County-level socio-economic disparities in COVID-19 mortality in the USA

Disparities in COVID-19-Related Mortality Among Older Adults With Alzheimer's Disease and Related Dementias: Variations Over Time

Older adults with Alzheimer's disease and related dementias (ADRD) had a high risk of COVID-19-related mortality. Racial and ethnic minorities were disproportionally impacted by the pandemic. The variations in disparities, including racial and ethnic disparities and disparities across communities, in COVID-19-related mortality across the different stages of the COVID-19 pandemic among the ADRD population are unknown. This observational study estimated linear probability models for community-dwelling older adults with ADRD who were diagnosed with COVID-19 in 2020 and 2021 using multiple national data (e.g., Medicare data), accounting for individual and community characteristics. Disparities in 30-day mortality were compared between 2020 and 2021. The socioeconomic disparity in COVID-19-related mortality across communities became insignificant during the later stage of the pandemic, ethnic differences in COVID-19-related mortality decreased but persisted, and racial disparity remained largely unchanged. The study provides insights into interventions to mitigate lingering disparities in health outcomes among the vulnerable population.

Impact of Repeated Reimbursement Penalties on Hospital Total Quality Scores

OBJECTIVES

The incidence of hospital-acquired conditions (HACs) is a serious public health issue with implications ranging from patient morbidity and mortality to negative financial impacts on patients and health care systems. Despite substantial efforts to address and reduce HACs, research into the effect of quality improvement programs is inconclusive. This study seeks to better understand the relationship between repeated reimbursement penalties and improvement in HAC quality scores.

METHODS

A quantitative comparative analysis of U.S. health care data was conducted. Data on quality outcomes and hospital characteristics were sourced from the Hospital-Acquired Condition Reduction Program from fiscal years 2018 and 2019 and the Centers for Medicare & Medicaid Services Inpatient Prospective Payment System impact files, respectively.

RESULTS

In total, 3123 U.S. hospitals were analyzed to compare differences between total HAC scores of hospitals with and without penalties in consecutive years. Hospitals with repeated penalties had significantly greater improvement in scores ( t497.262 = -13.00, P < 0.001), and the impact was greatest in small hospitals (<100 beds). Repeated penalties had a smaller impact on disproportionate share hospitals (Cohen d = 0.73). Among all hospitals, the effect of repeated penalties was large (Cohen d = 0.75).

CONCLUSIONS

This study suggests that repeated penalties can improve quality scores in U.S. hospitals. However, the effect may be exaggerated for smaller hospitals and those that serve patient populations with a relatively higher socioeconomic status. The reason disproportionate share hospitals did not show as much improvement as nondisproportionate hospitals may be because hospitals serving vulnerable populations often have fewer resources.

Quantifying income inequality in years of life lost to COVID-19: a prediction model approach using Dutch administrative data

BACKGROUND

Low socioeconomic status and underlying health increase the risk of fatal outcomes from COVID-19, resulting in more years of life lost (YLL) among the poor. However, using standard life expectancy overestimates YLL to COVID-19. We aimed to quantify YLL associated with COVID-19 deaths by sex and income quartile, while accounting for the impact of individual-level pre-existing health on remaining life expectancy for all Dutch adults aged 50+.

METHODS

Extensive administrative data were used to model probability of dying within the year for the entire 50+ population in 2019, considering age, sex, disposable income and health care use (n = 6 885 958). The model is used to predict mortality probabilities for those who died of COVID-19 (had they not died) in 2020. Combining these probabilities in life tables, we estimated YLL by sex and income quartile. The estimates are compared with YLL based on standard life expectancy and income-stratified life expectancy.

RESULTS

Using standard life expectancy results in 167 315 YLL (8.4 YLL per death) which is comparable to estimates using income-stratified life tables (167 916 YLL with 8.2 YLL per death). Considering pre-existing health and income, YLL decreased to 100 743, with 40% of years lost in the poorest income quartile (5.0 YLL per death). Despite individuals in the poorest quartile dying at younger ages, there were minimal differences in average YLL per COVID-19 death compared with the richest quartile.

CONCLUSIONS

Accounting for prior health significantly affects estimates of YLL due to COVID-19. However, inequality in YLL at the population level is primarily driven by higher COVID-19 deaths among the poor. To reduce income inequality in the health burden of future pandemics, policies should focus on limiting structural differences in underlying health and exposure of lower income groups.

Towards closing socio-economic status disparities in COVID-19 premature mortality: a nationwide and trend analysis in Chile

BACKGROUND

Socio-economic status (SES) disparities in coronavirus disease 2019 (COVID-19) mortality have been reported but complete information and time trends are scarce. In this study, we analysed the years of life lost (YLL) due to COVID-19 premature mortality during the pandemic in Chile and its evolution according to SES and sex compared with a counterfactual scenario [cerebrovascular accidents (stroke)].

METHOD

We used Chile's national mortality databases from 2020 to 2022. YLL and age-standardized YLL and mortality rates by sex and by epidemic waves were determined. The 346 communes were stratified into SES groups according to their poverty index quintile. Negative binomial regression models were used to test trends.

RESULTS

In >2 years of the pandemic, the COVID-19 YLL was 975 937, corresponding to 61 174 deaths. The YLL rate per 100 000 inhabitants was 1027 for males and 594 for females. There was a heterogeneous distribution of YLL rates and the regional level. Communes in the most advantaged SES quintile (Q5) had the highest YLL during the first wave compared with those in the lowest SES quintile (Q1) (P < 0.001) but the opposite was true during the second wave. COVID-19 YLL trends declined and differences between Q1 and Q2 vs Q5 converged from the second to the fourth waves (0.33 and 0.15, Ptrend < 0.001 and Ptrend = 0.024). YLL declined but differences persisted in stroke (-0.002, Ptrend = 0.979).

CONCLUSIONS

COVID-19 deaths resulted in a higher impact on premature death in Chile, especially in men, with a heterogeneous geographic distribution along the territory. SES and sex disparities in COVID-19 premature mortality had narrowed by the end of the pandemic.

Inequality and COVID-19 in Sweden: Relative risks of nine bad life events, by four social gradients, in pandemic vs. prepandemic years

The COVID-19 pandemic struck societies directly and indirectly, not just challenging population health but disrupting many aspects of life. Different effects of the spreading virus-and the measures to fight it-are reported and discussed in different scientific fora, with hard-to-compare methods and metrics from different traditions. While the pandemic struck some groups more than others, it is difficult to assess the comprehensive impact on social inequalities. This paper gauges social inequalities using individual-level administrative data for Sweden's entire population. We describe and analyze the relative risks for different social groups in four dimensions-gender, education, income, and world region of birth-to experience three types of COVID-19 incidence, as well as six additional negative life outcomes that reflect general health, access to medical care, and economic strain. During the pandemic, the overall population faced severe morbidity and mortality from COVID-19 and saw higher all-cause mortality, income losses and unemployment risks, as well as reduced access to medical care. These burdens fell more heavily on individuals with low income or education and on immigrants. Although these vulnerable groups experienced larger absolute risks of suffering the direct and indirect consequences of the pandemic, the relative risks in pandemic years (2020 and 2021) were conspicuously similar to those in prepandemic years (2016 to 2019).

Variation in mortality burden of the COVID-19 pandemic across federal states in Germany

BACKGROUND

Intra-annual excess mortality is the most reliable measure of losses of lives due to short-term risk factors. The objectives of our study are (i) to estimate excess mortality across German states in the course of the coronavirus disease 2019 (COVID-19) pandemic years 2020 and 2021 and (ii) to identify possible regional-level determinants of spatial inequality in pandemic-related excess mortality.

METHODS

We use weekly mortality data series for the calculation of weekly death rates, standardized by age for each federal state of Germany. We estimate the expected level of mortality as state-specific mortality trends and excess mortality in 2020 and 2021. We explore ecological statistical relationships between excess mortality, COVID-19 morbidity, and selected regional socioeconomic indicators using fixed-effects regression models.

RESULTS

Our study shows that during the first pandemic year, there was South-to-North gradient in excess mortality in Germany, with excess mortality being higher in the South. Over the course of the second pandemic year 2021, this gradient changed to become an East-to-West gradient, with excess mortality being higher in the East. The results of the study show stronger effects of COVID-19 morbidity on excess mortality in East Germany. State-level indicators reflecting economic activity, employment, and capacity of intensive care units show significant correlations with excess mortality across the states.

CONCLUSIONS

The results show pronounced state-level differences in the magnitude of excess mortality during the COVID-19 pandemic in Germany. Economic activity, employment and capacity of intensive care units were the most important state-level characteristics associated with the observed spatial variations in excess mortality.

Scottish Index of Multiple Deprivation (SIMD) indicators as predictors of mortality among patients hospitalised with COVID-19 disease in the Lothian Region, Scotland during the first wave: a cohort study

BACKGROUND

Sars-CoV-2, the causative agent of COVID-19, has led to more than 226,000 deaths in the UK and multiple risk factors for mortality including age, sex and deprivation have been identified. This study aimed to identify which individual indicators of the Scottish Index of Multiple Deprivation (SIMD), an area-based deprivation index, were predictive of mortality.

METHODS

This was a prospective cohort study of anonymised electronic health records of 710 consecutive patients hospitalised with Covid-19 disease between March and June 2020 in the Lothian Region of Southeast Scotland. Data sources included automatically extracted data from national electronic platforms and manually extracted data from individual admission records. Exposure variables of interest were SIMD quintiles and 12 indicators of deprivation deemed clinically relevant selected from the SIMD. Our primary outcome was mortality. Age and sex adjusted univariable and multivariable analyses were used to determine measures of association between exposures of interest and the primary outcome.

RESULTS

After adjusting for age and sex, we found an increased risk of mortality in the more deprived SIMD quintiles 1 and 3 (OR 1.75, CI 0.99-3.08, p = 0.053 and OR 2.17, CI 1.22-3.86, p = 0.009, respectively), but this association was not upheld in our multivariable model containing age, sex, Performance Status and clinical parameters of severity at admission. Of the 12 pre-selected indicators of deprivation, two were associated with greater mortality in our multivariable analysis: income deprivation rate categorised by quartile (Q4 (most deprived): 2.11 (1.20-3.77) p = 0.011)) and greater than expected hospitalisations due to alcohol per SIMD data zone (1.96 (1.28-3.00) p = 0.002)).

CONCLUSIONS

SIMD as an aggregate measure of deprivation was not predictive of mortality in our cohort when other exposure measures were accounted for. However, we identified a two-fold increased risk of mortality in patients residing in areas with greater income-deprivation and/or number of hospitalisations due to alcohol. In areas where aggregate measures fail to capture pockets of deprivation, exploring the impact of specific SIMD indicators may be helpful in targeting resources to residents at risk of poorer outcomes from Covid-19.

The Effect of COVID-19 on Dual-Eligible Beneficiaries: A Scoping Review

OBJECTIVES

To examine the impact of COVID-19 on clinical health outcomes and health-related social needs among Medicaid-Medicare dual-eligible beneficiaries.

DESIGN

Scoping review.

SETTING AND PARTICIPANTS

Dual eligibles during COVID-19.

METHODS

We performed a comprehensive scoping review including observational studies, clinical trials, and original empirical research studies of PubMed and CINAHL. We generated a list of terms related to programs that both serve dual eligibles and address our desired outcomes. With the assistance of a medical librarian, we identified relevant abstracts published during COVID-19 meeting our inclusion criteria. We performed full-text reviews of relevant abstracts and selected the final studies. We extracted the study population, design, and major findings, then conducted thematic analysis.

RESULTS

1100 articles were identified, with 439 deemed relevant. On full text-review, 15 articles met inclusion criteria representing more than 86 million Medicare beneficiaries. No studies were specific only to dual eligibles. Topic areas included in this review include COVID-19 case counts (2 articles), mortality (8 articles), hospitalizations (7 articles), food insecurity (1 article), self-reported mental health (1 article), and social connectedness (2 articles). Dual eligibles had disparate COVID-19-related outcomes from Medicare-only enrollees in 12 of 15 studies. Studies show higher mortality for dual eligibles overall, but this was not true for dual eligibles in nursing homes and assisted living communities. Dual eligibles were more likely to experience food insecurity. More favorably, dual eligibles reported greater social connectedness.

CONCLUSIONS AND IMPLICATIONS

Dual eligibles had different outcomes from Medicare-only recipients in multiple health outcomes and health-related social needs during COVID-19, but studies are limited, particularly in terms of health-related social needs. Future work focusing on outcomes only among dual-eligible beneficiaries, integrated care programs, and fiscal alignment between Medicare and Medicaid plans may help stakeholders address health needs specific to dual eligibles.

Impact of the COVID-19 Pandemic on the Socioeconomic Inequalities in Mortality in Spanish Provinces

BACKGROUND

Although many studies have assessed the socioeconomic inequalities caused by COVID-19 in several health outcomes, there are numerous issues that have been poorly addressed. For instance, have socioeconomic inequalities in mortality from COVID-19 increased? What impact has the pandemic had on inequalities in specific causes of mortality other than COVID-19? Are the inequalities in COVID-19 mortality different from other causes? In this paper we have attempted to answer these questions for the case of Spain.

METHODS

We used a mixed longitudinal ecological design in which we observed mortality from 2005 to 2020 in the 54 provinces into which Spain is divided. We considered mortality from all causes, not excluding, and excluding mortality from COVID-19; and cause-specific mortality. We were interested in analysing the trend of the outcome variables according to inequality, controlling for both observed and unobserved confounders.

RESULTS

Our main finding was that the increased risk of dying in 2020 was greater in the Spanish provinces with greater inequality. In addition, we have found that: (i) the pandemic has exacerbated socioeconomic inequalities in mortality, (ii) COVID-19 has led to gender differences in the variations in risk of dying (higher in the case of women) and (iii) only in cardiovascular diseases and Alzheimer did the increased risk of dying differ between the most and least unequal provinces. The increase in the risk of dying was different by gender (greater in women) for cardiovascular diseases and cancer.

CONCLUSION

Our results can be used to help health authorities know where and in which population groups future pandemics will have the greatest impact and, therefore, be able to take appropriate measures to prevent such effects.

Beyond the biomedical, towards the agentic: A paradigm shift for population health science

Life expectancy in the United States is decreasing. Health disparities are widening. Growing evidence for and integration of social and structural determinants into theory and practice has not yet improved outcomes. The COVID-19 pandemic reinforced the fact. In this paper, we argue that the biomedical model and its underlying scientific paradigm of causal determinism, which currently dominate population health, cannot meet population health needs. While criticism of the biomedical model is not new, this paper advances the field by going beyond criticism to recognize the need for a paradigm shift. In the first half of the paper, we present a critical analysis of the biomedical model and the paradigm of causal determinism. In the second half, we outline the agentic paradigm and present a structural model of health based on generalizable, group-level processes. We use the experience of the COVID-19 pandemic to illustrate the practical applications of our model. It will be important for future work to investigate the empirical and pragmatic applications of our structural model of population health.

Premature cardiovascular disease mortality with overweight and obesity as a risk factor: estimating excess mortality in the United States during the COVID-19 pandemic

BACKGROUND

The United States has experienced high levels of excess mortality during the COVID-19 pandemic and also has high prevalence of overweight and obesity, which increases the risk of severe infection and death from the virus. This study uses multiple cause of death data to estimate excess premature cardiovascular disease mortality in the USA in 2020 for which overweight and obesity was a risk factor.

METHODS

The contribution of overweight and obesity to premature (35-74 years) cardiovascular disease mortality was measured as cardiovascular disease reported on the death certificate with one or more of diabetes, chronic kidney disease, obesity, lipidemias or hypertensive heart disease (DKOLH-CVD). Excess mortality was calculated as the difference between actual and expected age-standardised death rates. Expected deaths were estimated using negative binomial regressions of monthly deaths during 2010-19.

RESULTS

Excess DKOLH-CVD mortality in March-December 2020 was 29% (95% uncertainty interval 28-31%) for males and 30% (28-32%) for females, much higher than for all causes (males 19% (18-21%), females 16% (14-17%)). Excess mortality was higher where two or more DKOLH conditions (males 40% (37-43%), females 41% (37-44%)) or obesity (males 42% (38-45%), females 47% (43-51%)) were reported. One-half of excess DKOLH-CVD mortality was reported as due to COVID-19, lower than the four-fifths of excess all-cause deaths. For home deaths, just over 10% of excess mortality for each cause classification was reported as due to COVID-19.

CONCLUSIONS

Excess premature cardiovascular disease mortality in the USA for which overweight and obesity was a risk factor was considerably higher than for all causes, exacerbating adverse pre-pandemic trends. The contribution of COVID-19 to excess mortality appears significantly under-reported for home deaths.

Why were some countries more successful than others in curbing early COVID-19 mortality impact? A cross-country configurational analysis

Why was there considerable variation in initial COVID-19 mortality impact across countries? Through a configurational lens, this paper examines which configurations of five conditions-a delayed public-health response, past epidemic experience, proportion of elderly in population, population density, and national income per capita-influence early COVID-19 mortality impact measured by years of life lost (YLL). A fuzzy-set qualitative comparative analysis (fsQCA) of 80 countries identifies four distinctive pathways associated with high YLL rate and four other different pathways leading to low YLL rate. Results suggest that there is no singular "playbook"-a set of policies that countries can follow. Some countries failed differently, whereas others succeeded differently. Countries should take into account their situational contexts to adopt a holistic response strategy to combat any future public-health crisis. Regardless of the country's past epidemic experience and national income levels, a speedy public-health response always works well. For high-income countries with high population density or past epidemic experience, they need to take extra care to protect elderly populations who may otherwise overstretch healthcare capacity.

Socioeconomic differences in COVID-19 infection, hospitalisation and mortality in urban areas in a region in the South of Europe

BACKGROUND

To analyse differences in confirmed cases, hospitalisations and deaths due to COVID-19 related to census section socioeconomic variables.  METHODS: Ecological study in the 12 largest municipalities in Andalusia (Spain) during the first three epidemic waves of the COVID-19 (02/26/20-03/31/21), covering 2,246 census sections (unit of analysis) and 3,027,000 inhabitants. Incidence was calculated, standardised by age and sex, for infection, hospitalisation and deaths based on average gross income per household (AGI) for the census tracts in each urban area. Association studied using a Poisson Bayesian regression model with random effects for spatial smoothing.

RESULTS

There were 140,743 cases of COVID-19, of which 12,585 were hospitalised and 2,255 died. 95.2% of cases were attributed to the second and third waves, which were jointly analysed. We observed a protective effect of income for infection in 3/12 cities. Almeria had the largest protective effect (smoothed relative risk (SRR) = 0.84 (0.75-0.94 CI 95%). This relationship reappeared with greater magnitude in 10/12 cities for hospitalisation, lowest risk in Algeciras SRR = 0.41 (0.29-0.56). The pattern was repeated for deaths in all urban areas and reached statistical significance in 8 cities. Lowest risk in Dos Hermanas SRR = 0.35 (0.15-0.81).

CONCLUSIONS

Income inequalities by geographical area were found in the incidence of COVID-19. The strengths of the association increased when analysing the severe outcomes of hospitalisations and, above all, deaths.

Environmental health, COVID-19, and the syndemic: internal medicine facing the challenge

Internists are experts in complexity, and the COVID-19 pandemic is disclosing complex and unexpected interactions between communicable and non-communicable diseases, environmental factors, and socio-economic disparities. The medicine of complexity cannot be limited to facing comorbidities and to the clinical management of multifaceted diseases. Evidence indicates how climate change, pollution, demographic unbalance, and inequalities can affect the spreading and outcomes of COVID-19 in vulnerable communities. These elements cannot be neglected, and a wide view of public health aspects by a "one-health" approach is strongly and urgently recommended. According to World Health Organization, 35% of infectious diseases involving the lower respiratory tract depend on environmental factors, and infections from SARS-Cov-2 is not an exception. Furthermore, environmental pollution generates a large burden of non-communicable diseases and disabilities, increasing the individual vulnerability to COVID-19 and the chance for the resilience of large communities worldwide. In this field, the awareness of internists must increase, as privileged healthcare providers. They need to gain a comprehensive knowledge of elements characterizing COVID-19 as part of a syndemic. This is the case when pandemic events hit vulnerable populations suffering from the increasing burden of chronic diseases, disabilities, and social and economic inequalities. Mastering the interplay of such events requires a change in overall strategy, to adequately manage not only the SARS-CoV-2 infection but also the growing burden of non-communicable diseases by a "one health" approach. In this context, experts in internal medicine have the knowledge and skills to drive this change.

COVID-19 mortality and deprivation: pandemic, syndemic, and endemic health inequalities

COVID-19 has exacerbated endemic health inequalities resulting in a syndemic pandemic of higher mortality and morbidity rates among the most socially disadvantaged. We did a scoping review to identify and synthesise published evidence on geographical inequalities in COVID-19 mortality rates globally. We included peer-reviewed studies, from any country, written in English that showed any area-level (eg, neighbourhood, town, city, municipality, or region) inequalities in mortality by socioeconomic deprivation (ie, measured via indices of multiple deprivation: the percentage of people living in poverty or proxy factors including the Gini coefficient, employment rates, or housing tenure). 95 papers from five WHO global regions were included in the final synthesis. A large majority of the studies (n=86) found that COVID-19 mortality rates were higher in areas of socioeconomic disadvantage than in affluent areas. The subsequent discussion reflects on how the unequal nature of the pandemic has resulted from a syndemic of COVID-19 and endemic inequalities in chronic disease burden.

County-Level Life Expectancy Change: A Novel Metric for Monitoring Public Health

Life expectancy (LE) is a core measure of population health. Studies have confirmed the predictive importance of modifiable determinants on LE, but less is known about their association with LE change over time at the US county level. In addition, we explore the predictive association of LE change with COVID-19 mortality. We used a linear regression model to calculate county-level annual LE change from 2011 to 2016, and categorized LE change (≤-0.1 years change per year as decreasing, ≥0.1 years as increasing, otherwise no change). A multinomial regression model was used to determine the association between modifiable determinants of health indicators from the County Health Rankings and LE change. A Poisson regression model was used to evaluate the relationship between change in life expectancy and COVID-19 mortality through September 2021. Among 2943 counties, several modifiable determinants of health were significantly associated with odds of being in increasing LE or decreasing LE counties, including adult smoking, obesity, unemployment, and proportion of children in poverty. The presence of an increasing LE in 2011-2016, as compared to no change, was significantly associated with a 5% decrease in COVID-19 mortality between 2019 and 2021 (β = 0.953, 95% CI: 0.943, 0.963). We demonstrated that change in LE at the county level is a useful metric for tracking public health progress, measuring the impact of public health initiatives, and gauging preparedness and vulnerability for future public health emergencies.

Associations of Clinical Factors and Blood Groups With the Severity of COVID-19 Infection in Makkah City, Saudi Arabia

Context

The possible associations between the different blood groups and clinical factors with COVID-19 infection among patients in Makkah city.

Objective

To investigate the relationship between ABO blood groups and COVID-19 infection in patients who were tested positive and to elucidate the most common ABO blood groups with a higher infectivity of COVID-19 and disease association.

Materials and Methods

This was an observational cross-sectional study that included COVID-19 patients diagnosed with PCR and who were hospitalized in Al-Noor Specialist Hospital (Makkah) during the period between March to November 2020. The ABO and Rhesus blood groups alongside the clinical characteristics were determined and retrieved from medical records and HESN of the Ministry of Health of the Kingdom of Saudi Arabia (KSA).

Results

The overall confirmed COVID-19 cases included in this study were 1,583 patients who underwent positive PCR testing between March and November 2020. The frequencies of blood groups were as follows: group O⁺ (37%), group A⁺ (29.2%), group B⁺ (22.6%), group AB⁺ (5.1%), group O^- (2.8%), group B^- (1.8%), group A^- (1.1%), and group AB^- (0.4%). However, no significant correlations were observed for ABO groups and Rh types with the severity of COVID-19 illness. Conversely, signs and symptoms of respiratory distress syndrome (RDS), pneumonia, and respiratory failure symptoms, alongside a history of diabetes mellitus, hypertension, chronic kidney diseases, and congestive heart failure significantly increased the risk of death from COVID-19 infection. Moreover, the rates of fever, cough, and asthma were markedly lower in the deceased group compared with the recovered group of patients.

Conclusion

The association between the different blood groups with the prevalence and mortality of COVID-19 among infected patients has yet to be elucidated as we found no significant differences in the observed versus expected distribution of ABO phenotypes among the included cases. The prevalence of RDS, pneumonia, and respiratory failure was found higher among hospitalized COVID-19 patients in the deceased group. However, other factors such as fever, cough, and asthma appeared to be more significantly lower than in the recovered group.

Heterogeneity in subnational mortality in the context of the COVID-19 pandemic: the case of Belgian districts in 2020

BACKGROUND

The COVID-19 pandemic has led to major shocks in mortality trends in many countries. Yet few studies have evaluated the heterogeneity of the mortality shocks at the sub-national level, rigorously accounting for the different sources of uncertainty.

METHODS

Using death registration data from Belgium, we first assess change in the heterogeneity of districts' standardized mortality ratios in 2020, when compared to previous years. We then measure the shock effect of the pandemic using district-level values of life expectancy, comparing districts' observed and projected life expectancy, accounting for all sources of uncertainty (stemming from life-table construction at district level and from projection methods at country and district levels). Bayesian modelling makes it easy to combine the different sources of uncertainty in the assessment of the shock. This is of particular interest at a finer geographical scale characterized by high stochastic variation in annual death counts.

RESULTS

The heterogeneity in the impact of the pandemic on all-cause mortality across districts is substantial: while some districts barely show any impact, the Bruxelles-Capitale and Mons districts experienced a decrease in life expectancy at birth of 2.24 (95% CI:1.33-3.05) and 2.10 (95% CI:0.86-3.30) years, respectively. The year 2020 was associated with an increase in the heterogeneity of mortality levels at a subnational scale in comparison to past years, measured in terms of both standardized mortality ratios and life expectancies at birth. Decisions on uncertainty thresholds have a large bearing on the interpretation of the results.

CONCLUSION

Developing sub-national mortality estimates taking careful account of uncertainty is key to identifying which areas have been disproportionately affected.

Changes in prenatal testing during the COVID-19 pandemic

OBJECTIVE

The coronavirus disease 2019 (COVID-19) pandemic disrupted healthcare delivery, including prenatal care. The study objective was to assess if timing of routine prenatal testing changed during the COVID-19 pandemic.

METHODS

Retrospective observational cohort study using claims data from a regional insurer (Highmark) and electronic health record data from two academic health systems (Penn Medicine and Yale New Haven) to compare prenatal testing timing in the pre-pandemic (03/10/2018-12/31/2018 and 03/10/2019-12/31/2019) and early COVID-19 pandemic (03/10/2020-12/31/2020) periods. Primary outcomes were second trimester fetal anatomy ultrasounds and gestational diabetes (GDM) testing. A secondary analysis examined first trimester ultrasounds.

RESULTS

The three datasets included 31,474 pregnant patients. Mean gestational age for second trimester anatomy ultrasounds increased from the pre-pandemic to COVID-19 period (Highmark 19.4 vs. 19.6 weeks; Penn: 20.1 vs. 20.4 weeks; Yale: 18.8 vs. 19.2 weeks, all p < 0.001). There was a detectable decrease in the proportion of patients who completed the anatomy survey <20 weeks' gestation across datasets, which did not persist at <23 weeks' gestation. There were no consistent changes in timing of GDM screening. There were significant reductions in the proportion of patients with first trimester ultrasounds in the academic institutions (Penn: 57.7% vs. 40.6% and Yale: 78.7% vs. 65.5%, both p < 0.001) but not Highmark. Findings were similar with multivariable adjustment.

CONCLUSION

While some prenatal testing happened later in pregnancy during the pandemic, pregnant patients continued to receive appropriately timed testing. Despite disruptions in care delivery, prenatal screening remained a priority for patients and providers during the COVID-19 pandemic.