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

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Abstract

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.

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Fear of the coronavirus (COVID-19): Predictors in an online study conducted in March 2020

Gaëtan Mertens, Lotte Gerritsen, Stefanie Duijndam … (2020)

Highlights • The coronavirus (COVID-19) outbreak is causing increased fear and worries. • In an online study (N = 439) we investigated predictors of fear of the coronavirus. • Increased fear was related to perceived risks for loved ones and health anxiety. • Increased fear was also related to regular and social media use. • We discuss implications for the management of fear of the coronavirus.

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Time series regression studies in environmental epidemiology

Krishnan Bhaskaran, Antonio Gasparrini, Shakoor Hajat … (2013)

Time series regression studies have been widely used in environmental epidemiology, notably in investigating the short-term associations between exposures such as air pollution, weather variables or pollen, and health outcomes such as mortality, myocardial infarction or disease-specific hospital admissions. Typically, for both exposure and outcome, data are available at regular time intervals (e.g. daily pollution levels and daily mortality counts) and the aim is to explore short-term associations between them. In this article, we describe the general features of time series data, and we outline the analysis process, beginning with descriptive analysis, then focusing on issues in time series regression that differ from other regression methods: modelling short-term fluctuations in the presence of seasonal and long-term patterns, dealing with time varying confounding factors and modelling delayed (‘lagged’) associations between exposure and outcome. We finish with advice on model checking and sensitivity analysis, and some common extensions to the basic model.

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Morbidity, mortality, and long-term consequences associated with diarrhoea from Cryptosporidium infection in children younger than 5 years: a meta-analyses study

Ibrahim Khalil, Christopher Troeger, Puja C Rao … (2018)

Summary Background The protozoan Cryptosporidium is a leading cause of diarrhoea morbidity and mortality in children younger than 5 years. However, the true global burden of Cryptosporidium infection in children younger than 5 years might have been underestimated in previous quantifications because it only took account of the acute effects of diarrhoea. We aimed to demonstrate whether there is a causal relation between Cryptosporidium and childhood growth and, if so, to quantify the associated additional burden. Methods The Global Burden of Diseases, Injuries, and Risk Factors study (GBD) 2016 was a systematic and scientific effort to quantify the morbidity and mortality associated with more than 300 causes of death and disability, including diarrhoea caused by Cryptosporidium infection. We supplemented estimates on the burden of Cryptosporidium in GBD 2016 with findings from a systematic review of published and unpublished cohort studies and a meta-analysis of the effect of childhood diarrhoea caused by Cryptosporidium infection on physical growth. Findings In 2016, Cryptosporidium infection was the fifth leading diarrhoeal aetiology in children younger than 5 years, and acute infection caused more than 48 000 deaths (95% uncertainty interval [UI] 24 600–81 900) and more than 4·2 million disability-adjusted life-years lost (95% UI 2·2 million–7·2 million). We identified seven data sources from the scientific literature and six individual-level data sources describing the relation between Cryptosporidium and childhood growth. Each episode of diarrhoea caused by Cryptosporidium infection was associated with a decrease in height-for-age Z score (0·049, 95% CI 0·014–0·080), weight-for-age Z score (0·095, 0·055–0·134), and weight-for-height Z score (0·126, 0·057–0·194). We estimated that diarrhoea from Cryptosporidium infection caused an additional 7·85 million disability-adjusted life-years (95% UI 5·42 million–10·11 million) after we accounted for its effect on growth faltering—153% more than that estimated from acute effects alone. Interpretation Our findings show that the substantial short-term burden of diarrhoea from Cryptosporidium infection on childhood growth and wellbeing is an underestimate of the true burden. Interventions designed to prevent and effectively treat infection in children younger than 5 years will have enormous public health and social development impacts. Funding The Bill & Melinda Gates Foundation.