The spatial distribution and Calculator for Severity and Death for COVID-19

Background: Latin America has one of the highest COVID-19 mortality rates in the world, driven by inequality in its population. We aimed to analyze the spatial distribution and factors associated with the risk of SARS and death in COVID-19 cases using routine record data and to develop and validate a prognostic tool for risk of death by Covid-19. Methods: : A cross-sectional study was conducted from March 2020 to April 2021 in the South Zone of the city of São Paulo, SP, Brazil, with 16,061 positive cases of COVID-19. The data were -obtained from the records of the Brazilian Ministry of Health notification systems for flu-like syndrome (eSUS-VE) and hospitalized SARS (SIVEP-Gripe). The spatial distribution of the cases is represented in 2D kernel density. To assess the possible factors associated with the outcomes, generalized linear and generalized additive logistic models were adjusted. To assess the discriminatory power the C-statistic was used. A calculator was developed based on a prognostic model for the risk of death, validated with accuracy measures in the sample, internal validation and temporal validation. Results: : The average age of patients was 42.1 years. Evolved to SARS 925 (11.98%) and 375 (2.37%) died. The comorbidities associated with a higher risk of SARS were obesity (OR=25.32) and immunodepression (OR=12.15). The comorbidities associated with a higher risk of death were renal diseases (OR=11.8) and obesity (OR=8.49), with clinical and demographic information being more important than the spatial area. The COVID-19 risk of death calculator showed an accuracy of 92.2% in the sample build, 92.3% in the internal validation and 80% in the temporal validation. Conclusions: Age and comorbidities were identified as the most associated factors to the severity of the disease. For the death analysis, the socioeconomic condition is included in addition to these factors. The calculator can be used and implemented in services of varying complexity because it contains easily accessible information to guide prevention and care.