Selected article for: "Corona virus and exponential growth"

Author: Costa de Assis, Sanderson José; Lopes, Johnnatas Mikael; Guedes, Marcello Barbosa Otoni Gonçalves; Sanchis, Geronimo José Bouzas; Araujo, Diego Neves; Roncalli, Angelo Giuseppe
Title: Primary health care and social isolation against COVID-19 in Northeastern Brazil: Ecological time-series study
  • Cord-id: u08vpw3f
  • Document date: 2021_5_13
  • ID: u08vpw3f
    Snippet: 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 diagnose
    Document: 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 = 0.0025(0.71x); 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.

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