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SARS-CoV-2 virus emerged as a new threat to humans and spread around the world, leaving a large death toll. As of January 2023, Brazil is among the countries with the highest number of registered deaths. Nonpharmacological and pharmacological interventions have been heterogeneously implemented in the country, which, associated with large socioeconomic differences between the country regions, has led to distinct virus spread dynamics. Here, we investigate the spatiotemporal dispersion of SARS-CoV-2 lineages in the Pernambuco state (Northeast Brazil) throughout the distinct epidemiological scenarios that unfolded in the first 2 years of the pandemic. We generated a total of 1,389 new SARS-CoV-2 genomes from June 2020 to August 2021. This sampling captured the arrival, communitary transmission, and the circulation of the B1.1, B.1.1.28, and B.1.1.33 lineages; the emergence of the former variant of interest P.2; and the emergence and fast replacement of all previous variants by the more transmissible variant of concern P.1 (Gamma). Based on the incidence and lineage spread pattern, we observed an East-to-West to inner state pattern of transmission, which is in agreement with the transmission of more populous metropolitan areas to medium- and small-size country-side cities in the state. Such transmission patterns may be partially explained by the main routes of traffic across municipalities in the state. Our results highlight that the fine-grained intrastate analysis of lineages and incidence spread can provide actionable insights for planning future nonpharmacological intervention for air-borne transmissible human pathogens.IMPORTANCEDuring the COVID-19 pandemic, Brazil was one of the most affected countries, mainly due its continental-size, socioeconomic differences among regions, and heterogeneous implementation of intervention methods. In order to investigate SARS-CoV-2 dynamics in the state of Pernambuco, we conducted a spatiotemporal dispersion study, covering the period from June 2020 to August 2021, to comprehend the dynamics of viral transmission during the first 2 years of the pandemic. Throughout this study, we were able to track three significant epidemiological waves of transmission caused by B1.1, B.1.1.28, B.1.1.33, P.2, and P.1 lineages. These analyses provided valuable insights into the evolution of the epidemiological landscape, contributing to a deeper understanding of the dynamics of virus transmission during the early years of the pandemic in the state of Pernambuco., Competing Interests: The authors declare no conflict of interest.

The pandemic caused by Covid-19 is still present around the world. Despite advances in combating the disease, such as vaccine development, identifying infected individuals is still essential to optimize the control of human-to-human transmission of the virus. The main technique for detecting the virus is the RT-PCR method, which, despite its high relative cost, has a high accuracy in detecting the coronavirus. Given this, a method capable of performing the identification quickly, accurately, and inexpensively is necessary. Thus, this work aimed to analyze the feasibility of a new technique for identifying SARS-CoV-2 through the use of optical spectroscopy in the visible and near-infrared range (Vis-NIR) combined with machine learning algorithms. Spectral signals were obtained from nasopharyngeal swab samples previously analyzed using the RT-PCR method. The specimens were provided by the Molecular Diagnosis Laboratory of Covid-19 at Univasf. A total of 314 samples were analyzed, comprising 42 testing positive and 272 testing negative for Covid-19. Digital signal processing techniques, such as Savitzky-Golay filters and statistical methods were used to eliminate spurious elements from the original data and extract relevant features. Supervised machine learning algorithms such as SVM, Random Forest, and Naive Bayes classifiers were used to perform automatic sample identification. To evaluate the performance of the models, a 5-fold cross-validation technique was applied. With the proposed methodology, it was possible to achieve an accuracy of 75%, a sensitivity of 80%, and a specificity of 70%, in addition to an area under the ROC curve of 0.81, in the identification of nasopharyngeal swab samples from previously diagnosed individuals. From these results, it was possible to conclude that Vis-NIR spectroscopy is a promising, fast and relatively low cost technique to identify the SARS-CoV-2., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Introduction: COVID-19 is a major public health concern in this century. The causative agent SARS-CoV-2, is highly contagious and spreads continuously across territories. Spatial analysis is of enormous importance in the process of understanding the disease and its transmission mechanisms. We aimed to identify the risk areas for COVID-19 and analyze their association with social vulnerability in Maceió, Alagoas. The study was conducted in 2020. Methodology: This is an ecological study to evaluate the incidence, mortality and case fatality rate of COVID-19 and their relationship with 12 indicators of human development and social vulnerability. Multivariate and spatial statistics were applied. A 95% confidence interval and a 5% confidence level were considered. Results: The spatial scan statistic revealed the existence of six high-risk clusters for the incidence of COVID-19. The regression model showed that social indicators, such as literacy of people, residents of private households, households with more than four residents, and resident brown population, were associated with COVID-19 transmission in Maceió-AL. The disease affected localities whose populations are exposed to a context of intense socioeconomic vulnerability. Conclusions: Based on the results, it is necessary to adopt measures that take into account the social determinants of health in order to minimize the damage caused by the pandemic. [ABSTRACT FROM AUTHOR]

• The analyzes showed that the COVID-19 pandemic impacted Schistosomiasis Control Program actions in endemic municipalities of Alagoas state. • Our results showed a decrease in the worked population analyzed in the state program in 2020 and 2021. • There was a reduction in the number of Kato-Katz tests performed in 2020 and 2021. • We identified a reduction in the number of diagnoses of all parasitic diseases analyzed in 2020 and 2021 in Alagoas, except Taenia sp., which had a considerable increase in new cases diagnosed in 2021; • Clusters of municipalities formed with a percentage of negative change, comprising the central regions and northeast of Alagoas (the state's coastal area). Schistosomiasis remains a serious public health concern in Brazil and the Schistosomiasis Control Program (PCE) was elaborated to assist in the control of the disease. Nevertheless, the irruption of the COVID-19 pandemic may have impacted the program. Herein, we assessed the impact of the pandemic on PCE actions in an endemic area in the region with the highest positivity rate for schistosomiasis in Brazil. We conducted an ecological, population-based study using data from the PCE of the state of Alagoas, between 2015 and 2021, to calculate the percentage of change. The temporal trend analysis was performed using the segmented log-linear regression model. To evaluate the spatial distribution of the data, choropleth maps were made showing the values of the% of change. Moran maps was elaborated to indicate the critical areas. Our analysis showed a decrease in the population surveyed in 2020 (-41.00%) and 2021 (-18.42%). Likewise, there was a reduction in the number of Kato-Katz tests performed (2020 = -43.45%; and in 2021 = -19.63%) and, consequently, a drop in the rate of positive tests (-37.98% in 2020 and -26.14% in 2021). Importantly, treatment of positive cases was lower than 80% (77.44% in 2020 and 77.38% in 2021). Additionally, spatial clusters with negative percentage values of up to -100% of the PCE indicators were identified mostly in the municipalities of the coastal areas that are historically most affected by schistosomiasis. Taken together, our analyzes corroborate that PCE actions in endemic municipalities of Alagoas were impacted by the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]