Impact of the COVID-19 restrictions on the epidemiology of Cryptosporidium spp. in England and Wales, 2015-2021: a time series analysis.

Introduction. In England and Wales, cryptosporidiosis cases peak in spring and autumn, associated with zoonotic/environmental exposures (Cryptosporidium parvum, spring/autumn) and overseas travel/water-based activities (Cryptosporidium hominis, autumn). Coronavirus disease 2019 (COVID-19) restrictions prevented social mixing, overseas travel and access to venues (swimming pools/restaurants) for many months, potentially increasing environmental exposures as people sought alternative countryside activities.Hypothesis. COVID-19 restrictions reduced incidence of C. hominis cases and potentially increased incidence of C. parvum cases.Aim. To inform/strengthen surveillance programmes, we investigated the impact of COVID-19 restrictions on the epidemiology of C. hominis and C. parvum cases.Methodology. Cases were extracted from the Cryptosporidium Reference Unit (CRU) database (1 January 2015 to 31 December 2021). We defined two periods for pre- and post-COVID-19 restrictions implementation, corresponding to before and after the first UK-wide lockdown on 23 March 2020. We conducted a time series analysis, assessing differences in C. parvum and C. hominis incidence, trends and periodicity between these periods.Results. There were 21 304 cases (C. parvum=12 246; C. hominis=9058). Post-restrictions implementation incidence of C. hominis dropped by 97.5 % (95 % CI: 95.4-98.6 %; P<0.001). The decreasing incidence trend pre-restrictions was not observed post-restrictions implementation due to lack of cases. No periodicity change was observed post-restrictions implementation. There was a strong social gradient; there was a higher proportion of cases in deprived areas. For C. parvum, post-restrictions implementation incidence fell by 49.0 % (95 % CI: 38.4-58.3 %; P<0.001). There was no pre-restrictions incidence trend but an increasing incidence trend post-restrictions implementation. A periodicity change was observed post-restriction implementation, peaking 1 week earlier in spring and 2 weeks later in autumn. The social gradient was the inverse of that for C. hominis. Where recorded, 22 % of C. hominis and 8 % of C. parvum cases had travelled abroad.Conclusion. C. hominis cases almost entirely ceased post-restrictions implementation, reinforcing that foreign travel seeds infections. C. parvum incidence fell sharply but recovered post-restrictions implementation, consistent with relaxation of restrictions. Future exceedance reporting for C. hominis should exclude the post-restriction implementation period but retain it for C. parvum (except the first 6 weeks post-restrictions implementation). Infection prevention and control advice should be improved for people with gastrointestinal illness (GI) symptoms to ensure hand hygiene and swimming pool avoidance.

Social, demographic and behavioural determinants of SARS-CoV-2 infection: a case-control study carried out during mass community testing of asymptomatic individuals in South Wales, December 2020.

Between 21 November and 22 December 2020, a SARS-CoV-2 community testing pilot took place in the South Wales Valleys. We conducted a case-control study in adults taking part in the pilot using an anonymous online questionnaire. Social, demographic and behavioural factors were compared in people with a positive lateral flow test (cases) and a sample of negatives (controls). A total of 199 cases and 2621 controls completed a questionnaire (response rates: 27.1 and 37.6% respectively). Following adjustment, cases were more likely to work in the hospitality sector (aOR 3.39, 95% CI 1.43-8.03), social care (aOR 2.63, 1.22-5.67) or healthcare (aOR 2.31, 1.29-4.13), live with someone self-isolating due to contact with a case (aOR 3.07, 2.03-4.62), visit a pub (aOR 2.87, 1.11-7.37) and smoke or vape (aOR 1.54, 1.02-2.32). In this community, and at this point in the epidemic, reducing transmission from a household contact who is self-isolating would have the biggest public health impact (population-attributable fraction: 0.2). As restrictions on social mixing are relaxed, hospitality venues will become of greater public health importance, and those working in this sector should be adequately protected. Smoking or vaping may be an important modifiable risk factor.

A large outbreak of COVID-19 in a UK prison, October 2020 to April 2021.

Prisons are susceptible to outbreaks. Control measures focusing on isolation and cohorting negatively affect wellbeing. We present an outbreak of coronavirus disease 2019 (COVID-19) in a large male prison in Wales, UK, October 2020 to April 2021, and discuss control measures.We gathered case-information, including demographics, staff-residence postcode, resident cell number, work areas/dates, test results, staff interview dates/notes and resident prison-transfer dates. Epidemiological curves were mapped by prison location. Control measures included isolation (exclusion from work or cell-isolation), cohorting (new admissions and work-area groups), asymptomatic testing (case-finding), removal of communal dining and movement restrictions. Facemask use and enhanced hygiene were already in place. Whole-genome sequencing (WGS) and interviews determined the genetic relationship between cases plausibility of transmission.Of 453 cases, 53% (n = 242) were staff, most aged 25-34 years (11.5% females, 27.15% males) and symptomatic (64%). Crude attack-rate was higher in staff (29%, 95% CI 26-64%) than in residents (12%, 95% CI 9-15%).Whole-genome sequencing can help differentiate multiple introductions from person-to-person transmission in prisons. It should be introduced alongside asymptomatic testing as soon as possible to control prison outbreaks. Timely epidemiological investigation, including data visualisation, allowed dynamic risk assessment and proportionate control measures, minimising the reduction in resident welfare.

Assessing the exposure to air pollution during transport in urban areas – Evidence review

Introduction In recent years, questions have been asked about how people's exposure to air pollution varies across different transport modes, particularly in urban areas and how various factors, such as route choice and proximity to motorised transport for active travellers, characteristics of public transport vehicles, ventilation settings for cars and time of the day, may affect exposure. Methods A comprehensive review was carried out to identify studies reporting measurements of pollutant concentrations in urban transport microenvironments published between January 2016 and July 2020 in Medline, Scopus and Embase databases. Average exposure values and ranges per transport mode were calculated, as well as the ratios of exposure between transport modes and factors within the same study. Results Higher concentrations of air pollutants were often experienced in motorised transport compared to cycling and walking. However, closing car windows and operating ventilation in recirculation mode was found to lower particulate pollution concentrations inside cars. Pedestrians and cyclists were generally exposed to lower concentrations of air pollution when using routes separated from motorised traffic;the exposure of cyclists could be over three times higher when cycling on a high-traffic route compared to cycling on a traffic-free route and over four times higher when comparing cycling on-carriageway with cycling on a separated cycle lane. Conclusions The consolidation of evidence from this review can inform consistent public health messaging as well as development of transport and planning policies in urban areas. Considering wider, long-term public health and environmental benefits, every effort should be made to prioritise active travel and public transport and enable more people to use these modes. Also, the COVID-19 pandemic has resulted in clear changes in travelling. Maintaining some of these changes, such as reductions in the numbers of unnecessary motorised trips could be beneficial through reductions in congestion and air pollution.

Risk factors for outbreaks of COVID-19 in care homes following hospital discharge: A national cohort analysis.

BACKGROUND: The population of adult residential care homes has been shown to have high morbidity and mortality in relation to COVID-19. METHODS: We examined 3115 hospital discharges to a national cohort of 1068 adult care homes and subsequent outbreaks of COVID-19 occurring between 22 February and 27 June 2020. A Cox proportional hazards regression model was used to assess the impact of time-dependent exposure to hospital discharge on incidence of the first known outbreak, over a window of 7-21 days after discharge, and adjusted for care home characteristics, including size and type of provision. RESULTS: A total of 330 homes experienced an outbreak, and 544 homes received a discharge over the study period. Exposure to hospital discharge was not associated with a significant increase in the risk of a new outbreak (hazard ratio 1.15, 95% CI 0.89, 1.47, P = .29) after adjusting for care home characteristics. Care home size was the most significant predictor. Hazard ratios (95% CI) in comparison with homes of <10 residents were as follows: 3.40 (1.99, 5.80) for 10-24 residents; 8.25 (4.93, 13.81) for 25-49 residents; and 17.35 (9.65, 31.19) for 50+ residents. When stratified for care home size, the outbreak rates were similar for periods when homes were exposed to a hospital discharge, in comparison with periods when homes were unexposed. CONCLUSION: Our analyses showed that large homes were at considerably greater risk of outbreaks throughout the epidemic, and after adjusting for care home size, a discharge from hospital was not associated with a significant increase in risk.