ABSTRACT OBJECTIVE To evaluate the prevalence of reported symptoms of flu-like syndrome (FS) among HCW and compare HCW and non-HCW on the chance of reporting these symptoms, this study analyzed data of a population-based survey conducted in Brazil. METHODS A cross-sectional analysis was performed with self-reported data from the Brazilian National Household Sample Survey (PNAD Covid-19) from May 2020. The authors analyzed a probability sample of 125,179 workers, aged 18 to 65, with monthly income lower than US$ 3 500. The variable HCW or non-HCW was the covariate of interest and having reported FS symptoms or not was the outcome variable. Authors tested interactions of HCW with other covariates. A logit model – when controlling for sociodemographic, employment, and geographic characteristics – investigated the chance of HCW reporting FS compared to non-HCW. RESULTS HCW have a significant effect (odds ratio of 1.369) on reporting FS symptoms when compared to non-HCW. HCW account for 4.17% of the sample, with a higher frequency of FS (3.38%) than observed for non-HCW (2.43%). Female, non-white and older individuals had higher chance to report FS. CONCLUSIONS The HCW had a higher chance of reporting symptoms than non-HCW aged over 18 years in the labor force. These results emphasize guidelines for preventive measures to reduce workplace exposures in the healthcare facilities. The prevalence is disproportionately affecting HCW women and HCW non-whites. In the regions North and Northeast the steeper progression is consistent with the hypothesis of socioeconomic factors, and it explains the greater prevalence in HCW and non-HCW living in those territories.

ABSTRACT OBJECTIVE To evaluate the prevalence of reported symptoms of flu-like syndrome (FS) among HCW and compare HCW and non-HCW on the chance of reporting these symptoms, this study analyzed data of a population-based survey conducted in Brazil. METHODS A cross-sectional analysis was performed with self-reported data from the Brazilian National Household Sample Survey (PNAD Covid-19) from May 2020. The authors analyzed a probability sample of 125,179 workers, aged 18 to 65, with monthly income lower than US$ 3 500. The variable HCW or non-HCW was the covariate of interest and having reported FS symptoms or not was the outcome variable. Authors tested interactions of HCW with other covariates. A logit model – when controlling for sociodemographic, employment, and geographic characteristics – investigated the chance of HCW reporting FS compared to non-HCW. RESULTS HCW have a significant effect (odds ratio of 1.369) on reporting FS symptoms when compared to non-HCW. HCW account for 4.17% of the sample, with a higher frequency of FS (3.38%) than observed for non-HCW (2.43%). Female, non-white and older individuals had higher chance to report FS. CONCLUSIONS The HCW had a higher chance of reporting symptoms than non-HCW aged over 18 years in the labor force. These results emphasize guidelines for preventive measures to reduce workplace exposures in the healthcare facilities. The prevalence is disproportionately affecting HCW women and HCW non-whites. In the regions North and Northeast the steeper progression is consistent with the hypothesis of socioeconomic factors, and it explains the greater prevalence in HCW and non-HCW living in those territories.

Resumo: O presente trabalho tem por objetivo avaliar o impacto do Pronaf no PIB da economia brasileira e nos PIBs setoriais (PIB de serviços, agropecuário e industrial) a partir da aplicação de regressão quantílica com efeitos fixos para dados em painel. Além disso, diante da questão relativa à distribuição dos recursos, avaliam-se os diferentes resultados dentro do contexto regional, isto é, os diferentes impactos nas cinco macrorregiões do País (Norte, Nordeste, Centro-Oeste, Sudeste e Sul). O uso do modelo de regressão quantílica com efeitos fixos para dados em painel se justifica pelo fato de que as variáveis usadas na análise apresentam forte desigualdade entre os municípios brasileiros. Ao observar a resposta de cada quantil, e não apenas em relação à média, bem como levar em consideração o controle dos efeitos fixos, os efeitos do Pronaf sobre o PIB podem ser melhor captados. Os principais resultados obtidos indicam que há um efeito positivo do programa sobre o PIB total e PIBs setoriais. Apesar de o programa ser de caráter nacional, há diferentes efeitos entre as regiões, que sugerem que (i) mudanças e aprimoramentos no Pronaf possam ser conduzidos de maneira pertinente à cada região e que (ii) os recursos possam ser descentralizados.

Abstract: This study aims to assess the impact of Pronaf on the Brazilian GDP and on sectoral GDP (services, agricultural and industrial) from the application of quantile regression with fixed effects for panel data. Given the criticism regarding the distribution of resources, we also evaluate the different results within the regional context, i.e. the different impacts in the five geographical regions of Brazil (North, Northeast, Midwest, Southeast and South). We use the quantile regression model with fixed effects to panel database, since the variables used in the analysis provide strong inequality between municipalities. By observing the response of each quantile, not just from the average, as well as taking into account the control of fixed effects, the effects of Pronaf on GDP can be better captured. Although the program is national, the different results between regions suggest that (i) changes and improvements in Pronaf should be conducted properly to each region and (ii) it is clear the necessity to decentralize resources.