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ObjectiveTo establish the impact of the first six months of the COVID-19 outbreak response of gastrointestinal (GI) infection trends in England. DesignRetrospective ecological study using routinely collected national and regional surveillance data from eight Public Health England coordinated laboratory, outbreak and syndromic surveillance systems using key dates of UK governmental policy change to assign phases for comparison between 2020 and historic data. ResultsDecreases in GI illness activity were observed across all surveillance indicators as COVID-19 cases began to peak. Compared to the 5-year average (2015-2019), during the first six months of the COVD-19 response, there was a 52% decrease in GI outbreaks reported (1,544 vs. 3,208 (95% CI: 2,938 - 3,478) and a 34% decrease in laboratory confirmed cases (27,859 vs. 42,495 (95% CI: 40,068 - 44,922). GI indicators began to rise during the first lockdown and lockdown easing, although all remained substantially lower than historic figures. Reductions in laboratory confirmed cases were observed across all age groups and both sexes, with geographical heterogeneity observed in diagnosis trends. Health seeking behaviour changed substantially, with attendances decreasing prior to lockdown across all indicators. ConclusionsThere has been a marked change in trends of GI infections in the context of the COVID-19 pandemic. The drivers of this change are likely to be multifactorial; while changes in health seeking behaviour, pressure on diagnostic services and surveillance system ascertainment have undoubtably played a role there has likely been a true decrease in the incidence for some pathogens resulting from the control measures and restrictions implemented. This suggests that if some of these changes in behaviour such as improved hand hygiene were maintained, then we could potentially see sustained reductions in the burden of GI illness. Strengths and limitations of this studyO_LIOur findings show that there has been a marked change in the burden of GI infections during the COVID-19 outbreak, and although undoubtably changes to health care and surveillance ascertainment have played a role, there does appear to be a true decrease in incidence. These findings suggest that if effective implementation of infection control measures were maintained, then we could see sustained reductions in the person to person transmission of GI illness in England. C_LIO_LIThis study was strengthened by the triangulation of data from several national and regional-based surveillance systems; using this approach we could determine that the trends observed were consistent across all indicators. C_LIO_LIIt has not been possible to definitively differentiate the relative contributions of the reduced ascertainment of GI infections versus a true decrease in GI disease burden in this study, which an additional focussed analysis could address. C_LIO_LIThis analysis includes only the first six-months of the COVID-19 outbreak response, and further longitudinal analyses will be performed to explore this further and assess any change as we move into further phases of the pandemic C_LI
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The spatio-temporal dynamics of an outbreak provide important insights to help direct public health resources intended to control transmission. They also provide a focus for detailed epidemiological studies and allow the timing and impact of interventions to be assessed. A common approach is to aggregate case data to administrative regions. Whilst providing a good visual impression of change over space, this method masks spatial variation and assumes that disease risk is constant across space. Risk factors for COVID-19 (e.g. population density, deprivation and ethnicity) vary from place to place across England so it follows that risk will also vary spatially. Kernel density estimation compares the spatial distribution of cases relative to the underlying population, unfettered by arbitrary geographical boundaries, to produce a continuous estimate of spatially varying risk. Using test results from healthcare settings in England (Pillar 1 of the UK Government testing strategy) and freely available methods and software, we estimated the spatial and spatio-temporal risk of COVID-19 infection across England for the first six months of 2020. Widespread transmission was underway when partial lockdown measures were introduced on the 23rd March 2020 and the greatest risk erred towards large urban areas. The rapid growth phase of the outbreak coincided with multiple introductions to England from the European mainland. The spatio-temporal risk was highly labile throughout. In terms of controlling transmission, the most important practical application is the accurate identification of areas within regions that may require tailored intervention strategies. We recommend that this approach is absorbed into routine surveillance outputs in England. Further risk characterisation using widespread community testing (Pillar 2) data is needed as is the increased use of predictive spatial models at fine spatial scales.
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BackgroundHouseholds appear to be the highest risk setting for transmission of COVID-19. Large household transmission studies were reported in the early stages of the pandemic in Asia with secondary attack rates ranging from 5-30% but few large scale household transmission studies have been conducted outside of Asia. MethodsA prospective case ascertained study design based on the World Health Organization FFX protocol was undertaken in the UK following the detection of the first case in late January 2020. Household contacts of cases were followed using enhanced surveillance forms to establish whether they developed symptoms of COVID-19, became confirmed cases and their outcomes. Household secondary attack rates and serial intervals were estimated. Individual and household basic reproduction numbers were also estimated. The incubation period was estimated using known point source exposures that resulted in secondary cases. ResultsA total of 233 households with two or more people were included with a total of 472 contacts. The overall household SAR was 37% (95% CI 31-43%) with a mean serial interval of 4.67 days, an R0 of 1.85 and a household reproduction number of 2.33. We find lower secondary attack rates in larger households. SARs were highest when the primary case was a child. We estimate a mean incubation period of around 4.5 days. ConclusionsHigh rates of household transmission of COVID-19 were found in the UK emphasising the need for preventative measures in this setting. Careful monitoring of schools reopening is needed to monitor transmission from children.
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ObjectivesFollowing detection of the first virologically-confirmed cases of COVID-19 in Great Britain, an enhanced surveillance study was initiated by Public Health England to describe the clinical presentation, course of disease and underlying health conditions associated with infection of the first few hundred cases. MethodsInformation was collected on the first COVID-19 cases according to the First Few X WHO protocol. Case-control analyses of the sensitivity, specificity and predictive value of symptoms and underlying health conditions associated with infection were conducted. Point prevalences of underlying health conditions among the UK general population were presented. FindingsThe majority of FF100 cases were imported (51.4%), of which the majority had recent travel to Italy (71.4%). 24.7% were secondary cases acquired mainly through household contact (40.4%). Children had lower odds of COVID-19 infection compared with the general population. The clinical presentation of cases was dominated by cough, fever and fatigue. Non-linear relationships with age were observed for fever, and sensitivity and specificity of symptoms varied by age. Conditions associated with higher odds of COVID-19 infection (after adjusting for age and sex) were chronic heart disease, immunosuppression and multimorbidity. ConclusionThis study presents the first epidemiological and clinical summary of COVID-19 cases in Great Britain. The FFX study design enabled systematic data collection. The study characterized underlying health conditions associated with infection and set relative risks in context with population prevalence estimates. It also provides important evidence for generating case definitions to support public health risk assessment, clinical triage and diagnostic algorithms.
