Lessons learned and lessons missed: Impact of the Covid-19 pandemic on all-cause mortality in 40 industrialised countries prior to mass vaccination (preprint)

Industrialised countries have varied in their early response to the Covid-19 pandemic, and how they have adapted to new situations and knowledge since the pandemic began. These variations in preparedness and policy may lead to different death tolls from Covid-19 as well as from other diseases. We applied an ensemble of 16 Bayesian probabilistic models to vital statistics data to estimate the impacts of the pandemic on weekly all-cause mortality for 40 industrialised countries from mid-February 2020 through mid-February 2021, before a large segment of the population was vaccinated in any of these countries. Taken over the entire year, an estimated 1,401,900 (95% credible interval 1,259,700-1,572,500) more people died in these 40 countries than would have been expected had the pandemic not taken place. This is equivalent to 140 (126-157) additional deaths per 100,000 people and a 15% (13-17) increase in deaths over this period in all of these countries combined. In Iceland, Australia and New Zealand, mortality was lower over this period than what would be expected if the pandemic had not occurred, while South Korea and Norway experienced no detectable change in mortality. In contrast, the populations of the USA, Czechia, Slovakia and Poland experienced at least 20% higher mortality. There was substantial heterogeneity across countries in the dynamics of excess mortality. The first wave of the pandemic, from mid-February to the end of May 2020, accounted for over half of excess deaths in Scotland, Spain, England and Wales, Canada, Sweden, Belgium and Netherlands. At the other extreme, the period between mid-September 2020 and mid-February 2021 accounted for over 90% of excess deaths in Bulgaria, Croatia, Czechia, Hungary, Latvia, Montenegro, Poland, Slovakia and Slovenia. Until the great majority of national and global populations have vaccine-acquired immunity, minimising the death toll of the pandemic from Covid-19 and other diseases will remain dependent on actions to delay and contain infections and continue routine health and social care.

Community factors and excess mortality in first wave of the COVID-19 pandemic. (preprint)

Risk factors for increased risk of death from Coronavirus Disease 19 (COVID-19) have been identified1,2 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 at the community level during the first wave of the pandemic in England. We used geocoded data on all deaths in people aged 40 years and older during March-May 2020 compared with 2015-2019 in 6,791 local communities. 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 high percent of people with a non-White ethnicity (including Black, Asian and other minority ethnic groups). Conversely, after accounting for other community characteristics, we found no association between population density or air pollution and excess mortality. Overall, the social and environmental variables accounted for around 15% of the variation in mortality at community level. Effective and timely public health and healthcare measures that target the communities at greatest risk are urgently needed if England and other industrialised countries are to avoid further widening of inequalities in mortality patterns during the second wave.

Long-term exposure to air-pollution and COVID-19 mortality in England: a hierarchical spatial analysis (preprint)

Background: Recent studies suggested a link between long-term exposure to air-pollution and COVID-19 mortality. However, due to their ecological design, based on large spatial units, they neglect the strong localised air-pollution patterns, and potentially lead to inadequate confounding adjustment. We investigated the effect of long-term exposure to NO2 and PM2.5 on COVID-19 deaths up to June 30, 2020 in England using high geographical resolution. Methods: We included 38 573 COVID-19 deaths up to June 30, 2020 at the Lower Layer Super Output Area level in England (n=32 844 small areas). We retrieved averaged NO2 and PM2.5 concentration during 2014-2018 from the Pollution Climate Mapping. We used Bayesian hierarchical models to quantify the effect of air-pollution while adjusting for a series of confounding and spatial autocorrelation. Findings: We find a 0.5% (95% credible interval: -0.2%-1.2%) and 1.4% (-2.1%-5.1%) increase in COVID-19 mortality rate for every 1g/m3 increase in NO2 and PM2.5 respectively, after adjusting for confounding and spatial autocorrelation. This corresponds to a posterior probability of a positive effect of 0.93 and 0.78 respectively. The spatial relative risk at LSOA level revealed strong patterns, similar for the different pollutants. This potentially captures the spread of the disease during the first wave of the epidemic. Interpretation: Our study provides some evidence of an effect of long-term NO2 exposure on COVID-19 mortality, while the effect of PM2.5 remains more uncertain. Funding: Medical Research Council, Wellcome Trust, Environmental Protection Agency and National Institutes of Health.

Magnitude, demographics and dynamics of the impact of the first phase of the Covid-19 pandemic on all-cause mortality in 17 industrialised countries (preprint)

The Covid-19 pandemic affects mortality directly through infection as well as through changes in the social, environmental and healthcare determinants of health1. The impacts on mortality are likely to vary across countries in magnitude, timing, and age and sex composition. Here, we applied an ensemble of 16 Bayesian probabilistic models to vital statistics data, by age group and sex, to consistently and comparably estimate the impacts of the first phase of the pandemic on all-cause mortality for 17 industrialised countries. The models accounted for factors that affect death rates including seasonality, temperature, and public holidays, as well as for medium-long-term secular trends and the dependency of death rates in each week on those in preceding week(s). From mid-February through the end of May 2020, an estimated 202,900 (95% credible interval 179,400-224,900) more people died in these 17 countries than would have had the pandemic not taken place. Nearly three quarters of these excess deaths occurred in England and Wales, Italy and Spain, where less than half of the total population of these countries live. When all-cause mortality is considered, the total number of deaths, deaths per 100,000 people, and relative increase in deaths were similar between men and women in most countries. Further, in many countries, the balance of excess deaths changed from male-dominated early in the pandemic to being equal or female-dominated later on. Taken over the entire first phase of the pandemic, there was no detectable rise in all-cause mortality in New Zealand, Bulgaria, Hungary, Norway, Denmark and Finland and for women in Austria and Switzerland (posterior probability of an increase in deaths <90%). Women in Portugal and men in Austria experienced relatively small increases in all-cause mortality, with posterior probabilities of 90-99%. For men in Switzerland and Portugal, and both sexes in the Netherlands, France, Sweden, Belgium, Italy, Scotland, Spain and England and Wales, all-cause mortality increased as a result of the pandemic with a posterior probability >99%. After accounting for population size, England and Wales and Spain experienced the highest death toll, nearly 100 deaths per 100,000 people; they also had the largest relative (percent) increase in deaths (37% (95% credible interval 30-44) in England and Wales; 38% (31-44) in Spain). New Zealand, Bulgaria, Hungary, Norway, Denmark and Finland experienced changes in deaths that ranged from possible slight declines to increases of no more than 5%. The large impact in England and Wales stems partly from having experienced (together with Spain) the highest weekly increases in deaths, more than doubling in some weeks, and having had (together with Sweden) the longest duration when deaths exceeded levels that would be expected in the absence of the pandemic. The heterogeneous magnitude and character of the excess deaths due to the Covid-19 pandemic reflect differences in how well countries have managed the pandemic (e.g., timing, extent and adherence to lockdowns and other social distancing measures; effectiveness of test, trace and isolate mechanisms), and the resilience and preparedness of the health and social care system (e.g., effective facility and community care pathways; minimising spread of infection within hospitals and care homes, and between them and the community).

Age- and sex-specific total mortality impacts of the early weeks of the Covid-19 pandemic in England and Wales: Application of a Bayesian model ensemble to mortality statistics (preprint)

Background: The Covid-19 pandemic affects mortality directly through infection as well as through changes in the social, environmental and healthcare determinants of health. The impacts on mortality are likely to vary, in both magnitude and timing, by age and sex. Our aim was to estimate the total mortality impacts of the pandemic, by sex, age group and week. Methods: We developed an ensemble of 16 Bayesian models that probabilistically estimate the weekly number of deaths that would be expected had the Covid-19 pandemic not occurred. The models account for seasonality of death rates, medium-long-term trends in death rates, the impact of temperature on death rates, association of death rates in each week on those in preceding week(s), and the impact of bank holidays. We used data from January 2010 through mid-February 2020 (i.e., week starting 15th February 2020) to estimate the parameters of each model, which was then used to predict the number of deaths for subsequent weeks as estimates of death rates if the pandemic had not occurred. We subtracted these estimates from the actual reported number of deaths to measure the total mortality impact of the pandemic. Results: In the week that began on 21st March, the same week that a national lockdown was put in place, there was a >92% probability that there were more deaths in men and women aged [≥]45 years than would occur in the absence of the pandemic; the probability was 100% from the subsequent week. Taken over the entire period from mid-February to 8th May 2020, there were an estimated [~] 49,200 (44,700-53,300) or 43% (37-48) more deaths than would be expected had the pandemic not taken place. 22,900 (19,300-26,100) of these deaths were in females (40% (32-48) higher than if there had not been a pandemic), and 26,300 (23,800-28,700) in males (46% (40-52) higher). The largest number of excess deaths occurred among women aged >85 years (12,400; 9,300-15,300), followed by men aged >85 years (9,600; 7,800-11,300) and 75-84 years (9,000; 7,500-10,300). The cause of death assigned to the majority (37,295) of these excess deaths was Covid-19. There was nonetheless a >99.99% probability that there has been an increase in deaths assigned to other causes in those aged [≥]45 years. However, by the 8th of May, the all-cause excess mortality had become virtually equal to deaths assigned to Covid-19, and non-Covid excess deaths had diminished to close to zero, or possibly become negative, in all age-sex groups. Interpretation: The death toll of Covid-19 pandemic, in middle and older ages, is substantially larger than the number of deaths reported as a result of confirmed infection, and was visible in vital statistics when the national lockdown was put in place. When all-cause mortality is considered, the mortality impact of the pandemic on men and women is more similar than when comparing deaths assigned to Covid-19 as underlying cause of death.

Accessibility and allocation of public parks and gardens during COVID-19 social distancing in England and Wales (preprint)

Visiting parks and gardens may attenuate the adverse physical and mental health impacts of social distancing implemented to reduce the spread of COVID-19. We quantified access to public parks and gardens in urban areas of England and Wales, and the potential for park crowdedness during periods of high use. We combined data from the Office for National Statistics and Ordnance Survey to quantified (i) the number of parks within 500 and 1,000 metres of urban postcodes (i.e., availability), (ii) the distance of postcodes to the nearest park (i.e., accessibility), and (iii) per-capita space in each park for people living within 1,000m. We examined variability by city and share of flats. Around 25.4 million people can access public parks or gardens within a ten-minute walk, while 3.8 million residents live farther away; of these 21% are children and 13% are elderly. Areas with a higher share of flats on average are closer to a park but people living in these areas are potentially less able to meet social distancing requirements while in parks during periods of high use. Cities in England and Wales can provide residents with access to green space that enables outdoor exercise and play during social distancing. Keeping public parks and gardens open, might require measures such as dedicated park times for different age groups or entry allocation systems that, combined with smartphone apps or drones, can monitor and manage the total number of people using the park.