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

TL;DR

This study analyzes how public policies in Paraná, Brazil, addressed the COVID-19 pandemic, finding uneven implementation and correlations between measures and outcomes.

Contribution

The study provides a quantitative analysis of public policy responses to the pandemic in Paraná, Brazil, using novel statistical methods to assess their effectiveness.

Findings

Coping measures and resource allocation varied significantly across municipalities in Paraná.

Vaccination coverage correlated strongly with incidence rates and new deaths.

Measures like mask mandates and business closures showed significant correlations with pandemic outcomes.

Abstract

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 Paraná, Brazil.

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 Transparência website, which is dedicated to making public all expenditures, and epidemiological bulletins released by the Health Department of the state of Paraná. 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.

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.

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.