scholarly journals Rapid Impact Analysis of B 1.1.7 Variant on the Spread of SARS-CoV-2 in North Carolina

2021 ◽  
Author(s):  
Michael DeWitt
Keyword(s):  
North Carolina ◽  
Impact Analysis ◽  
Reproduction Number ◽  
Population Level ◽  
Vaccination Rate ◽  
Vaccination Rates ◽  
Current Vaccine ◽  
Spread Of Infection ◽  
The Impact ◽  
Pharmaceutical Interventions

AbstractBackgroundSeveral cases of the B1.1.7 variant of the SARS-CoV-2 virus were identified in North Carolina first on January 23, 2021 in Mecklenburg County and later in Guilford County on January 28, 2021.[1,2] This variant has been associated with higher levels of transmissibility.[3–6] This study examines the potential impact of increased transmissibility as the B1.1.7 variant becomes more predominant given current vaccine distribution plans and existing non-pharmaceutical interventions (NPIs).MethodWe explored the anticipated impact on the effective reproduction number for North Carolina and Guilford County given the date of import of B1.1.7. The approximate growth rate in proportion of B1.1.7 observed in the United Kingdom was fit and used to establish the estimate share of B1.1.7 circulating in North Carolina. Using the nowcasted reproduction numbers, a stochastic discrete compartmental model was fit with the current vaccination rates and B1.1.7 transmissibility to estimate the impact on the effective reproduction number.ResultsWe found that the effective reproduction number for North Carolina and Guilford County may exceed one, indicating a return to accelerating spread of infection in April as the proportion of B1.1.7 increases. The effective reproduction number will likely decrease into March, then increase as the proportion of B1.1.7 increases in circulation in the population.ConclusionsExisting non-pharmaceutical interventions will need to remain in effect through the spring. Given the current vaccination rate and these interventions, it is likely that there will be an increase in SARS-CoV-2 infections. The impact of the variant will likely be heterogeneous across North Carolina given the reproduction number and volume of susceptible persons in each county at the time of introduction of the variant. Age-based vaccinations will likely reduce the overall impact on hospitalizations. This analysis underlines the need for population level genetic surveillance to confirm the proportion of variants circulating.

scholarly journals The effects of non-pharmaceutical interventions on SARS-CoV-2 transmission in different socioeconomic populations in Kuwait: A modelling study

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Fatima Khadadah ◽  
Abdullah A. Al-Shammari ◽  
Ahmad Alhashemi ◽  
Dari Alhuwail ◽  
Bader Al-Saif ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Reproduction Number ◽  
Public Health Intervention ◽  
Population Level ◽  
Socioeconomic Groups ◽  
Before And After ◽  
Cross Transmission ◽  
Community Transmission ◽  
The Impact ◽  
Pharmaceutical Interventions

Background: Aggressive non-pharmaceutical interventions (NPIs) may reduce transmission of SARS-CoV2. The extent to which these interventions are successful in stopping the spread have not been characterized in countries with distinct socioeconomic groups. We compared the effects of a partial lockdown on disease transmission among Kuwaitis (P1) and non-Kuwaitis (P2) living in Kuwait. Methods: We fit a metapopulation Susceptible-Exposed-Infectious-Recovered (SEIR) model to reported cases stratified by two groups to estimate the impact of a lockdown on the effective reproduction number (Re). We estimated the basic reproduction number (R0) for the transmission in each group and simulated the potential trajectories of an outbreak from the first recorded case of community transmission until 12 days after the lockdown. We estimated R­e values of both groups before and after the lockdown, simulated the effect of these values on epidemic curves and explored a range of cross-transmission scenarios. Results: We estimate R0 at 1·06 (95% CI: 1·05-1·28) for P1 and 1·83 (1·58-2·33) for P2. On March 22nd, Re for P1 and P2 are estimated at 1·13 (1·07-1·17) and 1·38 (1·25-1·63) respectively. After the curfew had taken effect, Re for P1 dropped modestly to 1·04 (1·02-1·06) but almost doubled for P2 to 2·47 (1·98-3·45). Our simulated epidemic trajectories show that the partial curfew measure modestly reduced and delayed the height of the peak in P1, yet significantly elevated and hastened the peak in P2. Modest cross-transmission from P2 to P1 elevated the height of the peak in P1 and brought it forward in time closer to the peak of P2.    Conclusion: Our results demonstrate that a lockdown can reduce SARS-CoV2 transmission in one subpopulation but accelerate it in another. At the population level, the consequences of lockdowns may vary across the socioeconomic spectrum. Any public health intervention needs to be sensitive to disparities within populations.

scholarly journals Synergetic measures needed to control infection waves and contain SARS-CoV-2 transmission

2021 ◽  
Author(s):  
Hang Su ◽  
Yafang Cheng ◽  
Ulrich Poeschl
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Scientific Discourse ◽  
Protective Measure ◽  
Protective Measures ◽  
Vaccination Rates ◽  
The Public ◽  
Individual Measure ◽  
The Impact ◽  
Pharmaceutical Interventions

The public and scientific discourse on how to mitigate the COVID-19 pandemic is often focused on the impact of individual protective measures, in particular on immunization by vaccination. In view of changing virus variants and conditions, however, it seems not clear if vaccination or any other single protective measure alone may suffice to contain the transmission of SARS-CoV-2. Here, we investigate the effectiveness and synergies of vaccination and different non-pharmaceutical interventions such as universal masking (surgical, N95/FFP2), distancing & ventilation, contact reduction, and testing & isolation as a function of compliance in the population. We find that it would be difficult to contain SARS-CoV-2 transmission by any individual measure as currently available under realistic conditions. Instead, we show how multiple synergetic measures can be and have to be combined to decrease and keep the effective reproduction number (Re) below unity, even for virus variants with increased basic reproduction number (R0). We suggest that the presented approach and results can be used to design and communicate efficient strategies for mitigating the COVID-19 pandemic, depending on R0 as well as the efficacy and compliance achieved with each protective measure. At vaccination rates around 70%, the combination and synergies of universal masking, distancing & ventilation, and testing & isolation with moderate compliances around 30% appear well suited to keep Re below 1 and prevent or suppress infection waves. Higher compliance or additional measures like contact reductions (confinement/lockdown) are required to effectively and swiftly break intense waves of infection. For schools, we find that the transmission of SARS-CoV-2 can be contained by 2-3 tests per week combined with distancing & ventilation and masking.

scholarly journals Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e043010
Author(s):  
Jane Lyons ◽  
Ashley Akbari ◽  
Fatemeh Torabi ◽  
Gareth I Davies ◽  
Laura North ◽  
...  
Keyword(s):  
Policy Development ◽  
Healthcare Utilisation ◽  
Population Data ◽  
Population Level ◽  
Risk Groups ◽  
Service Utilisation ◽  
Natural Experiments ◽  
Spread Of Infection ◽  
The Impact

IntroductionThe emergence of the novel respiratory SARS-CoV-2 and subsequent COVID-19 pandemic have required rapid assimilation of population-level data to understand and control the spread of infection in the general and vulnerable populations. Rapid analyses are needed to inform policy development and target interventions to at-risk groups to prevent serious health outcomes. We aim to provide an accessible research platform to determine demographic, socioeconomic and clinical risk factors for infection, morbidity and mortality of COVID-19, to measure the impact of COVID-19 on healthcare utilisation and long-term health, and to enable the evaluation of natural experiments of policy interventions.Methods and analysisTwo privacy-protecting population-level cohorts have been created and derived from multisourced demographic and healthcare data. The C20 cohort consists of 3.2 million people in Wales on the 1 January 2020 with follow-up until 31 May 2020. The complete cohort dataset will be updated monthly with some individual datasets available daily. The C16 cohort consists of 3 million people in Wales on the 1 January 2016 with follow-up to 31 December 2019. C16 is designed as a counterfactual cohort to provide contextual comparative population data on disease, health service utilisation and mortality. Study outcomes will: (a) characterise the epidemiology of COVID-19, (b) assess socioeconomic and demographic influences on infection and outcomes, (c) measure the impact of COVID-19 on short -term and longer-term population outcomes and (d) undertake studies on the transmission and spatial spread of infection.Ethics and disseminationThe Secure Anonymised Information Linkage-independent Information Governance Review Panel has approved this study. The study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.

scholarly journals The Effect of Vaccination Rates on the Infection of COVID-19 under the Vaccination Rate below the Herd Immunity Threshold

2021 ◽  
Vol 18 (14) ◽  
pp. 7491
Author(s):  
Yi-Tui Chen
Keyword(s):  
Infection Rate ◽  
Herd Immunity ◽  
The United States ◽  
Vaccination Rate ◽  
Infection Rates ◽  
Vaccination Rates ◽  
The United Kingdom ◽  
The World ◽  
Almost All ◽  
The Impact

Although vaccination is carried out worldwide, the vaccination rate varies greatly. As of 24 May 2021, in some countries, the proportion of the population fully vaccinated against COVID-19 has exceeded 50%, but in many countries, this proportion is still very low, less than 1%. This article aims to explore the impact of vaccination on the spread of the COVID-19 pandemic. As the herd immunity of almost all countries in the world has not been reached, several countries were selected as sample cases by employing the following criteria: more than 60 vaccine doses per 100 people and a population of more than one million people. In the end, a total of eight countries/regions were selected, including Israel, the UAE, Chile, the United Kingdom, the United States, Hungary, and Qatar. The results find that vaccination has a major impact on reducing infection rates in all countries. However, the infection rate after vaccination showed two trends. One is an inverted U-shaped trend, and the other is an L-shaped trend. For those countries with an inverted U-shaped trend, the infection rate begins to decline when the vaccination rate reaches 1.46–50.91 doses per 100 people.

scholarly journals The effects of non-pharmaceutical interventions on SARS-CoV-2 transmission in different socioeconomic populations in Kuwait: a modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fatima Khadadah ◽  
Abdullah A. Al-Shammari ◽  
Ahmad Alhashemi ◽  
Dari Alhuwail ◽  
Bader Al-Saif ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Reproduction Number ◽  
Transmission Model ◽  
Socioeconomic Groups ◽  
Before And After ◽  
Cross Transmission ◽  
Community Transmission ◽  
The Impact ◽  
Pharmaceutical Interventions ◽  
The Basic Reproduction Number

Abstract Background Aggressive non-pharmaceutical interventions (NPIs) may reduce transmission of SARS-CoV-2. The extent to which these interventions are successful in stopping the spread have not been characterized in countries with distinct socioeconomic groups. We compared the effects of a partial lockdown on disease transmission among Kuwaitis (P1) and non-Kuwaitis (P2) living in Kuwait. Methods We fit a modified metapopulation SEIR transmission model to reported cases stratified by two groups to estimate the impact of a partial lockdown on the effective reproduction number ($$ {\mathcal{R}}_e $$ R e ). We estimated the basic reproduction number ($$ {\mathcal{R}}_0 $$ R 0 ) for the transmission in each group and simulated the potential trajectories of an outbreak from the first recorded case of community transmission until 12 days after the partial lockdown. We estimated $$ {\mathcal{R}}_e $$ R e values of both groups before and after the partial curfew, simulated the effect of these values on the epidemic curves and explored a range of cross-transmission scenarios. Results We estimate $$ {\mathcal{R}}_e $$ R e at 1·08 (95% CI: 1·00–1·26) for P1 and 2·36 (2·03–2·71) for P2. On March 22nd, $$ {\mathcal{R}}_e $$ R e for P1 and P2 are estimated at 1·19 (1·04–1·34) and 1·75 (1·26–2·11) respectively. After the partial curfew had taken effect, $$ {\mathcal{R}}_e $$ R e for P1 dropped modestly to 1·05 (0·82–1·26) but almost doubled for P2 to 2·89 (2·30–3·70). Our simulated epidemic trajectories show that the partial curfew measure greatly reduced and delayed the height of the peak in P1, yet significantly elevated and hastened the peak in P2. Modest cross-transmission between P1 and P2 greatly elevated the height of the peak in P1 and brought it forward in time closer to the peak of P2. Conclusion Our results indicate and quantify how the same lockdown intervention can accentuate disease transmission in some subpopulations while potentially controlling it in others. Any such control may further become compromised in the presence of cross-transmission between subpopulations. Future interventions and policies need to be sensitive to socioeconomic and health disparities.

scholarly journals Simulating the impact of vaccination rates on the initial stages of a COVID-19 outbreak in New Zealand (Aotearoa) with a stochastic model

2021 ◽  
Author(s):  
Leighton M Watson
Keyword(s):  
New Zealand ◽  
Stochastic Model ◽  
Process Model ◽  
Branching Process ◽  
Total Population ◽  
Median Number ◽  
Vaccination Rate ◽  
Vaccination Rates ◽  
The Impact ◽  
Different Levels

Aim: The August 2021 COVID-19 outbreak in Auckland has caused the New Zealand government to transition from an elimination strategy to suppression, which relies heavily on high vaccination rates in the population. As restrictions are eased and as COVID-19 leaks through the Auckland boundary, there is a need to understand how different levels of vaccination will impact the initial stages of COVID-19 outbreaks that are seeded around the country. Method: A stochastic branching process model is used to simulate the initial spread of a COVID-19 outbreak for different vaccination rates. Results: High vaccination rates are effective at minimizing the number of infections and hospitalizations. Increasing vaccination rates from 20% (approximate value at the start of the August 2021 outbreak) to 80% (approximate proposed target) of the total population can reduce the median number of infections that occur within the first four weeks of an outbreak from 1011 to 14 (25th and 75th quantiles of 545-1602 and 2-32 for V=20% and V=80%, respectively). As the vaccination rate increases, the number of breakthrough infections (infections in fully vaccinated individuals) and hospitalizations of vaccinated individuals increases. Unvaccinated individuals, however, are 3.3x more likely to be infected with COVID-19 and 25x more likely to be hospitalized. Conclusion: This work demonstrates the importance of vaccination in protecting individuals from COVID-19, preventing high caseloads, and minimizing the number of hospitalizations and hence limiting the pressure on the healthcare system.

scholarly journals The Public Health Impact of Delaying a Second Dose of the BNT162b2 or mRNA-1273 COVID-19 Vaccine

2021 ◽  
Author(s):  
Santiago Romero-Brufau ◽  
Ayush Chopra ◽  
Alex J Ryu ◽  
Esma Gel ◽  
Ramesh Raskar ◽  
...  
Keyword(s):  
Vaccination Strategy ◽  
Population Level ◽  
Health Impact ◽  
Vaccination Rate ◽  
Agent Based Modeling ◽  
Sensitivity Analyses ◽  
Agent Based ◽  
Cumulative Mortality ◽  
Vaccination Rates ◽  
The Public

AbstractObjectivesTo estimate population health outcomes under delayedsecond dose versus standard schedule SARS-CoV-2 mRNA vaccination.DesignAgent-based modeling on a simulated population of 100,000 based on a real-world US county. The simulation runs were replicated 10 times. To test the robustness of these findings, simulations were performed under different estimates for single-dose efficacy and vaccine administration rates, and under the possibility that a vaccine prevents only symptoms but not asymptomatic spread.Settingpopulation level simulation.Participants100,000 agents are included in the simulation, with a representative distribution of demographics and occupations. Networks of contacts are established to simulate potentially infectious interactions though occupation, household, and random interactionsInterventionswe simulate standard Covid-19 vaccination, versus delayed-second-dose vaccination prioritizing first dose. Sensitivity analyses include first-dose vaccine efficacy of 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; and an alternative vaccination strategy that implements delayed-second-dose only for those under 65 years of age.Main outcome measurescumulative Covid-19 mortality over 180 days, cumulative infections and hospitalizations.ResultsOver all simulation replications, the median cumulative mortality per 100,000 for standard versus delayed second dose was 226 vs 179; 233 vs 207; and 235 vs 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% population per day, both under sterilizing and non-sterilizing vaccine assumptions, resulting in absolute cumulative mortality reductions between 26 and 47 per 100,000. The delayed-second-dose for those under 65 performed consistently well under all vaccination rates tested.ConclusionsA delayed-second-dose vaccination strategy, at least for those under 65, could result in reduced cumulative mortality under certain conditions.

scholarly journals Modeling-Based Estimate of the Vaccination Rate, Lockdown Rules and COVID-19

Healthcare ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1245
Author(s):  
Chinlin Guo ◽  
Wei-Chiao Chang
Keyword(s):  
Critical Factor ◽  
Economic Loss ◽  
Vaccination Rate ◽  
Slight Reduction ◽  
High Morbidity ◽  
Vaccination Rates ◽  
Significant Difference ◽  
Simulation Scenario ◽  
Set Up ◽  
Spread Of Infection

COVID-19 has become a severe infectious disease and has caused high morbidity and mortality worldwide. Restriction rules such as quarantine and city lockdown have been implemented to mitigate the spread of infection, leading to significant economic impacts. Fortunately, development and inoculation of COVID-19 vaccines are being conducted on an unprecedented scale. The effectiveness of vaccines raises a hope that city lockdown might not be necessary in the presence of ongoing vaccination, thereby minimizing economic loss. The question, however, is how fast and what type of vaccines should be inoculated to control the disease without limiting economic activity. Here, we set up a simulation scenario of COVID-19 outbreak in a modest city with a population of 2.5 million. The basic reproduction number (R0) was ranging from 1.0 to 5.5. Vaccination rates at 1000/day, 10,000/day and 100,000/day with two types of vaccine (effectiveness v = 51% and 89%) were given. The results indicated that R0 was a critical factor. Neither high vaccination rate (10,000 persons/day) nor high-end vaccine (v = 89%) could control the disease when the scenario was at R0 = 5.5. Unless an extremely high vaccination rate was given (>4% of the entire population/per day), no significant difference was found between two types of vaccine. With the population scaled to 25 million, the required vaccination rate was >1,000,000/day, a quite unrealistic number. Nevertheless, with a slight reduction of R0 from 5 to 3.5, a significant impact of vaccine inoculation on disease control was observed. Thus, our study raised the importance of estimating transmission dynamics of COVID-19 in a city before determining the subsequent policy.

Use Of A Mobile Cart Influenza Program For Vaccination Of Hospital Employees

2004 ◽  
Vol 25 (11) ◽  
pp. 918-922 ◽  
Author(s):  
Catherine Sartor ◽  
Herve Tissot-Dupont ◽  
Christine Zandotti ◽  
Francoise Martin ◽  
Pierre Roques ◽  
...  
Keyword(s):  
Influenza Vaccination ◽  
Vaccination Rate ◽  
Associate Professor ◽  
University Hospital ◽  
Vaccination Program ◽  
Vaccination Rates ◽  
Vaccination Acceptance ◽  
The Impact ◽  
Haenszel Test

AbstractObjective:Rates of annual influenza vaccination of healthcare workers (HCWs) remained low in our university hospital. This study was conducted to evaluate the impact of a mobile cart influenza vaccination program on HCW vaccination.Methods:From 2000 to 2002, the employee health service continued its annual influenza vaccination program and the mobile cart program was implemented throughout the institution. This program offered influenza vaccination to all employees directly on the units. Each employee completed a questionnaire. Vaccination rates were analyzed using the Mantel–Haenszel test.Results:The program proposed vaccination to 50% to 56% of the employees. Among the nonvaccinated employees, 52% to 53% agreed to be vaccinated. The compliance with vaccination varied from 61% to 77% among physicians and medical students and from 38% to 55% among nurses and other employees. Vaccination of the chief or associate professor of the unit was associated with a higher vaccination rate of the medical staff (P < .01). Altogether, the vaccination program led to an increase in influenza vaccination among employees from 6% in 1998 and 7% in 1999 before the mobile cart program to 32% in 2000, 35% in 2001, and 32% in 2002 (P < .001).Conclusions:The mobile cart program was associated with a significantly increased vaccination acceptance. Our study was able to identify HCW groups for which the mobile cart was effective and highlight the role of the unit head in its success.

scholarly journals The influence of a community intervention on influenza vaccination knowledge and behavior among diabetic patients

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Lili Tao ◽  
Ming Lu ◽  
Xiaoning Wang ◽  
Xiaoyan Han ◽  
Shuming Li ◽  
...  
Keyword(s):  
Influenza Vaccine ◽  
Influenza Vaccination ◽  
Community Intervention ◽  
Vaccination Rate ◽  
Control Group ◽  
Diabetic Patients ◽  
Vaccination Rates ◽  
Significant Difference ◽  
The Impact ◽  
Experimental Group

Abstract Background This study was conducted to evaluate the impact of a comprehensive community intervention on cognition and inoculation behaviors of diabetic patients immunized with influenza vaccine. Methods A total of 1538 diabetic patients aged 35 years and above for outpatient visits and follow-up treatments were selected from six community health service centers (three for the experimental group, and the other three for the control group) in Chaoyang District, Beijing. Comprehensive interventions applied to the experimental group include patient intervention and community climate interventions. We compared the total awareness of influenza vaccine knowledge and influenza vaccination rates between the two groups before and after the intervention. Results Before the intervention, the total awareness rate of influenza vaccine in the experimental group and the control group was similar (50.6 and 50.2%, respectively. P = 0.171). After the intervention, the awareness rate of influenza vaccine in the experimental group and the control group increased. The amplitude of the increase was similar (70.3 and 70.1%, respectively. P = 0.822,). Before the intervention, there was no significant difference in the influenza vaccination rate between the experimental group and the control group (29.0 and 26.8%, respectively. P = 0.334). After the intervention, the vaccination rate of the experimental group was higher than that of the control group. The difference was statistically significant (The vaccination rate 45.8 and 27.4% for the experimental group and the control group, respectively. P < 0.001). Conclusion Comprehensive community interventions had a positive effect on vaccination in diabetic patients. Trial registration ChiCTR1900025194, registered in Aug,16th, 2019. Retrospectively registered.

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