scholarly journals Dynamic prioritization of COVID-19 vaccines when social distancing is limited for essential workers

2021 ◽  
Vol 118 (16) ◽  
pp. e2025786118
Author(s):  
Jack H. Buckner ◽  
Gerardo Chowell ◽  
Michael R. Springborn
Keyword(s):  
Optimal Allocation ◽  
Rapid Development ◽  
Vaccination Campaign ◽  
The United States ◽  
Years Of Life Lost ◽  
Social Distancing ◽  
Health Goals ◽  
Temporal Flexibility ◽  
Nonpharmaceutical Interventions ◽  
Epidemiological Characteristics

COVID-19 vaccines have been authorized in multiple countries, and more are under rapid development. Careful design of a vaccine prioritization strategy across sociodemographic groups is a crucial public policy challenge given that 1) vaccine supply will be constrained for the first several months of the vaccination campaign, 2) there are stark differences in transmission and severity of impacts from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across groups, and 3) SARS-CoV-2 differs markedly from previous pandemic viruses. We assess the optimal allocation of a limited vaccine supply in the United States across groups differentiated by age and essential worker status, which constrains opportunities for social distancing. We model transmission dynamics using a compartmental model parameterized to capture current understanding of the epidemiological characteristics of COVID-19, including key sources of group heterogeneity (susceptibility, severity, and contact rates). We investigate three alternative policy objectives (minimizing infections, years of life lost, or deaths) and model a dynamic strategy that evolves with the population epidemiological status. We find that this temporal flexibility contributes substantially to public health goals. Older essential workers are typically targeted first. However, depending on the objective, younger essential workers are prioritized to control spread or seniors to directly control mortality. When the objective is minimizing deaths, relative to an untargeted approach, prioritization averts deaths on a range between 20,000 (when nonpharmaceutical interventions are strong) and 300,000 (when these interventions are weak). We illustrate how optimal prioritization is sensitive to several factors, most notably, vaccine effectiveness and supply, rate of transmission, and the magnitude of initial infections.

scholarly journals Dynamic Prioritization of COVID-19 Vaccines When Social Distancing is Limited for Essential Workers

2020 ◽  
Author(s):  
Jack H. Buckner ◽  
Gerardo Chowell ◽  
Michael R. Springborn
Keyword(s):  
Optimal Allocation ◽  
Rapid Development ◽  
Vaccination Campaign ◽  
Years Of Life Lost ◽  
Social Distancing ◽  
Demographic Groups ◽  
Health Goals ◽  
Temporal Flexibility ◽  
Policy Objectives ◽  
Epidemiological Characteristics

AbstractCOVID-19 vaccines have been authorized in multiple countries and more are under rapid development. Careful design of a vaccine prioritization strategy across socio-demographic groups is a crucial public policy challenge given that (1) vaccine supply will be constrained for the first several months of the vaccination campaign, (2) there are stark differences in transmission and severity of impacts from SARS-CoV-2 across groups, and (3) SARS-CoV-2 differs markedly from previous pandemic viruses. We assess the optimal allocation of a limited vaccine supply in the U.S. across groups differentiated by age and also essential worker status, which constrains opportunities for social distancing. We model transmission dynamics using a compartmental model parameterized to capture current understanding of the epidemiological characteristics of COVID-19, including key sources of group heterogeneity (susceptibility, severity, and contact rates). We investigate three alternative policy objectives (minimizing infections, years of life lost, or deaths) and model a dynamic strategy that evolves with the population epidemiological status. We find that this temporal flexibility contributes substantially to public health goals. Older essential workers are typically targeted first. However, depending on the objective, younger essential workers are prioritized to control spread or seniors to directly control mortality. When the objective is minimizing deaths, relative to an untargeted approach, prioritization averts deaths on a range between 20,000 (when non-pharmaceutical interventions are strong) and 300,000 (when these interventions are weak). We illustrate how optimal prioritization is sensitive to several factors, most notably vaccine effectiveness and supply, rate of transmission, and the magnitude of initial infections.

scholarly journals Optimal Allocation of the Limited COVID-19 Vaccine Supply in South Korea

2021 ◽  
Vol 10 (4) ◽  
pp. 591
Author(s):  
Eunha Shim
Keyword(s):  
South Korea ◽  
Vaccine Efficacy ◽  
Optimal Allocation ◽  
Age Distribution ◽  
Case Fatality ◽  
Vaccination Strategy ◽  
Years Of Life Lost ◽  
Incidence And Mortality ◽  
Specific Contact ◽  
Epidemiological Characteristics

Initial supply of the coronavirus disease (COVID-19) vaccine may be limited, necessitating its effective use. Herein, an age-structured model of COVID-19 spread in South Korea is parameterized to understand the epidemiological characteristics of COVID-19. The model determines optimal vaccine allocation for minimizing infections, deaths, and years of life lost while accounting for population factors, such as country-specific age distribution and contact structure, and various levels of vaccine efficacy. A transmission-blocking vaccine should be prioritized in adults aged 20–49 years and those older than 50 years to minimize the cumulative incidence and mortality, respectively. A strategy to minimize years of life lost involves the vaccination of adults aged 40–69 years, reflecting the relatively high case-fatality rates and years of life lost in this age group. An incidence-minimizing vaccination strategy is highly sensitive to vaccine efficacy, and vaccines with lower efficacy should be administered to teenagers and adults aged 50–59 years. Consideration of age-specific contact rates and vaccine efficacy is critical to optimize vaccine allocation. New recommendations for COVID-19 vaccines under consideration by the Korean Centers for Disease Control and Prevention are mainly based on a mortality-minimizing allocation strategy.

scholarly journals SARS-CoV-2 Viral and Serological Testing When College Campuses Reopen: Some Practical Considerations

2020 ◽  
pp. 1-5
Author(s):  
Isaac Chun-Hai Fung ◽  
Chi-Ngai Cheung ◽  
Andreas Handel
Keyword(s):  
Public Space ◽  
Control Strategies ◽  
The United States ◽  
College Campuses ◽  
Serological Testing ◽  
Social Distancing ◽  
University Campuses ◽  
Nonpharmaceutical Interventions ◽  
Personal Protective Behaviors ◽  
Close Contacts

ABSTRACT The coronavirus disease 2019 (COVID-19) pandemic prompted universities across the United States to close campuses in Spring 2020. Universities are deliberating whether, when, and how they should resume in-person instruction in Fall 2020. In this essay, we discuss some practical considerations for the use of 2 potentially useful control strategies based on testing: (1) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcriptase-polymerase chain reaction (RT-PCR) testing followed by case-patient isolation and quarantine of close contacts, and (2) serological testing followed by an “immune shield” approach, that is, low social distancing requirements for seropositive persons. The isolation of case-patients and quarantine of close contacts may be especially challenging, and perhaps prohibitively difficult, on many university campuses. The “immune shield” strategy might be hobbled by a low positive predictive value of the tests used in populations with low seroprevalence. Both strategies carry logistical, ethical, and financial implications. The main nonpharmaceutical interventions will remain methods based on social distancing (eg, capping class size) and personal protective behaviors (eg, universal facemask wearing in public space) until vaccines become available, or unless the issues discussed herein can be resolved in such a way that using mass testing as main control strategies becomes viable.

scholarly journals Alzheimers's disease: Epidemiological characteristics and its prevention

2021 ◽  
Vol 50 (2) ◽  
pp. 57-72
Author(s):  
Jovan Grujičić ◽  
Aleksandra Nikolić
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Detection ◽  
Cause Of Death ◽  
The United States ◽  
Brain Inflammation ◽  
Years Of Life Lost ◽  
Modifiable Risk Factors ◽  
Epidemiological Characteristics

Alzheimer's disease is a progressive neurodegenerative brain disease that is of immense public health interest. Worldwide, according to data from 2018, the approximated number of people living with Alzheimer's was at a minimum 50 million. In the United States, according to data from 2021, there were as many as 6.2 million people age 65 and over living with Alzheimer's. In the last 20 years, Alzheimer's disease is being recorded 145.2% more frequently as the cause of death, partially due to the cause of death being more accurately attributed, but mostly due to the growing frequency of Alzheimer's disease due to the aging of the population. Based on years of life lost(YLL), Alzheimer's disease was the fourth, according to years of life with disability (YLD) nineteenth and according to the sum indicator DALY (Disability Adjusted Life Years) sixth leading cause of burden amongst diseases in the USA in 2016. The nonmodifiable risk factors for developing Alzheimer's disease are age, genetics, and family history, while the modifiable risk factors are smoking, diabetes, midlife obesity, hypertension, prehypertension, high cholesterol, insufficient physical activity, unhealthy diet, shorter length of formal education, low level of mental stimulation at work, traumatic brain injury, poor sleep, alcohol abuse, and hearing impairment. It is estimated that by reducing the modifiable risk factors, 40% of cases of Alzheimer's dementia can be prevented or postponed. The biomarkers that can be used for early detection of this disease are betaamyloid protein that forms beta-amyloid plaques, abnormal tau protein accumulated inside neurons, the existence of brain inflammation and atrophy. While we wait for researchers to find a cure for this illness, it is important to raise awareness of available screening methods for early detection of Alzheimer's disease and prevention opportunities.

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

10.2196/27419 ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. e27419
Author(s):  
Junjiang Li ◽  
Philippe Giabbanelli
Keyword(s):  
United States ◽  
Large Scale ◽  
Vaccination Campaign ◽  
Vaccination Strategy ◽  
The United States ◽  
Current Evidence ◽  
Logistic Growth ◽  
Agent Based ◽  
Current Availability ◽  
Nonpharmaceutical Interventions

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

scholarly journals Rapid Deployment of an Algorithm to Triage Dental Emergencies During COVID-19 Pandemic

2021 ◽  
Author(s):  
Sharon C Perelman ◽  
Steven Erde ◽  
Lynda Torre ◽  
Tunaidi Ansari
Keyword(s):  
Rapid Development ◽  
The United States ◽  
Healthcare Systems ◽  
Patient Needs ◽  
Columbia University ◽  
Dental Infection ◽  
Screening Algorithm ◽  
Rapid Deployment ◽  
Medical Infrastructure ◽  
Insight Into

Abstract COVID-19 quickly immobilized healthcare systems in the United States during the early stages of the outbreak. While much of the ensuing response focused on supporting the medical infrastructure, Columbia University College of Dental Medicine pursued a solution to triage and safely treat patients with dental emergencies amidst the pandemic. Considering rapidly changing guidelines from governing bodies, dental infection control protocols and our clinical faculty's expertise, we modeled, built, and implemented a screening algorithm, which provides decision support as well as insight into COVID-19 status and clinical comorbidities, within a newly integrated Electronic Health Record (EHR). Once operationalized, we analyzed the data and outcomes of its utilization and found that it had effectively guided providers in triaging patient needs in a standardized methodology. This article describes the algorithm's rapid development to assist faculty providers in identifying patients with the most urgent needs, thus prioritizing treatment of dental emergencies during the pandemic.

scholarly journals A Bibliometric Insight of Genetic Factors in ASD: Emerging Trends and New Developments

2020 ◽  
Vol 11 (1) ◽  
pp. 33
Author(s):  
Kang Wang ◽  
Weicheng Duan ◽  
Yijie Duan ◽  
Yuxin Yu ◽  
Xiuyi Chen ◽  
...  
Keyword(s):  
Genetic Factors ◽  
De Novo ◽  
Rapid Development ◽  
The United States ◽  
Research Area ◽  
Scientific Output ◽  
Autism Spectrum ◽  
De Novo Mutations ◽  
Emerging Trends ◽  
Genetic Abnormalities

Autism spectrum disorder (ASD) cases have increased rapidly in recent decades, which is associated with various genetic abnormalities. To provide a better understanding of the genetic factors in ASD, we assessed the global scientific output of the related studies. A total of 2944 studies published between 1997 and 2018 were included by systematic retrieval from the Web of Science (WoS) database, whose scientific landscapes were drawn and the tendencies and research frontiers were explored through bibliometric methods. The United States has been acting as a leading explorer of the field worldwide in recent years. The rapid development of high-throughput technologies and bioinformatics transferred the research method from the traditional classic method to a big data-based pipeline. As a consequence, the focused research area and tendency were also changed, as the contribution of de novo mutations in ASD has been a research hotspot in the past several years and probably will remain one into the near future, which is consistent with the current opinions of the major etiology of ASD. Therefore, more attention and financial support should be paid to the deciphering of the de novo mutations in ASD. Meanwhile, the effective cooperation of multi-research centers and scientists in different fields should be advocated in the next step of scientific research undertaken.

scholarly journals Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Corentin Cot ◽  
Giacomo Cacciapaglia ◽  
Francesco Sannino
Keyword(s):  
Infection Rate ◽  
The United States ◽  
Strong Decrease ◽  
Social Distancing ◽  
Mobility Data ◽  
Actual Measure ◽  
The Us ◽  
The Impact ◽  
Political Decisions ◽  
Mobility Reduction

AbstractWe employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in Europe and in the United States. We identify the period of enacted social distancing via Google and Apple data, independently from the political decisions. Our analysis allows us to classify different shades of social distancing measures for the first wave of the pandemic. We observe a strong decrease in the infection rate occurring two to five weeks after the onset of mobility reduction. A universal time scale emerges, after which social distancing shows its impact. We further provide an actual measure of the impact of social distancing for each region, showing that the effect amounts to a reduction by 20–40% in the infection rate in Europe and 30–70% in the US.

scholarly journals Public Compliance With Social Distancing Measures and SARS-CoV-2 Spread

2021 ◽  
pp. 003335492110112
Author(s):  
Hongjie Liu ◽  
Chang Chen ◽  
Raul Cruz-Cano ◽  
Jennifer L. Guida ◽  
Minha Lee
Keyword(s):  
Growth Rate ◽  
Reproduction Number ◽  
Early Stage ◽  
Human Mobility ◽  
The United States ◽  
Density Change ◽  
Regression Coefficients ◽  
Daily Growth Rate ◽  
Daily Growth ◽  
Social Distancing

Objective We quantified the association between public compliance with social distancing measures and the spread of SARS-CoV-2 during the first wave of the epidemic (March–May 2020) in 5 states that accounted for half of the total number of COVID-19 cases in the United States. Methods We used data on mobility and number of COVID-19 cases to longitudinally estimate associations between public compliance, as measured by human mobility, and the daily reproduction number and daily growth rate during the first wave of the COVID-19 epidemic in California, Illinois, Massachusetts, New Jersey, and New York. Results The 5 states mandated social distancing directives during March 19-24, 2020, and public compliance with mandates started to decrease in mid-April 2020. As of May 31, 2020, the daily reproduction number decreased from 2.41-5.21 to 0.72-1.19, and the daily growth rate decreased from 0.22-0.77 to –0.04 to 0.05 in the 5 states. The level of public compliance, as measured by the social distancing index (SDI) and daily encounter-density change, was high at the early stage of implementation but decreased in the 5 states. The SDI was negatively associated with the daily reproduction number (regression coefficients range, –0.04 to –0.01) and the daily growth rate (from –0.009 to –0.01). The daily encounter-density change was positively associated with the daily reproduction number (regression coefficients range, 0.24 to 1.02) and the daily growth rate (from 0.05 to 0.26). Conclusions Social distancing is an effective strategy to reduce the incidence of COVID-19 and illustrates the role of public compliance with social distancing measures to achieve public health benefits.

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