scholarly journals Agent-Based Simulation of Covid-19 Vaccination Policies in CovidSIMVL

2021 ◽  
Author(s):  
Ernie Chang ◽  
Kenneth A. Moselle
Keyword(s):  
Disease Modeling ◽  
Transmission Dynamics ◽  
Discussion Section ◽  
Agent Based ◽  
Degree Of Protection ◽  
Department Of Health ◽  
Project Outcomes ◽  
The Us ◽  
Local Contexts ◽  
Infectious Disease Modeling

ABSTRACTAn agent-based infectious disease modeling tool (CovidSIMVL) is employed in this paper to explore outcomes associated with MRNA two-dose vaccination regimens set out in Emergency Use Authorization (EUA) documents submitted by Pfizer and Moderna to the US Department of Health & Human Services. As well, the paper explores outcomes associated with a third “Hybrid” policy that reflects ranges of expected levels of protection according to Pfizer and Moderna EUA’s, but entails a 35 day separation between first and second dose, which exceeds the 21 days set out in Pfizer documentation or the 28 days in Moderna documentation.Four CovidSIMVL parameters are varied in the course of 75 simulated clinical trials. Two relate directly to the vaccines and their impacts (duration between doses; degree of expected protection conferred by different vaccines following first or second dose). Two relate to the simulation contexts to which the vaccines are applied (degree of infectivity; duration of infectivity). The simulated trials demonstrate expected effects for timing of second dose, and for degree of protection associated with first and second dose of Pfizer and Moderna vaccines, and the effects are consistent with an assumed value of 75% for degree of protection after first and second doses for the Hybrid vaccine. However, the simulated trials suggest a more complex interaction between expected level of protection following first dose, timing of second dose and degree of infectivity. These results suggest that policy options should not be considered independent of the transmission dynamics that are manifested in the contexts in which the policies could be applied.CovidSIMVL embodies stochasticity in the mechanisms that govern viral transmission, and it treats the basic reproduction number (R0)as an emergent characteristic of transmission dynamics, not as a pre-set value that determines those dynamics. As such, results reported in this paper reflect outcomes that could happen, but do not necessarily reflect what is more or less likely to happen, given different configurations of parameters. The discussion section goes into some measure of detail regarding next steps that could be pursued to enhance the potential for agent-based models such as CovidSIMVL to inform exploration of possible vaccination policies, and to project outcomes that are possible or likely in local contexts, where stochasticity and heterogeneity of transmission must be featured in models that are intended to reflect local realism.

scholarly journals Two Distinct Dynamic Process Models of COVID-19 Spread with Divergent Vaccination Outcomes

2021 ◽  
Author(s):  
Ernie Chang ◽  
Kenneth Andrew Moselle
Keyword(s):  
Disease Modeling ◽  
Viral Transmission ◽  
Process Models ◽  
Mass Action ◽  
Causal Factors ◽  
Agent Based ◽  
Infection Dynamics ◽  
Kinematic Models ◽  
Spread Of Infection ◽  
Infectious Disease Modeling

Kinematic models of contagion-based viral transmission describe patterns of events over time (e.g., new infections), relying typically on systems of differential equations to reproduce those patterns. By contrast, agent-based models of viral transmission seek to relate those events or patterns of events to causes, expressed in terms of factors (parameters) that determine the dynamics that give rise to those events. This paper is concerned with the dynamics of contagion-based spread of infection. Dynamics that reflect time homogeneous vs inhomogeneous transmission rates are generated via an agent-based infectious disease modeling tool (CovidSIMVL - github.com/ecsendmail/MultiverseContagion). These different dynamics are treated as causal factors and are related to differences in vaccine efficacy in an array of simulated vaccination trials. Visualizations of simulated trials and associated metrics illustrate graphically some cogent reasons for not effectively hard-coding assumptions of dynamic temporal homogeneity, which come 'pre-packaged' with the mass action incidence assumption that underpins typical equation-based models of infection spread.

Investigating transmission dynamics of influenza in a public indoor venue: An agent-based modeling approach

2021 ◽  
Vol 157 ◽  
pp. 107327
Author(s):  
Yuan Zhou ◽  
Alexander Nikolaev ◽  
Ling Bian ◽  
Li Lin ◽  
Lin Li
Keyword(s):  
Agent Based Modeling ◽  
Transmission Dynamics ◽  
Agent Based ◽  
Modeling Approach

Enhancing measurement in health outcomes research supported by Agencies within the US Department of Health and Human Services

2007 ◽  
Vol 16 (S1) ◽  
pp. 175-186 ◽  
Author(s):  
Bryce B. Reeve ◽  
Laurie B. Burke ◽  
Yen-pin Chiang ◽  
Steven B. Clauser ◽  
Lisa J. Colpe ◽  
...  
Keyword(s):  
Health Outcomes ◽  
Outcomes Research ◽  
Human Services ◽  
Health And Human Services ◽  
Health Outcomes Research ◽  
Department Of Health ◽  
The Us

Should Blood Lead Screening Recommendations Be Revised?

PEDIATRICS ◽  
1994 ◽  
Vol 93 (2) ◽  
pp. 201-204
Author(s):  
Birt Harvey
Keyword(s):  
Universal Screening ◽  
Human Services ◽  
Blood Lead ◽  
Consensus Conference ◽  
National Institutes Of Health ◽  
Department Of Health ◽  
Area Of Interest ◽  
The Us ◽  
Control And Prevention ◽  
Blood Lead Screening

In October 1991, the Centers for Disease Control and Prevention (CDC) recommended blood lead (BPb) screening for virtually all 1-year-old children and, preferably, for all 2-year-old children as well.1 In April 1993, the US Department of Health and Human Services distributed guidelines recommending that all newborns, regardless of race or ethnicity, be screened for sickle cell anemia.2 In June 1993, the National Institutes of Health issued a consensus conference recommendation that all infants be tested for hearing impairment within the first 3 months of life, preferably before newborns leave the hospital.3 In each instance, these screening recommendations were developed because a group of experts, after identifying a child health problem within its area of interest, believed that universal screening was indicated.

Evidence-Based Patient Decontamination: An Integral Component of Mass Exposure Chemical Incident Planning and Response

2014 ◽  
Vol 8 (3) ◽  
pp. 260-266 ◽  
Author(s):  
Adam D. Leary ◽  
Michael D. Schwartz ◽  
Mark A. Kirk ◽  
Joselito S. Ignacio ◽  
Elaine B. Wencil ◽  
...  
Keyword(s):  
Medical Treatment ◽  
Homeland Security ◽  
Multiple Time ◽  
Chemical Toxicity ◽  
Department Of Homeland Security ◽  
Department Of Health ◽  
The Us ◽  
Patient Health ◽  
Health Support ◽  
Health Demands

AbstractDecontaminating patients who have been exposed to hazardous chemicals can directly benefit the patients’ health by saving lives and reducing the severity of toxicity. While the importance of decontaminating patients to prevent the spread of contamination has long been recognized, its role in improving patient health outcomes has not been as widely appreciated. Acute chemical toxicity may manifest rapidly—often minutes to hours after exposure. Patient decontamination and emergency medical treatment must be initiated as early as possible to terminate further exposure and treat the effects of the dose already absorbed. In a mass exposure chemical incident, responders and receivers are faced with the challenges of determining the type of care that each patient needs (including medical treatment, decontamination, and behavioral health support), providing that care within the effective window of time, and protecting themselves from harm. The US Department of Health and Human Services and Department of Homeland Security have led the development of national planning guidance for mass patient decontamination in a chemical incident to help local communities meet these multiple, time-sensitive health demands. This report summarizes the science on which the guidance is based and the principles that form the core of the updated approach. (Disaster Med Public Health Preparedness. 2014;0:1–7)

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