Death Counts Research Articles

Observational studies generate misleading results about the health effects of air pollution: Evidence from chronic air pollution and COVID-19 outcomes.

Several observational studies from locations around the globe have documented a positive correlation between air pollution and the severity of COVID-19 disease. Observational studies cannot identify the causal link between air quality and the severity of COVID-19 outcomes, and these studies face three key identification challenges: 1) air pollution is not randomly distributed across geographies; 2) air-quality monitoring networks are sparse spatially; and 3) defensive behaviors to mediate exposure to air pollution and COVID-19 are not equally available to all, leading to large measurement error bias when using rate-based COVID-19 outcome measures (e.g., incidence rate or mortality rate). Using a quasi-experimental design, we explore whether traffic-related air pollutants cause people with COVID-19 to suffer more extreme health outcomes in New York City (NYC). When we address the previously overlooked challenges to identification, we do not detect causal impacts of increased chronic concentrations of traffic-related air pollutants on COVID-19 death or hospitalization counts in NYC census tracts.

Estimates of congenital cytomegalovirus-attributable infant mortality in high-income countries: A review.

As many as 5%-10% of infants with symptomatic congenital cytomegalovirus (cCMV) disease, or 0.4%-0.8% of all liveborn infants with cCMV infection, die in early infancy in high-income countries. However, estimates are uncertain due to several potential biases that can result from data limitations and study designs. First, infants with cCMV infections who die prior to diagnosis, which usually occurs at 1-4weeks after birth, may be excluded from both the count of deaths and the denominator of cCMV births, resulting in left truncation and immortal time biases. These 'biases' are features of the data and do not reflect bias on the part of researchers, but understanding the potential existence of threats to validity can help with interpretation of findings. Left truncation of infant deaths occurring prior to diagnosis of cCMV can result in understatement of the burden of infant deaths due to cCMV. Conversely, overestimation of infant deaths associated with symptomatic cCMV may occur in clinical case series owing to greater representation of relatively severely affected infants owing to ascertainment and referral biases. In this review, we summarise the characteristics of 26 studies that reported estimates of cCMV-associated infant deaths, including potential biases or limitations to which those estimates may have been subject. We discuss study designs whose implementation might generate improved estimates of infant deaths attributable to cCMV. More complete estimates of the overall public health impact of cCMV could inform current and future screening, prevention, and vaccine research.

Effect of age, period, and birth cohort on diabetes mellitus mortality rate in Colombia, 1983-2022. An analytical cross-sectional study

Objective: To estimate the contributions of the effects of age, period, and birth cohort on the trend in the mortality rate due to Diabetes Mellitus (DM) in Colombia during the years 1983-2022. Methods: Analytical observational study, with pooled cross-sectional data, using mortality records and population projections from the National Department of Statistics. The count of deaths due to DM for each age group, period and cohort was organized in quinquennia. A multiple quasi-Poisson model was applied using the intrinsic estimator method with collapsing intention. The mortality rate ratio (MRR) of each age group, period, and cohort compared to the overall average rate was reported, along with the 95% confidence interval (CI). Results: A total of 234,117 DM-related deaths were recorded. In general, mortality due to DM increased with age. The lowest mortality was observed in the 5-9 years age group (MRR 0.04; 95% CI 0.03 to 0.06), while the highest occurred in the 85 years and older age group (MRR 18.49; 95% CI 16.88 to 20.25). Regarding the cohort effect, a lower MRR was found as cohorts got younger, with an MRR of 1.58 (95% CI 1.42 to 1.77) for the 1898-1902 cohort and 0.11 (95% CI 0.05 to 0.25) for the 2018-2022 cohort. At the period level, MRR increased between 1983-2002, stabilized between 2003-2007, and decreased between 2008-2017. However, between 2018 and 2022, a further increase was recorded. Conclusion: Public health actions should ensure healthy aging, continuous control of diabetes complications, and health care awareness in new generations.

Mortality burden attributable to exceptional PM2.5 air pollution events in Australian cities: A health impact assessment

BackgroundPeople living in Australian cities face increased mortality risks from exposure to extreme air pollution events due to bushfires and dust storms. However, the burden of mortality attributable to exceptional PM2.5 levels has not been well characterised. We assessed the burden of mortality due to PM2.5 pollution events in Australian capital cities between 2001 and 2020. MethodsFor this health impact assessment, we obtained data on daily counts of deaths for all non-accidental causes and ages from the Australian National Vital Statistics Register. Daily concentrations of PM2.5 were estimated at a 5 km grid cell, using a Random Forest statistical model of data from air pollution monitoring sites combined with a range of satellite and land use-related data. We calculated the exceptional PM2.5 levels for each extreme pollution exposure day using the deviation from a seasonal and trend loess decomposition model. The burden of mortality was examined using a relative risk concentration-response function suggested in the literature. FindingsOver the 20-year study period, we estimated 1454 (95 % CI 987, 1920) deaths in the major Australian cities attributable to exceptional PM2.5 exposure levels. The mortality burden due to PM2.5 exposure on extreme pollution days was considerable. Variations were observed across Australia. Despite relatively low daily PM2.5 levels compared to global averages, all Australian cities have extreme pollution exposure days, with PM2.5 concentrations exceeding the World Health Organisation Air Quality Guideline standard for 24-h exposure. Our analysis results indicate that nearly one-third of deaths from extreme air pollution exposure can be prevented with a 5 % reduction in PM2.5 levels on days with exceptional pollution. InterpretationExposure to exceptional PM2.5 events was associated with an increased mortality burden in Australia's cities. Policies and coordinated action are needed to manage the health risks of extreme air pollution events due to bushfires and dust storms under climate change.

Comparative impact assessment of COVID-19 policy interventions in five South Asian countries using reported and estimated unreported death counts during 2020-2021.

There has been raging discussion and debate around the quality of COVID death data in South Asia. According to WHO, of the 5.5 million reported COVID-19 deaths from 2020-2021, 0.57 million (10%) were contributed by five low and middle income countries (LMIC) countries in the Global South: India, Pakistan, Bangladesh, Sri Lanka and Nepal. However, a number of excess death estimates show that the actual death toll from COVID-19 is significantly higher than the reported number of deaths. For example, the IHME and WHO both project around 14.9 million total deaths, of which 4.5-5.5 million were attributed to these five countries in 2020-2021. We focus our gaze on the COVID-19 performance of these five countries where 23.5% of the world population lives in 2020 and 2021, via a counterfactual lens and ask, to what extent the mortality of one LMIC would have been affected if it adopted the pandemic policies of another, similar country? We use a Bayesian semi-mechanistic model developed by Mishra et al. (2021) to compare both the reported and estimated total death tolls by permuting the time-varying reproduction number (Rt) across these countries over a similar time period. Our analysis shows that, in the first half of 2021, mortality in India in terms of reported deaths could have been reduced to 96 and 102 deaths per million compared to actual 170 reported deaths per million had it adopted the policies of Nepal and Pakistan respectively. In terms of total deaths, India could have averted 481 and 466 deaths per million had it adopted the policies of Bangladesh and Pakistan. On the other hand, India had a lower number of reported COVID-19 deaths per million (48 deaths per million) and a lower estimated total deaths per million (80 deaths per million) in the second half of 2021, and LMICs other than Pakistan would have lower reported mortality had they followed India's strategy. The gap between the reported and estimated total deaths highlights the varying level and extent of under-reporting of deaths across the subcontinent, and that model estimates are contingent on accuracy of the death data. Our analysis shows the importance of timely public health intervention and vaccines for lowering mortality and the need for better coverage infrastructure for the death registration system in LMICs.

Area-based social inequalities in adult mortality: construction of French deprivation-specific life tables for the period 2016-2018.

In order to tackle social inequalities in mortality, it is crucial to quantify them. We produced French deprivation-specific life tables for the period 2016-2018 to measure the social gradient in adult all-cause mortality. Data from the Permanent Demographic Sample (EDP) were used to provide population and death counts by age, sex and deprivation quintile. The European Deprivation Index (EDI), applied at a sub-municipal geographical level, was used as an ecological measure of deprivation. Smoothed mortality rates were calculated using a one-dimensional Poisson counts smoothing method with P-Splines. We calculated life expectancies by age, sex and deprivation quintile as well as interquartile mortality rate ratios (MRR). At the age of 30, the difference in life expectancy between the most and least deprived groups amounted to 3.9 years in males and 2.2 years in females. In terms of relative mortality inequalities, the largest gaps between extreme deprivation groups were around age 55 for males (MRR = 2.22 [2.0; 2.46] at age 55), around age 50 in females (MRR = 1.77 [1.48; 2.1] at age 47), and there was a decrease or disappearance of the gaps in the very older adults. There is a strong social gradient in all-cause mortality in France for males and females. The methodology for building these deprivation-specific life tables is reproducible and could be used to monitor its development. The tables produced should contribute to improving studies on net survival inequalities for specific diseases by taking into account the pre-existing social gradient in all-cause mortality.

Excess deaths associated with COVID-19 by rurality and demographic factors in the United States.

To estimate percent excess deaths during the COVID-19 pandemic by rural-urban residence in the United States and to describe rural-urban disparities by age, sex, and race/ethnicity. Using US mortality data, we used overdispersed Poisson regression models to estimate monthly expected death counts by rurality of residence, age group, sex, and race/ethnicity, and compared expected death counts with observed deaths. We then summarized excess deaths over 6 6-month time periods. There were 16.9% (95% confidence interval [CI]: 16.8, 17.0) more deaths than expected between March 2020 and February 2023. The percent excess varied by rurality (large central metro: 18.2% [18.1, 18.4], large fringe metro: 15.6% [15.5, 15.8], medium metro: 18.1% [18.0, 18.3], small metro: 15.5% [15.3, 15.7], micropolitan rural: 16.3% [16.1, 16.5], and noncore rural: 15.8% [15.6, 16.1]). The percent excess deaths were 20.2% (20.1, 20.3) for males and 13.6% (13.5, 13.7) for females, and highest for Hispanic persons (49% [49.0, 49.6]), followed by non-Hispanic Black persons (28% [27.5, 27.9]) and non-Hispanic White persons (12% [11.6, 11.8]). The 6-month time periods with the highest percent excess deaths for large central metro areas were March 2020-August 2020 and September 2020-February 2021; for all other areas, these time periods were September 2020-February 2021 and September 2021-February 2022. Percent excess deaths varied by rurality, age group, sex, race/ethnicity, and time period. Monitoring excess deaths by rurality may be useful in assessing the impact of the pandemic over time, as rural-urban patterns appear to differ.

Costs of Fatal and Nonfatal Firearm Injuries in the U.S., 2019 and 2020

Firearm-related injuries are among the five leading causes of death for people aged 1-44 years in the U.S. The immediate and long-term harms of firearm injuries pose an economic burden on society. Fatal and nonfatal firearm injury costs in the U.S. were estimated providing up-to-date economic burden estimates. Counts of nonfatal firearm injuries were obtained from the 2019-2020 Healthcare Cost and Utilization Project Nationwide Emergency Department Sample. Data on nonfatal injury intent were obtained from the National Electronic Injury Surveillance System - Firearm Injury Surveillance System. Counts of deaths (firearm as underlying cause) were obtained from the 2019-2020 multiple cause-of-death mortality data from the National Vital Statistics System. Analyses were conducted in 2023. The total cost of firearm related injuries and deaths in the U.S. for 2020 was $493.2 billion, a 16 percent increase compared with 2019. There are significant disparities in the cost of firearm deaths in 2019-2020, with non-Hispanic Black people, males, and young and middle-aged groups being the most affected. Most of the nonfatal firearm injury-related costs are attributed to hospitalization. These findings highlight the racial/ethnic differences in fatal firearm injuries and the disproportionate cost burden to urban areas. Addressing this important public health problem can help ameliorate the costs to our society from the rising rates of firearm injuries.

Regional clustering and waves patterns due to COVID-19 by the index virus and the lambda/gamma, and delta/omicron SARS-CoV-2 variants in Peru.

Coronavirus disease 2019 (COVID-19) impact varies substantially due to various factors, so it is critical to characterize its main differences to inform decision-makers about where to focus their interventions and differentiate mitigation strategies. Up to this date, little is known about the patterns and regional clustering of COVID-19 waves worldwide. We assessed the patterns and regional clustering of COVID-19 waves in Peru by using the weekly mortality rates for each of the 25 regions as an outcome of interest. We obtained the death counts from the National Informatics System of Deaths and population estimates from the National Registry of Identification and Civil Status. In addition, we characterized each wave according to its duration, peak, and mortality rates by age group and gender. Additionally, we used polynomial regression models to compare them graphically and performed a cluster analysis to identify regional patterns. We estimated the average mortality rate at the first, second, and third waves at 13.01, 14.12, and 9.82 per 100,000 inhabitants, respectively, with higher mortality rates among elders and men. The patterns of each wave varied substantially in terms of duration, peak, impact, and wave shapes. Based on our clustering analysis, during the first wave caused by the index virus, the 25 regions of Peru presented six different wave patterns. However, the regions were clustered in two different wave patterns during the second and third, caused by alpha/lambda/delta and omicron. The propagation of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) variants behaved in Peru with varying wave patterns and regional clustering. During the COVID-19 pandemic, the weekly mortality rates followed different spatiotemporal patterns with solid clustering, which might help project the impact of future waves of COVID-19.

Life-expectancy changes from 2019 to 22: A case study of Japan using provisional death count

Many countries struggled with suppressing the incidence of COVID-19 caused by SARS-CoV-2 Omicron variant (B.1.1.529). As the epidemic size of COVID-19 in 2022 became bigger than earlier years in Japan, the present study aimed to estimate life expectancy at birth at the end of 2022, using provisional death datasets in Aichi and Fukui prefectures. We collected monthly death count from 2019 to the end of 2022, computing the period life table. While the life expectancy at birth in Aichi, 2019 was 84.6 years, it was very slightly extended to 84.7 years in 2020 and 2021, followed by a shortening for nearly 0.4 years in 2022. In Fukui, monotonous extension pattern was seen, i.e., 85.5 years in 2019, 85.6 in 2020, followed by 85.8 and 86.2 years in 2021 and 2022, respectively. Although decades-long trend of extending life expectancy at birth was partly discontinued from 2020 due to the pandemic at the national level, we have shown that the pandemic impact was still small in Japan by the end of 2022. First Omicron wave occurred shortly after primary series vaccination, and even real time booster program was underway during that wave. Different demographic consequences between Aichi and Fukui are explained by differential epidemic sizes prior to vaccination.

The Global Burden of Type 2 Diabetes Attributable to Dietary Risks: Insights from the Global Burden of Disease Study 2019.

The Global Burden of Disease Study (GBD) 2019 reveals an increasing prevalence of Type 2 Diabetes Mellitus (T2DM) from 1990 to 2019. This study delves into the role of dietary risk factors across different demographic and socioeconomic groups. Utilizing data from the GBD 2019, it analyzes age-adjusted T2DM metrics-death counts, Disability-Adjusted Life Years (DALYs), and Age-Standardized Rates (ASRs)-stratified by age, sex, and region. The study employed Estimated Annual Percentage Changes (EAPCs) to track trends over time. The results show that in 2019, 26.07% of T2DM mortality and 27.08% of T2DM DALYs were attributable to poor diets, particularly those low in fruits and high in red and processed meats. There was a marked increase in both the death rate and DALY rate associated with dietary risks over this period, indicating the significant impact of dietary factors on the global T2DM landscape. Geographic variations in T2DM trends were significant, with regions like Southern Sub-Saharan Africa and Central Asia experiencing the most substantial increases in Age-Standardized Mortality Rate (ASMR) and Age-Standardized DALY Rate (ASDR). A positive correlation was noted between Socio-Demographic Index (SDI) and T2DM burden due to dietary risk factors. The study concludes that targeted public health initiatives promoting dietary changes could substantially reduce the global T2DM burden.

The impact of fine particulate matter on chronic obstructive pulmonary disease deaths in Pudong New Area, Shanghai, during a long period of air quality improvement

Chronic obstructive pulmonary disease (COPD) deaths attributed to fine particulate matter (with an aerodynamic equivalent diameter <2.5 μm, PM2.5) exposure are a common global public health concern. Recent improvements in air quality and the corresponding health benefits have received much attention. Thus, we have explored the trends of PM2.5 pollution improvement on COPD deaths during an important period of air pollution control (2008–2017) in Pudong New Area, Shanghai, China. Data, including daily COPD death counts, meteorological variables, and ambient air pollutants, were collected from 2008 to 2017. Generalized additive models were fitted to evaluate the percent change (%) in pollution-related COPD deaths. The results showed that the number of days with daily PM2.5 concentrations <35 μg/m3 increased from 19 days (5.19%) in 2008 to 166 days (45.48%) in 2017, and PM2.5 concentrations >75 μg/m3 decreased from 222 days (60.66%) in 2008 to 33 days (9.04%) in 2017. The associations in the overall period between 2008 and 2017 was significant. In subperiod analysis, each 10 μg/m3 increment in PM2.5 was associated with a percent change (%) of 0.89 (95% confidence interval [CI], 0.37, 1.42) at lag 5 and 0.78 (95% CI, 0.26, 1.30) at lag 6 during 2008–2013. Significant results were also found at lag 0–5 [percent change (%), 1.12 (95% CI, 0.09, 2.17)], lag 0–6 [percent change (%), 1.52 (95% CI, 0.43, 2.62)] and lag 0–7 [percent change (%), 1.72 (95% CI, 0.57, 2.88)] during 2008–2013. By contrast, no significant association was found between 2014 and 2017. In conclusion, the decreased COPD deaths associated with PM2.5 exposure were found, especially after the air quality improvement turning point in 2014.

The effects of diurnal temperature range on mortality and emergency department presentations in Victoria state of Australia: A time-series analysis

State of Victoria, Australia (SVA) has a wide variation of diurnal temperatures (DTR). DTR has been reported to be associated with risk of mortality and morbidity. We examined the association between exposure to DTR and risk of all-cause mortality and emergency department (ED) presentations in the SVA. We obtained data on daily counts of deaths and ED presentations, and weather data from 1 st January 2000─2019. We applied a quasi-Poisson time-series regression analysis to examine the association between daily DTR exposures and risk of mortality and ED presentations. The analyses were queried by age, sex, seasons, ED presentations triages, and departure status. Risk of mortality and ED presentation increased by 0.33% (95% CI: 0.24%–0.43%), and 0.094% (95% CI: 0.077%–0.11%) in relation to one degree increase in the daily DTR. The association between DTR and ED presentations was stronger in children (0–15 years) (0.38% [95% CI: 0.34%–0.42%]) and the elderly (75+ years) (0.34% [95% CI: 0.29%–0.39%]). Resuscitation, which was consistently accounted for the highest vulnerability to DTR variation, increased by 0.79% (95% CI: 0.60%–0.99%). This study suggests that the risk of mortality and ED presentations associates with the increase of DTR. Children, the elderly, and their caregivers need to be made aware of the health risk posed by DTR.

A web-based analytical framework for the detection and visualization space-time clusters of COVID-19

ABSTRACT The COVID-19 pandemic has had a profound impact worldwide and continues to spread due to various mutations of the virus. Many governmental and nonprofit agencies at different levels have quickly developed COVID-19 dashboards to disseminate information on the pandemic to the public. However, most of these systems have mainly distributed “plain” information (e.g. cases, death counts, vaccination), and rarely provided insights that can be gained from spatiotemporal analyses, such as the detection of emerging clusters. The results from these analyses hold tremendous potential for health policymakers as they try to identify ways to slow down transmission. We present a web-based geographic framework to detect and visualize space-time clusters of COVID-19. Our tightly coupled framework integrates the prospective space-time scan statistics and local indicators of spatial association (LISA) with novel 2D and 3D interactive visuals in a cyber environment (http://159.223.164.41/app/). We illustrate the applicability of our approach using COVID-19 data for the continental US. Our framework is portable to other regions that may experience infectious diseases but is also flexible to handle data of different spatial and temporal granularities. This paper fits within an effort to integrate space-time analytics for the monitoring of infectious diseases in web environment, ultimately improving health surveillance systems.

Is there a sex difference in mortality rates in paediatric intensive care units?: a systematic review.

Mortality rates in infancy and childhood are lower in females than males. However, for children admitted to Paediatric Intensive Care Units (PICU), mortality has been reported to be lower in males, although males have higher admission rates. This female mortality excess for the subgroup of children admitted in intensive care is not well understood. To address this, we carried out a systematic literature review to summarise the available evidence. Our review studies the differences in mortality between males and females aged 0 to <18 years, while in a PICU, to examine whether there was a clear difference (in either direction) in PICU mortality between the two sexes, and, if present, to describe the magnitude and direction of this difference. Any studies that directly or indirectly reported the rates of mortality in children admitted to intensive care by sex were eligible for inclusion. The search strings were based on terms related to the population (those admitted into a paediatric intensive care unit), the exposure (sex), and the outcome (mortality). We used the search databases MEDLINE, Embase, and Web of Science as these cover relevant clinical publications. We assessed the reliability of included studies using a modified version of the risk of bias in observational studies of exposures (ROBINS-E) tool. We considered estimating a pooled effect if there were at least three studies with similar populations, periods of follow-up while in PICU, and adjustment variables. We identified 124 studies of which 114 reported counts of deaths by males and females which gave a population of 278,274 children for analysis, involving 121,800 (44%) females and 156,474 males (56%). The number of deaths and mortality rate for females were 5,614 (4.61%), and for males 6,828 (4.36%). In the pooled analysis, the odds ratio of female to male mortality was 1.06 [1.01 to 1.11] for the fixed effect model, and 1.10 [1.00 to 1.21] for the random effects model. Overall, males have a higher admission rate to PCU, and potentially lower overall mortality in PICU than females. www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=203009, identifier (CRD42020203009).

Global, regional, and national mortality due to unintentional carbon monoxide poisoning, 2000–2021: results from the Global Burden of Disease Study 2021

Unintentional carbon monoxide poisoning is a largely preventable cause of death that has received insufficient attention. We aimed to conduct a comprehensive global analysis of the demographic, temporal, and geographical patterns of fatal unintentional carbon monoxide poisoning from 2000 to 2021. As part of the latest Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), unintentional carbon monoxide poisoning mortality was quantified using the GBD cause of death ensemble modelling strategy. Vital registration data and covariates with an epidemiological link to unintentional carbon monoxide poisoning informed the estimates of death counts and mortality rates for all locations, sexes, ages, and years included in the GBD. Years of life lost (YLLs) were estimated by multiplying deaths by remaining standard life expectancy at age of death. Population attributable fractions (PAFs) for unintentional carbon monoxide poisoning deaths due to occupational injuries and high alcohol use were estimated. In 2021, the global mortality rate due to unintentional carbon monoxide poisoning was 0·366 per 100 000 (95% uncertainty interval 0·276-0·415), with 28 900 deaths (21 700-32 800) and 1·18 million YLLs (0·886-1·35) across all ages. Nearly 70% of deaths occurred in males (20 100 [15 800-24 000]), and the 50-54-year age group had the largest number of deaths (2210 [1660-2590]). The highest mortality rate was in those aged 85 years or older with 1·96 deaths (1·38-2·32) per 100 000. Eastern Europe had the highest age-standardised mortality rate at 2·12 deaths (1·98-2·30) per 100 000. Globally, there was a 53·5% (46·2-63·7) decrease in the age-standardised mortality rate from 2000 to 2021, although this decline was not uniform across regions. The overall PAFs for occupational injuries and high alcohol use were 13·6% (11·9-16·0) and 3·5% (1·4-6·2), respectively. Improvements in unintentional carbon monoxide poisoning mortality rates have been inconsistent across regions and over time since 2000. Given that unintentional carbon monoxide poisoning is almost entirely preventable, policy-level interventions that lower the risk of carbon monoxide poisoning events should be prioritised, such as those that increase access to improved heating and cooking devices, reduce carbon monoxide emissions from generators, and mandate use of carbon monoxide alarms. Bill & Melinda Gates Foundation.

Interactive effects of ambient fine particulate matter and ozone on daily mortality in 372 cities: two stage time series analysis

ObjectiveTo investigate potential interactive effects of fine particulate matter (PM2.5) and ozone (O3) on daily mortality at global level.DesignTwo stage time series analysis.Setting372 cities across 19 countries and regions.PopulationDaily counts...

Mortality risks associated with floods in 761 communities worldwide: time series study

ObjectiveTo evaluate lag-response associations and effect modifications of exposure to floods with risks of all cause, cardiovascular, and respiratory mortality on a global scale.DesignTime series study.Setting761 communities in 35 countries...

Social inequalities and COVID-19 mortality between neighborhoods of Bariloche city, Argentina

BackgroundThe COVID-19 pandemic has shown how intraurban inequalities are likely to reinforce health and social inequalities. Studies at small area level help to visualize social inequialities hidden in large areas as cities or regions.AimTo describe the spatial patterning of COVID-19 death rates in neighborhoods of the medium-sized city of Bariloche, Argentina, and to explore its relationship with the socioeconomic characteristics of neighborhoods.MethodsWe conducted an ecological study in Bariloche, Argentina. The outcome was counts of COVID-19 deaths between June 2020 and May 2022 obtained from the surveillance system and georeferenced to neighborhoods. We estimated crude- and age-adjusted death rates by neighborhood using a Bayesian approach through a Poisson regression that accounts for spatial-autocorrelation via Conditional Autoregressive (CAR) structure. We also analyzed associations of age-adjusted death rates with area-level socioeconomic indicators.ResultsMedian COVID-19 death rate across neighborhoods was 17.9 (10th/90th percentile of 6.3/35.2) per 10,000 inhabitants. We found lower age-adjusted rates in the city core and western part of the city. The age-adjusted death rate in the most deprived areas was almost double than in the least deprived areas, with an education-related relative index of inequality (RII) of 2.14 (95% CI 1.55 to 2.96).ConclusionWe found spatial heterogeneity and intraurban variability in age-adjusted COVID-19 death rates, with a clear social gradient, and a higher burden in already deprived areas. This highlights the importance of studying inequalities in health outcomes across small areas to inform placed-based interventions.

Cause-of-Death Contributions to Declining Mortality Improvements and Life Expectancies Using Cause-Specific Scenarios

In recent years, improvements in all-cause mortality rates and life expectancies for males and females in England and Wales have slowed down. In this article, cause-specific mortality data for England and Wales from 2001 to 2018 are used to investigate the cause-specific contributions to the slowdown in improvements. Cause-specific death counts in England and Wales are modeled using negative binomial regression, and a breakpoint in the linear temporal trend in log mortality rates is investigated. Cause-specific scenarios are generated, where the post-breakpoint temporal trends for certain causes are reverted to pre-breakpoint rates and the effects of these changes on age-standardized mortality rates and period life expectancies are explored. These scenarios are used to quantify cause-specific contributions to the mortality improvement slowdown. Reductions in improvements at older ages in circulatory system diseases, as well as the worsening of mortality rates due to mental and behavioral illnesses and nervous system diseases, provide the greatest contributions to the reduction of improvements in age-standardized mortality rates and period life expectancies. Future period life expectancies scenarios are also generated, where cause-specific mortality rate trends are assumed to either persist or be reverted. In the majority of scenarios, the reversion of cause-specific mortality trends in a single cause of death results in the worsening of period life expectancies at birth and age 65 for both males and females. This work enhances the understanding of cause-specific contributions to the slowdown in all-cause mortality rate improvements from 2001 to 2018, while also providing insights into causes of death that are drivers of life expectancy improvements. The findings are of benefit to researchers, policymakers, and insurance professionals.