Publications by authors named "Gary Lin"

Background: Rapid, accessible, and accurate testing was paramount to an effective US COVID-19 response. Federal partners supported SARS-CoV-2 testing scale-up through an interagency-coordinated approach that focused on expanding supply chains, research and development, validation, and improving patient access. We aimed to provide an overview of the federal efforts to scale up the testing response and study the impact of scale-up.

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The COVID-19 pandemic highlighted the need for robust epidemic forecasts, projecting health burden over short- and medium-term time horizons. Many COVID-19 forecasting models incorporate information on infection transmission, disease progression, and the effects of interventions, but few combine information on how individuals change their behavior based on altruism, fear, risk perception, or personal economic circumstances. Moreover, early models of COVID-19 produced under- and over-estimates, failing to consider the complexity of human responses to disease threat and prevention measures.

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Importance: Understanding the susceptibility and infectiousness of children and adolescents in comparison to adults is important to appreciate their role in the COVID-19 pandemic.

Objective: To determine SARS-CoV-2 susceptibility and infectiousness of children and adolescents with adults as comparator for three variants (wild-type, alpha, delta) in the household setting. We aimed to identify the effects independent of vaccination or prior infection.

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Background: During the COVID-19 pandemic there was a plethora of dynamical forecasting models created, but their ability to effectively describe future trajectories of disease was mixed. A major challenge in evaluating future case trends was forecasting the behavior of individuals. When behavior was incorporated into models, it was primarily incorporated exogenously (e.

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Background: The emergence of antimalarial drug resistance poses a major threat to effective malaria treatment and control. This study aims to inform policymakers and vaccine developers on the potential of an effective malaria vaccine in reducing drug-resistant infections.

Methods: A compartmental model estimating cases, drug-resistant cases, and deaths averted from 2021 to 2030 with a vaccine against Plasmodium falciparum infection administered yearly to 1-year-olds in 42 African countries.

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The inherent stochasticity in transmission of hospital-acquired infections (HAIs) has complicated our understanding of transmission pathways. It is particularly difficult to detect the impact of changes in the environment on acquisition rate due to stochasticity. In this study, we investigated the impact of uncertainty (epistemic and aleatory) on nosocomial transmission of HAIs by evaluating the effects of stochasticity on the detectability of seasonality of admission prevalence.

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Background: Despite decades of research on predictors of extubation success, use of ventilatory support after extubation is common and 10-20% of patients require re-intubation. Proportional assist ventilation (PAV) mode automatically calculates estimated total work of breathing (total WOB). Here, we assessed the performance of total WOB to predict extubation failure in invasively ventilated subjects.

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Article Synopsis
  • Policymakers face challenges in making decisions with limited information and conflicting predictions from different models, especially during crises like the COVID-19 pandemic.
  • A study brought together multiple modeling teams to assess reopening strategies in a mid-sized U.S. county, revealing consistent rankings for interventions despite variations in projection magnitudes.
  • The findings indicated that reopening workplaces could lead to a significant increase in infections, while restrictions could greatly reduce cumulative infections, highlighting the trade-offs between public health and economic activity with no optimal reopening strategy identified.
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Mounting evidence suggests the primary mode of SARS-CoV-2 transmission is aerosolized transmission from close contact with infected individuals. While transmission is a direct result of human encounters, falling humidity may enhance aerosolized transmission risks similar to other respiratory viruses (e.g.

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Artificial intelligence (AI) refers to the performance of tasks by machines ordinarily associated with human intelligence. Machine learning (ML) is a subtype of AI; it refers to the ability of computers to draw conclusions (ie, learn) from data without being directly programmed. ML builds from traditional statistical methods and has drawn significant interest in healthcare epidemiology due to its potential for improving disease prediction and patient care.

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Workers in the oil and gas industry are at risk for exposure to a number of physical and chemical hazards at the workplace. Chemical hazard risks include inhalation of crude oil or its volatile components. While several studies have investigated the neurotoxic effects of volatile hydrocarbons, in general, there is a paucity of studies assessing the neurotoxicity of crude oil vapor (COV).

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Objective: We analyzed the efficacy, cost, and cost-effectiveness of predictive decision-support systems based on surveillance interventions to reduce the spread of carbapenem-resistant Enterobacteriaceae (CRE).

Design: We developed a computational model that included patient movement between acute-care hospitals (ACHs), long-term care facilities (LTCFs), and communities to simulate the transmission and epidemiology of CRE. A comparative cost-effectiveness analysis was conducted on several surveillance strategies to detect asymptomatic CRE colonization, which included screening in ICUs at select or all hospitals, a statewide registry, or a combination of hospital screening and a statewide registry.

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Objectives: As of 13 January 2021, there have been 3 113 963 confirmed cases of SARS-CoV-2 and 74 619 deaths across the African continent. Despite relatively lower numbers of cases initially, many African countries are now experiencing an exponential increase in case numbers. Estimates of the progression of disease and potential impact of different interventions are needed to inform policymaking decisions.

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Background: COVID-19 vaccines have been approved and made available. While questions of vaccine allocation strategies have received significant attention, important questions remain regarding the potential impact of the vaccine given uncertainties regarding efficacy against transmission, availability, timing, and durability.

Methods: We adapted a susceptible-exposed-infectious-recovered (SEIR) model to examine the potential impact on hospitalization and mortality assuming increasing rates of vaccine efficacy, coverage, and administration.

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The study objective assessed the energy demand and economic cost of two hospital-based COVID-19 infection control interventions: negative pressure (NP) treatment rooms and xenon pulsed ultraviolet (XP-UV) equipment. After projecting COVID-19 hospitalizations, a Hospital Energy Model and Infection De-escalation Models quantified increases in energy demand and reductions in infections. The NP intervention was applied to 11, 22, and 44 rooms for small, medium, and large hospitals, while the XP-UV equipment was used eight, nine, and ten hours a day.

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Objectives: Our goal was to optimize infection control of paired environmental control interventions within hospitals to reduce methicillin-resistant (MRSA), carbapenem-resistant (CRE), and vancomycin-resistant (VRE).

Background: The most widely used infection control interventions are deployment of handwashing (HW) stations, control of relative humidity (RH), and negative pressure (NP) treatment rooms. Direct costs of multidrug-resistant organism (MDRO) infections are typically not included in the design of such interventions.

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Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed.

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Objective: Clinical trials ensure that pharmaceutical treatments are safe, efficacious, and effective for public consumption, but are extremely complex, taking up to 10 years and $2.6 billion to complete. One main source of complexity arises from the collaboration between actors, and network science methodologies can be leveraged to explore that complexity.

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Hydraulic fracturing (fracking) is a process used to recover oil and gas from shale rock formation during unconventional drilling. Pressurized liquids containing water and sand (proppant) are used to fracture the oil- and natural gas-laden rock. The transportation and handling of proppant at well sites generate dust aerosols; thus, there is concern of worker exposure to such fracking sand dusts (FSD) by inhalation.

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In this article, we report a graphene oxide-based nanosensor incorporating semiconductor quantum dots linked to DNA-aptamers that functions as a 'turn-off' fluorescent nanosensor for detection of low concentrations of analytes. A specific demonstration of this turn-off aptasensor is presented for the case of the detection of mercury (II) ions. In this system, ensembles of aptamer-based quantum-dot sensors are anchored onto graphene oxide (GO) flakes which provide a platform for analyte detection in the vicinity of GO.

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Welding fumes (WF) are a complex mixture of toxic metals and gases, inhalation of which can lead to adverse health effects among welders. The presence of manganese (Mn) in welding electrodes is cause for concern about the potential development of Parkinson's disease (PD)-like neurological disorder. Consequently, from an occupational safety perspective, there is a critical need to prevent adverse exposures to WF.

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Welding generates complex metal aerosols, inhalation of which is linked to adverse health effects among welders. An important health concern of welding fume (WF) exposure is neurological dysfunction akin to Parkinson's disease (PD). Some applications in manufacturing industry employ a variant welding technology known as "weld-bonding" that utilizes resistance spot welding, in combination with adhesives, for metal-to-metal welding.

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Occupational exposure to welding fumes (WF) is thought to cause Parkinson's disease (PD)-like neurological dysfunction. An apprehension that WF may accelerate the onset of PD also exists. Identifying reliable biomarkers of exposure and neurotoxicity are therefore critical for biomonitoring and neurological risk characterization of WF exposure.

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Consequent to the 2010 Deepwater Horizon oil spill in the Gulf of Mexico, there is an emergent concern about the short- and long-term adverse health effects of exposure to crude oil, weathered-oil products, and oil dispersants among the workforce employed to contain and clean up the spill. Oil dispersants typically comprise of a mixture of solvents and surfactants that break down floating oil to micrometer-sized droplets within the water column, thus preventing it from reaching the shorelines. As dispersants are generally sprayed from the air, workers are at risk for exposure primarily via inhalation.

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