scholarly journals Modeling the Transmission of the SARS-CoV-2 Delta Variant in a Partially Vaccinated Population

Viruses ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 158
Author(s):  
Ugo Avila-Ponce de León ◽  
Eric Avila-Vales ◽  
Kuanlin Huang
Keyword(s):  
Virus Transmission ◽  
Face Mask ◽  
Sensitivity Analyses ◽  
Contact Tracing ◽  
Behavioral Measures ◽  
Vaccination Rates ◽  
Gradual Loss ◽  
The Us ◽  
Induced Immunity ◽  
Different Levels

In a population with ongoing vaccination, the trajectory of a pandemic is determined by how the virus spreads in unvaccinated and vaccinated individuals that exhibit distinct transmission dynamics based on different levels of natural and vaccine-induced immunity. We developed a mathematical model that considers both subpopulations and immunity parameters, including vaccination rates, vaccine effectiveness, and a gradual loss of protection. The model forecasted the spread of the SARS-CoV-2 delta variant in the US under varied transmission and vaccination rates. We further obtained the control reproduction number and conducted sensitivity analyses to determine how each parameter may affect virus transmission. Although our model has several limitations, the number of infected individuals was shown to be a magnitude greater (~10×) in the unvaccinated subpopulation compared to the vaccinated subpopulation. Our results show that a combination of strengthening vaccine-induced immunity and preventative behavioral measures like face mask-wearing and contact tracing will likely be required to deaccelerate the spread of infectious SARS-CoV-2 variants.

scholarly journals Modeling the transmission of the SARS-CoV-2 delta variant in a partially vaccinated population

2021 ◽  
Author(s):  
Ugo Avila ◽  
Eric Avila ◽  
Kuan-lin Huang
Keyword(s):  
Reproduction Number ◽  
Virus Transmission ◽  
Transmission Dynamics ◽  
Sensitivity Analyses ◽  
Behavioral Measures ◽  
Vaccination Rates ◽  
Gradual Loss ◽  
The Us ◽  
Induced Immunity ◽  
Different Levels

In a population with ongoing vaccination, the trajectory of a pandemic is determined by how the virus spreads in unvaccinated and vaccinated individuals that exhibit distinct transmission dynamics based on different levels of natural and vaccine-induced immunity. We developed a mathematical model that considers both subpopulations and immunity parameters including vaccination rates, vaccine effectiveness, and a gradual loss of protection. The model forecasted the spread of the SARS-CoV-2 delta variant in the US under varied transmission and vaccination rates. We further obtained the control reproduction number and conducted sensitivity analyses to determine how each parameter may affect virus transmission. Our results show that a combination of strengthening vaccine-induced immunity and preventative behavioral measures will likely be required to deaccelerate the rise of infectious SARS-CoV-2 variants.

scholarly journals Vaccines alone are no silver bullets: a modeling study on the impact of efficient contact tracing on COVID-19 infection and transmission

2021 ◽  
Author(s):  
Dhesi Baha Raja ◽  
Nur Asheila Abdul Taib ◽  
Alvin Kuo Jing Teo ◽  
Vivek Jason Jayaraj ◽  
Choo-Yee Ting
Keyword(s):  
Public Health ◽  
Computer Simulation ◽  
In Silico ◽  
Vaccination Rate ◽  
Sensitivity Analyses ◽  
Contact Tracing ◽  
Vaccination Rates ◽  
Current Transmission ◽  
The Impact ◽  
Multiple Scenarios

AbstractBackgroundThe computer simulation presented in this study aimed to investigate the effect of contact tracing on COVID-19 transmission and infection in the context of rising vaccination rates.MethodsThis study proposed a deterministic SEIRV model with contact tracing and vaccination components. We initialized some parameters using the Malaysian COVID-19 data to inform the model. We defined contact tracing effectiveness as the proportion of contacts of a positive case that was successfully traced and vaccination rate as the proportion of daily doses administered per population in Malaysia. Sensitivity analyses on the untraced and infectious populations were conducted. The study presented in silico findings on multiple scenarios by varying the contact tracing effectiveness and daily vaccination rates.ResultsAt a vaccination rate of 1.4%, a contact tracing with the effectiveness of 70% could delay the peak of untraced asymptomatic cases by 17 days and reduce the highest number of daily cases by 70% compared with a 30% contact tracing effectiveness. A similar trend was observed for symptomatic cases when a similar experiment setting was used. We also performed sensitivity analyses by using different combinations of contact tracing effectiveness and vaccination rates. In all scenarios, the effect of contact tracing on COVID-19 incidence persisted for both asymptomatic and symptomatic cases.ConclusionDespite testing only on two public health and social measures (PHSMs), we observed the scenario with low contact tracing and increasing vaccination rates successfully mimicked the current transmission trend in Malaysia. Hence, while vaccines are progressively rolled out, efficient contact tracing must be rapidly implemented concurrently to reach, find, test, isolate, and support the affected populations to bring the pandemic under control.

A model to account for the consequences of host nutrition on the outcome of gastrointestinal parasitism in sheep: model evaluation

Parasitology ◽  
2007 ◽  
Vol 134 (9) ◽  
pp. 1279-1289 ◽  
Author(s):  
D. VAGENAS ◽  
S. C. BISHOP ◽  
I. KYRIAZAKIS
Keyword(s):  
Mathematical Model ◽  
Worm Burden ◽  
Management Strategies ◽  
Sensitivity Analyses ◽  
Sheep Model ◽  
Host Nutrition ◽  
Gastrointestinal Parasitism ◽  
Different Characteristics ◽  
Nutritional Strategies ◽  
Different Levels

SUMMARYThis paper describes sensitivity analyses and expectations obtained from a mathematical model developed to account for the effects of host nutrition on the consequences of gastrointestinal parasitism in sheep. The scenarios explored included different levels of parasitic challenge at different planes of nutrition, for hosts differing only in their characteristics for growth. The model was able to predict the consequences of host nutrition on the outcome of parasitism, in terms of worm burden, number of eggs excreted per gram faeces and animal performance. The model outputs predict that conclusions on the ability of hosts of different characteristics for growth to cope with parasitism (i.e. resistance) depend on the plane of nutrition. Furthermore, differences in the growth rate of sheep, on their own, are not sufficient to account for differences in the observed resistance of animals. The model forms the basis for evaluating the consequences of differing management strategies and environments, such as breeding for certain traits associated with resistance and nutritional strategies, on the consequences of gastrointestinal parasitism on sheep.

scholarly journals Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jonatan Almagor ◽  
Stefano Picascia
Keyword(s):  
High Rate ◽  
Contact Tracing ◽  
Agent Based Model ◽  
Agent Based ◽  
The Social ◽  
Behavioural Factors ◽  
The Impact ◽  
Different Levels ◽  
User Rate

AbstractA contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.

scholarly journals Examining the interplay between face mask usage, asymptomatic transmission, and social distancing on the spread of COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Adam Catching ◽  
Sara Capponi ◽  
Ming Te Yeh ◽  
Simone Bianco ◽  
Raul Andino
Keyword(s):  
Social Distance ◽  
Large Fraction ◽  
Real Life ◽  
Virus Transmission ◽  
Face Mask ◽  
Social Distancing ◽  
Viral Spread ◽  
The Face ◽  
Asymptomatic Individuals ◽  
High Virus

AbstractCOVID-19’s high virus transmission rates have caused a pandemic that is exacerbated by the high rates of asymptomatic and presymptomatic infections. These factors suggest that face masks and social distance could be paramount in containing the pandemic. We examined the efficacy of each measure and the combination of both measures using an agent-based model within a closed space that approximated real-life interactions. By explicitly considering different fractions of asymptomatic individuals, as well as a realistic hypothesis of face masks protection during inhaling and exhaling, our simulations demonstrate that a synergistic use of face masks and social distancing is the most effective intervention to curb the infection spread. To control the pandemic, our models suggest that high adherence to social distance is necessary to curb the spread of the disease, and that wearing face masks provides optimal protection even if only a small portion of the population comply with social distance. Finally, the face mask effectiveness in curbing the viral spread is not reduced if a large fraction of population is asymptomatic. Our findings have important implications for policies that dictate the reopening of social gatherings.

scholarly journals COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society

2021 ◽  
pp. 0272989X2110030
Author(s):  
Serin Lee ◽  
Zelda B. Zabinsky ◽  
Judith N. Wasserheit ◽  
Stephen M. Kofsky ◽  
Shan Liu
Keyword(s):  
Large City ◽  
Face Mask ◽  
School Closure ◽  
Contact Tracing ◽  
The Novel ◽  
Agent Based ◽  
Social Distancing ◽  
Variable Compliance ◽  
Novel Coronavirus ◽  
Nonpharmaceutical Interventions

As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.

scholarly journals Public health impact of delaying second dose of BNT162b2 or mRNA-1273 covid-19 vaccine: simulation agent based modeling study

BMJ ◽  
2021 ◽  
pp. n1087
Author(s):  
Santiago Romero-Brufau ◽  
Ayush Chopra ◽  
Alex J Ryu ◽  
Esma Gel ◽  
Ramesh Raskar ◽  
...  
Keyword(s):  
Hospital Admissions ◽  
Vaccination Strategy ◽  
Population Based ◽  
Agent Based Modeling ◽  
Sensitivity Analyses ◽  
Agent Based ◽  
Cumulative Mortality ◽  
Vaccination Rates ◽  
Dose Strategy ◽  
Modeling Study

AbstractObjectiveTo estimate population health outcomes with delayed second dose versus standard schedule of SARS-CoV-2 mRNA vaccination.DesignSimulation agent based modeling study.SettingSimulated population based on real world US county.ParticipantsThe simulation included 100 000 agents, with a representative distribution of demographics and occupations. Networks of contacts were established to simulate potentially infectious interactions though occupation, household, and random interactions.InterventionsSimulation of standard covid-19 vaccination versus delayed second dose vaccination prioritizing the first dose. The simulation runs were replicated 10 times. Sensitivity analyses included first dose vaccine efficacy of 50%, 60%, 70%, 80%, and 90% after day 12 post-vaccination; vaccination rate of 0.1%, 0.3%, and 1% of population per day; assuming the vaccine prevents only symptoms but not asymptomatic spread (that is, non-sterilizing vaccine); and an alternative vaccination strategy that implements delayed second dose for people under 65 years of age, but not until all those above this age have been vaccinated.Main outcome measuresCumulative covid-19 mortality, cumulative SARS-CoV-2 infections, and cumulative hospital admissions due to covid-19 over 180 days.ResultsOver all simulation replications, the median cumulative mortality per 100 000 for standard dosing versus delayed second dose was 226 v 179, 233 v 207, and 235 v 236 for 90%, 80%, and 70% first dose efficacy, respectively. The delayed second dose strategy was optimal for vaccine efficacies at or above 80% and vaccination rates at or below 0.3% of the population per day, under both sterilizing and non-sterilizing vaccine assumptions, resulting in absolute cumulative mortality reductions between 26 and 47 per 100 000. The delayed second dose strategy for people under 65 performed consistently well under all vaccination rates tested.ConclusionsA delayed second dose vaccination strategy, at least for people aged under 65, could result in reduced cumulative mortality under certain conditions.

Data-driven inferences of agency-level risk and response communication on COVID-19 through social media-based interactions

2021 ◽  
Vol 19 (7) ◽  
pp. 59-82
Author(s):  
Md Ashraf Ahmed, PhD Candidate ◽  
Arif Mohaimin Sadri, PhD ◽  
M. Hadi Amini, PhD, DEng
Keyword(s):  
Public Health ◽  
Social Media ◽  
Information Dissemination ◽  
Topic Model ◽  
Face Mask ◽  
Community Response ◽  
Machine Learning Algorithms ◽  
Data Driven ◽  
Contact Tracing ◽  
Online Social Media

Risk perception and risk averting behaviors of public agencies in the emergence and spread of COVID-19 can be retrieved through online social media (Twitter), and such interactions can be echoed in other information outlets. This study collected time-sensitive online social media data and analyzed patterns of health risk communication of public health and emergency agencies in the emergence and spread of novel coronavirus using data-driven methods. The major focus is toward understanding how policy-making agencies communicate risk and response information through social media during a pandemic and influence community response—ie, timing of lockdown, timing of reopening, etc.—and disease outbreak indicators—ie, number of confirmed cases and number of deaths. Twitter data of six major public organizations (1,000-4,500 tweets per organization) are collected from February 21, 2020 to June 6, 2020. Several machine learning algorithms, including dynamic topic model and sentiment analysis, are applied over time to identify the topic dynamics over the specific timeline of the pandemic. Organizations emphasized on various topics—eg, importance of wearing face mask, home quarantine, understanding the symptoms, social distancing and contact tracing, emerging community transmission, lack of personal protective equipment, COVID-19 testing and medical supplies, effect of tobacco, pandemic stress management, increasing hospitalization rate, upcoming hurricane season, use of convalescent plasma for COVID-19 treatment, maintaining hygiene, and the role of healthcare podcast in different timeline. The findings can benefit emergency management, policymakers, and public health agencies to identify targeted information dissemination policies for public with diverse needs based on how local, federal, and international agencies reacted to COVID-19.

Theorising anti-racism in health and social care

2021 ◽  
Author(s):  
Esme Choonara
Keyword(s):  
White Supremacy ◽  
Social Care ◽  
Black Lives Matter ◽  
Health And Social Care ◽  
The Us ◽  
Per Se ◽  
The Uk ◽  
Different Levels

The emergence of the Black Lives Matter movement in 2020 in the context of a COVID-19 pandemic that was already disproportionally impacting on the lives of people from black, Asian and other minority ethnicities in the UK and the US has provoked scrutiny of how racism impacts on all areas of our lives. This article will examine some competing theories of racism, and ask what theoretical tools we need to successfully confront racism in health and social care. In particular, it will scrutinise the different levels at which racism operates – individual, institutional and structural – and ask how these are related. Furthermore, it will argue against theories that see racism as a product of whiteness per se or ‘white supremacy’, insisting instead that racism should be understood as firmly bound to the functioning and perpetuation of capitalism.

scholarly journals Evaluating the effectiveness of social distancing interventions against COVID-19

2020 ◽  
Author(s):  
Laura Matrajt ◽  
Tiffany Leung
Keyword(s):  
Mathematical Model ◽  
Contact Tracing ◽  
Old Adults ◽  
Social Distancing ◽  
The Us

AbstractSARS-CoV-2 has infected over 140,000 people as of March 14, 2020. We use a mathematical model to investigate the effectiveness of social distancing interventions lasting six weeks in a middle-sized city in the US. We explore four social distancing strategies by reducing the contacts of adults over 60 years old, adults over 60 years old and children, all adults (25, 75 or 95% compliance), and everyone in the population. Our results suggest that social distancing interventions can avert cases by 20% and hospitalizations and deaths by 90% even with modest compliance within adults as long as the intervention is kept in place, but the epidemic is set to rebound once the intervention is lifted. Our models suggest that social distancing interventions will buy crucial time but need to occur in conjunction with testing and contact tracing of all suspected cases to mitigate transmission of SARS-CoV-2.

Sign in / Sign up

Export Citation Format

Share Document