The association between area deprivation and COVID-19 incidence: a municipality-level spatio-temporal study in Belgium, 2020–2021

Increased mortality in socioeconomic disadvantaged municipalities during the first phase of the COVID-19 pandemic in Lombardy region

BACKGROUND

Lombardy was the first European region most severely affected by the coronavirus disease 2019 pandemic in the spring of 2020. During that period, a substantial increase in socioeconomic inequality in total mortality was observed. This study aims to evaluate mortality data in the region up to September 2023 to verify whether the increased disparities between the poorest and the wealthiest municipalities persisted in the subsequent phases of the pandemic.

METHODS

This study analyzed mortality data from January 2019 to September 2023 in Lombardy's municipalities by month and pandemic phases characterized by the predominance of the different severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Municipalities were grouped according to the average income or pension of their residents. Age-standardized mortality rates (ASMRs) and the ASMR ratio between the poorest and the wealthiest municipalities were compared throughout the study period.

RESULTS

In the pre-pandemic period (January 2019 - February 2020), the ASMR ratio at all ages between the poorest and the wealthiest municipalities fluctuated between 1.12 [95% confidence interval (CI): 1.07-1.16] and 1.29 (95% CI: 1.25-1.34). In March 2020, the ASMR ratio increased to 1.49 (95% CI: 1.45-1.52 95%) and returned to values registered before the pandemic thereafter. A similar pattern was observed in the analysis of mortality ≥ 65, using the average pension for group municipalities.

CONCLUSIONS

During the dramatic circumstances that the region faced in March 2020, pre-existing socioeconomic inequalities substantially widened. With the reorganization of the health system and the availability of vaccines, these disparities returned to the levels recorded before the pandemic.

Area and individual level analyses of demographic and socio-economic disparities in COVID-19 vaccination uptake in Belgium

Vaccination has played a major role in overcoming the COVID-19 pandemic. However, vaccination status can be influenced by demographic and socio-economic factors at individual and area level. In the context of the LINK-VACC project, the Belgian vaccine register for the COVID-19 vaccination campaign was linked at individual level with other registers, notably the COVID-19 laboratory test results and demographic and socio-economic variables from the DEMOBEL database. The present article aims at investigating to which extent COVID-19 vaccination status is associated with area level and/or individual level demographic and socio-economic factors. From a sample of all individuals tested for SARS-CoV-2 (LINK-VACC sample) demographic and socio-economic indicators are derived and their impact on vaccination coverages at an aggregated geographical level (municipality) is quantified. The same indicators are calculated for the full Belgian population, allowing to assess the representativeness of the LINK-VACC sample with respect to the impact of demographic and socio-economic disparities on vaccination uptake. In a second step, hierarchical models are fitted to the individual level LINK-VACC data to disentangle the individual and municipality effects allowing to evaluate the added value of the availability of individual level data in this context. The most important effects observed at the individual level are reflected in the aggregated data at the municipality level. Multilevel analyses show that most of the demographic and socio-economic impacts on vaccination are captured at the individual level, although accounting for area level in individual level analyses improve the overall description.

Geospatial patterns of excess mortality in Belgium: Insights from the first year of the COVID-19 pandemic

OBJECTIVES

Belgium experienced multiple COVID-19 waves that hit various groups in the population, which changed the mortality pattern compared to periods before the pandemic. In this study, we investigated the geographical excess mortality trend in Belgium during the first year of the COVID-19 pandemic.

METHODS

We retrieved the number of deaths and population data in 2020 based on gender, age, and municipality of residence, and we made a comparison with the mortality data in 2017-2019 using a spatially discrete model.

RESULTS

Excess mortality was significantly associated with age, gender, and COVID-19 incidence, with larger effects in the second half of 2020. Most municipalities had higher risks of mortality with a number of exceptions in the northeastern part of Belgium. Some discrepancies in excess mortality were observed between the north and south regions.

CONCLUSIONS

This study offers useful insight into excess mortality and will aid local and regional authorities in monitoring mortality trends.

Breast cancer incidence, stage distribution, and treatment shifts during the 2020 COVID-19 pandemic: a nationwide population-level study

BACKGROUND

The first COVID-19 wave in 2020 necessitated temporary suspension of non-essential medical services including organized cancer screening programs in Belgium. This study assessed the impact of the pandemic on breast cancer (BC) incidence, stage at diagnosis, and management in Belgium in 2020.

METHODS

All Belgian residents diagnosed with in situ or invasive BC in 2015-2020 in the nationwide, population-based cancer registry database were included. Incidence trends for 2015-2019 were extrapolated to predict incidence and stage distribution for 2020 and compared with the observed values. National healthcare reimbursement data were used to examine treatment strategies. Exact tumor diameter and nodal involvement, extracted from pathology reports, were analyzed for 2019 and 2020.

RESULTS

74,975 tumors were selected for analysis of incidence and clinical stage. Invasive BC incidence declined by -5.0% in 2020, with a drop during the first COVID-19 wave (Mar-Jun; -23%) followed by a rebound (Jul-Dec; +7%). Predicted and observed incidence (in situ + invasive) was not different in patients < 50 years. In the 50-69 and 70 + age groups, significant declines of -4.1% and - 8.4% respectively were found. Excess declines were seen in clinical stage 0 and I in Mar-Jun, without excess increases in clinical stage II-IV tumors in Jul-Dec. There was no increase in average tumor diameter or nodal involvement in 2020. Patients diagnosed in Mar-Jun received significantly more neoadjuvant therapy, particularly neoadjuvant hormonal therapy for patients with clinical stage I-II BC.

CONCLUSIONS

BC incidence decline in 2020 in Belgium was largely restricted to very early-stage BC and patients aged 50 and over. Delayed diagnosis did not result in an overall progression to higher stage at diagnosis in 2020. Observed treatment adaptations in Belgium were successful in prioritizing patients for surgery while preventing tumor progression in those with surgical delay. Continuation of monitoring BC incidence and stage in the future is crucial.

Outreach work in Belgian primary care practices during COVID-19: results from the cross-sectional PRICOV-19 study

BACKGROUND

General practitioners (GPs) have a vital role in reaching out to vulnerable populations during and after the COVID-19 pandemic. Nonetheless, they experience many challenges to fulfill this role. This study aimed to examine associations between practice characteristics, patient population characteristics and the extent of deprivation of practice area on the one hand, and the level of outreach work performed by primary care practices (PCPs) during the COVID-19 pandemic on the other hand.

METHODS

Belgian data from the international PRICOV-19 study were analyzed. Data were collected between December 2020 and August 2021 using an online survey in PCPs. Practices were recruited through randomized and convenience sampling. Descriptive statistics and ordinal logistic regression analyses were performed. Four survey questions related to outreach work constitute the outcome variable. The adjusted models included four practice characteristics (practice type, being a teaching practice for GP trainees; the presence of a nurse or a nurse assistant and the presence of a social worker or health promotor), two patient population characteristics (social vulnerability and medical complexity) and an area deprivation index.

RESULTS

Data from 462 respondents were included. First, the factors significantly associated with outreach work in PCPs are the type of PCP (with GPs working in a group performing more outreach work), and the presence of a nurse (assistant), social worker or health promotor. Second, the extent of outreach work done by a PCP is significantly associated with the social vulnerability of the practice's patient population. This social vulnerability factor, affecting outreach work, differed with the level of medical complexity of the practice's patient population and with the level of deprivation of the municipality where the practice is situated.

CONCLUSIONS

In this study, outreach work in PCPs during the COVID-19 pandemic is facilitated by the group-type cooperation of GPs and by the support of at least one staff member of the disciplines of nursing, social work, or health promotion. These findings suggest that improving the effectiveness of outreach efforts in PCPs requires addressing organizational factors at the practice level. This applies in particular to PCPs having a more socially vulnerable patient population.

Socioeconomic Inequalities in SARS-CoV-2 Infection and COVID-19 Health Outcomes in Urban Italy During the COVID-19 Vaccine Rollout, January-November 2021

This study analysed the evolution of the association of socioeconomic deprivation (SED) with SARS-CoV-2 infection and COVID-19 outcomes in urban Italy during the vaccine rollout in 2021. We conducted a retrospective cohort analysis between January and November 2021, comprising of 16,044,530 individuals aged ≥ 20 years, by linking national COVID-19 surveillance system data to the Italian SED index calculated at census block level. We estimated incidence rate ratios (IRRs) of infection and severe COVID-19 outcomes by SED tercile relative to the least deprived tercile, over three periods defined as low (0-10%); intermediate (> 10-60%) and high (> 60-74%) vaccination coverage. We found patterns of increasing relative socioeconomic inequalities in infection, hospitalisation and death as COVID-19 vaccination coverage increased. Between the low and high coverage periods, IRRs for the most deprived areas increased from 1.09 (95%CI 1.03-1.15) to 1.28 (95%CI 1.21-1.37) for infection; 1.48 (95%CI 1.36-1.61) to 2.02 (95%CI 1.82-2.25) for hospitalisation and 1.57 (95%CI 1.36-1.80) to 1.89 (95%CI 1.53-2.34) for death. Deprived populations in urban Italy should be considered as vulnerable groups in future pandemic preparedness plans to respond to COVID-19 in particular during mass vaccination roll out phases with gradual lifting of social distancing measures.

Sociodemographic and socioeconomic disparities in COVID-19 vaccine uptake in Belgium: a nationwide record linkage study

BACKGROUND

Recent studies have identified important social inequalities in SARS-CoV-2 infections and related COVID-19 outcomes in the Belgian population. The aim of our study was to investigate the sociodemographic and socioeconomic characteristics associated with the uptake of COVID-19 vaccine in Belgium.

METHODS

We conducted a cross-sectional analysis of the uptake of a first COVID-19 vaccine dose among 5 342 110 adults (≥18 years) in Belgium on 31 August 2021. We integrated data from four national data sources: the Belgian vaccine register (vaccination status), COVID-19 Healthdata (laboratory test results), DEMOBEL (sociodemographic/socioeconomic data) and the Common Base Register for HealthCare Actors (individuals licensed to practice a healthcare profession in Belgium). We used multivariable logistic regression analysis for identifying characteristics associated with not having obtained a first COVID-19 vaccine dose in Belgium and for each of its three regions (Flanders, Brussels and Wallonia).

RESULTS

During the study period, 10% (536 716/5 342 110) of the Belgian adult population included in our study sample was not vaccinated with a first COVID-19 vaccine dose. A lower COVID-19 vaccine uptake was found among young individuals, men, migrants, single parents, one-person households and disadvantaged socioeconomic groups (with lower levels of income and education, unemployed). Overall, the sociodemographic and socioeconomic disparities were comparable for all regions.

CONCLUSIONS

The identification of sociodemographic and socioeconomic disparities in COVID-19 vaccination uptake is critical to develop strategies guaranteeing a more equitable vaccination coverage of the Belgian adult population.

Risk of partial school closure for COVID-19 by socio-economic level in the period 2020-22

BACKGROUND

The objective was to analyse the risk of partial school closure by economic level in Barcelona city.

METHODS

In this ecological study, the risk of partial school closure for the academic years 2020-21 and 2021-22 was estimated by dividing the total number of days that each child was in quarantine or isolation by the total number of days that each child was at risk to be in quarantine or isolation in the academic year. The association between partial school closure risk and mean income by district was estimated with the Spearman rho.

RESULTS

The lower the mean income, the higher the risk of partial closure (Spearman rho = 0.83; P-value = 0.003) during the academic year 2020-21. Specifically, the children from the district with the lowest income had a six times greater risk of partial school closure compared with those from the highest-income district. This risk did not show a significant socioeconomic gradient in the academic year 2021-22.

CONCLUSIONS

The risk of partial school closure presented an inverse socioeconomic gradient in the city of Barcelona according to average income by district in the academic year 2020-21. This distribution was not observed in the academic year 2021-22.

Stage shift and relative survival for head and neck cancer during the 2020 COVID-19 pandemic: a population-based study of temporal trends

Objective

During the first wave of the COVID-19 pandemic in 2020, non-essential health services were suspended in Belgium, and the public was ordered to socially isolate. Underdiagnosis of cancer during this period was reported worldwide. Certain risk factors for head and neck cancer (HNC) overlap with those for COVID-19 incidence and mortality, making underdiagnosis and subsequent stage shift of this potentially rapidly progressing cancer a major concern. We aimed to analyze incidence, clinical stage at presentation, and survival of patients diagnosed with HNC in 2020 in Belgium, considering recent temporal trends.

Methods

Using population-based data from the Belgian Cancer Registry (BCR), we extrapolated 2017-2019 trends in incidence, clinical stage, and 1-year relative survival (1yRS) of HNC to create an expected value for 2020 and compared this to the observed value.

Results

There were 9.5% fewer HNCs diagnosed in 2020, compared to the predicted incidence. Underdiagnosis was larger for males (-11.8%), patients aged 50-64 (-11.2%) and 65-79 (-11.1%), and for oral cavity cancer (-17.6%). Shifts to more advanced stages were observed in larynx and oropharynx tumors and for (male) patients aged 80+. A 2.4 percentage point decline in 1yRS was observed, relative to the increasing trends in 1yRS (2017-2019).

Conclusion

The COVID-19 pandemic led to underdiagnosis of HNC, resulting in shifts to more advanced stage at presentation in certain subgroups. A stage shift can be expected for the 9.5% of tumors not yet diagnosed at the end of 2020. HNC patients diagnosed in 2020 suffered higher than expected mortality.

Socio-Economic Factors Associated with Ethnic Disparities in SARS-CoV-2 Infection and Hospitalization

BACKGROUND

There is evidence that non-Italians presented higher incidence of infection and worse health outcomes if compared to native populations in the COVID-19 pandemic. The aim of the study was to compare Italian- and non-Italian-born health outcomes, accounting for socio-economic levels.

METHODS

We analyzed data relative to 906,463 people in Umbria (Italy) from 21 February 2020 to 31 May 2021. We considered the National Deprivation Index, the Urban-Rural Municipalities Index and the Human Development Index (HDI) of the country of birth. We used a multilevel logistic regression model to explore the influence of these factors on SARS-CoV-2 infection and hospitalization rates. Diagnosis in the 48 h preceding admission was an indicator of late diagnosis among hospitalized cases.

RESULTS

Overall, 54,448 persons tested positive (6%), and 9.7% of them were hospitalized. The risk of hospital admission was higher among non-Italians and was inversely related to the HDI of the country of birth. A diagnosis within 48 h before hospitalization was more frequent among non-Italians and correlated to the HDI level.

CONCLUSIONS

COVID-19 had unequal health outcomes among the population in Umbria. Reduced access to primary care services in the non-Italian group could explain our findings. Policies on immigrants' access to primary healthcare need to be improved.

Social and clinical risk factors associated with hospitalized COVID-19 patients in Brussels's deprived and multiethnic areas

BACKGROUND

In Belgium, the Brussels-Capital region was severely affected by the COVID-19 epidemic. Various hypotheses were mentioned in order to explain Brussels' excess disease spreading and mortality rate, but socioeconomic risk factors are increasingly recognized. This study's objective was to analyze clinical and social profiles of patients hospitalized for COVID-19, by nationality groups, in two hospitals located in Brussels's deprived and multiethnic areas.

METHODS

Data covered hospitalized COVID-19 patients from two Brussels hospitals (n = 787) between the 1st of March 2020 and the 31st of June 2020. Social data was collected using hospital records, and clinical data was extracted from hospitals' COVID-19 databases. Multivariable logistic regression models were used to estimate the odds ratios (OR) of the association between two outcomes (Intensive Care Unit admission and mortality) and risk factors (social and clinical).

RESULTS

Patients from Sub-Saharan Africa were younger, had a higher prevalence of obesity, lacked health insurance, and had the highest proportion of Intensive Care Unit (ICU) admission (27.7%) but the lowest mortality rates than other nationality groups. Patients from North Africa had a higher prevalence of diabetes compared to other nationality groups and a high proportion of European patients came from nursing homes. Patients deprived of health insurance had a higher risk of ICU admission compared to those who had insurance (OR IC95%; 1,9 1.1-3.6, p = 0.03). Other risk factors as sex and obesity were significantly associated to ICU admission and, age and hypertension were significantly associated to mortality.

CONCLUSION

Social and clinical profile of the patients differs between the nationality groups, and some risk factors for Intensive Care Unit admission and mortality were linked to more patients' precarious situation as the availability of health insurance. This study underlines the role of selected social health determinants and the importance of routinely collecting social along with clinical data.

Ecosystem degradation and the spread of Covid-19

The linkages between the emergence of zoonotic diseases and ecosystem degradation have been widely acknowledged by the scientific community and policy makers. In this paper we investigate the relationship between human overexploitation of natural resources, represented by the Human Appropriation of Net Primary Production Index (HANPP) and the spread of Covid-19 cases during the first pandemic wave in 730 regions of 63 countries worldwide. Using a Bayesian estimation technique, we highlight the significant role of HANPP as a driver of Covid-19 diffusion, besides confirming the well-known impact of population size and the effects of other socio-economic variables. We believe that these findings could be relevant for policy makers in their effort towards a more sustainable intensive agriculture and responsible urbanisation.

Association of socio-economic deprivation with COVID-19 incidence and fatality during the first wave of the pandemic in Italy: lessons learned from a local register-based study

BACKGROUND

COVID-19 has been characterised by its global and rapid spread, with high infection, hospitalisation, and mortality rates worldwide. However, the course of the pandemic showed differences in chronology and intensity in different geographical areas and countries, probably due to a multitude of factors. Among these, socio-economic deprivation has been supposed to play a substantial role, although available evidence is not fully in agreement. Our study aimed to assess incidence and fatality rates of COVID-19 across the levels of socio-economic deprivation during the first epidemic wave (March-May 2020) in the Italian Province of Foggia, Apulia Region.

METHODS

Based on the data of the regional active surveillance platform, we performed a retrospective epidemiological study among all COVID-19 confirmed cases that occurred in the Apulian District of Foggia, Italy, from March 1st to May 5th, 2020. Geocoded addresses were linked to the individual Census Tract (CT) of residence. Effects of socio-economic condition were calculated by means of the Socio-Economic and Health-related Deprivation Index (SEHDI) on COVID-19 incidence and fatality.

RESULTS

Of the 1054 confirmed COVID-19 cases, 537 (50.9%) were men, 682 (64.7%) were 0-64 years old, and 338 (32.1%) had pre-existing comorbidities. COVID-19 incidence was higher in the less deprived areas (p < 0.05), independently on age. The level of socio-economic deprivation did not show a significant impact on the vital status, while a higher fatality was observed in male cases (p < 0.001), cases > 65 years (p < 0.001), cases having a connection with a nursing home (p < 0.05) or having at least 1 comorbidity (p < 0.001). On the other hand, a significant protection for healthcare workers was apparent (p < 0.001).

CONCLUSIONS

Our findings show that deprivation alone does not affect COVID-19 incidence and fatality burden, suggesting that the burden of disease is driven by a complexity of factors not yet fully understood. Better knowledge is needed to identify subgroups at higher risk and implement effective preventive strategies.

Clinical and social determinants of health features of SARS-CoV-2 infection among Black and Caribbean Hispanic patients with heart failure: The SCAN-MP Study

Patients with heart failure (HF) often have multiple chronic conditions and are at increased risk for severe disease and mortality when infected by SARS-CoV-2, the virus that causes COVID-19. Furthermore, disparities in outcomes with COVID-19 have been associated with both racial/ethnic identity but also social determinants of health. Among older, urban-dwelling, minority patients with HF, we sought to characterize medical and non-medical factors associated with SARS-CoV-2 infection. Patients with HF living in Boston and New York City over 60 years of age participating in the Screening for Cardiac Amyloidosis with Nuclear Imaging (SCAN-MP) study between 12/1/2019 and 10/15/2021 (n = 180) were tested for nucleocapsid antibodies to SARS-CoV-2 and queried for symptomatic infection with PCR verification. Baseline testing included the Kansas City Cardiomyopathy Questionnaire (KCCQ), assessment of health literacy, biochemical, functional capacity, echocardiography, and a novel survey tool that determined living conditions, perceived risk of infection, and attitudes towards COVID-19 mitigation. The association of infection with prevalent socio-economic conditions was assessed by the area deprivation index (ADI). There were 50 overall cases of SARS-CoV-2 infection (28%) including 40 demonstrating antibodies to SARS-CoV-2 (indicative of prior infection) and 10 positive PCR tests. There was no overlap between these groups. The first documented case from New York City indicated infection prior to January 17, 2020. Among active smokers, none tested positive for prior SARS-CoV-2 infection (0 (0%) vs. 20 (15%), p = 0.004) vs. non-smokers. Cases were more likely to be taking ACE-inhibitors/ARBs compared to non-cases (78% vs 62%, p = 0.04). Over a mean follow-up of 9.6 months, there were 6 total deaths (3.3%) all unrelated to COVID-19. Death and hospitalizations (n = 84) were not associated with incident (PCR tested) or prior (antibody) SARS-CoV-2 infection. There was no difference in age, co-morbidities, living conditions, attitudes toward mitigation, health literacy, or ADI between those with and without infection. SARS-CoV-2 infection was common among older, minority patients with HF living in New York City and Boston, with evidence of infection documented in early January 2020. Health literacy and ADI were not associated with infection, and there was no increased mortality or hospitalizations among those infected with SARS-CoV-2.

Spatial Distribution of COVID-19 Hospitalizations and Associated Risk Factors in Health Insurance Data Using Bayesian Spatial Modelling

The onset of COVID-19 across the world has elevated interest in geographic information systems (GIS) for pandemic management. In Germany, however, most spatial analyses remain at the relatively coarse level of counties. In this study, we explored the spatial distribution of COVID-19 hospitalizations in health insurance data of the AOK Nordost health insurance. Additionally, we explored sociodemographic and pre-existing medical conditions associated with hospitalizations for COVID-19. Our results clearly show strong spatial dynamics of COVID-19 hospitalizations. The main risk factors for hospitalization were male sex, being unemployed, foreign citizenship, and living in a nursing home. The main pre-existing diseases associated with hospitalization were certain infectious and parasitic diseases, diseases of the blood and blood-forming organs, endocrine, nutritional and metabolic diseases, diseases of the nervous system, diseases of the circulatory system, diseases of the respiratory system, diseases of the genitourinary and symptoms, and signs and findings not classified elsewhere.

Influencia del índice de privación social en resultados durante la pandemia de COVID-19

Objetivo

Determinar la relación del índice de privación de la población con la utilización del sistema sanitario, la mala evolución y la mortalidad durante la pandemia de COVID-19.

Método

Estudio de cohorte retrospectivo de personas con infección por SARS-CoV-2 del 1 de marzo de 2020 al 9 de enero de 2022. Se recopilaron datos sociodemográficos, comorbilidad y tratamientos basales prescritos, otros datos basales y el índice de privación, estimado por sección censal. Se realizaron modelos multivariable de regresión logística multinivel para cada variable de resultado: fallecimiento, mala evolución (definida como fallecimiento o ingreso en la unidad de cuidados intensivos), ingreso y visitas a urgencias.

Resultados

La cohorte se compone de 371.237 personas con infección por SARS-CoV-2. En los modelos multivariable se observó un mayor riesgo de fallecimiento, de mala evolución, de ingreso hospitalario o de visita a urgencias en los quintiles de mayor privación en comparación con el quintil de menor privación. Para el riesgo de ser hospitalizado o de acudir a urgencias, en términos generales hubo diferencias entre todos los quintiles. También se observó que estas diferencias se daban en el primer y el tercer periodos de la pandemia para la mortalidad y la mala evolución, y en todos para el riesgo de ser ingresado o de acudir a urgencias.

Conclusiones

Los colectivos con mayor nivel de privación han tenido mayores tasas de mortalidad y de ingreso en comparación con los colectivos con unas tasas de privación más bajas. Es necesario realizar intervenciones que minimicen estas desigualdades.

Municipal Ethnic Composition and Disparities in COVID-19 Infections in New Jersey: A Blinder-Oaxaca Decomposition Analysis

COVID-19 has disproportionally impacted Latinx and Black communities in the US. Our study aimed to extend the understanding of ethnic disparities in COVID-19 case rates by using a unique dataset of municipal case rates across New Jersey (NJ) during the first 17 months of the pandemic. We examined the extent to which there were municipal-level ethnic disparities in COVID-19 infection rates during three distinct spikes in case rates over this period. Furthermore, we used the Blinder-Oaxaca decomposition analysis to identify municipal-level exposure and vulnerability factors that contributed to ethnic disparities and how the contributions of these factors changed across the three initial waves of infection. Two clear results emerged. First, in NJ, the COVID-19 infection risk disproportionally affected Latinx communities across all three waves during the first 17 months of the pandemic. Second, the exposure and vulnerability factors that most strongly contributed to higher rates of infection in Latinx and Black communities changed over time as the virus, alongside medical and societal responses to it, also changed. These findings suggest that understanding and addressing ethnicity-based COVID-19 disparities will require sustained attention to the systemic and structural factors that disproportionately place historically marginalized ethnic communities at greater risk of contracting COVID-19.

Area Deprivation and COVID-19 Incidence and Mortality in Bavaria, Germany: A Bayesian Geographical Analysis

Background

Area deprivation has been shown to be associated with various adverse health outcomes including communicable as well as non-communicable diseases. Our objective was to assess potential associations between area deprivation and COVID-19 standardized incidence and mortality ratios in Bavaria over a period of nearly 2 years. Bavaria is the federal state with the highest infection dynamics in Germany and demographically comparable to several other European countries.

Methods

In this retrospective, observational ecological study, we estimated the strength of associations between area deprivation and standardized COVID-19 incidence and mortality ratios (SIR and SMR) in Bavaria, Germany. We used official SARS-CoV-2 reporting data aggregated in monthly periods between March 1, 2020 and December 31, 2021. Area deprivation was assessed using the quintiles of the 2015 version of the Bavarian Index of Multiple Deprivation (BIMD 2015) at district level, analyzing the overall index as well as its single domains.

Results

Deprived districts showed higher SIR and SMR than less deprived districts. Aggregated over the whole period, the SIR increased by 1.04 (95% confidence interval (95% CI): 1.01 to 1.07, p = 0.002), and the SMR by 1.11 (95% CI: 1.07 to 1.16, p < 0.001) per BIMD quintile. This represents a maximum difference of 41% between districts in the most and least deprived quintiles in the SIR and 110% in the SMR. Looking at individual months revealed clear linear association between the BIMD quintiles and the SIR and SMR in the first, second and last quarter of 2021. In the summers of 2020 and 2021, infection activity was low.

Conclusions

In more deprived areas in Bavaria, Germany, higher incidence and mortality ratios were observed during the COVID-19 pandemic with particularly strong associations during infection waves 3 and 4 in 2020/2021. Only high infection levels reveal the effect of risk factors and socioeconomic inequalities. There may be confounding between the highly deprived areas and border regions in the north and east of Bavaria, making the relationship between area deprivation and infection burden more complex. Vaccination appeared to balance incidence and mortality rates between the most and least deprived districts. Vaccination makes an important contribution to health equality.