwe, Patrick J / Choi, Eunice Y / Mphepo, Gibson Y / Asgary, Ali / Bunch, Martin J / Chiotha, Sosten S / Matthew, Richard / Sanders, Brett F / Hipel, Keith W / vanLoon, Gary W / Orbinski, James

The journal of climate change and health

2024 Volume 15, Page(s) 100292

Abstract: Introduction: Climate change is a global phenomenon with far-reaching consequences, and its impact on human health is a growing concern. The intricate interplay of various factors makes it challenging to accurately predict and understand the ... ...

Abstract	Introduction: Climate change is a global phenomenon with far-reaching consequences, and its impact on human health is a growing concern. The intricate interplay of various factors makes it challenging to accurately predict and understand the implications of climate change on human well-being. Conventional methodologies have limitations in comprehensively addressing the complexity and nonlinearity inherent in the relationships between climate change and health outcomes. Objectives: The primary objective of this paper is to develop a robust theoretical framework that can effectively analyze and interpret the intricate web of variables influencing the human health impacts of climate change. By doing so, we aim to overcome the limitations of conventional approaches and provide a more nuanced understanding of the complex relationships involved. Furthermore, we seek to explore practical applications of this theoretical framework to enhance our ability to predict, mitigate, and adapt to the diverse health challenges posed by a changing climate. Methods: Addressing the challenges outlined in the objectives, this study introduces the Complex Adaptive Systems (CAS) framework, acknowledging its significance in capturing the nuanced dynamics of health effects linked to climate change. The research utilizes a blend of field observations, expert interviews, key informant interviews, and an extensive literature review to shape the development of the CAS framework. Results and discussion: The proposed CAS framework categorizes findings into six key sub-systems: ecological services, extreme weather, infectious diseases, food security, disaster risk management, and clinical public health. The study employs agent-based modeling, using causal loop diagrams (CLDs) tailored for each CAS sub-system. A set of identified variables is incorporated into predictive modeling to enhance the understanding of health outcomes within the CAS framework. Through a combination of theoretical development and practical application, this paper aspires to contribute valuable insights to the interdisciplinary field of climate change and health. Integrating agent-based modeling and CLDs enhances the predictive capabilities required for effective health outcome analysis in the context of climate change. Conclusion: This paper serves as a valuable resource for policymakers, researchers, and public health professionals by employing a CAS framework to understand and assess the complex network of health impacts associated with climate change. It offers insights into effective strategies for safeguarding human health amidst current and future climate challenges.
Language	English
Publishing date	2024-02-15
Publishing country	France
Document type	Journal Article
ISSN	2667-2782
ISSN (online)	2667-2782
DOI	10.1016/j.joclim.2023.100292
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Modelling COVID-19 transmission in a hemodialysis centre using simulation generated contacts matrices.

Tofighi, Mohammadali / Asgary, Ali / Merchant, Asad A / Shafiee, Mohammad Ali / Najafabadi, Mahdi M / Nadri, Nazanin / Aarabi, Mehdi / Heffernan, Jane / Wu, Jianhong

PloS one

2021 Volume 16, Issue 11, Page(s) e0259970

Abstract: The COVID-19 pandemic has been particularly threatening to patients with end-stage kidney disease (ESKD) on intermittent hemodialysis and their care providers. Hemodialysis patients who receive life-sustaining medical therapy in healthcare settings, face ...

Abstract	The COVID-19 pandemic has been particularly threatening to patients with end-stage kidney disease (ESKD) on intermittent hemodialysis and their care providers. Hemodialysis patients who receive life-sustaining medical therapy in healthcare settings, face unique challenges as they need to be at a dialysis unit three or more times a week, where they are confined to specific settings and tended to by dialysis nurses and staff with physical interaction and in close proximity. Despite the importance and critical situation of the dialysis units, modelling studies of the SARS-CoV-2 spread in these settings are very limited. In this paper, we have used a combination of discrete event and agent-based simulation models, to study the operations of a typical large dialysis unit and generate contact matrices to examine outbreak scenarios. We present the details of the contact matrix generation process and demonstrate how the simulation calculates a micro-scale contact matrix comprising the number and duration of contacts at a micro-scale time step. We have used the contacts matrix in an agent-based model to predict disease transmission under different scenarios. The results show that micro-simulation can be used to estimate contact matrices, which can be used effectively for disease modelling in dialysis and similar settings.
MeSH term(s)	COVID-19/transmission ; Computer Simulation ; Contact Tracing/statistics & numerical data ; Disease Transmission, Infectious/statistics & numerical data ; Hemodialysis Units, Hospital/statistics & numerical data ; Humans ; Models, Statistical
Language	English
Publishing date	2021-11-19
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0259970
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Estimating social contacts in mass gatherings for disease outbreak prevention and management: case of Hajj pilgrimage.

Tofighi, Mohammadali / Asgary, Ali / Tofighi, Ghassem / Najafabadi, Mahdi M / Arino, Julien / Amiche, Amine / Rahman, Ashrafur / McCarthy, Zachary / Bragazzi, Nicola Luigi / Thommes, Edward / Coudeville, Laurent / Grunnill, Martin David / Bourouiba, Lydia / Wu, Jianhong

Tropical diseases, travel medicine and vaccines

2022 Volume 8, Issue 1, Page(s) 19

Abstract: Background: Most mass gathering events have been suspended due to the SARS-CoV-2 pandemic. However, with vaccination rollout, whether and how to organize some of these mass gathering events arises as part of the pandemic recovery discussions, and this ... ...

Abstract	Background: Most mass gathering events have been suspended due to the SARS-CoV-2 pandemic. However, with vaccination rollout, whether and how to organize some of these mass gathering events arises as part of the pandemic recovery discussions, and this calls for decision support tools. The Hajj, one of the world's largest religious gatherings, was substantively scaled down in 2020 and 2021 and it is still unclear how it will take place in 2022 and subsequent years. Simulating disease transmission dynamics during the Hajj season under different conditions can provide some insights for better decision-making. Most disease risk assessment models require data on the number and nature of possible close contacts between individuals. Methods: We sought to use integrated agent-based modeling and discrete events simulation techniques to capture risky contacts among the pilgrims and assess different scenarios in one of the Hajj major sites, namely Masjid-Al-Haram. Results: The simulation results showed that a plethora of risky contacts may occur during the rituals. Also, as the total number of pilgrims increases at each site, the number of risky contacts increases, and physical distancing measures may be challenging to maintain beyond a certain number of pilgrims in the site. Conclusions: This study presented a simulation tool that can be relevant for the risk assessment of a variety of (respiratory) infectious diseases, in addition to COVID-19 in the Hajj season. This tool can be expanded to include other contributing elements of disease transmission to quantify the risk of the mass gathering events.
Language	English
Publishing date	2022-09-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2835327-4
ISSN	2055-0936
ISSN	2055-0936
DOI	10.1186/s40794-022-00177-3
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Article: An Agent-Based Modeling and Virtual Reality Application Using Distributed Simulation: Case of a COVID-19 Intensive Care Unit.

Possik, Jalal / Asgary, Ali / Solis, Adriano O / Zacharewicz, Gregory / Shafiee, Mohammad A / Najafabadi, Mahdi M / Nadri, Nazanin / Guimaraes, Abel / Iranfar, Hossein / Ma, Philip / Lee, Christie M / Tofighi, Mohammadali / Aarabi, Mehdi / Gorecki, Simon / Wu, Jianhong

IEEE transactions on engineering management

2022 Volume 70, Issue 8, Page(s) 2931–2943

Abstract: Hospitals and other healthcare settings use various simulation methods to improve their operations, management, and training. The COVID-19 pandemic, with the resulting necessity for rapid and remote assessment, has highlighted the critical role of ... ...

Abstract	Hospitals and other healthcare settings use various simulation methods to improve their operations, management, and training. The COVID-19 pandemic, with the resulting necessity for rapid and remote assessment, has highlighted the critical role of modeling and simulation in healthcare, particularly distributed simulation (DS). DS enables integration of heterogeneous simulations to further increase the usability and effectiveness of individual simulations. This article presents a DS system that integrates two different simulations developed for a hospital intensive care unit (ICU) ward dedicated to COVID-19 patients. AnyLogic has been used to develop a simulation model of the ICU ward using agent-based and discrete event modeling methods. This simulation depicts and measures physical contacts between healthcare providers and patients. The Unity platform has been utilized to develop a virtual reality simulation of the ICU environment and operations. The high-level architecture, an IEEE standard for DS, has been used to build a cloud-based DS system by integrating and synchronizing the two simulation platforms. While enhancing the capabilities of both simulations, the DS system can be used for training purposes and assessment of different managerial and operational decisions to minimize contacts and disease transmission in the ICU ward by enabling data exchange between the two simulations.
Language	English
Publishing date	2022-08-18
Publishing country	United States
Document type	Journal Article
ISSN	0018-9391
ISSN	0018-9391
DOI	10.1109/TEM.2022.3195813
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Article ; Online: Modelling Disease Mitigation at Mass Gatherings: A Case Study of COVID-19 at the 2022 FIFA World Cup.

Grunnill, Martin / Arino, Julien / McCarthy, Zachary / Bragazzi, Nicola Luigi / Coudeville, Laurent / Thommes, Edward / Amiche, Amine / Ghasemi, Abbas / Bourouiba, Lydia / Tofighi, Mohammadali / Asgary, Ali / Baky-Haskuee, Mortaza / Wu, Jianhong

medRxiv

Abstract	The 2022 FIFA World Cup was the first major multi-continental sporting Mass Gathering Event (MGE) of the post COVID-19 era to allow foreign spectators. Such large-scale MGEs can potentially lead to outbreaks of infectious disease and contribute to the global dissemination of such pathogens. Here we adapt previous work and create a generalisable model framework for assessing the use of disease control strategies at such events, in terms of reducing infections and hospitalisations. This framework utilises a combination of meta-populations based on clusters of people and their vaccination status, Ordinary Differential Equation integration between fixed time events, and Latin Hypercube sampling. We use the FIFA 2022 World Cup as a case study for this framework. Pre-travel screenings of visitors were found to have little effect in reducing COVID-19 infections and hospitalisations. With pre-match screenings of spectators and match staff being more effective. Rapid Antigen (RA) screenings 0.5 days before match day outperformed RT-PCR screenings 1.5 days before match day. A combination of pre-travel RT-PCR and pre-match RA testing proved to be the most successful screening-based regime. However, a policy of ensuring that all visitors had a COVID-19 vaccination (second or booster dose) within a few months before departure proved to be much more efficacious. The State of Qatar abandoned all COVID-19 related travel testing and vaccination requirements over the period of the World Cup. Our work suggests that the State of Qatar may have been correct in abandoning the pre-travel testing of visitors. However, there was a spike in COVID-19 cases and hospitalisations within Qatar over the World Cup. The research outlined here suggests a policy requiring visitors to have had a recent COVID-19 vaccination may have prevented the increase in COVID-19 cases and hospitalisations during the world cup.
Keywords	covid19
Language	English
Publishing date	2023-03-29
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2023.03.27.23287214
Database	COVID19

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Article ; Online: Modelling COVID -19 Transmission in a Hemodialysis Centre Using Simulation Generated Contacts Matrices

Tofighi, Mohammadali / Asgary, Ali / Merchant, Asad A. / Shafiee, Mohammad Ali / M. Najafabadi, Mahdi / Nadri, Nazanin / Aarabi, Mehdi / Heffernan, Jane / Wu, Jianhong

medRxiv

Abstract: The COVID-19 pandemic has been particularly threatening to the patients with end-stage kidney disease (ESKD) on intermittent hemodialysis and their care providers. Hemodialysis patients who receive life-sustaining medical therapy in healthcare settings, ... ...

Abstract	The COVID-19 pandemic has been particularly threatening to the patients with end-stage kidney disease (ESKD) on intermittent hemodialysis and their care providers. Hemodialysis patients who receive life-sustaining medical therapy in healthcare settings, face unique challenges as they need to be at a dialysis unit three or more times a week, where they are confined to specific settings and tended to by dialysis nurses and staff with physical interaction and in close proximity. Despite the importance and critical situation of the dialysis units, modelling studies of the SARS-CoV-2 spread in these settings are very limited. In this paper, we have used a combination of discrete event and agent-based simulation models, to study the operations of a typical large dialysis unit and generate contact matrices to examine outbreak scenarios. We present the details of the contact matrix generation process and demonstrate how the simulation calculates a micro-scale contact matrix comprising the number and duration of contacts at a micro-scale time step. We have used the contacts matrix in an agent-based model to predict disease transmission under different scenarios. The results show that micro-simulation can be used to estimate contact matrices, which can be used effectively for disease modelling in dialysis and similar settings.
Keywords	covid19
Language	English
Publishing date	2021-01-06
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2021.01.03.21249175
Database	COVID19

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Article ; Online: Modelling disease mitigation at mass gatherings: A case study of COVID-19 at the 2022 FIFA World Cup.

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Book ; Online: Generating Simulation-Based Contacts Matrices for Disease Transmission Modelling at Special Settings

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Article ; Online: Complex adaptive systems-based framework for modeling the health impacts of climate change.

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Article ; Online: Modelling COVID-19 transmission in a hemodialysis centre using simulation generated contacts matrices.

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Article: Estimating social contacts in mass gatherings for disease outbreak prevention and management: case of Hajj pilgrimage.

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Article: An Agent-Based Modeling and Virtual Reality Application Using Distributed Simulation: Case of a COVID-19 Intensive Care Unit.

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Article ; Online: Modelling Disease Mitigation at Mass Gatherings: A Case Study of COVID-19 at the 2022 FIFA World Cup.

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Inter-library loan at ZB MED

Article ; Online: Modelling COVID -19 Transmission in a Hemodialysis Centre Using Simulation Generated Contacts Matrices

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Inter-library loan at ZB MED