scholarly journals Dynamics of SARS-CoV-2 with waning immunity in the UK population

2021 ◽  
Vol 376 (1829) ◽  
pp. 20200274 ◽  
Author(s):  
Thomas Crellen ◽  
Li Pi ◽  
Emma L. Davis ◽  
Timothy M. Pollington ◽  
Tim C. D. Lucas ◽  
...  
Keyword(s):  
Deterministic Model ◽  
Herd Immunity ◽  
Secondary Wave ◽  
Daily Maximum ◽  
Case Scenario ◽  
Worst Case ◽  
Policy Makers ◽  
Contact Data ◽  
Age Structured ◽  
The Uk

The dynamics of immunity are crucial to understanding the long-term patterns of the SARS-CoV-2 pandemic. Several cases of reinfection with SARS-CoV-2 have been documented 48–142 days after the initial infection and immunity to seasonal circulating coronaviruses is estimated to be shorter than 1 year. Using an age-structured, deterministic model, we explore potential immunity dynamics using contact data from the UK population. In the scenario where immunity to SARS-CoV-2 lasts an average of three months for non-hospitalized individuals, a year for hospitalized individuals, and the effective reproduction number after lockdown ends is 1.2 (our worst-case scenario), we find that the secondary peak occurs in winter 2020 with a daily maximum of 387 000 infectious individuals and 125 000 daily new cases; threefold greater than in a scenario with permanent immunity. Our models suggest that longitudinal serological surveys to determine if immunity in the population is waning will be most informative when sampling takes place from the end of the lockdown in June until autumn 2020. After this period, the proportion of the population with antibodies to SARS-CoV-2 is expected to increase due to the secondary wave. Overall, our analysis presents considerations for policy makers on the longer-term dynamics of SARS-CoV-2 in the UK and suggests that strategies designed to achieve herd immunity may lead to repeated waves of infection as immunity to reinfection is not permanent. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.

scholarly journals Dynamics of SARS-CoV-2 with Waning Immunity in the UK Population

2020 ◽  
Author(s):  
Thomas Crellen ◽  
Li Pi ◽  
Emma Davis ◽  
Timothy M Pollington ◽  
Tim C D Lucas ◽  
...  
Keyword(s):  
Deterministic Model ◽  
Herd Immunity ◽  
Secondary Peak ◽  
Daily Maximum ◽  
Case Scenario ◽  
Worst Case ◽  
Antibody Titres ◽  
Contact Data ◽  
Age Structured ◽  
The Uk

The dynamics of immunity are crucial to understanding the long-term patterns of the SARS-CoV-2 pandemic. While the duration and strength of immunity to SARS-CoV-2 is currently unknown, specific antibody titres to related coronaviruses SARS-CoV and MERS-CoV have been shown to wane in recovered individuals, and immunity to seasonal circulating coronaviruses is estimated to be shorter than one year. Using an age-structured, deterministic model, we explore different potential immunity dynamics using contact data from the UK population. In the scenario where immunity to SARS-CoV-2 lasts an average of three months for non-hospitalised individuals, a year for hospitalised individuals, and the effective reproduction number (Rt) after lockdown is 1.2 (our worst case scenario), we find that the secondary peak occurs in winter 2020 with a daily maximum of 409,000 infectious individuals; almost three-fold greater than in a scenario with permanent immunity. Our models suggests that longitudinal serological surveys to determine if immunity in the population is waning will be most informative when sampling takes place from the end of the lockdown until autumn 2020. After this period, the proportion of the population with antibodies to SARS-CoV-2 is expected to increase due to the secondary peak. Overall, our analysis presents considerations for policy makers on the longer term dynamics of SARS-CoV-2 in the UK and suggests that strategies designed to achieve herd immunity may lead to repeated waves of infection if immunity to re-infection is not permanent.

scholarly journals A place in the sun? Healthcare rights of retired UK citizens in Spain post-Brexit

2017 ◽  
Vol 12 (3) ◽  
pp. 297-307 ◽  
Author(s):  
Joaquin Cayon-De Las Cuevas ◽  
Tamara Hervey
Keyword(s):  
Capacity Planning ◽  
European Economic Area ◽  
Gear Up ◽  
Case Scenario ◽  
Worst Case ◽  
Spanish Law ◽  
Legal Position ◽  
The Uk ◽  
Care Costs ◽  
Spanish Legislation

AbstractAt least 100,000 retired UK citizens currently live in Spain. Under EU law, they are entitled to access the Spanish National Health Service (NHS) with minimum administrative difficulty. What will their legal position be under a ‘no-deal Brexit’? This is a question of Spanish law. The worst case scenario is that they will have to reapply for their residence permits under the Spanish legislation applicable to non-EU/European Economic Area citizens, with all the administrative inconvenience and cost entailed. If they successfully reapply, their personal health care costs will be considerably higher than at present, should they choose to remain in Spain. Very obvious questions of capacity planning arise. The Spanish system will potentially need to gear up for a significant administrative effort. Given the distinct possibility of a ‘no-deal Brexit’, the UK NHS should prepare to welcome significant numbers of pensioners home.

Lithological controls on soil formation rates and the implications for soil sustainability

2020 ◽  
Author(s):  
Daniel Evans ◽  
John Quinton ◽  
Andrew Tye ◽  
Angel Rodes ◽  
Jessica Davies ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Soil Formation ◽  
Case Scenario ◽  
Worst Case ◽  
Radionuclide Analysis ◽  
Rock Types ◽  
Soil Sustainability ◽  
The Uk ◽  
The Impact ◽  
Cosmogenic Radionuclide

<p>Soils deliver multiple ecosystem services and their long-term sustainability is fundamentally determined by the rates at which they form and erode. Our knowledge and understanding of soil formation is not commensurate with that of soil erosion, but developments in cosmogenic radionuclide analysis have enabled soil scientists to more accurately constrain the rates at which soils form from bedrock. To date, all three major rock types – igneous, sedimentary and metamorphic lithologies – have been examined in such work. Soil formation rates have been measured and compared between these rock types but the impact of rock characteristics such as mineralogy or porosity on soil formation rates has seldom been explored. In this UK-based study, we addressed this knowledge gap by using cosmogenic radionuclide analysis to investigate whether the lithological variability of sandstone governs pedogenesis. Soil formation rates from two arable hillslopes underlain by different types of arenite sandstone were calculated. Rates ranged from 0.090 to 0.193 mm yr<sup>-1</sup> and although the sandstones differed in porosity, no significant differences in soil formation rates were found between them. On the contrary, these rates significantly differed from those measured at two other sandstone-based sites in the UK, and with the rates compiled in global inventory of cosmogenic studies on sandstone-based soils. We suggest that this is due to the absence of matrix and the greater porosities exhibited at our UK sites in comparison to the matrix-abundant, less porous wackes that have been studied previously. We then used soil formation rates to calculate first-order soil lifespans for both of our hillslopes. In a worst case scenario, the lifespan of the A horizon at one of our sites could be eroded in less than 40 years, with bedrock exposure occurring in less than 190 years.  This underlines the urgency required in ameliorating rates of soil erosion. However, we also demonstrate the importance of measuring soil erosion and formation in parallel, at the site of interest, rather than calculating a mean rate from the literature, as we demonstrate soil formation rates can vary significantly among variants of the same rock type.</p><p> </p>

scholarly journals Estimates of SARS-COV-2 Behavior in the COVID-19 Crisis: Addressing Sample-Selection Bias for Public Health Applications

2020 ◽  
Author(s):  
John Straka
Keyword(s):  
Selection Bias ◽  
Sample Selection ◽  
Herd Immunity ◽  
Model Specification ◽  
Sample Selection Bias ◽  
Case Scenario ◽  
Worst Case ◽  
Reproduction Ratio ◽  
Social Distancing ◽  
The U.S

This study surveys and assesses the implications from recent empirical studies and reports to highlight the characteristics of SARS-Cov-2 and the COVID-19 crisis, and then proposes a recursive bivariate probit (RBP) model specification and possible applications. The RBP model addresses sample selection bias to estimate key determinants of virus infection given nonrandom testing. Applicable to anonymized case-level or widely available local-area data in the U.S., multiple data sources are shown. With suitable data the model can control for observed (e.g. population density) and unobserved factors to estimate the marginal effects of varying state-prescribed measures and behavioral social distancing. Case-level scoring models may, in addition, eventually assist in clinical diagnostic assessments. Although not proposed to substitute for more random population testing and other methods, results could also be used in advance of more testing. Uncertain assumptions in epidemiological models reflect unclear effects from gradations of social distancing now occurring. Despite many calls for broader testing and targeted quarantining in the U.S., many practical obstacles remain, leaving unknowns, especially across local areas. Differing local transmission rates respond to stronger or weaker social distancing and quarantining. High risks from latent non-quarantining spread warn of potential overwhelming local outbreaks. The insidious nature of SARS-Cov-2 invites complacency, especially in non-hotspot areas. Complacent behaviors can fail to adequately address the public-goods problem, leading to various forms of continued local and macro COVID-19 waves and crises. To assess a worst case scenario, no model projection is needed, only the herd immunity threshold equation, estimates of the reproduction ratio, and the estimated mortality rate. With no ultimately successful countermeasures in treatment, vaccine, and non-pharmaceutical interventions (NPIs), the analysis here suggests an eventual number of deaths much like the 1918 pandemic in U.S. deaths per capita (1.8-2.7 million U.S. deaths) and in the total number of deaths worldwide (around 50 million). This toll also reflects a hypothetical global “surrender” strategy of business-as-usual and no social distancing, which in practice no nation has followed. Some successes across the three broad social countermeasure efforts – which appears most likely, in a mix of outcomes – can lessen the high social costs.

scholarly journals Flattening the curve is not enough, we need to squash it: An explainer using a simple model

2020 ◽  
Author(s):  
ES McBryde ◽  
MT Meehan ◽  
JM Trauer
Keyword(s):  
Deterministic Model ◽  
Reproduction Number ◽  
Herd Immunity ◽  
International Travel ◽  
Effective Control ◽  
Curve Versus ◽  
Successful Control ◽  
The Difference ◽  
The Uk ◽  
Local Transmission

AbstractBackgroundAround the world there are examples of both effective control (e.g., South Korea, Japan) and less successful control (e.g., Italy, Spain, United States) of COVID-19 with dramatic differences in the consequent epidemic curves. Models agree that flattening the curve without controlling the epidemic completely is insufficient and will lead to an overwhelmed health service. A recent model, calibrated for the UK and US, demonstrated this starkly.MethodsWe used a simple compartmental deterministic model of COVID-19 transmission in Australia, to illustrate the dynamics resulting from shifting or flattening the curve versus completely squashing it.ResultsWe find that when the reproduction number is close to one, a small decrease in transmission leads to a large reduction in burden (i.e., cases, deaths and hospitalisations), but achieving this early in the epidemic through social distancing interventions also implies that the community will not reach herd immunity.ConclusionsAustralia needs not just to shift and flatten the curve, but to squash it by getting the reproduction number below one. This will require Australia to achieve transmission rates at least two thirds lower than those seen in the most severely affected countries.The knownCOVID-19 has been diagnosed in over 4,000 Australians. Up until mid-March, most were from international travel, but now we are seeing a rise in locally acquired cases.The newThis study uses a simple transmission dynamic model to demonstrate the difference between moderate changes to the reproduction number and forcing the reproduction number below one.The implicationsLowering local transmission is becoming important in reducing the transmission of COVID-19. To maintain control of the epidemic, the focus should be on those in the community who do not regard themselves as at risk.

scholarly journals Cost/effectiveness model of dabigatran in the prevention of venous thromboembolism in major orthopedic surgery: Adaptation for Italy

2010 ◽  
Vol 11 (2) ◽  
pp. 91-101 ◽  
Author(s):  
Orietta Zaniolo ◽  
Sorrel E. Wolowacz ◽  
Lorenzo Pradelli
Keyword(s):  
Cost Effectiveness ◽  
Orthopedic Surgery ◽  
Case Scenario ◽  
Worst Case ◽  
Worst Case Scenario ◽  
Life Years ◽  
Major Orthopedic Surgery ◽  
Acquisition Costs ◽  
Alternative Scenarios ◽  
The Uk

Venous thromboembolic events (VTE) represent a dangerous complication of major orthopedic surgery, especially in total hip replacement (THR) and total knee replacement (TKR) procedures. Dabigatran etexilate (DBG), a direct and reversible thrombin inhibitor, has proven its non-inferiority with respect to enoxaparin 40mg once-daily, a low molecular weight heparin (LMWH), in the prevention of VTE in patients undergoing THR and TKR, in the RE-NOVATE and RE-MODEL trials, respectively. The objective of this analysis was to estimate cost/effectiveness and cost/utility of DBG compared to standard care for the prevention of VTE in Italy. A decision analytic, Markov-chain based model, originally developed for the UK, was adapted to the Italian context. The adaptation involved cost and demographic characteristics, clinical and utility data were not altered. Costs were taken from national observational studies, where available. Otherwise, current prices and tariffs were applied. Resource consumption was derived from practice guidelines or taken from the UK model. According to the prevalent national practice, extended prophylaxis is considered for both surgical procedures. The time horizon of the analysis was patients’ lifetimes. In order to consider different alternatives for drug dispensation and, consequently, National Health Service acquisition costs, alternative scenarios were developed. A further scenario, excluding LMWHs administration costs (“worst-case” scenario), was considered. Compared to LMWHs, DBG was associated with an expected increase of 0.019 life-years (LYs) and 0.014 quality-adjusted life-years (QALYs) per THR patient and of 0.024 LYs and 0.019 QALYs per TKR patient. DBG-related costs were lower than LMWH in both procedures, with a mean difference ranging from 89 to 116 € for THR, and 107 to 142 for TKR, depending on the LMWH product. Higher acquisition costs for DBG were completely offset and inverted by avoided administration expenses and, to a lesser extent, by savings in VTE management. The results of alternative scenarios confirm the dominance of DBG, with a net saving ranging between 119 €, when both drugs were obtained by auction, and 32 €, when the auction price was applied but DBG was dispensed through territorial pharmacies. The corresponding estimates for TKR were 148 and 54 €. In the “worst-case” scenario, DBG was no longer dominant, with a cost per LYs of 2,788 and 4,514 € and a cost per QALY gained of 3,619 and 5,926 €, for TKR and THR respectively. In conclusion, DBG dominated LMWHs, and was cost-saving and non-inferior in terms of efficacy and safety, except for in the “worst-case” scenario, in which the incremental cost/effectiveness ratio estimate was lower than commonly accepted thresholds in health economics.

Reverse Internationalization?

2019 ◽  
pp. 32-53 ◽  
Author(s):  
Keith John Lay
Keyword(s):  
Open System ◽  
Current System ◽  
Academic Staff ◽  
University Rankings ◽  
Case Scenario ◽  
International Faculty ◽  
Worst Case ◽  
System A ◽  
History Of ◽  
The Uk

This chapter first describes UK HE from a systems theory perspective through reflection on the history of UK HE and the current system in relation to the criteria that are used to assess and audit universities. The current position of UK HE within the larger global HE system is then considered through analysis of the latest university rankings lists. Having identified the key elements of the current UK HE system and highlighted the centrality of international academic staff within that system, the rhetoric in the academic and political discourse and the printed media is then focused upon in order to highlight the potential impact of Brexit on how UK HE performs as an open system. A best case/worst case scenario narrative follows, resulting in the recommendation of fast action from the UK government to safeguard the retention and hiring of international faculty, a key element in the enviable current open system that is UK HE.

scholarly journals Changing Primary Energy Consumption Due to COVID-19: The Study 20 European Economies

2020 ◽  
Author(s):  
Seyed Reza Mirnezami ◽  
Sajad Rajabi
Keyword(s):  
Energy Consumption ◽  
Supply And Demand ◽  
Primary Energy ◽  
Primary Energy Consumption ◽  
Case Scenario ◽  
Worst Case ◽  
Policy Makers ◽  
Worst Case Scenario ◽  
European Economies ◽  
Demand Patterns

Abstract With the outbreak of the coronavirus in countries around the world, governments have decided to impose restrictions and social distancing. Closures of businesses, and hence changes in supply and demand patterns during this period, have deepened concerns among policy makers. In this article, we investigate the change in primary energy consumption in the 20 European countries that have the highest GDP. To this end, 10 different shock scenarios and its limitations are considered. By implementing these shocks into input-output modelling, changes in primary energy consumption are calculated. The results show that according to the best scenario (rapid and complete economy restoration), Russia with 3.5% and Italy with 2.88% will have the largest decrease, and according to the worst case scenario (explosive exacerbation of disease and complete quarantine), Spain with 14% and Italy with 13% will have the largest reduction in energy consumption. In addition, considering the total changes in primary energy consumption of these 20 countries, according to the best scenario, it will decrease by 1.81% and according to the worst-case scenario, it will decrease by 10.46%. We discuss about possibilities that energy consumption permanently declines.

scholarly journals COVID-19: Forecasting short term hospital needs in France

2020 ◽  
Author(s):  
Clément Massonnaud ◽  
Jonathan Roux ◽  
Pascal Crépey
Keyword(s):  
Healthcare System ◽  
National Level ◽  
Metropolitan Region ◽  
Short Term ◽  
Case Scenario ◽  
Worst Case ◽  
Capacity Limits ◽  
Catchment Areas ◽  
Referral Hospitals ◽  
Age Structured

1AbstractEurope is now considered as the epicenter of the SARS-CoV-2 pandemic, France being among the most impacted country. In France, there is an increasing concern regarding the capacity of the healthcare system to sustain the outbreak, especially regarding intensive care units (ICU). The aim of this study was to estimate the dynamics of the epidemic in France, and to assess its impact on healthcare resources for each French metropolitan Region. We developed a deterministic, age-structured, Susceptible-Exposed-Infectious-Removed (SEIR) model based on catchment areas of each COVID-19 referral hospitals. We performed one month ahead predictions (up to April 14, 2020) for three different scenarios (R0 = 1.5, R0 = 2.25, R0 = 3), where we estimated the daily number of COVID-19 cases, hospitalizations and deaths, the needs in ICU beds per Region and the reaching date of ICU capacity limits. At the national level, the total number of infected cases is expected to range from 22,872 in the best case (R0 = 1.5) to 161,832 in the worst case (R0 = 3), while the total number of deaths would vary from 1,021 to 11,032, respectively. At the regional level, all ICU capacities may be overrun in the worst scenario. Only seven Regions may lack ICU beds in the mild scenario (R0 = 2.25) and only one in the best case. In the three scenarios, Corse may be the first Region to see its ICU capacities overrun. The two other Regions, whose capacity will be overrun shortly after are Grand-Est and Bourgogne-Franche-Comté. Our analysis shows that, even in the best case scenario, the French healthcare system will very soon be overwhelmed. While drastic social distancing measures may temper our results, a massive reorganization leading to an expansion of French ICU capacities seems to be necessary to manage the coming wave of critically affected COVID-19 patients.

scholarly journals Estimates of SARS-COV-2 Behavior in the COVID-19 Crisis: Addressing Sample-Selection Bias for Public Health Applications

2020 ◽  
Author(s):  
John Straka
Keyword(s):  
Selection Bias ◽  
Sample Selection ◽  
Herd Immunity ◽  
Model Specification ◽  
Sample Selection Bias ◽  
Case Scenario ◽  
Worst Case ◽  
Reproduction Ratio ◽  
Social Distancing ◽  
The U.S

This study surveys and assesses the implications from recent empirical studies and reports to highlight the characteristics of SARS-Cov-2 and the COVID-19 crisis, and then proposes a recursive bivariate probit (RBP) model specification and possible applications. The RBP model addresses sample selection bias to estimate key determinants of virus infection given nonrandom testing. Applicable to anonymized case-level or widely available local-area data in the U.S., multiple data sources are shown. With suitable data the model can control for observed (e.g. population density) and unobserved factors to estimate the marginal effects of varying state-prescribed measures and behavioral social distancing. Case-level scoring models may, in addition, eventually assist in clinical diagnostic assessments. Although not proposed to substitute for more random population testing and other methods, results could also be used in advance of more testing. Uncertain assumptions in epidemiological models reflect unclear effects from gradations of social distancing now occurring. Despite many calls for broader testing and targeted quarantining in the U.S., many practical obstacles remain, leaving unknowns, especially across local areas. Differing local transmission rates respond to stronger or weaker social distancing and quarantining. High risks from latent non-quarantining spread warn of potential overwhelming local outbreaks. The insidious nature of SARS-Cov-2 invites complacency, especially in non-hotspot areas. Complacent behaviors can fail to adequately address the public-goods problem, leading to various forms of continued local and macro COVID-19 waves and crises. To assess a worst-case scenario, no model projection is needed, only the herd immunity threshold equation, estimates of the reproduction ratio, and the estimated mortality rate. With no ultimately successful countermeasures in treatment, vaccine, and non-pharmaceutical interventions (NPIs), the analysis here suggests an eventual number of deaths much like the 1918 pandemic in U.S. deaths per capita (1.8-2.7 million U.S. deaths) and in the total number of deaths worldwide (around 50 million). This toll also reflects a hypothetical global “surrender” strategy of business-as-usual and no social distancing, which in practice no nation has followed. Some successes across the three broad social countermeasure efforts – which appears most likely, in a mix of outcomes – can lessen the high social costs.

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