Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty

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

Published: Nov. 20, 2023

Our ability to forecast epidemics far into the future is constrained by many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify state critical epidemic drivers. Since December 2020, U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams make months ahead SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function both scenario validity model calibration. We show remained close reality for 22 weeks on average before arrival unanticipated variants invalidated key assumptions. An ensemble participating models preserved variation between (using linear opinion pool method) was consistently more reliable than any single in periods valid assumptions, while projection interval coverage near target levels. were used guide pandemic response, illustrating value collaborative hubs

Language: Английский

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An evaluation of prospective COVID-19 modelling studies in the USA: from data to science translation

The Lancet Digital Health, Journal Year: 2022, Volume and Issue: 4(10), P. e738 - e747

Published: Sept. 20, 2022

Infectious disease modelling can serve as a powerful tool for situational awareness and decision support policy makers. However, COVID-19 efforts faced many challenges, from poor data quality to changing human behaviour. To extract practical insight the large body of literature available, we provide narrative review with systematic approach that quantitatively assessed prospective, data-driven studies in USA. We analysed 136 papers, focused on aspects models are essential have documented forecasting window, methodology, prediction target, datasets used, geographical resolution each study. also found fraction papers did not evaluate performance (25%), express uncertainty (50%), or state limitations (36%). remedy some these identified gaps, recommend adoption EPIFORGE 2020 model reporting guidelines creating an information-sharing system is suitable fast-paced infectious outbreak science.

Language: Английский

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Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination

eLife, Journal Year: 2022, Volume and Issue: 11

Published: June 21, 2022

In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths parts of United States. At time, with slowed vaccination uptake, this novel was expected increase risk pandemic resurgence US summer fall 2021. As part COVID-19 Scenario Modeling Hub, an ensemble nine mechanistic models produced 6-month scenario projections for July-December 2021 These estimated substantial resurgences across resulting from more variant, projected occur most US, coinciding school business reopening. The scenarios revealed that reaching higher vaccine coverage reduced size duration substantially, impacts largely concentrated a subset states lower coverage. Despite accurate projection surges occurring timing, magnitude substantially underestimated by compared reported during July-December, highlighting continued challenges predict evolving pandemic. Vaccination uptake remains critical limiting transmission disease, particularly Higher goals at onset surge new were avert over 1.5 million cases 21,000 deaths, although may have had even greater impacts, considering model.

Language: Английский

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COVID-19 Variant Detection with a High-Fidelity CRISPR-Cas12 Enzyme

Journal of Clinical Microbiology, Journal Year: 2022, Volume and Issue: 60(7)

Published: June 29, 2022

Laboratory tests for the accurate and rapid identification of SARS-CoV-2 variants can potentially guide treatment COVID-19 patients inform infection control public health surveillance efforts. Here, we present development validation a variant DETECTR assay incorporating loop-mediated isothermal amplification (LAMP) followed by CRISPR-Cas12 based single nucleotide polymorphism (SNP) mutations in spike (S) gene. This targets L452R, E484K/Q/A, N501Y mutations, at least one which is found nearly all major variants. In comparison three different Cas12 enzymes, only newly identified enzyme CasDx1 was able to accurately identify targeted SNP mutations. An analysis pipeline CRISPR-based from 261 clinical samples yielded concordance 97.3% agreement 98.9% (258 261) lineage classification, using whole-genome sequencing and/or real-time RT-PCR as test comparators. We also showed that detection E484A mutation necessary sufficient Omicron other circulating patient samples. These findings demonstrate utility faster simpler diagnostic method compared with laboratories.

Language: Английский

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Multiple models for outbreak decision support in the face of uncertainty

Proceedings of the National Academy of Sciences, Journal Year: 2023, Volume and Issue: 120(18)

Published: April 25, 2023

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches decision analysis, expert judgment, aggregation, we convened multiple teams to evaluate COVID-19 reopening strategies a mid-sized United States county early in pandemic. Projections seventeen distinct models were inconsistent magnitude but highly consistent ranking interventions. The 6-mo-ahead aggregate projections well line with observed outbreaks US counties. results showed that up half population could be infected full workplace reopening, while restrictions reduced median cumulative infections by 82%. Rankings interventions across public health objectives, there was strong trade-off between outcomes duration closures, no win-win intermediate identified. Between-model variation high; thus provide valuable risk quantification making. This approach can applied evaluation any setting where are used inform case study demonstrated utility our one several multimodel efforts laid groundwork Scenario Modeling Hub, which has provided rounds real-time scenario situational awareness making Centers Disease Control Prevention since December 2020.

Language: Английский

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Public health impact of the U.S. Scenario Modeling Hub

Epidemics, Journal Year: 2023, Volume and Issue: 44, P. 100705 - 100705

Published: July 18, 2023

Beginning in December 2020, the COVID-19 Scenario Modeling Hub has provided quantitative scenario-based projections for cases, hospitalizations, and deaths, aggregated across up to nine modeling groups. Projections spanned multiple months into future timely information on potential impacts of epidemiological uncertainties interventions. results were shared with public, public health partners, Centers Disease Control Response Team. The insights situational awareness informed decision-making mitigate disease burden (e.g., vaccination strategies). By aggregating from teams, rapidly synthesized times great uncertainty conveyed possible trajectories presence emerging variants. Here we detail several use cases these practice communication, including assessments whether directly or indirectly communication guidance. These include examples where comparisons projected outcomes under different scenarios used inform Advisory Committee Immunization Practices recommendations. We also describe challenges lessons learned during this highly beneficial collaboration.

Language: Английский

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Scenario design for infectious disease projections: Integrating concepts from decision analysis and experimental design

Epidemics, Journal Year: 2024, Volume and Issue: 47, P. 100775 - 100775

Published: May 24, 2024

Across many fields, scenario modeling has become an important tool for exploring long-term projections and how they might depend on potential interventions critical uncertainties, with relevance to both decision makers scientists. In the past decade, especially during COVID-19 pandemic, field of epidemiology seen substantial growth in use projections. Multiple scenarios are often projected at same time, allowing comparisons that can guide choice intervention, prioritization research topics, or public communication. The design is central their ability inform questions. this paper, we draw fields analysis statistical experiments propose a framework epidemiology, also other fields. We identify six different fundamental purposes designs (decision making, sensitivity analysis, situational awareness, horizon scanning, forecasting, value information) discuss those structure scenarios. aspects content process design, broadly all settings specifically multi-model ensemble As illustrative case study, examine first 17 rounds from U.S. Scenario Modeling Hub, then reflect future advancements could improve epidemiological settings.

Language: Английский

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A multiscale modeling framework for Scenario Modeling: Characterizing the heterogeneity of the COVID-19 epidemic in the US

Epidemics, Journal Year: 2024, Volume and Issue: 47, P. 100757 - 100757

Published: March 5, 2024

The Scenario Modeling Hub (SMH) initiative provides projections of potential epidemic scenarios in the United States (US) by using a multi-model approach. Our contribution to SMH is generated multiscale model that combines global metapopulation modeling approach (GLEAM) with local and mobility US (LEAM-US), first introduced here. LEAM-US consists 3142 subpopulations each representing single county across 50 states District Columbia, enabling us project state national trajectories COVID-19 cases, hospitalizations, deaths under different scenarios. age-structured, multi-strain. It integrates data on vaccine administration, human mobility, non-pharmaceutical interventions. contributed all 17 rounds SMH, allows for mechanistic characterization spatio-temporal heterogeneities observed during pandemic. Here we describe mathematical computational structure underpinning our model, present as case study results concerning emergence SARS-CoV-2 Alpha variant (lineage designation B.1.1.7). findings reveal considerable spatial temporal heterogeneity introduction diffusion variant, both at level individual combined statistical areas, it competes against ancestral lineage. We discuss key factors driving time required rise dominance within population, quantify significant impact had effective reproduction number level. Overall, show able capture complexity pandemic response US.

Language: Английский

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Doxycycline for the prevention of progression of COVID-19 to severe disease requiring intensive care unit (ICU) admission: A randomized, controlled, open-label, parallel group trial (DOXPREVENT.ICU)

PLoS ONE, Journal Year: 2023, Volume and Issue: 18(1), P. e0280745 - e0280745

Published: Jan. 23, 2023

After admission to hospital, COVID-19 progresses in a substantial proportion of patients critical disease that requires intensive care unit (ICU) admission.In pragmatic, non-blinded trial, 387 aged 40-90 years were randomised receive treatment with SoC plus doxycycline (n = 192) or only 195). The primary outcome was the need for ICU as judged by attending physicians. Three types analyses carried out outcome: "Intention treat" (ITT) based on randomisation; "Per protocol" (PP), excluding not treated according and "As treated" (AT), actual received. trial undertaken six hospitals India high-quality facilities. An online application serving electronic case report form developed enable screening, randomisation collection outcomes data.Adherence per protocol 95.1%. Among all participants, 77 (19.9%) needing admission. In three analyses, associated relative risk reduction (RRR) absolute (ARR): ITT 31.6% RRR, 7.4% ARR (P 0.063); PP 40.7% 9.6% 0.017); AT 43.2% 10.8% 0.007), numbers needed treat (NTT) 13.4 (ITT), 10.4 9.3 respectively. Doxycycline well tolerated single patient stopping due adverse events.In hospitalized patients, doxycycline, safe, inexpensive, widely available antibiotic anti-inflammatory properties, reduces when added SoC.

Language: Английский

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The US COVID-19 and Influenza Scenario Modeling Hubs: Delivering long-term projections to guide policy

Epidemics, Journal Year: 2023, Volume and Issue: 46, P. 100738 - 100738

Published: Dec. 29, 2023

Between December 2020 and April 2023, the COVID-19 Scenario Modeling Hub (SMH) generated operational multi-month projections of burden in US to guide pandemic planning decision-making context high uncertainty. This effort was born out an attempt coordinate, synthesize effectively use unprecedented amount predictive modeling that emerged throughout pandemic. Here we describe history this massive collective research effort, process convening maintaining open hub active over multiple years, provide a blueprint for future efforts. We detail generating 17 rounds scenarios at different stages pandemic, disseminating results public health community lay public. also highlight how SMH expanded generate influenza during 2022-23 season. identify key impacts on draw lessons improve collaborative efforts, scenario projections, interface between models policy.

Language: Английский

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