Community factors and excess mortality in the COVID-19 pandemic in England, Italy and Sweden.

BACKGROUND: Analyses of coronavirus disease 19 suggest specific risk factors make communities more or less vulnerable to pandemic-related deaths within countries. What is unclear is whether the characteristics affecting vulnerability of small communities within countries produce similar patterns of excess mortality across countries with different demographics and public health responses to the pandemic. Our aim is to quantify community-level variations in excess mortality within England, Italy and Sweden and identify how such spatial variability was driven by community-level characteristics. METHODS: We applied a two-stage Bayesian model to quantify inequalities in excess mortality in people aged 40 years and older at the community level in England, Italy and Sweden during the first year of the pandemic (March 2020-February 2021). We used community characteristics measuring deprivation, air pollution, living conditions, population density and movement of people as covariates to quantify their associations with excess mortality. RESULTS: We found just under half of communities in England (48.1%) and Italy (45.8%) had an excess mortality of over 300 per 100 000 males over the age of 40, while for Sweden that covered 23.1% of communities. We showed that deprivation is a strong predictor of excess mortality across the three countries, and communities with high levels of overcrowding were associated with higher excess mortality in England and Sweden. CONCLUSION: These results highlight some international similarities in factors affecting mortality that will help policy makers target public health measures to increase resilience to the mortality impacts of this and future pandemics.

A comparison of small-area deprivation indicators for public-health surveillance in Sweden.

AIMS: The aims of this study were to construct a small-area index of multiple deprivation (IMD) from single deprivation indicators (SDIs) and to compare the explanatory power of the IMD and SDIs with regard to mortality. We considered a small-area division of Sweden consisting of 5985 DeSO (Demografiska statistikområden), each with a population size between 653 and 4243 at the end of 2018. METHODS: Four SDIs were provided by open-source data: (a) the proportion of inhabitants with a low economic standard; (b) the proportion of inhabitants aged 25-64 years with ⩽12 years of schooling; (c) the proportion of inhabitants aged 16-64 years who were not in paid employment; and (d) the proportion of inhabitants who lived in a rented apartment/house. A four-indicator IMD was constructed using factor analysis. As a validation, the IMD and SDIs were compared by exploring their DeSO-level associations with spatially smoothed death rates, with robustness checks of associations across different small-area contexts defined by degree of urbanisation and distribution of immigrants from non-Western countries. RESULTS: The constructed IMD and SDI1 performed essentially equally and outperformed SDI2, SDI3 and SDI4. Associations between IMD/SDI1 and the spatially smoothed death rates were most pronounced within the age range 60-79 years, showing 5-8% lowered rates among those categorised in the least deprived quintiles of IMD and SDI1, respectively, and 7-9% elevated rates among those categorised in the most deprived quintiles. These associations were consistent within each small-area context. CONCLUSIONS: We suggest prioritisation of SDI1, that is, a DeSO-level deprivation indicator based on open-access data on economic standard, for public-health surveillance in Sweden.

Community factors and excess mortality in first wave of the COVID-19 pandemic in England.

Risk factors for increased risk of death from COVID-19 have been identified, but less is known on characteristics that make communities resilient or vulnerable to the mortality impacts of the pandemic. We applied a two-stage Bayesian spatial model to quantify inequalities in excess mortality in people aged 40 years and older at the community level during the first wave of the pandemic in England, March-May 2020 compared with 2015-2019. Here we show that communities with an increased risk of excess mortality had a high density of care homes, and/or high proportion of residents on income support, living in overcrowded homes and/or with a non-white ethnicity. We found no association between population density or air pollution and excess mortality. Effective and timely public health and healthcare measures that target the communities at greatest risk are urgently needed to avoid further widening of inequalities in mortality patterns as the pandemic progresses.

Disease mapping of early- and late-stage cancer to monitor inequalities in early detection: a study of cutaneous malignant melanoma.

We consider disease mapping of early- and late-stage cancer, in order to identify and monitor inequalities in early detection. Our method is demonstrated by mapping cancer incidence at high geographical resolution using data on 10,302 cutaneous malignant melanoma (CMM) cases within the 3.7 million population of South-West Sweden. The cases were geocoded into small-areas, each with a population size between 600 and 2600 and accessible socio-demographic data. Using the disease mapping application Rapid Inquiry Facility (RIF) 4.0, we produced regional maps to visualise spatial variations in stage I, II and III-IV CMM incidences, complemented by local maps to explore the variations within two urban areas. Pronounced spatial disparities in stage I CMM incidence were revealed by the regional and local maps. Stage I CMM incidence was markedly higher in wealthier small-areas, in particular within each urban area. A twofold higher stage I incidence was observed, on average, in the wealthiest small-areas (upper quintile) than in the poorest small-areas (lower quintile). We identified in the regional map of stage III-IV CMM two clusters of higher or lower than expected late-stage incidences which were quite distinct from those identified for stage I. In conclusion, our analysis of CMM incidences supported the use of this method of cancer stage incidence mapping for revealing geographical and socio-demographic disparities in cancer detection.

Software application profile: the Rapid Inquiry Facility 4.0: an open access tool for environmental public health tracking.

The Rapid Inquiry Facility 4.0 (RIF) is a new user-friendly and open-access tool, developed by the UK Small Area Health Statistics Unit (SAHSU), to facilitate environment public health tracking (EPHT) or surveillance (EPHS). The RIF is designed to help public health professionals and academics to rapidly perform exploratory investigations of health and environmental data at the small-area level (e.g. postcode or detailed census areas) in order to identify unusual signals, such as disease clusters and potential environmental hazards, whether localized (e.g. industrial site) or widespread (e.g. air and noise pollution). The RIF allows the use of advanced disease mapping methods, including Bayesian small-area smoothing and complex risk analysis functionalities, while accounting for confounders. The RIF could be particularly useful to monitor spatio-temporal trends in mortality and morbidity associated with cardiovascular diseases, cancers, diabetes and chronic lung diseases, or to conduct local or national studies on air pollution, flooding, low-magnetic fields or nuclear power plants.

Risk of congenital anomalies near municipal waste incinerators in England and Scotland: Retrospective population-based cohort study.

BACKGROUND: Few studies have investigated congenital anomalies in relation to municipal waste incinerators (MWIs) and results are inconclusive. OBJECTIVES: To conduct a national investigation into the risk of congenital anomalies in babies born to mothers living within 10 km of an MWI associated with: i) modelled concentrations of PM10 as a proxy for MWI emissions more generally and; ii) proximity of residential postcode to nearest MWI, in areas in England and Scotland that are covered by a congenital anomaly register. METHODS: Retrospective population-based cohort study within 10 km of 10 MWIs in England and Scotland operating between 2003 and 2010. Exposure was proximity to MWI and log of daily mean modelled ground-level particulate matter ≤10 µm diameter (PM10) concentrations. RESULTS: Analysis included 219,486 births, stillbirths and terminations of pregnancy for fetal anomaly of which 5154 were cases of congenital anomalies. Fully adjusted odds ratio (OR) per doubling in PM10 was: 1·00 (95% CI 0·98-1·02) for all congenital anomalies; 0·99 (0·97-1·01) for all congenital anomalies excluding chromosomal anomalies. For every 1 km closer to an MWI adjusted OR was: 1·02 (1·00-1·04) for all congenital anomalies combined; 1·02 (1·00-1·04) for all congenital anomalies excluding chromosomal anomalies; and, for specific anomaly groups, 1·04 (1·01-1·08) for congenital heart defect sand 1·07 (1·02-1·12) for genital anomalies. DISCUSSION: We found no increased risk of congenital anomalies in relation to modelled PM10 emissions, but there were small excess risks associated with congenital heart defects and genital anomalies in proximity to MWIs. These latter findings may well reflect incomplete control for confounding, but a possible causal effect cannot be excluded.

Fetal growth, stillbirth, infant mortality and other birth outcomes near UK municipal waste incinerators; retrospective population based cohort and case-control study.

BACKGROUND: Some studies have reported associations between municipal waste incinerator (MWI) exposures and adverse birth outcomes but there are few studies of modern MWIs operating to current European Union (EU) Industrial Emissions Directive standards. METHODS: Associations between modelled ground-level particulate matter ≤10 µm in diameter (PM10) from MWI emissions (as a proxy for MWI emissions) within 10 km of each MWI, and selected birth and infant mortality outcomes were examined for all 22 MWIs operating in Great Britain 2003-10. We also investigated associations with proximity of residence to a MWI. Outcomes used were term birth weight, small for gestational age (SGA) at term, stillbirth, neonatal, post-neonatal and infant mortality, multiple births, sex ratio and preterm delivery sourced from national registration data from the Office for National Statistics. Analyses were adjusted for relevant confounders including year of birth, sex, season of birth, maternal age, deprivation, ethnicity and area characteristics and random effect terms were included in the models to allow for differences in baseline rates between areas and in incinerator feedstock. RESULTS: Analyses included 1,025,064 births and 18,694 infant deaths. There was no excess risk in relation to any of the outcomes investigated during pregnancy or early life of either mean modelled MWI PM10 or proximity to an MWI. CONCLUSIONS: We found no evidence that exposure to PM10 from, or living near to, an MWI operating to current EU standards was associated with harm for any of the outcomes investigated. Results should be generalisable to other MWIs operating to similar standards.