Returning to a Normal Life via COVID-19 Vaccines in the United States: A Large-scale Agent-Based Simulation Study

JMIR Medical Informatics, Journal Year: 2021, Volume and Issue: 9(4), P. e27419 - e27419

Published: April 14, 2021

In 2020, COVID-19 has claimed more than 300,000 deaths in the United States alone. Although nonpharmaceutical interventions were implemented by federal and state governments States, these efforts have failed to contain virus. Following Food Drug Administration's approval of two vaccines, however, hope for return normalcy been renewed. This rests on an unprecedented nationwide vaccine campaign, which faces many logistical challenges is also contingent several factors whose values are currently unknown.We study effectiveness a campaign response different efficacies, willingness population be vaccinated, daily capacity under plans. To characterize possible outcomes most accurately, we account interactions between vaccines through 6 scenarios that capture range impacts from interventions.We used large-scale, cloud-based, agent-based simulations implementing vaccination using COVASIM, open-source model peer-reviewed studies accounts individual heterogeneity multiplicity contact networks. Several modifications parameters simulation logic made better align with current evidence. We chose intervention applied following both plan proposed Operation Warp Speed (former Trump administration) one million per day, Biden administration. accounted unknowns efficacies levels compliance varying parameters. For each experiment, cumulative infection growth was fitted logistic model, carrying capacities rates recorded.For plans all scenarios, presence considerably lowers total number infections when life returns normal, even as low 20%. noted unintended consequence; given availability estimates focus vaccinating individuals age categories, significant reduction results counterintuitive situation higher then leads infections.Although potent, alone cannot effectively end pandemic adopted strategy. Nonpharmaceutical need continue enforced ensure high so rate immunity established outpaces induced infections.

Language: Английский

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Comparative effectiveness of contact tracing interventions in the context of the COVID-19 pandemic: a systematic review

European Journal of Epidemiology, Journal Year: 2023, Volume and Issue: 38(3), P. 243 - 266

Published: Feb. 16, 2023

Abstract Contact tracing is a non-pharmaceutical intervention (NPI) widely used in the control of COVID-19 pandemic. Its effectiveness may depend on number factors including proportion contacts traced, delays tracing, mode contact (e.g. forward, backward or bidirectional training), types who are traced index cases cases), setting where household workplace). We performed systematic review evidence regarding comparative interventions. 78 studies were included review, 12 observational (ten ecological studies, one retrospective cohort study and pre-post with two patient cohorts) 66 mathematical modelling studies. Based results from six can be effective at controlling COVID-19. Two high quality showed incremental adding digital to manual tracing. One intermediate that increases associated drop mortality, acceptable prompt case clusters / symptomatic individuals led reduction reproduction R. Within seven exploring context implementation other interventions, was found have an effect epidemic not remaining five However, limitation many these lack description extent we identified following highly policies: (1) coverage either medium-term immunity, efficacious isolation/quarantine and/ physical distancing (2) hybrid app adoption isolation/ quarantine social distancing, (3) secondary (4) eliminating delays, (5) (6) reopening educational institutions. also highlighted role enhance some interventions 2020 lockdown reopening. While limited, shows for epidemic. More empirical accounting required.

Language: Английский

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SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs

Nature Genetics, Journal Year: 2023, Volume and Issue: 55(1), P. 26 - 33

Published: Jan. 1, 2023

The first step in SARS-CoV-2 genomic surveillance is testing to identify people who are infected. However, global rates falling as we emerge from the acute health emergency and remain low many low- middle-income countries (mean = 27 tests per 100,000 day). We simulated COVID-19 epidemics a prototypical country investigate how rates, sampling strategies sequencing proportions jointly impact outcomes, showed that spatiotemporal biases delay time detection of new variants by weeks months can lead unreliable estimates variant prevalence, even when proportion samples sequenced increased. Accordingly, investments wider access diagnostics support approximately 100 day could enable more timely reliable prevalence. performance programs fundamentally limited diagnostic testing.

Language: Английский

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AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods

Osong Public Health and Research Perspectives, Journal Year: 2024, Volume and Issue: 15(2), P. 115 - 136

Published: March 28, 2024

Objectives: The coronavirus disease 2019 (COVID-19) pandemic continues to pose significant challenges the public health sector, including that of United Arab Emirates (UAE). objective this study was assess efficiency and accuracy various deep-learning models in forecasting COVID-19 cases within UAE, thereby aiding nation’s authorities informed decision-making.Methods: This utilized a comprehensive dataset encompassing confirmed cases, demographic statistics, socioeconomic indicators. Several advanced deep learning models, long short-term memory (LSTM), bidirectional LSTM, convolutional neural network (CNN), CNN-LSTM, multilayer perceptron, recurrent (RNN) were trained evaluated. Bayesian optimization also implemented fine-tune these models.Results: evaluation framework revealed each model exhibited different levels predictive precision. Specifically, RNN outperformed other architectures even without optimization. Comprehensive perspective analytics conducted scrutinize dataset.Conclusion: transcends academic boundaries by offering critical insights enable UAE deploy targeted data-driven interventions. model, which identified as most reliable accurate for specific context, can significantly influence decisions. Moreover, broader implications research validate capability techniques handling complex datasets, thus transformative potential healthcare sectors.

Language: Английский

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Task-oriented machine learning surrogates for tipping points of agent-based models

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: May 15, 2024

Abstract We present a machine learning framework bridging manifold learning, neural networks, Gaussian processes, and Equation-Free multiscale approach, for the construction of different types effective reduced order models from detailed agent-based simulators systematic numerical analysis their emergent dynamics. The specific tasks interest here include detection tipping points, uncertainty quantification rare events near them. Our illustrative examples are an event-driven, stochastic financial market model describing mimetic behavior traders, compartmental epidemic on Erdös-Rényi network. contrast pros cons surrogate effort involved in Importantly, proposed reveals that, around dynamics both benchmark can be effectively described by one-dimensional differential equation, thus revealing intrinsic dimensionality normal form type point. This allows significant reduction computational cost interest.

Language: Английский

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Modeling and investigating the spread of COVID-19 dynamics with Atangana-Baleanu fractional derivative: a numerical prospective

Physica Scripta, Journal Year: 2024, Volume and Issue: 99(3), P. 035255 - 035255

Published: Feb. 12, 2024

Abstract Fractional-order models have been used in the study of COVID-19 to incorporate memory and hereditary properties into systems Moira Xu (2003) Respirology 8 S9â14. These applied analyze dynamics behavior novel coronavirus. Various fractional-order proposed, including SIR SEIR models, with addition compartments such as asymptomatic classes virus repositories. Overall, proven be effective studying spread COVID-19. In this paper, we propose a nonlinear fractional model employing Atangana-Baleanu derivative describe To offer clearer perspective, our investigation incorporates two distinct quarantine stages within population. The first class consists individuals who not yet contracted but chosen self-isolate at home. second encompasses are infected undergoing hospitals. Additionally, introduce vaccination class, consisting portion population that has received is now reduced risk infection. Fixed point theorems employed prove existence uniqueness solutions. model’s threshold parameter R 0 calculated investigate pandemic’s future dynamics. Toufik-Atangana scheme obtain numerical solutions for model. Further, analyzed data assess how impacts virus.The includes parameters determine speed effectiveness measures. evaluate accuracy model, simulate graphical results stage compared them integer-order derivative. mathematical shows both equilibrium points locally stable. Moreover, gain deeper understanding disease, conduct sensitivity analysis examine effect on . recommends continuing hospitalization home isolation until transmission reduces sufficiently after vaccination. given provides useful insights suggests measures controlling its spread.

Language: Английский

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The SARS-CoV-2 test scale-up in the USA: an analysis of the number of tests produced and used over time and their modelled impact on the COVID-19 pandemic

The Lancet Public Health, Journal Year: 2025, Volume and Issue: 10(1), P. e47 - e57

Published: Jan. 1, 2025

Language: Английский

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Impact of RSVpreF vaccination on reducing the burden of respiratory syncytial virus in infants and older adults

Nature Medicine, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 9, 2025

Language: Английский

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Hybrid metapopulation agent-based epidemiological models for efficient insight on the individual scale: a contribution to green computing

Infectious Disease Modelling, Journal Year: 2025, Volume and Issue: 10(2), P. 571 - 590

Published: Jan. 11, 2025

Emerging infectious diseases and climate change are two of the major challenges in 21st century. Although over past decades, highly-resolved mathematical models have contributed understanding dynamics great aid when it comes to finding suitable intervention measures, they may need substantial computational effort produce significant CO2 emissions. Two popular modeling approaches for mitigating disease agent-based population-based models. Agent-based (ABMs) offer a microscopic view thus able capture heterogeneous human contact behavior mobility patterns. However, insights on individual-level come with high that scales number agents. On other hand, (PBMs) using e.g. ordinary differential equations (ODEs) computationally efficient even large populations due their complexity being independent population size. Yet, restricted granularity as assume (to some extent) homogeneous well-mixed population. To manage trade-off between level detail, we propose spatial- temporal-hybrid use ABMs only an area or time frame interest. account relevant influences dynamics, e.g., from outside, commuting activities, models, adding moderate costs. Our hybridization approach demonstrates reduction by up 98% - without losing required depth information focus frame. The hybrid used our numerical simulations based recently proposed however, any combination ABM PBM could be used, too. Concluding, epidemiological can provide individual scale where necessary, aggregated possible, thereby making contribution green computing.

Language: Английский

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Modelling the impact of relaxing COVID ‐19 control measures during a period of low viral transmission

The Medical Journal of Australia, Journal Year: 2020, Volume and Issue: 214(2), P. 79 - 83

Published: Nov. 18, 2020

Objectives To assess the risks associated with relaxing coronavirus disease 2019 (COVID-19)-related physical distancing restrictions and lockdown policies during a period of low viral transmission. Design Network-based transmission in households, schools, workplaces, variety community spaces activities were simulated an agent-based model, Covasim. Setting The model was calibrated for baseline scenario reflecting epidemiological policy environment Victoria March–May 2020, Intervention Policy changes easing COVID-19-related from May 2020 context interventions that included testing, contact tracing (including smartphone app), quarantine. Main outcome measure Increase detected COVID-19 cases following relaxation restrictions. Results facilitate individuals large numbers unknown people (eg, opening bars, increased public transport use) greatest risk case increasing; leading to smaller, structured gatherings known contacts small social gatherings, schools) lower risks. In our rise some notable only two months after their implementation. Conclusions Removing several within short time should be undertaken care, as consequences may not apparent more than months. Our findings support continuation work home (to reduce strategies mitigate re-opening venues.

Language: Английский

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