Mortalidade e Análise Espacial da COVID-19 nas Regionais de Saúde do Paraná

Abstract

In late December 2019, an outbreak of pneumonia was detected in the city of Wuhan, China. On March 11, 2020, the World Health Organization reported that the SARS-CoV-2 outbreak had become a pandemic. This study aims to analyze mortality from COVID-19 in the 22 Health Districts of the State of Paraná, from March 2020 to May 2021. This is an ecological study, using spatial area analysis techniques. It comprised the 22 Health Districts of Paraná. Crude and age-standardized COVID-19 mortality rates were calculated for the total and by sex and age group. For the spatial analysis, maps representing the age-standardized mortality rates by COVID-19 were prepared. Correlations between COVID-19 mortality rates and demographic, socioeconomic and health indicators were also analyzed, as well as comparisons between Health Regions with lower and higher COVID-19 mortality rates in relation to the same indicators. The significance level was 5%. As a result, data from 27,658 deaths caused by COVID-19 were found in the 22 Health Regions of the State of Paraná, where the crude general mortality rate was 240 deaths per 100,000 inhabitants. The highest rates age-standardized group were observed for the 8th (Francisco Beltrão), with 324 per 100,000 inhab. followed by the 14th (Paranavaí), with 314 per 100,000 inhab.) and the 1st (Paranaguá), with 307 per 100,000 inhab.). The lowest age-standardized rates were observed for the 15th Health Region (Maringá) and 16th (Apucarana), with rates of 139 deaths per 100,000 inhabitants each. There was a large percentage variation between crude and standardized mortality rates by age group, from a decrease of - 51.7% to an increase of 79.4%. Most Health Districts, 59.1% (n=13), had higher rates after standardization. Mortality rates were significantly higher for men compared to women (p<0.001). Mortality rates in all Health Regions increased progressively with increasing age. Among the analyzed variables, the greater the number of specialist physicians in the SUS per 100,000 inhabitants (p=0.022) and the greater the number of total nurses per 100,000 inhabitants (p=0.041), the significantly lower were the standardized mortality rates for COVID-19. The Health Districts with the highest total number of CT scanners in use per 100,000 inhabitants (p=0.049) and the highest total number of physiotherapists per 100,000 inhabitants (p=0.023), had significantly lower mortality rates compared to the regions with the lowest numbers of these indicators. No significant associations or correlations were observed between age-standardized mortality rates and demographic and socioeconomic indicators. The findings of this study highlighted the importance of analyzing mortality from COVID-19, its characteristics and possible associations with demographic, socioeconomic and health indicators. These analyzes can support the development of specific public policies for the prevention and treatment of future diseases.