scholarly journals Mechanistic model calibration and the dynamics of the COVID-19 epidemic in the UK (the past, the present and the future)

2021 ◽  
Author(s):  
Mark J Willis ◽  
Allen Wright ◽  
Victoria Bramfitt ◽  
Harry Conn ◽  
Robyn Talyor
Keyword(s):  
Reproduction Number ◽  
Mechanistic Model ◽  
National Level ◽  
Human Interaction ◽  
Vaccine Uptake ◽  
Model Parameters ◽  
Continuous Simulation ◽  
Vaccination Rates ◽  
The Uk ◽  
Case Data

We augment the well-known susceptible - infected - recovered - deceased (SIRD) epidemiological model to include vaccination dynamics, implemented as a piecewise continuous simulation. We calibrate this model to reported case data in the UK at a national level. Our modelling approach decouples the inherent characteristics of the infection from the degree of human interaction (as defined by the effective reproduction number, Re). This allows us to detect and infer a change in the characteristic of the infection, for example the emergence of the Kent variant, We find that that the infection rate constant (k) increases by around 89% as a result of the B.1.1.7 (Kent) COVID-19 variant in England. Through retrospective analysis and modelling of early epidemic case data (between March 2020 and May 2020) we estimate that ~1.2M COVID-19 infections were unreported in the early phase of the epidemic in the UK. We also obtain an estimate of the basic reproduction number as, R0=3.23. We use our model to assess the UK Government's roadmap for easing the third national lockdown as a result of the current vaccination programme. To do this we use our estimated model parameters and a future forecast of the daily vaccination rates of the next few months. Our modelling predicts an increased number of daily cases as NPIs are lifted in May and June 2021. We quantify this increase in terms of the vaccine rollout rate and in particular the percentage vaccine uptake rate of eligible individuals, and show that a reduced take up of vaccination by eligible adults may lead to a significant increase in new infections.

An evaluation of influenza vaccine uptake in UK medical students

2021 ◽  
Author(s):  
G Gray ◽  
J Cooper
Keyword(s):  
Medical Students ◽  
Influenza Vaccine ◽  
Medical School ◽  
Influenza Vaccination ◽  
Service Evaluation ◽  
Vaccination Status ◽  
Vaccine Uptake ◽  
Vaccination Rates ◽  
Increased Risk ◽  
The Uk

Abstract Background The annual influenza vaccination is recommended for all front-line healthcare workers in the UK and is a crucial way of reducing mortality for vulnerable patient groups. However, to date the UK government has never explicitly monitored influenza vaccine uptake in medical students. This is important to ascertain, as students regularly move between clinical areas and are both a perfect vector for the spread of influenza and at an increased risk of contracting influenza themselves. Aims This service evaluation was designed to evaluate the effectiveness of an influenza vaccination programme in one UK medical school and make recommendations to increase vaccination rates in the future. Methods This service evaluation collected data about medical student uptake of influenza vaccination in one UK medical school. Two hundred and fifty-one students at different course stages completed questionnaires, answering questions on vaccination status and Likert-scale ‘belief’ questions to assess the subjective reasons behind vaccine refusal. Results There was a substantial difference between year group cohorts (~20%), with significantly higher vaccination rates in the preclinical year group. Two significant negative predictors of vaccination were found (P < 0.001), related to scepticism over the effectiveness of the vaccine and lack of convenient access to the vaccination. Results indicated that integrating information about the influenza vaccine into the curriculum would reduce lack of knowledge over the efficacy of the vaccine. The centralization of vaccination programmes at mandatory university-based learning events would mitigate against the problem of diversity of vaccination locations and lack of central accountability. Conclusions The results of this service evaluation provide significant predictors of vaccination status for medical students and potential occupational health interventions to improve vaccine uptake in this group.

scholarly journals The Impact of COVID-19 Vaccination on California's Return to Normalcy

2021 ◽  
Author(s):  
Maria L Daza-Torres ◽  
Yury Elena Garcia Puerta ◽  
Alec J Schmidt ◽  
James L Sharpnack ◽  
Bradley H Pollock ◽  
...  
Keyword(s):  
Transmission Rate ◽  
Realistic Model ◽  
Vaccine Uptake ◽  
Model Parameters ◽  
Baseline Scenario ◽  
Effective Population ◽  
Vaccination Rates ◽  
Population Sizes ◽  
Incident Cases ◽  
The Impact

SARS-CoV-2 has infected nearly 3.7 million and killed 61,722 Californians, as of May 22, 2021. Non-pharmaceutical interventions have been instrumental in mitigating the spread of the coronavirus. However, as we ease restrictions, widespread implementation of COVID-19 vaccines is essential to prevent its resurgence. In this work, we addressed the adequacy and deficiency of vaccine uptake within California and the possibility and severity of resurgence of COVID-19 as restrictions are lifted given the current vaccination rates. We implemented a real-time Bayesian data assimilation approach to provide projections of incident cases and deaths in California following the reopening of its economy on June 15, 2021. We implemented scenarios that vary vaccine uptake prior to reopening, and transmission rates and effective population sizes following the reopening. For comparison purposes, we adopted a baseline scenario using the current vaccination rates, which projects a total 11,429 cases and 429 deaths in a 15-day period after reopening. We used posterior estimates based on CA historical data to provide realistic model parameters after reopening. When the transmission rate is increased after reopening, we projected an increase in cases by 21.8% and deaths by 4.4% above the baseline after reopening. When the effective population is increased after reopening, we observed an increase in cases by 51.8% and deaths by 12.3% above baseline. A 30% reduction in vaccine uptake alone has the potential to increase cases and deaths by 35% and 21.6%, respectively. Conversely, increasing vaccine uptake by 30% could decrease cases and deaths by 26.1% and 17.9%, respectively. As California unfolds its plan to reopen its economy on June 15, 2021, it is critical that social distancing and public behavior changes continue to be promoted, particularly in communities with low vaccine uptake. The Centers of Disease Control's (CDC) recommendation to ease mask-wearing for fully vaccinated individuals despite major inequities in vaccine uptake in counties across the state highlights some of the logistical challenges that society faces as we enthusiastically phase out of this pandemic.

scholarly journals 1422. Burden of Pertussis in South Korea: Implications for adults

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S718-S718
Author(s):  
Bruce Mungall ◽  
Hyungwoo Kim ◽  
Kyu-Bin Oh
Keyword(s):  
Literature Review ◽  
South Korea ◽  
National Level ◽  
Vaccine Uptake ◽  
Childhood Vaccination ◽  
Vaccine Preventable Diseases ◽  
Vaccination Rates ◽  
Antibody Levels ◽  
The Impact ◽  
Pertussis Epidemiology

Abstract Background There are a limited number of published studies on pertussis disease burden and epidemiology in South Korea, particularly those evaluating the impact in adults. Methods We conducted a systematic literature review on pertussis epidemiology and burden of disease in South Korea. The objective was to highlight evidence gaps which could help improve awareness about pertussis disease in adults in South Korea. Results Of 940 articles published between January 2000 to December 2019, 19 articles provided data for pertussis epidemiology and 9 provided data in adults. Laboratory confirmation rates in adults varied according to methodology, likely influenced by study/sampling variations. Three studies reported serological evidence of infection in adolescents and adults (33-57%). Among cases, the average cough duration was 16.5 days (range 7-30 days) and over 85% of cases presented with paroxysmal cough, while only 25% of cases or less presented with a characteristic whoop or post-tussive vomiting. Importantly, in 4 studies reporting vaccination status, almost all adult cases had no history of pertussis vaccination since childhood. Conclusion Primary childhood vaccination rates in South Korea are among the highest globally, while adult pertussis vaccine uptake appears to be quite low. Our literature review suggests that pertussis is underreported in adults, as evidenced by serology data demonstrating that tetanus antibody levels are low while pertussis toxin antibody levels are relatively high, suggesting continued circulation of community pertussis. These findings highlight the need for strategies such as maternal immunization and decennial revaccination of adults to address the changing epidemiology and waning immunity. Active pertussis testing/reporting and better utilization of adult vaccine registries is required to help provide robust data for vaccine decision-making at the national level. In the current COVID-19 environment, strategies that can reduce clinic or hospital visits will have substantial benefits to authorities managing rapid increases in health care resource utilization, and vaccine preventable diseases provide an easy and immediate target for achieving that goal. Disclosures Bruce Mungall, PhD, the GSK group of companies (Employee, Shareholder) Hyungwoo Kim, MD, MPH, the GSK group of companies (Employee) Kyu-Bin Oh, MD, the GSK group of companies (Employee, Shareholder)

scholarly journals Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Swapnil Mishra ◽  
James A. Scott ◽  
Daniel J. Laydon ◽  
Seth Flaxman ◽  
Axel Gandy ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Mechanistic Model ◽  
Total Mortality ◽  
Control Measures ◽  
Mortality Data ◽  
Time Varying ◽  
Per Capita ◽  
The Uk ◽  
The Impact ◽  
Counterfactual Approach

AbstractThe UK and Sweden have among the worst per-capita COVID-19 mortality in Europe. Sweden stands out for its greater reliance on voluntary, rather than mandatory, control measures. We explore how the timing and effectiveness of control measures in the UK, Sweden and Denmark shaped COVID-19 mortality in each country, using a counterfactual assessment: what would the impact have been, had each country adopted the others’ policies? Using a Bayesian semi-mechanistic model without prior assumptions on the mechanism or effectiveness of interventions, we estimate the time-varying reproduction number for the UK, Sweden and Denmark from daily mortality data. We use two approaches to evaluate counterfactuals which transpose the transmission profile from one country onto another, in each country’s first wave from 13th March (when stringent interventions began) until 1st July 2020. UK mortality would have approximately doubled had Swedish policy been adopted, while Swedish mortality would have more than halved had Sweden adopted UK or Danish strategies. Danish policies were most effective, although differences between the UK and Denmark were significant for one counterfactual approach only. Our analysis shows that small changes in the timing or effectiveness of interventions have disproportionately large effects on total mortality within a rapidly growing epidemic.

scholarly journals Application of SEIR Model in COVID-19 and The Effect of Lockdown on Reducing The Number of Active Cases

2020 ◽  
Vol 5 (2) ◽  
pp. 185-192
Author(s):  
Zulfan Adi Putra ◽  
Shahrul Azman Zainal Abidin
Keyword(s):  
Reproduction Number ◽  
Compartment Model ◽  
Daily Basis ◽  
Model Parameters ◽  
South East Asia ◽  
Actual Number ◽  
Seir Model ◽  
Sick People ◽  
Case Data ◽  
Very High

The spread of COVID-19 within a region in South East Asia has been modelled using a compartment model called SEIR (Susceptible, Exposed, Infected, Recovered). Actual number of sick people needing treatments, or the number active case data was used to obtain realistic values of the model parameters such as the reproduction number (R0), incubation, and recovery periods. It is shown that at the beginning of the pandemic where most people were still not aware, the R0 was very high as seen by the steep increase of people got infected and admitted to the hospitals. Few weeks after the lockdown of the region was in place and people were obeying the regulation and observing safe distancing, the R0 values dropped significantly and converged to a steady value of about 3. Using the obtained model parameters, fitted on a daily basis, the maximum number of active cases converged to a certain value of about 2500 cases. It is expected that in the early June 2020 that the number of active cases will drop to a significantly low level.

scholarly journals Assessing the effects of time-dependent restrictions and control actions to flatten the curve of COVID-19 in Kazakhstan

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10806
Author(s):  
Ton Duc Do ◽  
Meei Mei Gui ◽  
Kok Yew Ng
Keyword(s):  
Ad Hoc ◽  
Reproduction Number ◽  
National Level ◽  
Control Measures ◽  
Time Dependent ◽  
Transmission Dynamics ◽  
Model Parameters ◽  
Real World Data ◽  
Control Actions ◽  
And Control

This article presents the assessment of time-dependent national-level restrictions and control actions and their effects in fighting the COVID-19 pandemic. By analysing the transmission dynamics during the first wave of COVID-19 in the country, the effectiveness of the various levels of control actions taken to flatten the curve can be better quantified and understood. This in turn can help the relevant authorities to better plan for and control the subsequent waves of the pandemic. To achieve this, a deterministic population model for the pandemic is firstly developed to take into consideration the time-dependent characteristics of the model parameters, especially on the ever-evolving value of the reproduction number, which is one of the critical measures used to describe the transmission dynamics of this pandemic. The reproduction number alongside other key parameters of the model can then be estimated by fitting the model to real-world data using numerical optimisation techniques or by inducing ad-hoc control actions as recorded in the news platforms. In this article, the model is verified using a case study based on the data from the first wave of COVID-19 in the Republic of Kazakhstan. The model is fitted to provide estimates for two settings in simulations; time-invariant and time-varying (with bounded constraints) parameters. Finally, some forecasts are made using four scenarios with time-dependent control measures so as to determine which would reflect on the actual situations better.

scholarly journals A "Tail" of Two Cities: Fatality-based Modeling of COVID-19 Evolution in New York City and Cook County, IL

2020 ◽  
Author(s):  
Joshua Frieman
Keyword(s):  
New York ◽  
New York City ◽  
Reproduction Number ◽  
Social Contact ◽  
Cook County ◽  
Mitigation Measures ◽  
Model Parameters ◽  
Credible Intervals ◽  
Case Rate ◽  
Case Data

I describe SIR modeling of the COVID-19 pandemic in two U.S. urban environments, New York City (NYC) and Cook County, IL, from onset through mid-June, 2020. Since testing was not widespread early in the pandemic in the U.S., I rely on public fatality data to estimate model parameters and use case data only as a lower bound. Fits to the first 20 days of data determine a degenerate combination of the basic reproduction number, R0, and the mean time to removal from the infectious population, 1/γ with γ(R0 − 1) = 0.25(0.21) inverse days for NYC (Cook County). Equivalently, the initial doubling time was td = 2.8(3.4) days for NYC (Cook). The early fatality data suggest that both locations had infections in early February. I model the mitigation measures implemented in mid-March in both locations (distancing, quarantine, isolation, etc) via a time-dependent reproduction number Rt that declines monotonically from R0 to a smaller asymptotic value, R0(1-X), with a parameterized functional form. The timing (mid-March) and duration (several days) of the transitions in Rt appear well determined by the data. With flat priors on model parameters and the lower bound from reported cases, the NYC fatality data imply 95.45% credible intervals of R0 = 2.6 − 2.9, social contact reduction X = 69 − 76% and infection fatality rate f = 1 − 1.5%, with 19 − 27% of the population asymptotically infected. The case data relative to daily deaths suggest that the reported case rate as a fraction of true case rate grew linearly, reaching a plateau around April 20 for both NYC and Cook County; the models also suggest that the late-time NYC reported case rate was comparable to the true rate, while for Cook County it remained an underestimate. For Cook County, the fatality evolution was qualitatively different from NYC: after mitigation measures were implemented, daily fatality counts reached a plateau for about a month before tailing off. This is consistent with an SIR model that exhibits "critical slowing-down", in which Rt plateaus at a value just above unity. For Cook County, the 95.45% credible intervals for the model parameters are much broader and shifted downward, R0 = 1.4 − 4.7, X = 26 − 54%, and f = 0.1 − 0.6% with 15 − 88% of the population asymptotically infected. Despite the apparently lower efficacy of its social contact reduction measures, Cook County has had significantly fewer fatalities per population than NYC, D∞/N = 100 vs. 270 per 100,000. In the model, this is attributed to the lower inferred IFR for Cook; an external prior pointing to similar values of the IFR for the two locations would instead chalk up the difference in D/N to differences in the relative growth rate of the disease. I derive a model-dependent threshold, Xcrit, for "safe" re-opening, that is, for easing of contact reduction that would not trigger a second wave; for NYC, the models predict that increasing social contact by more than 20% from post-mitigation levels will lead to renewed spread, while for Cook County the threshold value is very uncertain, given the parameter degeneracies. The timing of 2nd-wave growth will depend on the amplitude of contact increase relative to Xcrit and on the asymptotic growth rate, and the impact in terms of fatalities will depend on the parameter f .

scholarly journals COVID-19 incidence and R decreased on the Isle of Wight after the launch of the Test, Trace, Isolate programme

2020 ◽  
Author(s):  
Michelle Kendall ◽  
Luke Milsom ◽  
Lucie Abeler-Dorner ◽  
Chris Wymant ◽  
Luca Ferretti ◽  
...  
Keyword(s):  
Control Method ◽  
Reproduction Number ◽  
National Level ◽  
Causal Link ◽  
Contact Tracing ◽  
Synthetic Control ◽  
Local Authorities ◽  
Isle Of Wight ◽  
Before And After ◽  
The Uk

In May 2020 the UK introduced a Test, Trace, Isolate programme in response to the COVID-19 pandemic. The programme was first rolled out on the Isle of Wight and included Version 1 of the NHS contact tracing app. We used COVID-19 daily case data to infer incidence of new infections and estimate the reproduction number R for each of 150 Upper Tier Local Authorities in England, and at the National level, before and after the launch of the programme on the Isle of Wight. We used Bayesian and Maximum-Likelihood methods to estimate R, and compared the Isle of Wight to other areas using a synthetic control method. We observed significant decreases in incidence and R on the Isle of Wight immediately after the launch. These results are robust across each of our approaches. Our results show that the sub-epidemic on the Isle of Wight was controlled significantly more effectively than the sub-epidemics of most other Upper Tier Local Authorities, changing from having the third highest reproduction number R (of 150) before the intervention to the tenth lowest afterwards. The data is not yet available to establish a causal link. However, the findings highlight the need for further research to determine the causes of this reduction, as these might translate into local and national non-pharmaceutical intervention strategies in the period before a treatment or vaccination becomes available.

scholarly journals Measuring the Impact of Exposure to COVID-19 Vaccine Misinformation on Vaccine Intent in the UK and US

2020 ◽  
Author(s):  
S. Loomba ◽  
A. de Figueiredo ◽  
S. J. Piatek ◽  
K. de Graaf ◽  
H. J. Larson
Keyword(s):  
Age Groups ◽  
Vaccine Uptake ◽  
Major Step ◽  
Vaccination Rates ◽  
The Us ◽  
Nationally Representative ◽  
The Uk ◽  
Vaccination Campaigns ◽  
The Impact ◽  
Intent To Vaccinate

The successful development and widespread acceptance of a SARS-CoV-2 vaccine will be a major step in fighting the pandemic, yet obtaining high uptake will be a challenging task, worsened by online misinformation. To help inform successful COVID-19 vaccination campaigns in the UK and US, we conducted a survey to quantify how online misinformation impacts COVID-19 vaccine uptake intent and identify socio-economic groups that are most at-risk of non-vaccination and most susceptible to online misinformation. Here, we report findings from nationally representative surveys in the UK and the US conducted in September 2020. We show that recent misinformation around a COVID-19 vaccine induces a fall in vaccination intent among those who would otherwise “definitely” vaccinate by 6.4 (3.8, 9.0) percentages points in the UK and 2.4 (0.1, 5.0) in the US, with larger decreases found in intent to vaccinate to protect others. We find evidence that socio-econo-demographic, political, and trust factors are associated with low intent to vaccinate and susceptibility to misinformation: notably, older age groups in the US are more susceptible to misinformation. We find evidence that scientific-sounding misinformation relating to COVID-19 and vaccines COVID-19 vaccine misinformation lowers vaccination intent, while corresponding factual information does not. These findings reveal how recent COVID-19 misinformation can impact vaccination rates and suggest pathways to robust messaging campaigns.

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