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1.
Epidemiol Infect ; 150: e100, 2022 05 12.
Article in English | MEDLINE | ID: covidwho-1947140

ABSTRACT

This paper presents a method used to rapidly assess the incursion and the establishment of community transmission of suspected SARS-CoV-2 variant of concern Delta (lineage B.1.617.2) into the UK in April and May 2021. The method described is independent of any genetically sequenced data, and so avoids the inherent lag times involved in sequencing of cases. We show that, between 1 April and 12 May 2021, there was a strong correlation between local authorities with high numbers of imported positive cases from India and high COVID-19 case rates, and that this relationship holds as we look at finer geographic detail. Further, we also show that Bolton was an outlier in the relationship, having the highest COVID-19 case rates despite relatively few importations. We use an artificial neural network trained on demographic data, to show that observed importations in Bolton were consistent with similar areas. Finally, using an SEIR transmission model, we show that imported positive cases were a contributing factor to persistent transmission in a number of local authorities, however they could not account for increased case rates observed in Bolton. As such, the outbreak of Delta variant in Bolton was likely not a result of direct importation from overseas, but rather secondary transmission from other regions within the UK.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Disease Outbreaks , Humans , SARS-CoV-2/genetics , United Kingdom/epidemiology
2.
ERJ Open Res ; 8(2)2022 Apr.
Article in English | MEDLINE | ID: covidwho-1866273

ABSTRACT

Introduction: Following the easing of COVID-19 restrictions in many countries, a surge in respiratory syncytial virus (RSV) hospitalisations was reported, surpassing yearly trends pre-pandemic. The changes to RSV epidemiology may have unforeseen effects on healthcare systems and populations globally, adding to the burden generated during the pandemic and placing increased demand on resources. Here we aim to identify recent global trends of RSV hospitalisation amongst children aged ≤5 years, to help inform policy makers in the planning of preventative interventions. Methods: We conducted a scoping review of published literature between January 2009 and May 2021. Using keywords "Hospital admissions, Respiratory syncytial virus, RSV, Bronchiolitis, Children" we located studies using Medline, EMCARE, CINAHL and HMIC. Studies were eligible if they reported on trends/data for RSV hospitalisation amongst children aged ≤5 years. The articles were reviewed by two independent reviewers. Findings: We assessed 3310 abstracts, reviewed 70 studies and included 56 studies in the final review. Findings were categorised into themes. The review highlighted that, although RSV incidence has been steadily increasing since 2009, the number of reported RSV hospitalisations decreased during lockdown. The highest numbers of hospitalisations were reported in children <1 year of age, particularly 0-2-month-old infants. Globally, RSV hospitalisations tend to peak in the winter months; however, since COVID-19 restrictions have eased, countries are reporting incidence peaks at different times, in contrast to the trends of previous years. Conclusion: With greater physical interactions due to the relaxation of COVID-19 restriction measures, RSV-related hospitalisations can be seen to increase amongst children aged ≤5 years, possibly surpassing the numbers reported in previous RSV seasons.

3.
SSRN; 2022.
Preprint in English | SSRN | ID: ppcovidwho-333480

ABSTRACT

Background: Paediatric Multisystem Inflammatory Syndrome (PIMS-TS) is a rare life-threatening complication that typically occurs several weeks after SARS-CoV-2 infection in children and young people (CYP). We used national and regional-level data from the COVID-19 pandemic wave in England to develop and optimise a model to predict PIMS-TS cases in subsequent waves. Methods: SARS-CoV-2 infections in CYP aged 0-15 years in England were estimated using the PHE-Cambridge real-time model. PIMS-TS cases were identified through the British Paediatric Surveillance Unit during the first pandemic wave (March-June 2020). Since November 2020, cases were identified through Secondary Uses Services (SUS), a national healthcare activity dataset. A predictive model was developed to estimate PIMS-TS risk and lag times after SARS-CoV-2 infection for the Alpha (weeks 1-10, 2021) and Delta (weeks 22-30, 2022) waves. Findings: During the Alpha wave, the model accurately predicted PIMS-TS cases (506 (95% CI: 491-531) vs 502 observed cases), with a median estimated the risk of 0·038% (IQR, 0·037-0·041%;38/100,000 infections) of paediatric SARS-CoV-2 infections. For the Delta wave, the median risk of PIMS-TS was significantly lower at 0·026% (IQR, 0·025-0·029%;27/100,000 infections) , with 212 observed PIMS-TS cases compared to 450 predicted by the model during June-October 2021. Interpretation: We developed a model that accurately predicted national and regional PIMS-TS cases in CYP during the Alpha wave. PIMS-TS cases were, however, 53% lower than predicted during the Delta wave. Further studies are needed to understand the mechanisms of the observed lower risk with the Delta variant.

4.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-307507

ABSTRACT

Background: Paediatric Multisystem Inflammatory Syndrome (PIMS-TS) is a rare life-threatening complication that occurs in some children two to four weeks after SARS-CoV-2 infection. Although the precise causal mechanisms underpinning the relationship between SARS-CoV-2 and PIMS-TS are unclear, several recent studies have confirmed a strong temporal association. This study provides further evidence in support of a causal and temporal link. A novel methodology is presented whereby PIMS-TS incidence parameters estimated from data published on SARS-CoV-2 in the first wave of the COVID-19 pandemic in England were used to make accurate projections of PIMS-TS cases in the second wave. Methods: Case classifications and data on PIMS-TS cases were obtained from the British Paediatric Surveillance Unit (BPSU) in an endeavour initiated by Public Heath England (PHE). The dataset contained all PIMS-TS cases presenting as symptomatic in England in the first wave of the pandemic. PIMS-TS incidence rates in children aged <15 years were estimated for the first wave and expressed as a fraction of SARS-CoV-2 cases. Data on SARS-CoV-2 cases were extracted from the PHE-Cambridge real-time model. Temporal analysis was performed to estimate the lag-time between peak SARS-CoV-2 incidence and peak PIMS-TS. The incidence and lag-time parameters estimated during the first wave were used to produce weekly projections of PIMS-TS cases in the second wave. These projections were then employed operationally in a clinical setting. Statistical analyses were performed to assess the accuracy of the forecasts once data on PIMS-TS cases were published by the BPSU approximately three months after the PIMS-TS forecasts were generated. Findings: Statistical analyses show that the PIMS-TS parameters estimated from the first wave produced accurate projections of PIMS-TS incidence in the second wave. Results at the aggregated national level showed there were no statistically significant differences observed between the PIMS-TS admission data and forecasts in England. Forecasts generated at the disaggregated regional level were also accurate, with no statistically significant differences observed between the PIMS-TS admissions data and forecasts in five of the nine Public Health England Centres (PHECs). However, a statistically significant divergence was observed between the PIMS-TS admissions data and the second wave forecasts in the regions of London and in the East, North West, and South West of England.Interpretation: This study provides further evidence in support of a causal and temporal association between SARS-CoV-2 and PIMS-TS, since data on SARS-CoV-2 incidence in the first wave of the COVID-19 pandemic in England have been shown to be a good baseline from which to generate forecasts of PIMS-TS incidence in the second wave, at both aggregated national and disaggregated regional levels.Funding Information: : Department of Health and Social Care (DHSC) Grant-in-aid funding to Public Health England (PHE).Declaration of Interests: None;this study did not receive any specific grant funding from external agencies in the public, commercial or not-for-profit sectors.Ethics Approval Statement: : PHE has legal permission under Regulation 3 of The Health Service (Control of Patient Information) Regulations 2002, to conduct national surveillance of communicable diseases in England and, as such, individual patient consent is not required. Public Health Wales, through the established order legislation, is required to conduct surveillance of communicable diseases in Wales and, as such, individual patient consent is not required. The surveillance protocol was approved by the Public Benefit and Privacy Panel for Health and Social Care in Scotland (Ref: 20210041, 19 May 2020).

5.
Epidemiol Infect ; 149: e238, 2021 11 04.
Article in English | MEDLINE | ID: covidwho-1500390

ABSTRACT

The effectiveness of screening travellers during times of international disease outbreak is contentious, especially as the reduction in the risk of disease importation can be very small. Border screening typically consists of travellers being thermally scanned for signs of fever and/or completing a survey declaring any possible symptoms prior to admission to their destination country; while more thorough testing typically exists, these would generally prove more disruptive to deploy. In this paper, we describe a simple Monte Carlo based model that incorporates the epidemiology of coronavirus disease-2019 (COVID-19) to investigate the potential decrease in risk of disease importation that might be achieved by requiring travellers to undergo screening upon arrival during the current pandemic. This is a purely theoretical study to investigate the maximum impact that might be attained by deploying a test or testing programme simply at the point of entry, through which we may assess such action in the real world as a method of decreasing the risk of importation. We, therefore, assume ideal conditions such as 100% compliance among travellers and the use of a 'perfect' test. In addition to COVID-19, we also apply the presented model to simulated outbreaks of influenza, severe acute respiratory syndrome (SARS) and Ebola for comparison. Our model only considers screening implemented at airports, being the predominant method of international travel. Primary results showed that in the best-case scenario, screening at the point of entry may detect a maximum of 8.8% of travellers infected with COVID-19, compared to 34.8.%, 9.7% and 3.0% for travellers infected with influenza, SARS and Ebola respectively. While results appear to indicate that screening is more effective at preventing disease ingress when the disease in question has a shorter average incubation period, our results suggest that screening at the point of entry alone does not represent a sufficient method to adequately protect a nation from the importation of COVID-19 cases.


Subject(s)
COVID-19/diagnosis , COVID-19/transmission , Mass Screening , SARS-CoV-2 , Travel , COVID-19/prevention & control , Humans , Models, Biological , Monte Carlo Method , Risk Factors
6.
Philos Trans R Soc Lond B Biol Sci ; 376(1829): 20200264, 2021 07 19.
Article in English | MEDLINE | ID: covidwho-1309684

ABSTRACT

Early assessments of the growth rate of COVID-19 were subject to significant uncertainty, as expected with limited data and difficulties in case ascertainment, but as cases were recorded in multiple countries, more robust inferences could be made. Using multiple countries, data streams and methods, we estimated that, when unconstrained, European COVID-19 confirmed cases doubled on average every 3 days (range 2.2-4.3 days) and Italian hospital and intensive care unit admissions every 2-3 days; values that are significantly lower than the 5-7 days dominating the early published literature. Furthermore, we showed that the impact of physical distancing interventions was typically not seen until at least 9 days after implementation, during which time confirmed cases could grow eightfold. We argue that such temporal patterns are more critical than precise estimates of the time-insensitive basic reproduction number R0 for initiating interventions, and that the combination of fast growth and long detection delays explains the struggle in countries' outbreak response better than large values of R0 alone. One year on from first reporting these results, reproduction numbers continue to dominate the media and public discourse, but robust estimates of unconstrained growth remain essential for planning worst-case scenarios, and detection delays are still key in informing the relaxation and re-implementation of interventions. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.


Subject(s)
COVID-19/epidemiology , Models, Theoretical , Pandemics , COVID-19/virology , Humans , Italy/epidemiology , Physical Distancing , SARS-CoV-2
7.
Bull World Health Organ ; 99(3): 178-189, 2021 Mar 01.
Article in English | MEDLINE | ID: covidwho-1256313

ABSTRACT

OBJECTIVE: To describe the clinical presentation, course of disease and health-care seeking behaviour of the first few hundred cases of coronavirus disease 2019 (COVID-19) in the United Kingdom of Great Britain and Northern Ireland. METHODS: We implemented the World Health Organization's First Few X cases and contacts investigation protocol for COVID-19. Trained public health professionals collected information on 381 virologically confirmed COVID-19 cases from 31 January 2020 to 9 April 2020. We actively followed up cases to identify exposure to infection, symptoms and outcomes. We also collected limited data on 752 symptomatic people testing negative for COVID-19, as a control group for analyses of the sensitivity, specificity and predictive value of symptoms. FINDINGS: Approximately half of the COVID-19 cases were imported (196 cases; 51.4%), of whom the majority had recent travel to Italy (140 cases; 71.4%). Of the 94 (24.7%) secondary cases, almost all reported close contact with a confirmed case (93 cases; 98.9%), many through household contact (37 cases; 39.8%). By age, a lower proportion of children had COVID-19. Most cases presented with cough, fever and fatigue. The sensitivity and specificity of symptoms varied by age, with nonlinear relationships with age. Although the proportion of COVID-19 cases with fever increased with age, for those with other respiratory infections the occurrence of fever decreased with age. The occurrence of shortness of breath also increased with age in a greater proportion of COVID-19 cases. CONCLUSION: The study has provided useful evidence for generating case definitions and has informed modelling studies of the likely burden of COVID-19.


Subject(s)
COVID-19/epidemiology , COVID-19/physiopathology , Adolescent , Adult , Age Distribution , Aged , Child , Child, Preschool , Dyspnea/epidemiology , Female , Humans , Infant , Male , Middle Aged , Respiratory Tract Infections/epidemiology , SARS-CoV-2 , Travel , United Kingdom/epidemiology , Young Adult
8.
Lancet Reg Health Eur ; 3: 100075, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1144857

ABSTRACT

BACKGROUND: Paediatric Multisystem Inflammatory Syndrome temporally associated with SARS-CoV-2 (PIMS-TS), first identified in April 2020, shares features of both Kawasaki disease (KD) and toxic shock syndrome (TSS). The surveillance describes the epidemiology and clinical characteristics of PIMS-TS in the United Kingdom and Ireland. METHODS: Public Health England initiated prospective national surveillance of PIMS-TS through the British Paediatric Surveillance Unit. Paediatricians were contacted monthly to report PIMS-TS, KD and TSS cases electronically and complete a detailed clinical questionnaire. Cases with symptom onset between 01 March and 15 June 2020 were included. FINDINGS: There were 216 cases with features of PIMS-TS alone, 13 with features of both PIMS-TS and KD, 28 with features of PIMS-TS and TSS and 11 with features of PIMS-TS, KD and TSS, with differences in age, ethnicity, clinical presentation and disease severity between the phenotypic groups. There was a strong geographical and temporal association between SARS-CoV-2 infection rates and PIMS-TS cases. Of those tested, 14.8% (39/264) children had a positive SARS-CoV-2 RT-PCR, and 63.6% (75/118) were positive for SARS-CoV-2 antibodies. In total 44·0% (118/268) required intensive care, which was more common in cases with a TSS phenotype. Three of five children with cardiac arrest had TSS phenotype. Three children (1·1%) died. INTERPRETATION: The strong association between SARS-CoV-2 infection and PIMS-TS emphasises the importance of maintaining low community infection rates to reduce the risk of this rare but severe complication in children and adolescents. Close follow-up will be important to monitor long-term complications in children with PIMS-TS. FUNDING: PHE.

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