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The potential utility of wastewater-based epidemiology as an early warning tool has been explored widely across the globe during the current COVID-19 pandemic. Methods to detect the presence of SARS-CoV-2 RNA in wastewater were developed early in the pandemic, and extensive work has been conducted to evaluate the relationship between viral concentration and COVID-19 case numbers at the catchment areas of sewage treatment works (STWs) over time. However, no attempt has been made to develop a model that predicts wastewater concentration at fine spatio-temporal resolutions covering an entire country, a necessary step towards using wastewater monitoring for the early detection of local outbreaks. We consider weekly averages of flow-normalised viral concentration, reported as the number of SARS-CoV-2 N1 gene copies per litre (gc/L) of wastewater available at 303 STWs over the period between 1 June 2021 and 30 March 2022. We specify a spatially continuous statistical model that quantifies the relationship between weekly viral concentration and a collection of covariates covering socio-demographics, land cover and virus-associated genomic characteristics at STW catchment areas while accounting for spatial and temporal correlation. We evaluate the models predictive performance at the catchment level through 10-fold cross-validation. We predict the weekly viral concentration at the population-weighted centroid of the 32,844 lower super output areas (LSOAs) in England, then aggregate these LSOA predictions to the Lower Tier Local Authority level (LTLA), a geography that is more relevant to public health policy-making. We also use the model outputs to quantify the probability of local changes of direction (increases or decreases) in viral concentration over short periods (e.g. two consecutive weeks). The proposed statistical framework is able to predict SARS-CoV-2 viral concentration in wastewater at high spatio-temporal resolution across England. Additionally, the probabilistic quantification of local changes can be used as an early warning tool for public health surveillance.
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BackgroundThe prevalence of SARS-CoV-2 infection continues to drive rates of illness and hospitalisations despite high levels of vaccination, with the proportion of cases caused by the Delta lineage increasing in many populations. As vaccination programs roll out globally and social distancing is relaxed, future SARS-CoV-2 trends are uncertain. MethodsWe analysed prevalence trends and their drivers using reverse transcription-polymerase chain reaction (RT-PCR) swab-positivity data from round 12 (between 20 May and 7 June 2021) and round 13 (between 24 June and 12 July 2021) of the REal-time Assessment of Community Transmission-1 (REACT-1) study, with swabs sent to non-overlapping random samples of the population ages 5 years and over in England. ResultsWe observed sustained exponential growth with an average doubling time in round 13 of 25 days (lower Credible Interval of 15 days) and an increase in average prevalence from 0.15% (0.12%, 0.18%) in round 12 to 0.63% (0.57%, 0.18%) in round 13. The rapid growth across and within rounds appears to have been driven by complete replacement of Alpha variant by Delta, and by the high prevalence in younger less-vaccinated age groups, with a nine-fold increase between rounds 12 and 13 among those aged 13 to 17 years. Prevalence among those who reported being unvaccinated was three-fold higher than those who reported being fully vaccinated. However, in round 13, 44% of infections occurred in fully vaccinated individuals, reflecting imperfect vaccine effectiveness against infection despite high overall levels of vaccination. Using self-reported vaccination status, we estimated adjusted vaccine effectiveness against infection in round 13 of 49% (22%, 67%) among participants aged 18 to 64 years, which rose to 58% (33%, 73%) when considering only strong positives (Cycle threshold [Ct] values < 27); also, we estimated adjusted vaccine effectiveness against symptomatic infection of 59% (23%, 78%), with any one of three common COVID-19 symptoms reported in the month prior to swabbing. Sex (round 13 only), ethnicity, household size and local levels of deprivation jointly contributed to the risk of higher prevalence of swab-positivity. DiscussionFrom end May to beginning July 2021 in England, where there has been a highly successful vaccination campaign with high vaccine uptake, infections were increasing exponentially driven by the Delta variant and high infection prevalence among younger, unvaccinated individuals despite double vaccination continuing to effectively reduce transmission. Although slower growth or declining prevalence may be observed during the summer in the northern hemisphere, increased mixing during the autumn in the presence of the Delta variant may lead to renewed growth, even at high levels of vaccination.
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BackgroundThe programme to vaccinate adults in England has been rapidly implemented since it began in December 2020. The community prevalence of SARS-CoV-2 anti-spike protein antibodies provides an estimate of total cumulative response to natural infection and vaccination. We describe the distribution of SARS-CoV-2 IgG antibodies in adults in England in May 2021 at a time when approximately 7 in 10 adults had received at least one dose of vaccine. MethodsSixth round of REACT-2 (REal-time Assessment of Community Transmission-2), a cross-sectional random community survey of adults in England, from 12 to 25 May 2021; 207,337 participants completed questionnaires and self-administered a lateral flow immunoassay test producing a positive or negative result. ResultsVaccine coverage with one or more doses, weighted to the adult population in England, was 72.9% (95% confidence interval 72.7-73.0), varying by age from 25.1% (24.5-25.6) of those aged 18 to 24 years, to 99.2% (99.1-99.3) of those 75 years and older. In adjusted models, odds of vaccination were lower in men (odds ratio [OR] 0.89 [0.85-0.94]) than women, and in people of Black (0.41 [0.34-0.49]) compared to white ethnicity. There was higher vaccine coverage in the least deprived and highest income households. People who reported a history of COVID-19 were less likely to be vaccinated (OR 0.61 [0.55-0.67]). There was high coverage among health workers (OR 9.84 [8.79-11.02] and care workers (OR 4.17 [3.20-5.43]) compared to non-key workers, but lower in hospitality and retail workers (OR 0.73 [0.64-0.82] and 0.77 [0.70-0.85] respectively) after adjusting for age and key covariates. The prevalence of antibodies (weighted to the adult population of England and adjusted for test characteristics) was 61.1% (95% CI 60.9-61.4), up from 6.6% (5.4-5.7) in round 4 (27 October to 10 November 2020) and 13.9% (13.7-14.1) in round 5 (26 January to 8 February 2021). Prevalence (adjusted and weighted) increased with age, from 35.8% (35.1-36.5) in those aged 18 to 24 years, to 95.3% (94.6-95.9) in people 75 and over. Antibodies were 30% less likely to be detected in men than women (adjusted OR 0.69, 0.68-0.70), and were higher in people of Asian (OR 1.67 [1.58-1.77]), Black (1.55 [1.41-1.69]), mixed 1.17 [1.06-1.29] and other (1.37 [1.23-1.51]) ethnicities compared with white ethnicity. Workers in hospitality (OR 0.69 [0.63-0.74]) and retail (0.71 [0.67-0.75]) were less likely to have antibodies. Following two doses of Pfizer-BioNTech vaccine, antibody positivity (adjusted for test performance) was 100% (100-100) at all ages except 80 years and older when it was 97.8% (95.9-99.6). For AstraZeneca positivity was over 90% up to age 69, and then 89.2% (88.5-89.9) in 70-79 year olds and 83.6% (78.5-88.3) in those aged 80 and over. Following a single dose of Pfizer-BioNTech positivity ranged from 100.0% (91.1-100.0) in those aged 18-29 to 32.2% (18.2-51.1) in those aged 70-79 years. For AstraZeneca this was 72.2% (68.5-75.9) in the youngest and 46.2% (40.0-52.7) in the oldest age group. DiscussionThe successful roll out of the vaccination programme in England has led to a high proportion of individuals having detectable antibodies, particularly in older age groups and those who have had two doses of vaccine. This is likely to be associated with high levels of protection from severe disease, and possibly from infection. Nonetheless, there remain some key groups with a lower prevalence of antibody, notably unvaccinated younger people, certain minority ethnic groups, those living in deprived areas and workers in some public facing employment. Obtaining improved rates of vaccination in these groups is essential to achieving high levels of protection against the virus through population immunity. FundingDepartment of Health and Social Care in England.
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The ongoing coronavirus disease 2019 (COVID-19) pandemic is heterogeneous throughout Africa and threatening millions of lives. Surveillance and short-term modeling forecasts are critical to provide timely information for decisions on control strategies. We use a model that explains the evolution of the COVID-19 pandemic over time in the entire African continent, parameterized by socioeconomic and geoeconomic variations and the lagged effects of social policy and meteorological history. We observed the effect of the human development index, containment policies, testing capacity, specific humidity, temperature and landlocked status of countries on the local within-country and external between-country transmission. One week forecasts of case numbers from the model were driven by the quality of the reported data. Seeking equitable behavioral and social interventions, balanced with coordinated country-specific strategies in infection suppression, should be a continental priority to control the COVID-19 pandemic in Africa.
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BackgroundCalls are increasing for widespread SARS-CoV-2 infection testing of people from populations with a very low prevalence of infection. We quantified the impact of less than perfect diagnostic test accuracy on populations, and on individuals, in low prevalence settings, focusing on false positives and the role of confirmatory testing. MethodsWe developed a simple, interactive tool to assess the impact of different combinations of test sensitivity, specificity and infection prevalence in a notional population of 100,000. We derived numbers of true positives, true negatives, false positives and false negatives, positive predictive value (PPV - the percentage of test positives that are true positives) and overall test accuracy for three testing strategies: (1) single test for all; (2) add repeat testing in test positives; (3) add further repeat testing in those with discrepant results. We also assessed the impact on test results for individuals having one, two or three tests under these three strategies. ResultsWith sensitivity of 80%, infection prevalence of 1 in 2,000, and specificity 99.9% on all tests, PPV in the tested population of 100,000 will be only 29% with one test, increasing to > 99.5% (100% when rounded to the nearest %) with repeat testing in strategies 2 or 3. More realistically, if specificity is 95% for the first and 99.9% for subsequent tests, single test PPV will be only 1%, increasing to 86% with repeat testing in strategy 2, or 79% with strategy 3 (albeit with 6 fewer false negatives than strategy 2). In the whole population, or in particular individuals, PPV increases as infection becomes more common in the population but falls to unacceptably low levels with lower test specificity. ConclusionTo avoid multiple unnecessary restrictions on whole populations, and in particular individuals, from widespread population testing for SARS-CoV-2, the crucial roles of extremely high test specificity and of confirmatory testing must be fully appreciated and incorporated into policy decisions.
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Control of the COVID-19 pandemic requires a detailed understanding of prevalence of SARS-CoV-2 virus in the population. Case-based surveillance is necessarily biased towards symptomatic individuals and sensitive to varying patterns of reporting in space and time. The real-time assessment of community transmission antigen study (REACT-1) is designed to overcome these limitations by obtaining prevalence data based on a nose and throat swab RT-PCR test among a representative community-based sample in England, including asymptomatic individuals. Here, we describe results comparing rounds 1 and 2 carried out during May and mid June / early July 2020 respectively across 315 lower tier local authority areas. In round 1 we found 159 positive samples from 120,620 tested swabs while round 2 there were 123 positive samples from 159,199 tested swabs, indicating a downwards trend in prevalence from 0.13% (95% CI, 0.11%, 0.15%) to 0.077% (0.065%, 0.092%), a halving time of 38 (28, 58) days, and an R of 0.89 (0.86, 0.93). The proportion of swab-positive participants who were asymptomatic at the time of sampling increased from 69% (61%, 76%) in round 1 to 81% (73%, 87%) in round 2. Although health care and care home workers were infected far more frequently than other workers in round 1, the odds were markedly reduced in round 2. Age patterns of infection changed between rounds, with a reduction by a factor of five in prevalence in 18 to 24 year olds. Our data were suggestive of increased risk of infection in Black and Asian (mainly South Asian) ethnicities. Using regional and detailed case location data, we detected increased infection intensity in and near London. Under multiple sensitivity analyses, our results were robust to the possibility of false positives. At the end of the initial lockdown in England, we found continued decline in prevalence and a shift in the pattern of infection by age and occupation. Community-based sampling, including asymptomatic individuals, is necessary to fully understand the nature of ongoing transmission.
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BackgroundStudies suggest that certain Black and Asian Minority Ethnic groups experience poorer outcomes from COVID-19 but these studies have not provided insight into potential reasons for this. We hypothesised that outcomes would be poorer for those of South Asian ethnicity hospitalised from a confirmed SARS-CoV-2 infection, once confounding factors, health seeking behaviours and community demographics were considered and that this might reflect a more aggressive disease course in these patients. MethodsPatients with confirmed SARS-CoV-2 infection requiring admission to University Hospitals Birmingham NHS Foundation Trust(UHB) in Birmingham UK between 10th March 2020-17th April 2020 were included. Standardised Admission Ratio(SAR) and Standardised Mortality Ratio(SMR) were calculated using observed COVID-19 admissions/deaths and 2011 census data. Hazard Ratio (aHR) for mortality was estimated using Cox proportional hazard model adjusting and propensity score matching. ResultsAll patients admitted to UHB with COVID-19 during the study period were included (2217 in total). Fifty-eight percent were male, 69.5% White and the majority (80.2%) had co-morbidities. Eighteen and a half percent were of South Asian ethnicity, and these patients were more likely to be younger, have no co-morbidities but twice the prevalence of diabetes than White patients. SAR and SMR suggested more admissions and deaths in South Asian patients than would be predicted and they were more likely to present with severe disease despite no delay in presentation since symptom onset. South Asian ethnicity was associated with an increased risk of death; both by Cox regression (Hazard Ratio 1.4 (95%CI 1.2-1.8) after adjusting for age, sex, deprivation and comorbidities and by propensity score matching, matching for the same factors but categorising ethnicity into South Asian or not (Hazard ratio 1.3 (1.0-1.6)). ConclusionsThose of South Asian ethnicity appear at risk of worse COVID-19 outcomes, further studies need to establish the underlying mechanistic pathways.
