A metropolitan-scale, three-dimensional agent-based model to assess the effectiveness of the COVID-19 Omicron wave interventions in a hyperdense city: a case study of Hong Kong

Koh, Keumseok; Tang, Ka Chung; Axhausen, Kay W.; Loo, Becky P.Y.

doi:10.1016/j.ijid.2022.06.042

Cited by 6 publications

(4 citation statements)

References 5 publications

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“…In the study by Koh et al [29], the authors simulate the spread of COVID-19 Omicron by using an innovative three-dimensional agent-based model that takes into account Hong Kong's vertically extended hyperdense urban environment. The model evaluated the efficacy of the "zero-COVID" initiatives, such as citywide lockdown and mandatory universal testing (CUT), that were under discussion during the Omicron wave in Hong Kong.…”

Section: Related Workmentioning

confidence: 99%

An Agent-Based Model for Disease Epidemics in Greece

Thomopoulos,

Tsichlas

2024

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In this research, we present the first steps toward developing a data-driven agent-based model (ABM) specifically designed for simulating infectious disease dynamics in Greece. Amidst the ongoing COVID-19 pandemic caused by SARS-CoV-2, this research holds significant importance as it can offer valuable insights into disease transmission patterns and assist in devising effective intervention strategies. To the best of our knowledge, no similar study has been conducted in Greece. We constructed a prototype ABM that utilizes publicly accessible data to accurately represent the complex interactions and dynamics of disease spread in the Greek population. By incorporating demographic information and behavioral patterns, our model captures the specific characteristics of Greece, enabling accurate and context-specific simulations. By using our proposed ABM, we aim to assist policymakers in making informed decisions regarding disease control and prevention. Through the use of simulations, policymakers have the opportunity to explore different scenarios and predict the possible results of various intervention measures. These may include strategies like testing approaches, contact tracing, vaccination campaigns, and social distancing measures. Through these simulations, policymakers can assess the effectiveness and feasibility of these interventions, leading to the development of well-informed strategies aimed at reducing the impact of infectious diseases on the Greek population. This study is an initial exploration toward understanding disease transmission patterns and a first step towards formulating effective intervention strategies for Greece.

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Section: Related Workmentioning

confidence: 99%

An Agent-Based Model for Disease Epidemics in Greece

Thomopoulos,

Tsichlas

2024

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“…Recent evidence further suggests that the emergence of SARS-CoV-2 variants is facilitated by superspreading events ( 62 ). This has happened with the OMICRON variants that are much more contagious than those with which the pandemic began in 2020 ( 63 ). Under these circumstances, the virus is much more effective at creating a superspreading environment.…”

Section: Policy Implications and Conclusionmentioning

confidence: 99%

“…Our analysis widens the investigation from a pure medical science focus to the environment, encompassing functions of places, location agglomeration, population density and human mobility patterns. Moreover, the empirical evidence generated can facilitate a better calibration and further refinements of theoretical models, such as the susceptible-infected-recovered and agent-based approaches [e.g., ( 4 , 63 , 64 )]. It is recognized that the travel behavior and spatial agglomeration of PoIs might have changed before, during, and after the pandemic periods.…”

Section: Policy Implications and Conclusionmentioning

confidence: 99%

Spatial risk for a superspreading environment: Insights from six urban facilities in six global cities across four continents

Loo

Tsoi

Axhausen

et al. 2023

Front. Public Health

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IntroductionThis study sets out to provide scientific evidence on the spatial risk for the formation of a superspreading environment.MethodsFocusing on six common types of urban facilities (bars, cinemas, gyms and fitness centers, places of worship, public libraries and shopping malls), it first tests whether visitors' mobility characteristics differ systematically for different types of facility and at different locations. The study collects detailed human mobility and other locational data in Chicago, Hong Kong, London, São Paulo, Seoul and Zurich. Then, considering facility agglomeration, visitors' profile and the density of the population, facilities are classified into four potential spatial risk (PSR) classes. Finally, a kernel density function is employed to derive the risk surface in each city based on the spatial risk class and nature of activities.ResultsResults of the human mobility analysis reflect the geographical and cultural context of various facilities, transport characteristics and people's lifestyle across cities. Consistent across the six global cities, geographical agglomeration is a risk factor for bars. For other urban facilities, the lack of agglomeration is a risk factor. Based on the spatial risk maps, some high-risk areas of superspreading are identified and discussed in each city.DiscussionIntegrating activity-travel patterns in risk models can help identify areas that attract highly mobile visitors and are conducive to superspreading. Based on the findings, this study proposes a place-based strategy of non-pharmaceutical interventions that balance the control of the pandemic and the daily life of the urban population.

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“…Evidently, an exact modeling from the real data for epidemic can offer valuable insights to evaluate and intervene the possible effect [9][10][11]. Here we chose the observational data to describe the feature of the proportion of the population, cumulative confirmed cases, cumulative deaths and current hospitalizations by age group through statistical measure，also the hospitalization, severe cases, cumulative death among different vaccinations firstly, then model and predict the confirmed cases for search out the exact point of non-increasing spot in the near future via time series model.…”

Section: Introductionmentioning

confidence: 99%

A Data Driven Study on the Variant of Covid-19 in Hong Kong

Ding

Xiang

2022

ijsmr

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The new wave of COVID-19 in Hong Kong, China was overwhelming again by “dynamic zero” strategy and non-pharmaceutical interventions (DZ-NPIs), which makes a time challenge to control the variant of this epidemic. We describe the variant of Covid-19 in Kong Hong to the infected proportion of the population, cumulative confirmed cases, cumulative deaths and current hospitalizations by age group via statistical measure firstly, then establish time series model for fitting the accumulative confirmed cases, further to predict the trend for searching out possible turning time-points. Non-linear regression model is created to feature the deaths series, then we figure out the parameters and educe the controlling condition for this epidemic. We expect our data-driven modeling process providing some insights to the controlling strategy for the new wave of the Covid-19 variant in Hong Kong, even in the mainland of China.

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A metropolitan-scale, three-dimensional agent-based model to assess the effectiveness of the COVID-19 Omicron wave interventions in a hyperdense city: a case study of Hong Kong

Cited by 6 publications

References 5 publications

An Agent-Based Model for Disease Epidemics in Greece

An Agent-Based Model for Disease Epidemics in Greece

Spatial risk for a superspreading environment: Insights from six urban facilities in six global cities across four continents

A Data Driven Study on the Variant of Covid-19 in Hong Kong

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