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The outbreak of COVID-19 has led to there being a worldwide socio-economic crisis, with major impacts on developing countries. Understanding the dynamics of the disease and its driving factors, on a small spatial scale, might support strategies to control infections. This paper explores the impact of the COVID-19 on neighborhoods of Recife, Brazil, for which we examine a set of drivers that combines socio-economic factors and the presence of non-stop services. A three-stage methodology was conducted by conducting a statistical and spatial analysis, including clusters and regression models. COVID-19 data were investigated concerning ten dates between April and July 2020. Hotspots of the most affected regions and their determinant effects were highlighted. We have identified that clusters of confirmed cases were carried from a well-developed neighborhood to socially deprived areas, along with the emergence of hotspots of the case-fatality rate. The influence of age-groups, income, level of education, and the access to essential services on the spread of COVID-19 was also verified. The recognition of variables that influence the spatial spread of the disease becomes vital for pinpointing the most vulnerable areas. Consequently, specific prevention actions can be developed for these places, especially in heterogeneous cities. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is one of the worst public health crises in Brazil and the world that has ever been faced. One of the main challenges that the healthcare systems have when decision-making is that the protocols tested in other epidemics do not guarantee success in controlling the spread of COVID-19, given its complexity. In this context, an effective response to guide the competent authorities in adopting public policies to fight COVID-19 depends on thoughtful analysis and effective data visualization, ideally based on different data sources. In this paper, we discuss and provide tools that can be helpful using data analytics to respond to the COVID-19 outbreak in Recife, Brazil. We use exploratory data analysis and inferential study to determine the trend changes in COVID-19 cases and their effective or instantaneous reproduction numbers. According to the data obtained of confirmed COVID-19 cases disaggregated at a regional level in this zone, we note a heterogeneous spread in most megaregions in Recife, Brazil. When incorporating quarantines decreed, effectiveness is detected in the regions. Our results indicate that the measures have effectively curbed the spread of the disease in Recife, Brazil. However, other factors can cause the effective reproduction number to not be within the expected ranges, which must be further studied. [ABSTRACT FROM AUTHOR]

Purpose: The recent increase in the number of infections and mortality rates in many regions has emphasized the cyclical nature of this pandemic, with new variants emerging constantly. Understanding what has been done by efficient administrations to contain the outbreak is essential while new immunization developments for the new variants are not available. Design/methodology/approach: This work adapts the traditional Banker, Charnes and Cooper (BCC) Variable Returns to Scale model for including panel data on the Brazilian Federal Government spending over the first pandemic months in Pernambuco to identify efficient municipalities and conduct a benchmark on the best practices, reactions and implications that can serve as a guide for the post-Covid recurrence era. Findings: The results provide an interesting panorama of municipal response to the pandemic and some quantitative and qualitative prospects on potentials for improvements from the perspective of efficient and inefficient cities. Only one administration (São Bento do Una) was identified as efficient for the entire period. The authors' benchmark and discussion are focused on this municipality. Originality/value: The authors believe this work has two innovative components. The first is a robust and systematic methodology integrating the advances in testing convexity and returns to scale in the construction of a production frontier based on panel data. The second is a discussion on what drives efficiency (benchmarking of best practices) in addition to how to quantitatively attain such efficiency prospects. To the best of the authors' knowledge, both methodological and empirical implications are original to the present manuscript. [ABSTRACT FROM AUTHOR]

Introduction: Abortion attitudes are influenced by people's socioeconomic and demographic circumstances and can be volatile during times of crisis. Brazil is an interesting case for examining abortion attitudes because of its strict abortion policies, changing religious landscape, high income inequality, and extreme uncertainty generated by the back-to-back Zika and COVID-19 crises. This study seeks to assess Brazilian women's attitudes toward abortion and whether religion and income explain these attitudes in the context of novel infectious disease epidemics. Methods: We used data from a population-based sample of 3996 women ages 18–34 in Pernambuco, Brazil, collected during the onset of the COVID-19 pandemic (May–September 2020). We conducted paired t-tests and multivariate-adjusted logistic regression models with adjusted Odds Ratios (aORs) and 95% CIs to assess differences in support for abortion in the case of fetal congenital Zika syndrome (CZS), maternal Zika infection during pregnancy, and maternal COVID-19 infection during pregnancy. Results: Significantly more women support the right to abortion in the case of fetal CZS (50%) than in the case of maternal Zika infection (40%) and maternal COVID-19 infection (31%). Support for abortion varies by income and religion. Controlling for other demographic characteristics, high-income women have higher odds of supporting abortion in the case of fetal CZS (aOR = 1.92; 95% CI: 1.25–2.94) and maternal Zika infection (aOR = 2.07; 95% CI: 1.33–3.21) than low-income women. Evangelical women have lower odds of supporting abortion in the case of maternal Zika infection (aOR = 0.65; 95% CI: 0.45–0.93) and marginally lower odds of supporting the right to abortion in the case of maternal COVID-19 infection (aOR = 0.69; 95% CI: 0.47–1.00) than women of other religious affiliations. Conclusions and Policy Implications: With increasingly conservative religious groups gaining size in Brazil, we expect to see increasing abortion restrictions. However, this research finds that a sizable portion of women across all incomes and religious affiliations support abortion, particularly in the case of fetal anomalies associated with Zika. [ABSTRACT FROM AUTHOR]

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Summary: Although SARS‐CoV‐2 surface contamination has been investigated in health care settings, little is known about the SARS‐CoV‐2 surface contamination in public urban areas, particularly in tropical countries. Here, we investigated the presence of SARS‐CoV‐2 on high‐touch surfaces in a large city in Brazil, one of the most affected countries by the COVID‐19 pandemic in the world. A total of 400 surface samples were collected in February 2021 in the City of Recife, Northeastern Brazil. A total of 97 samples (24.2%) tested positive for SARS‐CoV‐2 by RT‐qPCR using the CDC‐USA protocol. All the collection sites, except one (18/19, 94.7%) had at least one environmental surface sample contaminated. SARS‐CoV‐2 positivity was higher in public transport terminals (47/84, 55.9%), followed by health care units (26/84, 30.9%), beach areas (4/21, 19.0%), public parks (14/105, 13.3%), supply centre (2/21, 9.5%), and public markets (4/85, 4.7%). Toilets, ATMs, handrails, playgrounds and outdoor gyms were identified as fomites with the highest rates of SARS‐CoV‐2 detection. Taken together, our data provide a real‐world picture of SARS‐CoV‐2 dispersion in highly populated tropical areas and identify critical control points that need to be targeted to break SARS‐CoV‐2 transmission chains. [ABSTRACT FROM AUTHOR]