Spatial and temporal trends in social vulnerability and COVID-19 incidence and death rates in the United States

PLoS ONE, Journal Year: 2021, Volume and Issue: 16(3), P. e0248702 - e0248702

Published: March 24, 2021

Socially vulnerable communities may be at higher risk for COVID-19 outbreaks in the US. However, no prior studies examined temporal trends and differential effects of social vulnerability on incidence death rates. Therefore, we among counties with high low to quantify disparities over time.We conducted a longitudinal analysis examining rates from March 15 December 31, 2020, each US county using data USAFacts. We classified Social Vulnerability Index (SVI), percentile-based measure Centers Disease Control Prevention, values indicating more vulnerability. Using Bayesian hierarchical negative binomial model, estimated daily ratios (RRs) comparing first (lower) fourth (upper) SVI quartiles, adjusting rurality, percentage poor or fair health, female, smokers, average fine particulate matter (PM2.5), primary care physicians per 100,000 residents, temperature precipitation, proportion tested COVID-19.At outset pandemic, most had, average, fewer cases than least quartile. 28, observed crossover effect which experienced compared (RR = 1.05, 95% PI: 0.98, 1.12). Vulnerable had starting May 21 1.08, 1.00,1.16). by October, this trend reversed lower counties.The impact is not static but can migrate less back again time.

Language: Английский

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Different roles of interpersonal trust and institutional trust in COVID-19 pandemic control

Social Science & Medicine, Journal Year: 2021, Volume and Issue: 293, P. 114677 - 114677

Published: Dec. 22, 2021

Language: Английский

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Lessons from countries implementing find, test, trace, isolation and support policies in the rapid response of the COVID-19 pandemic: a systematic review

BMJ Open, Journal Year: 2021, Volume and Issue: 11(7), P. e047832 - e047832

Published: June 29, 2021

Objective To systematically learn lessons from the experiences of countries implementing find, test, trace, isolate, support (FTTIS) in first wave COVID-19 pandemic. Design, data sources and eligibility criteria We searched MEDLINE (PubMed), Cochrane Library, SCOPUS JSTOR, initially between 31 May 2019 21 January 2021. Research articles reviews on use contact tracing, testing, self-isolation quarantine for management were included review. Data extraction synthesis extracted information including study objective, design, methods, main findings implications. These tabulated a narrative was undertaken given diverse research designs, methods Results identified 118 eligible studies. core elements an effective system needed to interrupt spread novel infectious disease, where treatment or vaccination not yet available, as pertained initial stages report used shorten case finding time, improve accuracy efficiency tests, coordinate stakeholders actors involved FTTIS system, individuals isolating make appropriate digital tools. Conclusions our systematic review key components system. include border controls, restricted entry, inbound traveller comprehensive finding; repeated testing minimise false diagnoses pooled resource-limited circumstances; extended period tools tracing self-isolation. Support mental physical health livelihoods is undergoing self-isolation/quarantine. An integrated with rolling-wave planning can best respond fast-changing may inform considering these measures.

Language: Английский

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Compartmental structures used in modeling COVID-19: a scoping review

Infectious Diseases of Poverty, Journal Year: 2022, Volume and Issue: 11(1)

Published: June 21, 2022

The coronavirus disease 2019 (COVID-19) epidemic, considered as the worst global public health event in nearly a century, has severely affected more than 200 countries and regions around world. To effectively prevent control researchers have widely employed dynamic models to predict simulate epidemic's development, understand spread rule, evaluate effects of intervention measures, inform vaccination strategies, assist formulation prevention measures. In this review, we aimed sort out compartmental structures used COVID-19 provide reference for modeling other infectious diseases future. A scoping review on was conducted. 241 research articles published before May 14, 2021 were analyzed better model types COVID-19. Three dynamics analyzed: compartment expanded based susceptible-exposed-infected-recovered (SEIR) model, meta-population models, agent-based models. compartments SEIR are mainly according transmission characteristics, interventions, age structure. trade-off complex structures, basic or simply generally adopted. There been great deal COVID-19, help strategies. Researchers build actual situation, objectives complexity used. As epidemic remains uncertain poses major challenge humans, still need main tool dynamics, effects, scientific evidence development reviewed study guidance future also offer recommendations diseases.

Language: Английский

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Race, Ethnicity, Neighborhood Characteristics, and In-Hospital Coronavirus Disease-2019 Mortality

Medical Care, Journal Year: 2021, Volume and Issue: 59(10), P. 888 - 892

Published: Aug. 2, 2021

Background: Despite many studies reporting disparities in coronavirus disease-2019 (COVID-19) incidence and outcomes Black Hispanic/Latino populations, mechanisms are not fully understood to inform mitigation strategies. Objective: The aim was test whether neighborhood factors beyond individual patient-level associated with in-hospital mortality from COVID-19. We hypothesized that the Area Deprivation Index (ADI), a census-block-level composite measure, COVID-19 independently of race, ethnicity, other patient factors. Research Design: Multicenter retrospective cohort study examining mortality. Subjects: Inclusion required hospitalization positive SARS-CoV-2 or diagnosis at three large Midwestern academic centers. Measure(s): primary outcome Patient-level predictors included age, sex, insurance, body mass index, comorbidities, ventilation. Neighborhoods were examined through national ADI deprivation rank comparing across quintiles. Analyses used multivariable logistic regression fixed site effects. Results: Among 5999 patients median age 61 (interquartile range: 44–73), 48% male, 30% Black, 10.8% died. who died, 32% lived most disadvantaged quintile while 11% least quintile; 52% 24% Hispanic/Latino, 8.5% White neighborhoods. Living predicted higher (adjusted odds ratio: 1.74; 95% confidence interval: 1.13–2.67) independent race. Age, male Medicare coverage, ventilation also Conclusions: Neighborhood disadvantage Findings support calls consider measures for vaccine distribution policies mitigate disparities.

Language: Английский

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Effects of public-health measures for zeroing out different SARS-CoV-2 variants

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Aug. 29, 2023

Abstract Targeted public health interventions for an emerging epidemic are essential preventing pandemics. During 2020-2022, China invested significant efforts in strict zero-COVID measures to contain outbreaks of varying scales caused by different SARS-CoV-2 variants. Based on a multi-year empirical dataset containing 131 observed from April 2020 May 2022 and simulated scenarios, we ranked the relative intervention effectiveness their reduction instantaneous reproduction number. We found that, overall, social distancing (38% reduction, 95% prediction interval 31-45%), face masks (30%, 17-42%) close contact tracing (28%, 24-31%) were most effective. Contact was crucial during initial phases, while became increasingly prominent as spread persisted. In addition, infections with higher transmissibility shorter latent period posed more challenges these measures. Our findings provide quantitative evidence effects public-health zeroing out contagions contexts.

Language: Английский

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Using test positivity and reported case rates to estimate state-level COVID-19 prevalence and seroprevalence in the United States

PLoS Computational Biology, Journal Year: 2021, Volume and Issue: 17(9), P. e1009374 - e1009374

Published: Sept. 7, 2021

Accurate estimates of infection prevalence and seroprevalence are essential for evaluating informing public health responses vaccination coverage needed to address the ongoing spread COVID-19 in each United States (U.S.) state. However, reliable, timely data based on representative population sampling unavailable, reported case test positivity rates highly biased. A simple data-driven Bayesian semi-empirical modeling framework was developed used evaluate state-level using daily cases ratios. The model calibrated validated published state-wide data, further compared against two independent mathematical models. undiagnosed infections is found be well-approximated by a geometrically weighted average rate rate. Our accurately fits from across U.S. Prevalence our compare favorably those epidemiological As December 31, 2020, we estimate nation-wide 1.4% [Credible Interval (CrI): 1.0%-1.9%] 13.2% [CrI: 12.3%-14.2%], with ranging 0.2% 0.1%-0.3%] Hawaii 2.8% 1.8%-4.1%] Tennessee, 1.5% 1.2%-2.0%] Vermont 23% 20%-28%] New York. Cumulatively, correspond only one third actual infections. use this easy-to-communicate approach estimating will improve ability make decisions that effectively respond pandemic.

Language: Английский

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Spatiotemporal prediction of COVID-19 cases using inter- and intra-county proxies of human interactions

Nature Communications, Journal Year: 2021, Volume and Issue: 12(1)

Published: Nov. 8, 2021

Measurements of human interaction through proxies such as social connectedness or movement patterns have proved useful for predictive modeling COVID-19, which is a challenging task, especially at high spatial resolutions. In this study, we develop Spatiotemporal autoregressive model to predict county-level new cases COVID-19 in the coterminous US using spatiotemporal lags infection rates, interactions, mobility, and socioeconomic composition counties features. We capture interactions 1) Facebook- 2) cell phone-derived measures connectivity use them two separate models predicting COVID-19. evaluate on 14 forecast dates between 2020/10/25 2021/01/24 over one- four-week prediction horizons. Comparing our predictions with Baseline developed by Forecast Hub indicates an average 6.46% improvement Mean Absolute Errors (MAE) two-week horizon up 20.22% horizon, pointing strong power longer

Language: Английский

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SUIHTER : a new mathematical model for COVID-19. Application to the analysis of the second epidemic outbreak in Italy

Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences, Journal Year: 2021, Volume and Issue: 477(2253), P. 20210027 - 20210027

Published: Sept. 1, 2021

The COVID-19 epidemic is the latest in a long list of pandemics that have affected humankind last century. In this paper, we propose novel mathematical epidemiological model named SUIHTER from names seven compartments it comprises: susceptible uninfected individuals ( S ), undetected (both asymptomatic and symptomatic) infected U isolated I hospitalized H threatened T extinct E ) recovered R ). A suitable parameter calibration based on combined use least-squares method Markov chain Monte Carlo proposed with aim reproducing past history Italy, which surfaced late February still ongoing to date, validating terms its predicting capabilities. distinctive feature new allows one-to-one strategy between data are made available daily by Italian Civil Protection Department. then applied analysis emphasis second outbreak, emerged autumn 2020. particular, show can be suitably used predictive manner perform scenario at national level.

Language: Английский

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Assessing the effectiveness of test-trace-isolate interventions using a multi-layered temporal network

Infectious Disease Modelling, Journal Year: 2025, Volume and Issue: 10(3), P. 775 - 786

Published: March 14, 2025

Language: Английский

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