[Mapping Regional Differences in Infection Rates for the Coronavirus (COVID-19): Results of a Bayesian Approach to Administrative Districts of Bavaria]. / Kartografische Darstellung regionaler Unterschiede der Infektionsraten beim Coronavirus (COVID-19): Ergebnisse einer bayesianischen Glättung über Landkreise Bayerns.

BACKGROUND: Since the beginning of the COVID-19 pandemic, thematic maps showing the spread of the disease have been of great public interest. From the perspective of risk communication, those maps can be problematic, since random variation or extreme values may occur and cover up the actual regional patterns. One potential solution is applying spatial smoothing methods. The aim of this study was to show changes in incidence ratios over time in Bavarian districts using spatially smoothed maps. METHODS: Data on SARS-CoV-2 were provided by the Bavarian Health and Food Safety Authority on 29.10.2021 and 17.02.2022. The demographic data per district are derived from the Statistical Report of the Bavarian State Office for Statistics for 2019. Four age groups per sex (<18, 18-29, 30-64,>64 years) divided into 16 time periods (01/28/2020 to 12/31/2021) were included. Maps show standardized incidence ratios (SIR) spatially smoothed by Bayesian hierarchical modelling. RESULTS: The SIR varied remarkably between districts. Variations occurred for each time period, showing changing regional patterns over time. CONCLUSION: Smoothed health maps are suitable for showing trends in incidence ratios over time for COVID-19 in Bavaria and offer the advantage over traditional maps in giving more realistic estimates by including neighborhood relationships. The methodological approach can be seen as a first step to explain the regional heterogeneity in the pandemic, and to support improved risk communication.

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.

[Regional and Temporal Trends in SARS-CoV-2-Associated Mortality in Bavaria: An Age-Stratified Analysis Over 5 Quarters for Persons Aged 50 and Older]. / Regionale und zeitliche Trends der SARS-CoV-2 assoziierten Sterblichkeit in Bayern: Eine altersstratifizierte Analyse über 5 Quartale für Personen ab 50 Jahren.

OBJECTIVE: The aim of this study was to investigate the influence of regional factors such as incidence rate, hospitalizations, socio-economic status and nursing homes on the regional and temporal heterogeneity of SARS-CoV-2-associated mortality in Bavaria. METHODOLOGY: Official Bavarian SARS-CoV-2 reporting data were considered for three age groups (50-64, 65-74,>74 years) between March 2020 and April 2021. Maps of regional standardized mortality rates were spatially smoothed using a Bayesian hierarchical model. RESULTS: The picture of regional mortality was heterogeneous with an increasing gradient toward the northeast. Adjustment for standardized incidence rates, hospitalizations of infected persons, and availability of care homes for the elderly levelled the heterogeneity. CONCLUSION: The north-east gradient in Bavarian SARS-CoV-2-specific mortality rates is clearly explained by the comparable gradient in regional incidence rates. Other regional factors show a less clear influence.