scholarly journals The 2020 SARS-CoV-2 epidemic in England: key epidemiological drivers and impact of interventions

2021 ◽  
Author(s):  
Edward S. Knock ◽  
Lilith K. Whittles ◽  
John A. Lees ◽  
Pablo N. Perez-Guzman ◽  
Robert Verity ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Reproduction Number ◽  
Clinical Care ◽  
Herd Immunity ◽  
The Elderly ◽  
Surveillance Data ◽  
Control Measures ◽  
Care Homes ◽  
The Impact ◽  
Regional Surveillance

AbstractWe fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Among control measures implemented, only national lockdown brought the reproduction number below 1 consistently; introduced one week earlier it could have reduced first wave deaths from 36,700 to 15,700 (95%CrI: 8,900–26,800). Improved clinical care reduced the infection fatality ratio from 1.25% (95%CrI: 1.18%–1.33%) to 0.77% (95%CrI: 0.71%–0.84%). The infection fatality ratio was higher in the elderly residing in care homes (35.9%, 95%CrI: 29.1%–43.4%) than those residing in the community (10.4%, 95%CrI: 9.1%–11.5%). England is still far from herd immunity, with regional cumulative infection incidence to 1st December 2020 between 4.8% (95%CrI: 4.4%–5.1%) and 15.4% (95%CrI: 14.9%–15.9%) of the population.One-sentence summaryWe fit a mathematical model of SARS-CoV-2 transmission to surveillance data from England, to estimate transmissibility, severity, and the impact of interventions

scholarly journals Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England

2021 ◽  
pp. eabg4262
Author(s):  
Edward S. Knock ◽  
Lilith K. Whittles ◽  
John A. Lees ◽  
Pablo N. Perez-Guzman ◽  
Robert Verity ◽  
...  
Keyword(s):  
Clinical Care ◽  
Vaccination Campaign ◽  
Herd Immunity ◽  
Credible Interval ◽  
The Elderly ◽  
Surveillance Data ◽  
Control Measures ◽  
Care Homes ◽  
High Coverage ◽  
Degree Of Protection

We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modelling framework allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rteff) below 1 consistently; if introduced one week earlier it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 (95% credible interval [95%CrI]: 15,900–38,400). The infection fatality ratio decreased from 1.00% (95%CrI: 0.85%–1.21%) to 0.79% (95%CrI: 0.63%–0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95%CrI: 14.7%–35.2%) than those residing in the community (7.9%, 95%CrI: 5.9%–10.3%). On 2nd December 2020 England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95%CrI: 5.4%–10.2%) and 22.3% (95%CrI: 19.4%–25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow non-pharmaceutical interventions to be lifted without a resurgence of transmission.

scholarly journals Role of Mathematical Model in Curbing COVID-19 in Nigeria

2021 ◽  
Vol 3 (2) ◽  
pp. 135-147
Author(s):  
Chinwendu Emilian Madubueze ◽  
Nkiru Maria Akabuike ◽  
Sambo Dachollom
Keyword(s):  
Mathematical Model ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Viral Disease ◽  
Control Measures ◽  
Social Distancing ◽  
Testing Rate ◽  
Intervention Measures ◽  
The Impact ◽  
The Basic Reproduction Number

COVID-19 is a viral disease that is caused by Severe Acute Respiratory Syndrome coronavirus 2 (SARSCoV-2) which has no approved vaccine. Based on the available non-pharmacological interventions like wearing of face masks, observing social distancing, and lockdown, this work assesses the impact of non-pharmaceutical control measures (social distancing and use of face-masks) and mass testing on the transmission of COVID-19 in Nigeria. A mathematical model for COVID-19 is formulated with intervention measures (observing social distancing and wearing of face masks) and mass testing. The basic reproduction number, R_0, is computed using next-generation method while the disease-free equilibrium is found to be locally and globally asymptotically stable when R_0< 1. The model is parameterized using Nigeria data on COVID-19 in Nigeria. The basic reproduction number is found to be less than unity (R_0 < 1) either when the compliance with intervention measures is moderate (50% <= alpha< 70%) and the testing rate per day is moderate (0,5 <=alpha_2 < 0,7) or when the compliance with intervention measures is strict (alpha>=70%) and the testing rate per day is poor (alpha_2 = 0,3). This implies that Nigeria will be able to halt the spread of COVID-19 under these two conditions. However, it will be easier to enforce strict compliance with intervention measures in the presence of poor testing rate due to the limited availability of testing facilities and manpower in Nigeria. Hence, this study advocates that Nigerian governments (Federal and States) should aim at achieving a testing rate of at least 0.3 per day while ensuring that all the citizens strictly comply with wearing face masks and observing social distancing in public.

scholarly journals Modelling the Evolution of COVID-19 in High-Incidence European Countries and Regions: Estimated Number of Infections and Impact of Past and Future Intervention Measures

2020 ◽  
Vol 9 (6) ◽  
pp. 1825 ◽  
Author(s):  
Juan Fernández-Recio
Keyword(s):  
Reproduction Number ◽  
Mechanistic Model ◽  
Control Measures ◽  
European Countries ◽  
Intervention Measures ◽  
High Incidence ◽  
Future Outcomes ◽  
Long Term Impact ◽  
The Impact

A previously developed mechanistic model of COVID-19 transmission has been adapted and applied here to study the evolution of the disease and the effect of intervention measures in some European countries and territories where the disease has had a major impact. A clear impact of the major intervention measures on the reproduction number (Rt) has been found in all studied countries and territories, as already suggested by the drop in the number of deaths over time. Interestingly, the impact of such major intervention measures seems to be the same in most of these countries. The model has also provided realistic estimates of the total number of infections, active cases and future outcomes. While the predictive capabilities of the model are much more uncertain before the peak of the outbreak, we could still reliably predict the evolution of the disease after a major intervention by assuming the subsequent reproduction number from the current study. A greater challenge is to foresee the long-term impact of softer intervention measures, but this model can estimate the outcome of different scenarios and help to plan changes for the implementation of control measures in a given country or region.

scholarly journals Modelling the Effectiveness of Epidemic Control Measures in Preventing the Transmission of COVID-19 in Malaysia

2020 ◽  
Vol 17 (15) ◽  
pp. 5509 ◽  
Author(s):  
Balvinder Singh Gill ◽  
Vivek Jason Jayaraj ◽  
Sarbhan Singh ◽  
Sumarni Mohd Ghazali ◽  
Yoon Ling Cheong ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Model Calibration ◽  
Reproduction Number ◽  
Close Contact ◽  
Movement Control ◽  
Control Measures ◽  
Seir Model ◽  
Epidemic Curve ◽  
Reproduction Numbers ◽  
Control Order

Malaysia is currently facing an outbreak of COVID-19. We aim to present the first study in Malaysia to report the reproduction numbers and develop a mathematical model forecasting COVID-19 transmission by including isolation, quarantine, and movement control measures. We utilized a susceptible, exposed, infectious, and recovered (SEIR) model by incorporating isolation, quarantine, and movement control order (MCO) taken in Malaysia. The simulations were fitted into the Malaysian COVID-19 active case numbers, allowing approximation of parameters consisting of probability of transmission per contact (β), average number of contacts per day per case (ζ), and proportion of close-contact traced per day (q). The effective reproduction number (Rt) was also determined through this model. Our model calibration estimated that (β), (ζ), and (q) were 0.052, 25 persons, and 0.23, respectively. The (Rt) was estimated to be 1.68. MCO measures reduce the peak number of active COVID-19 cases by 99.1% and reduce (ζ) from 25 (pre-MCO) to 7 (during MCO). The flattening of the epidemic curve was also observed with the implementation of these control measures. We conclude that isolation, quarantine, and MCO measures are essential to break the transmission of COVID-19 in Malaysia.

scholarly journals Real-time estimation of the influenza-associated excess mortality in Hong Kong

2019 ◽  
Vol 147 ◽  
Author(s):  
Jessica Y. Wong ◽  
Edward Goldstein ◽  
Vicky J. Fang ◽  
Benjamin J. Cowling ◽  
Peng Wu
Keyword(s):  
Hong Kong ◽  
Real Time ◽  
Excess Mortality ◽  
Time Estimation ◽  
Surveillance Data ◽  
Control Measures ◽  
Influenza Surveillance ◽  
Mortality Data ◽  
Real Time Estimation ◽  
The Impact

Abstract Statistical models are commonly employed in the estimation of influenza-associated excess mortality that, due to various reasons, is often underestimated by laboratory-confirmed influenza deaths reported by healthcare facilities. However, methodology for timely and reliable estimation of that impact remains limited because of the delay in mortality data reporting. We explored real-time estimation of influenza-associated excess mortality by types/subtypes in each year between 2012 and 2018 in Hong Kong using linear regression models fitted to historical mortality and influenza surveillance data. We could predict that during the winter of 2017/2018, there were ~634 (95% confidence interval (CI): (190, 1033)) influenza-associated excess all-cause deaths in Hong Kong in population ⩾18 years, compared to 259 reported laboratory-confirmed deaths. We estimated that influenza was associated with substantial excess deaths in older adults, suggesting the implementation of control measures, such as administration of antivirals and vaccination, in that age group. The approach that we developed appears to provide robust real-time estimates of the impact of influenza circulation and complement surveillance data on laboratory-confirmed deaths. These results improve our understanding of the impact of influenza epidemics and provide a practical approach for a timely estimation of the mortality burden of influenza circulation during an ongoing epidemic.

scholarly journals Modeling the Effects of Helminth Infection on the Transmission Dynamics of Mycobacterium tuberculosis under Optimal Control Strategies

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Aristide G. Lambura ◽  
Gasper G. Mwanga ◽  
Livingstone Luboobi ◽  
Dmitry Kuznetsov
Keyword(s):  
Optimal Control ◽  
Equilibrium Point ◽  
Drug Administration ◽  
Mass Drug Administration ◽  
Helminth Infection ◽  
Reproduction Number ◽  
Control Strategies ◽  
Active Tuberculosis ◽  
Control Measures ◽  
The Impact

A deterministic mathematical model for the transmission and control of cointeraction of helminths and tuberculosis is presented, to examine the impact of helminth on tuberculosis and the effect of control strategies. The equilibrium point is established, and the effective reproduction number is computed. The disease-free equilibrium point is confirmed to be asymptotically stable whenever the effective reproduction number is less than the unit. The analysis of the effective reproduction number indicates that an increase in the helminth cases increases the tuberculosis cases, suggesting that the control of helminth infection has a positive impact on controlling the dynamics of tuberculosis. The possibility of bifurcation is investigated using the Center Manifold Theorem. Sensitivity analysis is performed to determine the effect of every parameter on the spread of the two diseases. The model is extended to incorporate control measures, and Pontryagin’s Maximum Principle is applied to derive the necessary conditions for optimal control. The optimal control problem is solved numerically by the iterative scheme by considering vaccination of infants for Mtb, treatment of individuals with active tuberculosis, mass drug administration with regular antihelminthic drugs, and sanitation control strategies. The results show that a combination of educational campaign, treatment of individuals with active tuberculosis, mass drug administration, and sanitation is the most effective strategy to control helminth-Mtb coinfection. Thus, to effectively control the helminth-Mtb coinfection, we suggest to public health stakeholders to apply intervention strategies that are aimed at controlling helminth infection and the combination of vaccination of infants and treatment of individuals with active tuberculosis.

scholarly journals Investigating the impact of vaccination and non-pharmaceutical measures in curbing COVID-19 spread: A South Africa perspective

2021 ◽  
Vol 19 (1) ◽  
pp. 1058-1077
Author(s):  
Shina D. Oloniiju ◽  
◽  
Olumuyiwa Otegbeye ◽  
Absalom E. Ezugwu ◽  
◽  
...  
Keyword(s):  
Reproduction Number ◽  
Transmission Probability ◽  
Control Measures ◽  
World Population ◽  
Reproduction Rate ◽  
Secondary Infections ◽  
Perform Sensitivity Analysis ◽  
African Context ◽  
The Impact ◽  
Effective Reaction

<abstract><p>The year 2020 brought about a pandemic that caught most of the world population by surprise and wreaked unimaginable havoc before any form of effective reaction could be put in place. COVID-19 is proving to be an epidemic that keeps on having an upsurge whenever it looks like it is being curbed. This pandemic has led to continuous strategizing on approaches to quelling the surge. The recent and welcome introduction of vaccines has led to renewed optimism for the population at large. The introduction of vaccines has led to the need to investigate the effect of vaccination among other control measures in the fight against COVID-19. In this study, we develop a mathematical model that captures the dynamics of the disease taking into consideration some measures that are easier to implement majorly within the African context. We consider quarantine and vaccination as control measures and investigate the efficacy of these measures in curbing the reproduction rate of the disease. We analyze the local stability of the disease-free equilibrium point. We also perform sensitivity analysis of the effective reproduction number to determine which parameters significantly lowers the effective reproduction number. The results obtained suggest that quarantine and a vaccine with at least $ 75\% $ efficacy and reducing transmission probability through sanitation and wearing of protective gears can significantly reduce the number of secondary infections.</p></abstract>

scholarly journals Are we allowed to visit now? Concerns and issues surrounding vaccination and infection risks in UK care homes during COVID-19

2021 ◽  
Author(s):  
Clarissa Marie Giebel ◽  
Kerry Hanna ◽  
Jacqueline Cannon ◽  
Paul Marlow ◽  
Hilary Tetlow ◽  
...  
Keyword(s):  
Scientific Evidence ◽  
Care Home ◽  
Home Visitation ◽  
Control Measures ◽  
Care Homes ◽  
Family Carers ◽  
Care Home Staff ◽  
The Uk ◽  
The Impact

Background: Vaccination uptake in the UK and increased care home testing are likely affecting care home visitation. With scant scientific evidence to date, the aim of this longitudinal qualitative study was to explore the impact of both (vaccination and testing) on the conduct and experiences of care home visits. Methods: Family carers of care home residents with dementia and care home staff from across the UK took part in baseline (October/November 2020) and follow-up interviews (March 2021). Public advisers were involved in all elements of the research. Data were analysed using thematic analysis. Results: Across 62 baseline and follow-up interviews with family carers (n=26; 11) and care home staff (n=16; 9), five core themes were developed: Delayed and inconsistent offers of face-to-face visits; Procedures and facilitation of visits; Frustration and anger among family carers; Variable uptake of the COVID-19 vaccine; Misinformation, education, and free choice. The variable uptake in staff, compared to family carers, was a key factor seemingly influencing visitation, with a lack of clear guidance leading care homes to implement infection control measures and visitation rights differently. Conclusions: We make five recommendations in this paper to enable improved care home visitation in the ongoing, and in future, pandemics. Visits need to be enabled and any changes to visiting rights must be used as a last resort, reviewed regularly in consultation with residents and carers and restored as soon as possible as a top priority, whilst more education needs to be provided surrounding vaccination for care home staff.

scholarly journals Modelling the evolution of COVID-19 in high-incidence European countries and regions: estimated number of infections and impact of past and future intervention measures

2020 ◽  
Author(s):  
Juan Fernandez-Recio
Keyword(s):  
Reproduction Number ◽  
Mechanistic Model ◽  
Control Measures ◽  
European Countries ◽  
Intervention Measures ◽  
High Incidence ◽  
Long Term Impact ◽  
The Impact ◽  
Over Time

A previously developed mechanistic model of COVID-19 transmission has been adapted and applied here to study the evolution of the disease and the effect of intervention measures in some European countries and territories where the disease had major impact. A clear impact of the major intervention measures on the reproduction number (Rt) has been found in all studied countries and territories, as already suggested by the drop in the number of deaths over time. Interestingly, the impact of such major intervention measures seems to be the same in most of these countries. The model has also provided realistic estimates of the total number of infections, active cases and future outcome. While the predictive capabilities of the model are much more uncertain before the peak of the outbreak, we could still reliably predict the evolution of the disease after a major intervention by assuming the afterwards reproduction number from current study. More challenging is to foresee the long-term impact of softer intervention measures, but this model can estimate the outcome of different scenarios and help planning changes in the implementation of control measures in a given country or region.

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