Analysis of public policies to combat COVID-19 in the state of Paraná, Brazil

被引:0
|
作者
Terre, Bruna Regina Bratti Frank [1 ]
Toso, Beatriz Rosana Goncalves de Oliveira [1 ]
Reis, Luiz Fernando [1 ]
Johann, Jerry Adriani [2 ]
机构
[1] Univ Estadual Oeste Parana, Ctr Ciencias Biol & Saude, Programa Pos Grad Stricto Sensu Biociencias & Saud, Cascavel, Brazil
[2] Univ Estadual Oeste Parana, Pro Reitoria Pesquisa Pos Grad, Programa Pos Grad Stricto Sensu Engn Agr, Cascavel, Brazil
关键词
COVID-19; public policy; health indicators; public administration; pandemic;
D O I
10.3389/fpubh.2024.1384561
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Introduction The COVID-19 pandemic had a great impact on several public sectors worldwide, requiring the implementation of public policies in an organized way to contain and control the disease. Thus, this study aimed to analyze public policies to face the COVID-19 pandemic in the State of Paran & aacute;, Brazil.Methods This was a cross-sectional, retrospective, quantitative survey carried out with data from March 2020 to March 2022 in the twenty-two municipalities that host the local health regions. Data collection was documentary, carried out from the municipal Portal da Transpar & ecirc;ncia website, which is dedicated to making public all expenditures, and epidemiological bulletins released by the Health Department of the state of Paran & aacute;. The variables analyzed were New Cases and Deaths, Mortality and Lethality Coefficient, Incidence Rate, Vaccination Coverage, Number of Hospital and ICU beds exclusive to COVID-19, Settled Expenses destined for COVID-19 and coping measures, namely, the Declaration of Public Health Emergency, Curfew, Mandatory use of masks, Businesses closure, Teleworking of risk groups, and Suspension of activities with crowds and of classes. After collection, data underwent descriptive analysis, and subsequently, the correlation of variables was analyzed using the Spearman test. Multiple linear regression was applied using the variable selection method called best subset selection (BSS). The dependent variables listed were incidence rate, new cases and new deaths.Results The results showed that coping measures, as well as the application of resources for the pandemic, were implemented heterogeneously in the municipalities studied, and the progression of the disease, the distribution of beds and vaccination occurred unevenly and may be a reflection of the limited Brazilian national governance. An important correlation was observed between the incidence rate and new deaths with vaccination coverage. In addition, the regression model showed that measures such as mandatory use of masks, closure of shops, suspension of classes, and curfew showed important correlations with the variables incidence rate, cases, and new deaths.Discussion The study highlighted the importance of carrying out a robust analysis of public policies to face emergencies of global importance so that government entities are prepared for future crises of great repercussions, such as the COVID-19 pandemic.
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