ArticleComputer methods and programs in biomedicine2021
Human activity pattern implications for modeling SARS-CoV-2 transmission.
Article in Computer methods and programs in biomedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed, 16 citations in OpenAlex.
- Early warning of emerging infectious diseases based on multimodal data.Biosafety and health · 2023Review
- The IHI Rochester Report 2022 on Healthcare Informatics Research: Resuming After the CoViD-19.Journal of healthcare informatics research · 2023Article
- Simulating patterns of life: More representative time-activity patterns that account for context.Environment international · 2023Review
- Microstructural evaluation and recommendations for face masks in community use to reduce the transmission of respiratory infectious diseases.Computer methods and programs in biomedicine · 2022Article
- Using simulation modelling and systems science to help contain COVID-19: A systematic review.Systems research and behavioral science · 2022Article
- Evaluation of the effects of meteorological factors on COVID-19 prevalence by the distributed lag nonlinear model.Journal of translational medicine · 2022Article
- A model based on cellular automata for investigating the impact of lockdown, migration and vaccination on COVID-19 dynamics.Computer methods and programs in biomedicine · 2021Article
- Review
- Feature fusion using deep learning for smartphone based human activity recognition.International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management · 2021Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 4 countries.
Funding
Abstract
BACKGROUND AND
objectivesSARS-CoV-2 emerged in December 2019 and rapidly spread into a global pandemic. Designing optimal community responses (social distancing, vaccination) is dependent on the stage of the disease progression, discovery of asymptomatic individuals, changes in virulence of the pathogen, and current levels of herd immunity. Community strategies may have severe and undesirable social and economic side effects. Modeling is the only available scientific approach to develop effective strategies that can minimize these unwanted side effects while retaining the effectiveness of the interventions.
methodsWe extended the agent-based model, SpatioTemporal Human Activity Model (STHAM), for simulating SARS-CoV-2 transmission dynamics.
resultsHere we present preliminary STHAM simulation results that reproduce the overall trends observed in the Wasatch Front (Utah, United States of America) for the general population. The results presented here clearly indicate that human activity patterns are important in predicting the rate of infection for different demographic groups in the population.
conclusionsFuture work in pandemic simulations should use empirical human activity data for agent-based techniques.
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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.