ArticleJournal of biomedical informatics2021
COVID-19 modelling by time-varying transmission rate associated with mobility trend of driving via Apple Maps.
Article in Journal of biomedical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- The impact of non-pharmaceutical interventions on COVID-19 transmission and its effect on life expectancy in two European regions.BMC public health · 2025Article
- Open e-commerce 1.0, five years of crowdsourced U.S. Amazon purchase histories with user demographics.Scientific data · 2024Article
- Article
- AA-forecast: anomaly-aware forecast for extreme events.Data mining and knowledge discovery · 2023Article
- The Apple Mobility Trends Data in Human Mobility Patterns during Restrictions and Prediction of COVID-19: A Systematic Review and Meta-Analysis.Healthcare (Basel, Switzerland) · 2022Review
- Recursive state and parameter estimation of COVID-19 circulating variants dynamics.Scientific reports · 2022Article
- Novel informatics approaches to COVID-19 Research: From methods to applications.Journal of biomedical informatics · 2022Article
- Feedback control of social distancing for COVID-19 via elementary formulae.IFAC-PapersOnLine · 2022Article
- Analysis of multi-strain infection of vaccinated and recovered population through epidemic model: Application to COVID-19.PloS one · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Compartment-based infectious disease models that consider the transmission rate (or contact rate) as a constant during the course of an epidemic can be limiting regarding effective capture of the dynamics of infectious disease. This study proposed a novel approach based on a dynamic time-varying transmission rate with a control rate governing the speed of disease spread, which may be associated with the information related to infectious disease intervention. Integration of multiple sources of data with disease modelling has the potential to improve modelling performance. Taking the global mobility trend of vehicle driving available via Apple Maps as an example, this study explored different ways of processing the mobility trend data and investigated their relationship with the control rate. The proposed method was evaluated based on COVID-19 data from six European countries. The results suggest that the proposed model with dynamic transmission rate improved the performance of model fitting and forecasting during the early stage of the pandemic. Positive correlation has been found between the average daily change of mobility trend and control rate. The results encourage further development for incorporation of multiple resources into infectious disease modelling in the future.
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Registered trials
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