COVID-19 in Brazilian cities: Impact of social determinants, coverage and quality of primary health care.

BACKGROUND: Brazil, as many other countries, have been heavily affected by COVID-19. This study aimed to analyze the impact of Primary health care and the family health strategy (FHS) coverage, the scores of the National Program for Improving Primary Care Access and Quality (PMAQ), and socioeconomic and social indicators in the number of COVID-19 cases in Brazilian largest cities. METHODS: This is an ecological study, carried out through the analysis of secondary data on the population of all Brazilian main cities, based on the analysis of a 26-week epidemiological epidemic week series by COVID-19. Statistical analysis was performed using Generalized Linear Models with an Autoregressive work correlation matrix. RESULTS: It was shown that greater PHC coverage and greater FHS coverage together with an above average PMAQ score are associated with slower dissemination and lower burden of COVID-19. CONCLUSION: It is evident that cities with less social inequality and restrictions of social protection combined with social development have a milder pandemic scenario. It is necessary to act quickly on these conditions for COVID-19 dissemination by timely actions with high capillarity. Expanding access to PHC and social support strategies for the vulnerable are essential.

Primary health care and social isolation against COVID-19 in Northeastern Brazil: Ecological time-series study.

BACKGROUND: Brazil is witnessing a massive increase of corona virus disease (COVID-19). Its peculiar primary health care (PHC) system faces a burden due to the contagion occurring in the community environment. Then, the aim is to estimate the effect of the coverage of primary health care and social isolation on the evolution of confirmed cases and deaths by COVID-19, controlling sociodemographic, economic and health system aspects. METHODS: A time series design was designed with data on diagnosed cases of COVID-19 and their deaths as outcomes in the capital cities of the Northeast region of Brazil. Independent variables such as PHC coverage, hospital beds, social isolation, demographic density, Gini index and other indicators were analyzed. A Autoregressive Generalized Linear Model method was applied for model the relationship. RESULTS: We identified an exponential growth of cases (y = 0.00250.71x; p-value<0,001). However, there is a high variability in the occurrence of outcomes. PHC coverage≥75% (χ2 = 9.27; p-value = 0.01) and social isolation rate (χ2 = 365.99; p-value<0.001) proved to be mitigating factors for the spread of COVID-19 and its deaths. Capitals with hospital beds ≥ 3.2 per thousand inhabitants had fewer deaths (χ2 = 9.02; p-value = 0.003), but this was influenced by PHC coverage (χ2 = 30,87; p-value<0.001). CONCLUSIONS: PHC mitigates the occurrence of Covid-19 and its deaths in a region of social vulnerability in Brazil together with social isolation. However, it is not known until when the system will withstand the overload in view of the low adhesion to social isolation, the lack of support and appropriate direction from the government to its population.