scholarly journals A spatial model of CoVID-19 transmission in England and Wales: early spread and peak timing

2020 ◽  
Author(s):  
Leon Danon ◽  
Ellen Brooks-Pollock ◽  
Mick Bailey ◽  
Matt Keeling
Keyword(s):  
Seasonal Changes ◽  
Capacity Planning ◽  
Census Data ◽  
Transmission Rate ◽  
Control Measures ◽  
Parameter Estimates ◽  
Peak Time ◽  
England And Wales ◽  
Minimal Impact ◽  
Starting Location

AbstractBackgroundAn outbreak of a novel coronavirus, named CoVID-19, was first reported in China on 31 December 2019. As of 9 February 2020, cases have been reported in 25 countries, including probable cases of human-to-human transmission in England.MethodsWe adapted an existing national-scale metapopulation model to capture the spread of CoVID-19 in England and Wales. We used 2011 census data to capture population sizes and population movement, together with parameter estimates from the current outbreak in China.ResultsWe predict that a CoVID-19 outbreak will peak 126 to 147 days (∼4 months) after the start of person-to-person transmission in England and Wales in the absence of controls, assuming biological parameters remain unchanged. Therefore, if person-to-person transmission persists from February, we predict the epidemic peak would occur in June. The starting location has minimal impact on peak timing, and model stochasticity varies peak timing by 10 days. Incorporating realistic parameter uncertainty leads to estimates of peak time ranging from 78 days to 241 days after person-to-person transmission has been established. Seasonal changes in transmission rate substantially impact the timing and size of the epidemic peak, as well as the total attack rate.DiscussionWe provide initial estimates of the potential course of CoVID-19 in England and Wales in the absence of control measures. These results can be refined with improved estimates of epidemiological parameters, and permit investigation of control measures and cost effectiveness analyses. Seasonal changes in transmission rate could shift the timing of the peak into winter months, which will have important implications for health-care capacity planning.

scholarly journals A spatial model of COVID-19 transmission in England and Wales: early spread, peak timing and the impact of seasonality

2021 ◽  
Vol 376 (1829) ◽  
pp. 20200272
Author(s):  
Leon Danon ◽  
Ellen Brooks-Pollock ◽  
Mick Bailey ◽  
Matt Keeling
Keyword(s):  
Seasonal Changes ◽  
Capacity Planning ◽  
Census Data ◽  
Transmission Rate ◽  
Parameter Estimates ◽  
Peak Time ◽  
England And Wales ◽  
Minimal Impact ◽  
Starting Location ◽  
The Impact

An outbreak of a novel coronavirus was first reported in China on 31 December 2019. As of 9 February 2020, cases have been reported in 25 countries, including probable human-to-human transmission in England. We adapted an existing national-scale metapopulation model to capture the spread of COVID-19 in England and Wales. We used 2011 census data to inform population sizes and movements, together with parameter estimates from the outbreak in China. We predict that the epidemic will peak 126 to 147 days (approx. 4 months) after the start of person-to-person transmission in the absence of controls. Assuming biological parameters remain unchanged and transmission persists from February, we expect the peak to occur in June. Starting location and model stochasticity have a minimal impact on peak timing. However, realistic parameter uncertainty leads to peak time estimates ranging from 78 to 241 days following sustained transmission. Seasonal changes in transmission rate can substantially impact the timing and size of the epidemic. We provide initial estimates of the epidemic potential of COVID-19. These results can be refined with more precise parameters. Seasonal changes in transmission could shift the timing of the peak into winter, with important implications for healthcare capacity planning. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK.

scholarly journals Exponential damping: The key to successful containment of COVID-19

2020 ◽  
Author(s):  
Feng Zhang ◽  
Jinmei Zhang ◽  
Menglan Cao ◽  
Yong Zhang ◽  
Cang Hui
Keyword(s):  
Transmission Rate ◽  
High Capacity ◽  
World Health Organisation ◽  
Positive Outcome ◽  
Control Measures ◽  
World Health ◽  
Peak Time ◽  
Global Public Health ◽  
Viral Spread ◽  
Damping Rate

AbstractDue to its excessively high capacity for human-to-human transmission, the 2019 novel coronavirus disease (COVID-19), first reported in Wuhan in China, spread rapidly to the entire nation and beyond, and has now been declared a global public health emergency. Understanding the transmission pattern of the virus and the efficacy of transmission control measures is crucial to ensuring regional and global disease control. Here we propose a simple model based on exponential infectious growth, but with a time-varying, largely damping, transmission rate. This model provides an excellent fit to the existing data from the 102 countries and regions which have reported cases for more than 6 days, and, we think, has largely captured the transmission patterns of the COVID-19 outbreak under a variety of intervention and control measures. We found that the damping rate, defined as the rate of the exponential decline in transmission rate, ranged from -0.125 to 0.513 d-1 globally (a negative damping rate represents acceleration in spread). The estimated peak time (when the fastest spread occurs) and the final number of infections were found to be greatly affected by the damping rate. Successful control measures, such as those implemented in China and South Korea, have resulted in a clear pattern of exponential damping in the viral spread (also shown during the 2003 outbreak of Severe Acute Respiratory Syndrome, SARS). The damping rate, therefore, could be used as an indicator for the efficacy of implemented control measures. Our model suggests that the COVID-19 outbreak is currently accelerating worldwide, especially rapidly in certain countries (e.g. USA and Australia) where exponential damping is yet to emerge. Consistent with the message from the World Health Organisation (WHO), we thus strongly suggest all countries to take active measures to contain this global pandemic. Slight increments in the damping rate from additional control efforts, especially in countries showing weak or no exponential damping in COVID-19 transmission, could lead to a radically more positive outcome in the fight to contain the pandemic.

scholarly journals The Office for National Statistics Longitudinal Study

2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Alison Sizer ◽  
Oliver Duke-Williams
Keyword(s):  
Longitudinal Study ◽  
Census Data ◽  
Sampling Bias ◽  
Large Sample Size ◽  
England And Wales ◽  
Large Sample ◽  
Small Areas ◽  
Pension Age ◽  
The Uk ◽  
State Pension

Background and Rationale The ONS Longitudinal Study (‘the LS’) covers England and Wales and includes individual data from the 1971 – 2011 decennial censuses and linked information on births, deaths and cancer registrations. It is representative of the population of England and Wales. Aim This presentation describes the LS and the linked administrative data, and showcases recent/ prominent examples of research. Methods and Approach The LS is built around samples drawn from decennial censuses, with its initial sample drawn from the 1971 Census. It also contains information about other people living in a sample-member’s household. Substantial emphasis is placed on security of access to the data and its responsible use. All research outputs are checked and are only released to users once disclosure control requirements are met. Linkage of study members from one census to another and vital events is carried out by ONS. Results The LS has been used for a variety of research. Using linked census and death records occupational differences in mortality rates have been researched. Individual records from all five censuses have been used to contribute to research social mobility, and research has also investigated the effects of long-term exposure to air pollution. Research has provided evidence of impact for social policy issues, e.g. health inequalities and the State Pension Age Review. Discussion The main strength of the LS is its large sample size (>1 million), making it the largest nationally representative longitudinal dataset in the UK. This allows analysis of small areas and specific population groups. Sampling bias is almost nil, and response rates are very high relative to other cohort and panel studies. Conclusion The ONS Longitudinal Study is a vital UK research asset, providing access to a large sample of census data linked across five censuses. It is strengthened through linkage to events data.

scholarly journals Potential impact of seasonal forcing on a SARS-CoV-2 pandemic

2020 ◽  
Author(s):  
Richard A. Neher ◽  
Robert Dyrdak ◽  
Valentin Druelle ◽  
Emma B. Hodcroft ◽  
Jan Albert
Keyword(s):  
Seasonal Variation ◽  
Infection Control ◽  
Transmission Rate ◽  
Health Care Systems ◽  
Control Measures ◽  
Rate Variation ◽  
Small Peak ◽  
Infection Control Measures ◽  
Care Systems ◽  
Novel Coronavirus

A novel coronavirus (SARS-CoV-2) first detected in Wuhan, China, has spread rapidly since December 2019, causing more than 80,000 confirmed infections and 2,700 fatalities (as of Feb 27, 2020). Imported cases and transmission clusters of various sizes have been reported globally suggesting a pandemic is likely.Here, we explore how seasonal variation in transmissibility could modulate a SARS-CoV-2 pandemic. Data from routine diagnostics show a strong and consistent seasonal variation of the four endemic coronaviruses (229E, HKU1, NL63, OC43) and we parameterize our model for SARS-CoV-2 using these data. The model allows for many subpopulations of different size with variable parameters. Simulations of different scenarios show that plausible parameters result in a small peak in early 2020 in temperate regions of the Northern Hemisphere and a larger peak in winter 2020/2021. Variation in transmission and migration rates can result in substantial variation in prevalence between regions.While the uncertainty in parameters is large, the scenarios we explore show that transient reductions in the incidence rate might be due to a combination of seasonal variation and infection control efforts but do not necessarily mean the epidemic is contained. Seasonal forcing on SARS-CoV-2 should thus be taken into account in the further monitoring of the global transmission. The likely aggregated effect of seasonal variation, infection control measures, and transmission rate variation is a prolonged pandemic wave with lower prevalence at any given time, thereby providing a window of opportunity for better preparation of health care systems.

scholarly journals Reassessing the evidence for universal school-age BCG vaccination in England and Wales: re-evaluating and updating a modelling study

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e031573
Author(s):  
Sam Abbott ◽  
Hannah Christensen ◽  
Ellen Brooks-Pollock
Keyword(s):  
Policy Change ◽  
Parameter Uncertainty ◽  
Incidence Rates ◽  
Parameter Estimates ◽  
School Age ◽  
England And Wales ◽  
Bcg Vaccination ◽  
Methodological Flaw ◽  
Notification Data ◽  
The Impact

ObjectivesIn 2005, England and Wales switched from universal BCG vaccination against tuberculosis (TB) disease for school-age children to targeted vaccination of neonates. We aimed to recreate and re-evaluate a previously published model, the results of which informed this policy change.DesignWe recreated an approach for estimating the impact of ending the BCG schools scheme, correcting a methodological flaw in the model, updating the model with parameter uncertainty and improving parameter estimates where possible. We investigated scenarios for the assumed annual decrease in TB incidence rates considered by the UK’s Joint Committee on Vaccination and Immunisation and explored alternative scenarios using notification data.SettingEngland and Wales.Outcome measuresThe number of vaccines needed to prevent a single notification and the average annual additional notifications caused by ending the policy change.ResultsThe previously published model was found to contain a methodological flaw and to be spuriously precise. It greatly underestimated the impact of ending school-age vaccination compared with our updated, corrected model. The updated model produced predictions with wide CIs when parameter uncertainty was included. Model estimates based on an assumption of an annual decrease in TB incidence rates of 1.9% were closest to those estimated using notification data. Using this assumption, we estimate that 1600 (2.5; 97.5% quantiles: 1300, 2000) vaccines would have been required to prevent a single notification in 2004.ConclusionsThe impact of ending the BCG schools scheme was found to be greater than previously thought when notification data were used. Our results highlight the importance of independent evaluations of modelling evidence, including uncertainty, and evaluating multiple scenarios when forecasting the impact of changes in vaccination policy.

Insufficient respiratory hazard identification in the safety data sheets for cleaning and disinfection products used in healthcare organisations across England and Wales

2021 ◽  
Vol 78 (4) ◽  
pp. 293-295
Author(s):  
Sewon Lee ◽  
Andrew C Povey ◽  
Martin J Seed ◽  
Martie van Tongeren
Keyword(s):  
Healthcare Workers ◽  
Safety Data ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Test Methods ◽  
Hazard Identification ◽  
Control Measures ◽  
Hazardous Chemicals ◽  
England And Wales ◽  
Cleaning And Disinfection

BackgroundExposure to cleaning and disinfection products has been associated with respiratory disorders such as asthma in cleaning and healthcare workers. Safety data sheets (SDSs) provide information on hazardous chemicals that are present in products to help users with risk assessment and implement appropriate control measures. However, they have potential limitations in identifying respiratory hazards due to a lack of regulatory test methods for respiratory sensitisation and irritation of chemicals.MethodsSDSs were first used to identify chemicals on the database as respiratory sensitisers and irritants. A quantitative structure–activity relationship (QSAR) model and an asthmagen list established by the Association of Occupational and Environmental Clinics (AOEC) were used to identify potential respiratory sensitisers and irritants (by the AOEC list only) in the cleaning and disinfection products.ResultsFrom a total of 459 cleaning and disinfection products used in healthcare organisations across England and Wales, 35 respiratory sensitisers not labelled as such on the SDS were identified by QSAR or AOEC. Only 2% of cleaning and disinfection products contained at least one respiratory sensitiser as identified by their SDSs; this was increased to 37.7% of products when the QSAR or the AOEC list was used.ConclusionsA significantly higher proportion of cleaning products contain respiratory hazardous chemicals, particularly respiratory sensitisers than would be expected from the information provided by SDSs alone. Cleaners and healthcare workers may, therefore, be insufficiently protected.

scholarly journals Assessing the role of two populations of Aedes japonicus japonicus for Zika virus transmission under a constant and a fluctuating temperature regime

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Uros Glavinic ◽  
Jasmin Varga ◽  
Anca Ioana Paslaru ◽  
Jeannine Hauri ◽  
Paul Torgerson ◽  
...  
Keyword(s):  
Constant Temperature ◽  
Temperature Regime ◽  
Zika Virus ◽  
Incubation Temperature ◽  
Transmission Rate ◽  
Control Measures ◽  
Fluctuating Temperature ◽  
Laboratory Conditions ◽  
Temperature Regimes ◽  
Two Populations

Abstract Background Since the huge epidemic of Zika virus (ZIKV) in Brazil in 2015, questions were raised to understand which mosquito species could transmit the virus. Aedes aegypti has been described as the main vector. However, other Aedes species (e.g. Ae. albopictus and Ae. japonicus) proven to be competent for other flaviviruses (e.g. West Nile, dengue and yellow fever), have been described as potential vectors for ZIKV under laboratory conditions. One of these, the Asian bush mosquito, Ae. japonicus, is widely distributed with high abundances in central-western Europe. In the present study, infection, dissemination and transmission rates of ZIKV (Dak84 strain) in two populations of Ae. japonicus from Switzerland (Zürich) and France (Steinbach, Haut-Rhin) were investigated under constant (27 °C) and fluctuating (14–27 °C, mean 23 °C) temperature regimes. Results The two populations were each able to transmit ZIKV under both temperature regimes. Infectious virus particles were detected in the saliva of females from both populations, regardless of the incubation temperature regime, from 7 days post-exposure to infectious rabbit blood. The highest amount of plaque forming units (PFU) (400/ml) were recorded 14 days post-oral infection in the Swiss population incubated at a constant temperature. No difference in terms of infection, dissemination and transmission rate were found between mosquito populations. Temperature had no effect on infection rate but the fluctuating temperature regime resulted in higher dissemination rates compared to constant temperature, regardless of the population. Finally, transmission efficiency ranged between 7–23% and 7–10% for the constant temperature and 0–10% and 3–27% under fluctuating temperatures for the Swiss and the French populations, respectively. Conclusions To the best of our knowledge, this is the first study confirming vector competence for ZIKV of Ae. japonicus originating from Switzerland and France at realistic summer temperatures under laboratory conditions. Considering the continuous spread of this species in the northern part of Europe and its adaptation at cooler temperatures, preventative control measures should be adopted to prevent possible ZIKV epidemics.

Hate crime against older people in England and Wales – an econometric enquiry

2014 ◽  
Vol 16 (3) ◽  
pp. 152-165 ◽  
Author(s):  
José Iparraguirre
Keyword(s):  
Older People ◽  
Latent Variable ◽  
Hate Crime ◽  
Census Data ◽  
Criminal Activity ◽  
Econometric Analysis ◽  
Data Availability ◽  
England And Wales ◽  
Content Type ◽  
Geographical Unit

Purpose – The purpose of this paper is to present an econometric analysis of hate crime against older people based on data for England and Wales for 2010-2011 disaggregated by Crown Prosecution Service area – a geographical unit which is co-terminus with local authorities. Design/methodology/approach – The authors ran different specifications of structural regression models including one latent variable and accounting for a number of interactions between the covariates. Findings – The paper suggests that the higher the level of other types of hate crime is in an area, the higher the level of hate crime against older people. Demographics are also significant: a higher concentration of older and young people partially explains hate crime levels against the former. Employment, income and educational deprivation are also associated with biased-crime against older people. Conviction rates seem to reduce hate crime against older people, and one indicator of intergenerational contact is not significant. Research limitations/implications – Due to data availability and quality, the paper only studies one years worth of data. Consequently, the research results may lack generalisability. Furthermore, the proxy variable for intergenerational contact may not be the most suitable indicator; however, there will not be any other indicators available until Census data come out. Practical implications – The paper suggests that factors underlying hate crime would also influence hate crime against older people. Besides, the results would not support the “generational clash” view. Tackling income, educational and employment deprivation would help significantly reduce the number of episodes of biased criminal activity against older people. Improving conviction rates of all types of hate crime would also contribute to the reduction of hate crime against older people. Originality/value – This paper presents the first econometric analysis of hate crime against older people.

The changing interaction of ethnic and socio-economic segregation in England and Wales, 1991–2011

Ethnicities ◽  
2015 ◽  
Vol 17 (3) ◽  
pp. 320-349 ◽  
Author(s):  
Richard Harris ◽  
Ron Johnston ◽  
David Manley
Keyword(s):  
Ethnic Groups ◽  
Minority Groups ◽  
Census Data ◽  
Economic Disadvantage ◽  
Full Time ◽  
Ethnic Segregation ◽  
Contributing Factors ◽  
England And Wales ◽  
Ethnic Residential Segregation ◽  
The Uk

Following the publication of the 2001 and 2011 Census data, considerable attention has been given to patterns of ethnic residential segregation within the UK. The evidence contributes to debates about integration; however, as Kapoor (2013) has argued, discussion about it also risks promoting the idea that what we measure is voluntary segregation, arising from the outcome of residential choices and a preference to live with one's ethno-cultural peers. In reality, ethnic and social segregation overlap and are easily confounded; it is important to pay attention to where they geographically coincide. In this paper we use an area typology to assess whether minority ethnic groups are disproportionately concentrated in neighbourhoods in England and Wales containing the lowest proportions of their adult populations in full-time employment, and evaluate how those concentrations have changed between 1991 and 2011. We consider the (residential) exposure of the ethnic groups to the White British and also to each other, and identify the groups affected by the persistence of economic disadvantage. The analysis shows that patterns of ethnic segregation intersect strongly with neighbourhoods of socio-economic disadvantage, with inequalities in the labour market and the increase of part-time working suggested as contributing factors. A decreased exposure to the White British is an increased characteristic of the disadvantaged neighbourhoods where minority groups live. However, exposure between those groups has increased.

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