scholarly journals Impact of vaccine prioritization strategies on mitigating COVID-19: an agent-based simulation study using an urban region in the United States

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hanisha Tatapudi ◽  
Rachita Das ◽  
Tapas K. Das
Keyword(s):  
Hypothesis Test ◽  
The United States ◽  
Urban Region ◽  
Published Data ◽  
Cumulative Number ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Significant Difference ◽  
The Impact ◽  
The U.S

Abstract Background Approval of novel vaccines for COVID-19 had brought hope and expectations, but not without additional challenges. One central challenge was understanding how to appropriately prioritize the use of limited supply of vaccines. This study examined the efficacy of the various vaccine prioritization strategies using the vaccination campaign underway in the U.S. Methods The study developed a granular agent-based simulation model for mimicking community spread of COVID-19 under various social interventions including full and partial closures, isolation and quarantine, use of face mask and contact tracing, and vaccination. The model was populated with parameters of disease natural history, as well as demographic and societal data for an urban community in the U.S. with 2.8 million residents. The model tracks daily numbers of infected, hospitalized, and deaths for all census age-groups. The model was calibrated using parameters for viral transmission and level of community circulation of individuals. Published data from the Florida COVID-19 dashboard was used to validate the model. Vaccination strategies were compared using a hypothesis test for pairwise comparisons. Results Three prioritization strategies were examined: a minor variant of CDC’s recommendation, an age-stratified strategy, and a random strategy. The impact of vaccination was also contrasted with a no vaccination scenario. The study showed that the campaign against COVID-19 in the U.S. using vaccines developed by Pfizer/BioNTech and Moderna 1) reduced the cumulative number of infections by 10% and 2) helped the pandemic to subside below a small threshold of 100 daily new reported cases sooner by approximately a month when compared to no vaccination. A comparison of the prioritization strategies showed no significant difference in their impacts on pandemic mitigation. Conclusions The vaccines for COVID-19 were developed and approved much quicker than ever before. However, as per our model, the impact of vaccination on reducing cumulative infections was found to be limited (10%, as noted above). This limited impact is due to the explosive growth of infections that occurred prior to the start of vaccination, which significantly reduced the susceptible pool of the population for whom infection could be prevented. Hence, vaccination had a limited opportunity to reduce the cumulative number of infections. Another notable observation from our study is that instead of adhering strictly to a sequential prioritizing strategy, focus should perhaps be on distributing the vaccines among all eligible as quickly as possible, after providing for the most vulnerable. As much of the population worldwide is yet to be vaccinated, results from this study should aid public health decision makers in effectively allocating their limited vaccine supplies.

scholarly journals Impact of Vaccine Prioritization Strategies on Mitigating COVID-19: An Agent-Based Simulation Study using an Urban Region in the United States

2021 ◽  
Author(s):  
Hanisha Tatapudi ◽  
Rachita Das ◽  
Tapas K. Das
Keyword(s):  
The United States ◽  
Urban Region ◽  
Published Data ◽  
Cumulative Number ◽  
Agent Based Simulation ◽  
Susceptible Population ◽  
Agent Based ◽  
Significant Difference ◽  
The Impact ◽  
The U.S

ABSTRACTBackgroundApproval of novel vaccines for COVID-19 has brought hope and expectations, but not without additional challenges. One central challenge is how to appropriately prioritize the use of limited supply of vaccines. This study evaluates various prioritization strategies and the efficacy of the vaccination campaign underway in the U.S.MethodsThe study develops a granular agent-based simulation model for mimicking community spread of COVID-19 under various social interventions including full and partial closures, isolation and quarantine, use of face mask and contact tracing, and vaccination. The model is populated with demographic and societal data for an urban community in the U.S. with 2.8 million residents as well as viral parameters. The model tracks daily numbers of infected, hospitalized, and deaths for all census age-groups. Model is calibrated using parameters for viral transmission and level of community circulation of individuals. Published data from the Florida COVID-19 dashboard is used to validate the model. Vaccination strategies are compared using hypothesis test for pairwise comparisons.ResultsThree prioritization strategies examined are: a close variant of the CDC recommendation, an age-stratified strategy, and a random strategy. The impact of vaccination is also contrasted with a no vaccination scenario. The comparison shows that the ongoing campaign in the U.S. using vaccines developed by Pfizer/BioNTech and Moderna is expected to 1) reduce the cumulative number of infection by 10% and 2) help the pandemic to subside below a small threshold of 100 daily new reported cases sooner by approximately a month. The prioritization strategies when compared with each other showed no significant difference in their impacts on pandemic mitigation.ConclusionsRecent explosive growth of the number of new COVID-19 cases in the U.S. continues to shrink the susceptible population. This, we believe, will likely limit the expected number of people that could be prevented from getting infected due to vaccination. A shrinking susceptible pool may also be an attributable reason for the observed lack of statistical difference among the outcomes of the prioritization strategies. However, the invariance of the strategies should give more latitude for decision makers in COVID-19 vaccine distribution.

scholarly journals Impact of Vaccine Prioritization Strategies on Mitigating COVID-19: An Agent-Based Simulation Study using an Urban Region in the United States

2021 ◽  
Author(s):  
Hanisha Tatapudi ◽  
Rachita Das ◽  
Tapas Das
Keyword(s):  
The United States ◽  
Urban Region ◽  
Published Data ◽  
Cumulative Number ◽  
Agent Based Simulation ◽  
Susceptible Population ◽  
Agent Based ◽  
Significant Difference ◽  
The Impact ◽  
The U.S

Abstract Background Approval of novel vaccines for COVID-19 has brought hope and expectations, but not without additional challenges. One central challenge is how to appropriately prioritize the use of limited supply of vaccines. This study evaluates various prioritization strategies and the efficacy of the vaccination campaign underway in the U.S.Methods The study develops a granular agent-based simulation model for mimicking community spread of COVID-19 under various social interventions including full and partial closures, isolation and quarantine, use of face mask and contact tracing, and vaccination. The model is populated with demographic and societal data for an urban community in the U.S. with 2.8 million residents as well as viral parameters. The model tracks daily numbers of infected, hospitalized, and deaths for all census age-groups. Model is calibrated using parameters for viral transmission and level of community circulation of individuals. Published data from the Florida COVID-19 dashboard is used to validate the model. Vaccination strategies are compared using hypothesis test for pairwise comparisons.Results Three prioritization strategies examined are: a close variant of the CDC recommendation, an age-stratified strategy, and a random strategy. The impact of vaccination is also contrasted with a no vaccination scenario. The comparison shows that the ongoing campaign in the U.S. using vaccines developed by Pfizer/BioNTech and Moderna is expected to 1) reduce the cumulative number of infection by 10% and 2) help the pandemic to subside below a small threshold of 100 daily new reported cases sooner by approximately a month. The prioritization strategies when compared with each other showed no significant difference in their impacts on pandemic mitigation.Conclusions Recent explosive growth of the number of new COVID-19 cases in the U.S. continues to shrink the susceptible population. This, we believe, will likely limit the expected number of people that could be prevented from getting infected due to vaccination. A shrinking susceptible pool may also be an attributable reason for the observed lack of statistical difference among the outcomes of the prioritization strategies. However, the invariance of the strategies should give more latitude for decision makers in COVID-19 vaccine distribution.

scholarly journals The impact of vaccination to control COVID-19 burden in the United States: A simulation modeling approach

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254456
Author(s):  
Oguzhan Alagoz ◽  
Ajay K. Sethi ◽  
Brian W. Patterson ◽  
Matthew Churpek ◽  
Ghalib Alhanaee ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Simulation Modeling ◽  
Vaccine Coverage ◽  
The United States ◽  
Agent Based Simulation ◽  
Vaccination Programs ◽  
Agent Based ◽  
Nonpharmaceutical Interventions ◽  
The Impact

Introduction Vaccination programs aim to control the COVID-19 pandemic. However, the relative impacts of vaccine coverage, effectiveness, and capacity in the context of nonpharmaceutical interventions such as mask use and physical distancing on the spread of SARS-CoV-2 are unclear. Our objective was to examine the impact of vaccination on the control of SARS-CoV-2 using our previously developed agent-based simulation model. Methods We applied our agent-based model to replicate COVID-19-related events in 1) Dane County, Wisconsin; 2) Milwaukee metropolitan area, Wisconsin; 3) New York City (NYC). We evaluated the impact of vaccination considering the proportion of the population vaccinated, probability that a vaccinated individual gains immunity, vaccination capacity, and adherence to nonpharmaceutical interventions. We estimated the timing of pandemic control, defined as the date after which only a small number of new cases occur. Results The timing of pandemic control depends highly on vaccination coverage, effectiveness, and adherence to nonpharmaceutical interventions. In Dane County and Milwaukee, if 50% of the population is vaccinated with a daily vaccination capacity of 0.25% of the population, vaccine effectiveness of 90%, and the adherence to nonpharmaceutical interventions is 60%, controlled spread could be achieved by June 2021 versus October 2021 in Dane County and November 2021 in Milwaukee without vaccine. Discussion In controlling the spread of SARS-CoV-2, the impact of vaccination varies widely depending not only on effectiveness and coverage, but also concurrent adherence to nonpharmaceutical interventions.

THE INFLUENCE OF SCOTTISH ACCOUNTANTS IN THE UNITED STATES: THE EARLY CASE OF THE SOCIETY OF ACCOUNTANTS IN EDINBURGH

1997 ◽  
Vol 24 (1) ◽  
pp. 117-141 ◽  
Author(s):  
T. A. LEE
Keyword(s):  
United States ◽  
General Theory ◽  
Research Program ◽  
The United States ◽  
The World ◽  
Early Case ◽  
The Impact ◽  
Chartered Accountants ◽  
The U.S

This study represents part of a long-term research program to investigate the influence of U.K. accountants on the development of professional accountancy in other parts of the world. It examines the impact of a small group of Scottish chartered accountants who emigrated to the U.S. in the late 1800s and early 1900s. Set against a general theory of emigration, the study's main results reveal the significant involvement of this group in the founding and development of U.S. accountancy. The influence is predominantly with respect to public accountancy and its main institutional organizations. Several of the individuals achieved considerable eminence in U.S. public accountancy.

scholarly journals Process Modeling and Simulation of Tableting—An Agent-Based Simulation Methodology for Direct Compression

Pharmaceutics ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 996
Author(s):  
Niels Lasse Martin ◽  
Ann Kathrin Schomberg ◽  
Jan Henrik Finke ◽  
Tim Gyung-min Abraham ◽  
Arno Kwade ◽  
...  
Keyword(s):  
Raw Materials ◽  
Pilot Scale ◽  
Physical Models ◽  
Agent Based Simulation ◽  
Validation Data ◽  
Agent Based ◽  
Industrial Processing ◽  
Digital Twins ◽  
Product And Process ◽  
The Impact

In pharmaceutical manufacturing, the utmost aim is reliably producing high quality products. Simulation approaches allow virtual experiments of processes in the planning phase and the implementation of digital twins in operation. The industrial processing of active pharmaceutical ingredients (APIs) into tablets requires the combination of discrete and continuous sub-processes with complex interdependencies regarding the material structures and characteristics. The API and excipients are mixed, granulated if required, and subsequently tableted. Thereby, the structure as well as the properties of the intermediate and final product are influenced by the raw materials, the parametrized processes and environmental conditions, which are subject to certain fluctuations. In this study, for the first time, an agent-based simulation model is presented, which enables the prediction, tracking, and tracing of resulting structures and properties of the intermediates of an industrial tableting process. Therefore, the methodology for the identification and development of product and process agents in an agent-based simulation is shown. Implemented physical models describe the impact of process parameters on material structures. The tablet production with a pilot scale rotary press is experimentally characterized to provide calibration and validation data. Finally, the simulation results, predicting the final structures, are compared to the experimental data.

scholarly journals How Representative Are Snowball Samples? Using the Ethnosurvey to Study Guatemala-U.S. Migration

2016 ◽  
Vol 666 (1) ◽  
pp. 64-76
Author(s):  
David P. Lindstrom
Keyword(s):  
Rhode Island ◽  
Composite Index ◽  
The United States ◽  
Mexican Migration ◽  
Background Characteristics ◽  
Household Location ◽  
Sample Weighting ◽  
Migrant Integration ◽  
The Impact ◽  
The U.S

This analysis draws on binational data from an ethnosurvey conducted in Guatemala and in the United States in Providence, Rhode Island, to develop a refinement of the weighting scheme that the Mexican Migration Project (MMP) uses. The alternative weighting procedure distinguishes between temporary and settled migrants by using a question on household location in the Guatemala questionnaire that is not used in the MMP. Demographic characteristics and integration experiences of the most recent U.S. trip are used to assess the composition and representativeness of the U.S. sample. Using a composite index of migrant integration to compare the impact of alternative U.S. sample weights on point estimates, I find that although the U.S. sample is broadly representative across a range of background characteristics, the MMP sample weighting procedure biases estimates of migrant integration downward.

scholarly journals International Trade and Foreign Direct Investment as Innovation Factors of the U.S. Economy

2014 ◽  
Vol 41 (1) ◽  
pp. 60-75
Author(s):  
Tomasz M. Napiórkowski
Keyword(s):  
Foreign Direct Investment ◽  
International Trade ◽  
Direct Investment ◽  
Positive Impact ◽  
The United States ◽  
Annual Data ◽  
Main Portion ◽  
The Impact ◽  
Total Impact ◽  
The U.S

Abstract The aim of this research is to asses the hypothesis that foreign direct investment (FDI) and international trade have had a positive impact on innovation in one of the most significant economies in the world, the United States (U.S.). To do so, the author used annual data from 1995 to 2010 to build a set of econometric models. In each model, 11 in total) the number of patent applications by U.S. residents is regressed on inward FDI stock, exports and imports of the economy as a collective, and in each of the 10 SITC groups separately. Although the topic of FDI is widely covered in the literature, there are still disagreements when it comes to the impact of foreign direct investment on the host economy [McGrattan, 2011]. To partially address this gap, this research approaches the host economy not only as an aggregate, but also as a sum of its components (i.e., SITC groups), which to the knowledge of this author has not yet been done on the innovation-FDI-trade plane, especially for the U.S. Unfortunately, the study suffers from the lack of available data. For example, the number of patents and other used variables is reported in the aggregate and not for each SITC groups (e.g., trade). As a result, our conclusions regarding exports and imports in a specific SITC category (and the total) impact innovation in the U.S. is reported in the aggregate. General notions found in the literature are first shown and discussed. Second, the dynamics of innovation, trade and inward FDI stock in the U.S. are presented. Third, the main portion of the work, i.e. the econometric study, takes place, leading to several policy applications and conclusions.

Modeling Consumer Decisions on Returning End-of-Use Products Considering Design Features and Consumer Interactions: An Agent Based Simulation Approach

2015 ◽  
Author(s):  
Ardeshir Raihanian Mashhadi ◽  
Behzad Esmaeilian ◽  
Sara Behdad
Keyword(s):  
Electronic Waste ◽  
Peer Pressure ◽  
Waste Stream ◽  
Contributing Factors ◽  
Agent Based Simulation ◽  
Design Features ◽  
Agent Based ◽  
Consumer Decisions ◽  
Take Back ◽  
The Impact

As electronic waste (e-waste) becomes one of the fastest growing environmental concerns, remanufacturing is considered as a promising solution. However, the profitability of take back systems is hampered by several factors including the lack of information on the quantity and timing of to-be-returned used products to a remanufacturing facility. Product design features, consumers’ awareness of recycling opportunities, socio-demographic information, peer pressure, and the tendency of customer to keep used items in storage are among contributing factors in increasing uncertainties in the waste stream. Predicting customer choice decisions on returning back used products, including both the time in which the customer will stop using the product and the end-of-use decisions (e.g. storage, resell, through away, and return to the waste stream) could help manufacturers have a better estimation of the return trend. The objective of this paper is to develop an Agent Based Simulation (ABS) model integrated with Discrete Choice Analysis (DCA) technique to predict consumer decisions on the End-of-Use (EOU) products. The proposed simulation tool aims at investigating the impact of design features, interaction among individual consumers and socio-demographic characteristics of end users on the number of returns. A numerical example of cellphone take-back system has been provided to show the application of the model.

Abstract 257: Urban Teaching and Non-Teaching Hospitals Outcomes: Myocardial Infarction

2017 ◽  
Vol 10 (suppl_3) ◽  
Author(s):  
Priscilla O Okunji ◽  
Johnnie Daniel
Keyword(s):  
Myocardial Infarction ◽  
Mortality Rate ◽  
Income Group ◽  
The United States ◽  
Teaching Hospitals ◽  
Age Difference ◽  
Age Group ◽  
Urban Teaching ◽  
Significant Difference ◽  
The Impact

Background: Patients with myocardial infarction reportedly have different outcomes on discharge according to hospital characteristics. In the present study, we evaluated the differences between urban teaching hospitals (UTH) and non-teaching hospitals (NTH), discharged in 2012. We also investigated on the outcomes. Methods: Sample of 117,808 subjects diagnosed with myocardial infarction were extracted from a nationwide inpatient stay dataset using the International Classification Data, ICD 9 code 41000 in the United States, according to hospital location, size, and teaching status. Results: The analysis of the data showed that more whites were admitted to both teaching and non teaching hospitals with more males (~24%) admitted than their female counterparts. However, blacks were admitted more (~15%) in urban teaching hospitals than medium urban non teaching hospitals. Age difference was noted as well, while age group (60-79 years) were admitted more in UTH, inversely urban non-teaching hospitals admitted more older (80 years or older) age group. A significant difference (~28%) was observed in both hospital categories with UTH admitting more patients of $1.00 - $38,999.00 income group than other income categories. In addition, it was observed that patients with MI stayed more (~5%) for 14 or more days, and charged more especially for income group of $80,000 or above in UTH than NTH. No significant difference was found in the mortality rate for both hospital categories. Conclusion: The overall outcomes showed that the mortality rate between urban teaching and non-teaching hospitals were non significant, though the inpatients MI stayed longer and were charged more in UTH than NTH. The authors call for the study to be replicated with a higher level of statistical measures to ascertain the impact of the variables on the outcomes for a more validated result.

Evolving oncology provider perspectives on care delivery during the COVID-19 pandemic.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18609-e18609
Author(s):  
Divya Ahuja Parikh ◽  
Meera Vimala Ragavan ◽  
Sandy Srinivas ◽  
Sarah Garrigues ◽  
Eben Lloyd Rosenthal ◽  
...  
Keyword(s):  
Cancer Care ◽  
Care Delivery ◽  
The United States ◽  
Advanced Practice ◽  
Curative Surgery ◽  
Time Points ◽  
Patients With Cancer ◽  
Provider Perspectives ◽  
Significant Difference ◽  
The Impact

e18609 Background: The COVID-19 pandemic prompted rapid changes in cancer care delivery. We sought to examine oncology provider perspectives on clinical decisions and care delivery during the pandemic and to compare provider views early versus late in the pandemic. Methods: We invited oncology providers, including attendings, trainees and advanced practice providers, to complete a cross-sectional online survey using a variety of outreach methods including social media (Twitter), email contacts, word of mouth and provider list-serves. We surveyed providers at two time points during the pandemic when the number of COVID-19 cases was rising in the United States, early (March 2020) and late (January 2021). The survey responses were analyzed using descriptive statistics and Chi-squared tests to evaluate differences in early versus late provider responses. Results: A total of 132 providers completed the survey and most were white (n = 73/132, 55%) and younger than 49 years (n = 88/132, 67%). Respondents were attendings in medical, surgical or radiation oncology (n = 61/132, 46%), advanced practice providers (n = 48/132, 36%) and oncology fellows (n = 16/132, 12%) who predominantly practiced in an academic medical center (n = 120/132, 91%). The majority of providers agreed patients with cancer are at higher risk than other patients to be affected by COVID-19 (n = 121/132, 92%). However, there was a significant difference in the proportion of early versus late providers who thought delays in cancer care were needed. Early in the pandemic, providers were more likely to recommend delays in curative surgery or radiation for early-stage cancer (p < 0.001), delays in adjuvant chemotherapy after curative surgery (p = 0.002), or delays in surveillance imaging for metastatic cancer (p < 0.001). The majority of providers early in the pandemic responded that “reducing risk of a complication from a COVID-19 infection to patients with cancer” was the primary reason for recommending delays in care (n = 52/76, 68%). Late in the pandemic, however, providers were more likely to agree that “any practice change would have a negative impact on patient outcomes” (p = 0.003). At both time points, the majority of providers agreed with the need for other care delivery changes, including screening patients for infectious symptoms (n = 128/132, 98%) and the use of telemedicine (n = 114/132, 86%) during the pandemic. Conclusions: We found significant differences in provider perspectives of delays in cancer care early versus late in the pandemic which reflects the swiftly evolving oncology practice during the COVID-19 pandemic. Future studies are needed to determine the impact of changes in treatment and care delivery on outcomes for patients with cancer.

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