ArticlePloS one2021
Predicting the effects of COVID-19 related interventions in urban settings by combining activity-based modelling, agent-based simulation, and mobile phone data.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 71 citations in OpenAlex.
- Integrating mathematical modelling and artificial intelligence to combat emerging viral syndemics: A systematic review.New microbes and new infections · 2026Review
- MEmilio: a high performance Modular EpideMIcs simuLatIOn software for multi-scale and comparative simulations of infectious disease dynamics.Scientific reports · 2026Article
- Mechanics of pandemics.EClinicalMedicine · 2026Review
- Graph neural network surrogates to leverage mechanistic expert knowledge towards reliable and immediate pandemic response.Scientific reports · 2026Article
- Inferring mobility reductions from COVID-19 disease spread along the urban-rural gradient.Frontiers in public health · 2026Article
- Hybrid metapopulation agent-based epidemiological models for efficient insight on the individual scale: A contribution to green computing.Infectious Disease Modelling · 2025Article
- Integrating Human Mobility Models with Epidemic Modeling: A Framework for Generating Synthetic Temporal Contact Networks.Entropy (Basel, Switzerland) · 2025Article
- Epihiper-A high performance computational modeling framework to support epidemic science.PNAS nexus · 2025Article
- Mobile phone data analyses for public health research: a scoping review.Frontiers in public health · 2025Article
- Novel travel time aware metapopulation models and multi-layer waning immunity for late-phase epidemic and endemic scenarios.PLoS computational biology · 2024Article
- Dynamic Contact Networks in Confined Spaces: Synthesizing Micro-Level Encounter Patterns through Human Mobility Models from Real-World Data.Entropy (Basel, Switzerland) · 2024Article
- Article
- Neural parameter calibration and uncertainty quantification for epidemic forecasting.PloS one · 2024Article
- Explicit modeling of antibody levels for infectious disease simulations in the context of SARS-CoV-2.iScience · 2023Article
- Source identification via contact tracing in the presence of asymptomatic patients.Applied network science · 2023Article
- Agent-Based Simulation for Infectious Disease Modelling over a Period of Multiple Days, with Application to an Airport Scenario.International journal of environmental research and public health · 2022Article
- A simulation-deep reinforcement learning (SiRL) approach for epidemic control optimization.Annals of operations research · 2022Article
- 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.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022Article
- Using simulation modelling and systems science to help contain COVID-19: A systematic review.Systems research and behavioral science · 2022Article
- Agent Simulation Model of COVID-19 Epidemic Agent-Based on GIS: A Case Study of Huangpu District, Shanghai.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Epidemiological simulations as a method are used to better understand and predict the spreading of infectious diseases, for example of COVID-19. This paper presents an approach that combines a well-established approach from transportation modelling that uses person-centric data-driven human mobility modelling with a mechanistic infection model and a person-centric disease progression model. The model includes the consequences of different room sizes, air exchange rates, disease import, changed activity participation rates over time (coming from mobility data), masks, indoors vs. outdoors leisure activities, and of contact tracing. It is validated against the infection dynamics in Berlin (Germany). The model can be used to understand the contributions of different activity types to the infection dynamics over time. It predicts the effects of contact reductions, school closures/vacations, masks, or the effect of moving leisure activities from outdoors to indoors in fall, and is thus able to quantitatively predict the consequences of interventions. It is shown that these effects are best given as additive changes of the reproduction number R. The model also explains why contact reductions have decreasing marginal returns, i.e. the first 50% of contact reductions have considerably more effect than the second 50%. Our work shows that is is possible to build detailed epidemiological simulations from microscopic mobility models relatively quickly. They can be used to investigate mechanical aspects of the dynamics, such as the transmission from political decisions via human behavior to infections, consequences of different lockdown measures, or consequences of wearing masks in certain situations. The results can be used to inform political decisions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.