An end-point multiplex RT-PCR for SARS-CoV-2, Influenza A and B detection, including simultaneous RNAse P amplification: a timely tool for more accessible differential diagnosis.

The multiplex molecular diagnostic assays described for severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2), influenza A (IAV) and B (IBV) viruses have been mainly based on real-time reaction, which limits their access to many laboratories or diagnostic institutions. To contribute to available strategies and expand access to differential diagnosis, we describe an end-point multiplex RT-PCR targeting SARS-CoV-2, IAV and IBV with simultaneous endogenous control amplification. Initially, we looked for well-established primers sets for SARS-CoV-2, IAV, IBV and RNAse P whose amplicons could be distinguished on agarose gel. The multiplex assay was then standardized by optimizing the reaction mix and cycle conditions. The limit of detection (LoD) was determined using titrated viruses (for SARS-CoV-2 and IAV) and by dilution from a pool of IBV-positive samples. The diagnostic performance of the multiplex was evaluated by testing samples with different RNAse P and viral loads, previously identified as positive or negative for the target viruses. The amplicons of IAV (146 bp), SARS-CoV-2 (113 bp), IBV (103 bp) and RNAse P (65 bp) were adequately distinguished in our multiplex. The LoD for SARS-CoV-2, IAV and IBV was 0.02 TCID50/ml, 0.07 TCID50/ml and 10-3 from a pool of positive samples, respectively. All samples positive for SARS-CoV-2 (n=70, Ct 17.2-36.9), IAV (n=53, Ct 14-34.9) and IBV (n=12, Ct 23.9-31.9) remained positive in our multiplex assay. RNAse P from negative samples (n=40, Ct 25.2-30.2) was also amplified in the multiplex. Overall, our assay is a timely and alternative tool for detecting SARS-CoV-2 and influenza viruses in laboratories with limited access to supplies/equipment.

Impact of COVID-19 on the epidemiology of respiratory viruses in southern Brazil / Impacto da COVID-19 na epidemiologia de vírus respiratórios no Rio Grande do Sul / Impacto epidemiológico de la COVID-19 sobre los virus respiratorios en sur de Brasil

Background and objectives: During the SARS-CoV-2 pandemic, reduction in detection of other Respiratory Viruses (RV) was observed. Epidemiological studies are needed to understand the impact of the pandemic on the circulation of RV. The aim of this study is to analyze the epidemiological profile of cases of severe acute respiratory infection (SARI) associated with the main RV in hospitalized patients from Rio Grande do Sul, Brazil (RS), between 2010 and 2019 (period A) and between 2020 and 2021 (period B). Methods: Data related to SARI cases in RS were retrieved from SIVEP-Gripe. Results: In period A there were more infections with Influenza, Parainfluenza, Adenovirus and Respiratory Syncytial Virus, while in period B most cases were of SARS-CoV-2 infection. The most affected age groups were individuals <5 years old (67.1%) in period A, and >60 years old (50%) in period B. The main symptoms were fever and cough in period A, and dyspnea and O2 saturation <95% in period B. The most reported comorbidities were lung diseases and chronic cardiovascular diseases in period A, and chronic cardiovascular diseases and diabetes mellitus in period B. Importantly, a higher fatality rate was observed in period B. Most cases occurred between May and July in period A, and in November and December 2021 in period B. Conclusion: This study reveals that the COVID-19 pandemic changed the epidemiological profile of SARI in RS, and most cases were in the elderly with chronic cardiovascular disease and diabetes mellitus.(AU)

Justificativa e Objetivos: Durante a pandemia de SARS-CoV-2 foi observada redução na detecção de outros vírus respiratórios (VR). Estudos epidemiológicos são importantes para uma melhor compreensão dos impactos da pandemia sobre a circulação de VR. O objetivo deste estudo foi analisar o perfil epidemiológico dos casos de síndrome respiratória aguda grave (SRAG) associados aos principais VR em pacientes internados no Rio Grande do Sul, Brasil (RS), entre 2010 e 2019 (período A) e entre 2020 e 2021 (período B). Métodos: Dados relacionados a casos de SRAG no RS foram obtidos do SIVEP-Gripe. Resultados: No período A houve mais infecções por Influenza, Parainfluenza, Adenovírus e Vírus Sincicial Respiratório, enquanto no período B a maioria foi por SARS-CoV-2. Os grupos etários mais afetados foram de indivíduos <5 anos de idade (67,1%) no período A, e >60 anos (50%) no período B. Os principais sintomas foram febre e tosse no período A, e dispneia e saturação de O2 <95% no período B. As principais comorbidades no período A foram pneumopatias e cardiopatias, enquanto no período B foram cardiopatias e diabetes mellitus. A mortalidade foi maior no período B. A maioria dos casos no período A foram entre maio e julho, e no período B entre novembro e dezembro de 2021. Conclusão: Este estudo revela que a pandemia de COVID-19 alterou o perfil epidemiológico de SRAG no RS, sendo a maioria dos casos em indivíduos idosos com doença cardiovascular e diabetes. (AU)

Justificación y Objetivos: Durante la pandemia por SARS-CoV-2 se observó reducción en la detección de otros virus respiratorios (VR). Los estudios epidemiológicos son importantes para comprender los impactos de la pandemia en la circulación de VR. Este estudio analizó variables epidemiológicas asociadas al Síndrome Respiratorio Agudo Grave (SRAG) en Rio Grande do Sul (RS), Brasil, antes de la aparición del SARS-CoV-2 (período A, 2010-2019) y durante la pandemia (período B, 2020-2021). Métodos: Los datos relacionados con los casos de SRAG en RS se obtuvieron de SIVEP-Gripe. Resultados: En el período A hubo más infecciones por Influenza, Parainfluenza, Adenovirus y Virus Respiratorio Sincitial, mientras que en el período B la mayoría de los casos fueron causados por SARS-CoV-2. Los grupos de edad más afectados fueron <5 años (67,1%) en el período A, y >60 años (50%) en el período B. Los principales síntomas fueron fiebre y tos en el período A, y disnea y saturación de O2 <95% en el período B. Las principales comorbilidades en el período A fueron enfermedades pulmonares y cardíacas, y en el período B fueron enfermedades cardíacas y diabetes mellitus. La mortalidad fue mayor en el período B. La mayoría de los casos en el período A fueron entre mayo y julio, y en el período B entre noviembre y diciembre. Conclusiones: Este estudio revela que la pandemia de COVID-19 cambió el perfil epidemiológico del SRAG en RS. La mayoría de los casos se dan en personas de edad avanzada con enfermedades cardiovasculares y diabetes. (AU)

Machine learning in predicting severe acute respiratory infection outbreaks.

Severe acute respiratory infection (SARI) outbreaks occur annually, with seasonal peaks varying among geographic regions. Case notification is important to prepare healthcare networks for patient attendance and hospitalization. Thus, health managers need adequate resource planning tools for SARI seasons. This study aims to predict SARI outbreaks based on models generated with machine learning using SARI hospitalization notification data. In this study, data from the reporting of SARI hospitalization cases in Brazil from 2013 to 2020 were used, excluding SARI cases caused by COVID-19. These data were prepared to feed a neural network configured to generate predictive models for time series. The neural network was implemented with a pipeline tool. Models were generated for the five Brazilian regions and validated for different years of SARI outbreaks. By using neural networks, it was possible to generate predictive models for SARI peaks, volume of cases per season, and for the beginning of the pre-epidemic period, with good weekly incidence correlation (R2 = 0.97; 95%CI: 0.95-0.98, for the 2019 season in the Southeastern Brazil). The predictive models achieved a good prediction of the volume of reported cases of SARI; accordingly, 9,936 cases were observed in 2019 in Southern Brazil, and the prediction made by the models showed a median of 9,405 (95%CI: 9,105-9,738). The identification of the period of occurrence of a SARI outbreak is possible using predictive models generated with neural networks and algorithms that employ time series.

Machine learning in predicting severe acute respiratory infection outbreaks / Aprendizado de máquina na previsão de surtos de síndrome respiratória aguda grave / Aprendizaje automático en la predicción de brotes de síndrome respiratorio agudo grave

Abstract: Severe acute respiratory infection (SARI) outbreaks occur annually, with seasonal peaks varying among geographic regions. Case notification is important to prepare healthcare networks for patient attendance and hospitalization. Thus, health managers need adequate resource planning tools for SARI seasons. This study aims to predict SARI outbreaks based on models generated with machine learning using SARI hospitalization notification data. In this study, data from the reporting of SARI hospitalization cases in Brazil from 2013 to 2020 were used, excluding SARI cases caused by COVID-19. These data were prepared to feed a neural network configured to generate predictive models for time series. The neural network was implemented with a pipeline tool. Models were generated for the five Brazilian regions and validated for different years of SARI outbreaks. By using neural networks, it was possible to generate predictive models for SARI peaks, volume of cases per season, and for the beginning of the pre-epidemic period, with good weekly incidence correlation (R2 = 0.97; 95%CI: 0.95-0.98, for the 2019 season in the Southeastern Brazil). The predictive models achieved a good prediction of the volume of reported cases of SARI; accordingly, 9,936 cases were observed in 2019 in Southern Brazil, and the prediction made by the models showed a median of 9,405 (95%CI: 9,105-9,738). The identification of the period of occurrence of a SARI outbreak is possible using predictive models generated with neural networks and algorithms that employ time series.

Resumo: Surtos de síndrome respiratória aguda grave (SRAG) ocorrem anualmente, com picos sazonais variando entre regiões geográficas. A notificação dos casos é importante para preparar as redes de atenção à saúde para o atendimento e internação dos pacientes. Portanto, os gestores de saúde precisam ter ferramentas adequadas de planejamento de recursos para as temporadas de SRAG. Este estudo tem como objetivo prever surtos de SRAG com base em modelos gerados com aprendizado de máquina usando dados de internação por SRAG. Foram incluídos dados sobre casos de hospitalização por SRAG no Brasil de 2013 a 2020, excluindo os casos causados pela COVID-19. Estes dados foram preparados para alimentar uma rede neural configurada para gerar modelos preditivos para séries temporais. A rede neural foi implementada com uma ferramenta de pipeline. Os modelos foram gerados para as cinco regiões brasileiras e validados para diferentes anos de surtos de SRAG. Com o uso de redes neurais, foi possível gerar modelos preditivos para picos de SRAG, volume de casos por temporada e para o início do período pré-epidêmico, com boa correlação de incidência semanal (R2 = 0,97; IC95%: 0,95-0,98, para a temporada de 2019 na Região Sudeste). Os modelos preditivos obtiveram uma boa previsão do volume de casos notificados de SRAG; dessa forma, foram observados 9.936 casos em 2019 na Região Sul, e a previsão feita pelos modelos mostrou uma mediana de 9.405 (IC95%: 9.105-9.738). A identificação do período de ocorrência de um surto de SRAG é possível por meio de modelos preditivos gerados com o uso de redes neurais e algoritmos que aplicam séries temporais.

Resumen: Brotes de síndrome respiratorio agudo grave (SRAG) ocurren todos los años, con picos estacionales que varían entre regiones geográficas. La notificación de los casos es importante para preparar las redes de atención a la salud para el cuidado y hospitalización de los pacientes. Por lo tanto, los gestores de salud deben tener herramientas adecuadas de planificación de recursos para las temporadas de SRAG. Este estudio tiene el objetivo de predecir brotes de SRAG con base en modelos generados con aprendizaje automático utilizando datos de hospitalización por SRAG. Se incluyeron datos sobre casos de hospitalización por SRAG en Brasil desde 2013 hasta 2020, salvo los casos causados por la COVID-19. Se prepararon estos datos para alimentar una red neural configurada para generar modelos predictivos para series temporales. Se implementó la red neural con una herramienta de canalización. Se generaron los modelos para las cinco regiones brasileñas y se validaron para diferentes años de brotes de SRAG. Con el uso de redes neurales, se pudo generar modelos predictivos para los picos de SRAG, el volumen de casos por temporada y para el inicio del periodo pre-epidémico, con una buena correlación de incidencia semanal (R2 = 0,97; IC95%: 0,95-0,98, para la temporada de 2019 en la Región Sudeste). Los modelos predictivos tuvieron una buena predicción del volumen de casos notificados de SRAG; así, se observaron 9.936 casos en 2019 en la Región Sur, y la predicción de los modelos mostró una mediana de 9.405 (IC95%: 9.105-9.738). La identificación del periodo de ocurrencia de un brote de SRAG es posible a través de modelos predictivos generados con el uso de redes neurales y algoritmos que aplican series temporales.

Clinical and sociodemographic aspects of cases of severe acute respiratory syndrome in southern Brazil / Aspectos clínicos e sociodemográficos dos casos de Síndrome Respiratória Aguda Grave no sul do Brasil / Aspectos clínicos y sociodemográficos de casos de Síndrome Respiratorio Agudo Severo en el sur de Brasil

Background and objectives: to compare the clinical and sociodemographic aspects of individuals with SARS reported in the countryside of Rio Grande do Sul in 2020 and 2021. Methods: a cross-sectional study, from March 2020 to October 2021. Clinical and sociodemographic variables of individuals with SARS symptoms were analyzed, compared through descriptive, univariate analyses, according to the year of reporting. Results: a total of 4,710 cases of SARS were reported; 53.4% were SARS related to COVID-19 in 2020 and 87.5% in 2021 (p<0.001). Comparing 2020 and 2021, the sociodemographic profile changed in terms of age group, skin color and education (p<0.001). Regarding clinical aspects, there was a reduction in prevalence of pre-existing health conditions, except obesity, changes in reported signs and symptoms and reduction in hospital and Intensive Care Unit admissions. Conclusion: the changes in the profile may reflect the effect of the different variants and the start of immunization for SARS-CoV-2.(AU)

Justificativa e objetivos: comparar, entre os anos de 2020 e 2021, os aspectos clínicos e sociodemográficos dos indivíduos com Síndrome Respiratória Aguda Grave (SRAG) notificados em uma região de saúde do interior do Rio Grande do Sul. Métodos: estudo transversal descritivo, realizado de março de 2020 a outubro de 2021. Foram analisadas variáveis clínicas e sociodemográficas de indivíduos com sintomas de SRAG, comparadas através de análises descritivas, univariadas, conforme o ano de notificação. Resultados: foram notificados 4.710 casos com SRAG; 53,4% foram SRAG relacionados à COVID-19 em 2020 e, 87,5%, em 2021 (p<0,001). Comparando os anos 2020 e 2021, o perfil sociodemográfico modificou quanto faixa etária, cor da pele e escolaridade (p<0,001). Quanto aos aspectos clínicos, houve redução da prevalência de condições de saúde preexistente, exceto obesidade, alterações nos sinais e sintomas relatados e diminuição de internações hospitalares e na Unidade de Terapia Intensiva. Conclusão: as mudanças no perfil podem refletir o efeito das diferentes variantes e o início da imunização para SARS-CoV-2.(AU)

Justificación y objetivos: comparar los aspectos clínicos y sociodemográficos de individuos con SARS notificados en el interior de Rio Grande do Sul en los años 2020 y 2021. Métodos: estudio descriptivo transversal, realizado de marzo de 2020 a octubre de 2021. Se analizaron variables clínicas y sociodemográficas de individuos con síntomas de SARS, comparadas mediante análisis descriptivos univariados, según el año de notificación. Resultados: se notificaron 4.710 casos de SARS; el 53,4% fueron SARS relacionados con COVID-19 en 2020 y el 87,5% en 2021 (p<0,001). Comparando los años 2020 y 2021, el perfil sociodemográfico cambió en cuanto a grupo de edad, color de piel y escolaridad (p<0,001). En cuanto a los aspectos clínicos, hubo reducción en la prevalencia de condiciones de salud preexistentes, excepto obesidad, cambios en los signos y síntomas reportados y reducción en los ingresos hospitalarios y en la Unidad de Cuidados Intensivos. Conclusión: los cambios en el perfil pueden reflejar el efecto de las diferentes variantes y el inicio de la inmunización para el SARS-CoV-2.(AU)

Chikungunya virus infection in the southernmost state of Brazil was characterised by self-limited transmission (2017-2019) and a larger 2021 outbreak.

BACKGROUND: Chikungunya is a mosquito-borne virus that has been causing large outbreaks in the Americas since 2014. In Brazil, Asian-Caribbean (AC) and East-Central-South-African (ECSA) genotypes have been detected and lead to large outbreaks in several Brazilian states. In Rio Grande do Sul (RS), the southernmost state of Brazil, the first cases were reported in 2016. OBJECTIVES AND METHODS: We employed genome sequencing and epidemiological investigation to characterise the Chikungunya fever (CHIKF) burden in RS between 2017-2021. FINDINGS: We detected an increasing CHIKF burden linked to travel associated introductions and communitary transmission of distinct lineages of the ECSA genotype during this period. MAIN CONCLUSIONS: Until 2020, CHIKV introductions were most travel associated and transmission was limited. Then, in 2021, the largest outbreak occurred in the state associated with the introduction of a new ECSA lineage. CHIKV outbreaks are likely to occur in the near future due to abundant competent vectors and a susceptible population, exposing more than 11 million inhabitants to an increasing infection risk.

Potential use of high-resolution melting analyses for SARS-CoV-2 genomic surveillance.

The pandemic caused by COVID-19 and the emergence of new variants of SARS-CoV-2 have generated clinical and epidemiological impacts on a global scale. The use of strategies for monitoring viral circulation and identifying mutations in genomic regions involved in host interaction are important measures to mitigate viral dissemination and reduce its likely complications on population health. In this context, the objective of this work was to explore the potential of high-resolution melting (HRM) analysis combined with one-step real-time reverse transcription PCR in a closed-tube system, as a fast and convenient method of screening for SARS-CoV-2 mutations with possible implications on host-pathogen interactions. The HRM analyses allowed the distinction of the Gamma, Zeta, Alpha, Delta, and Omicron variants against the predecessors (B.1.1.28, B.1.1.33) of occurrence in Brazil. It is concluded that the molecular tool standardized here has the potential to optimize the genomic surveillance of SARS-CoV-2, and could be adapted for genomic surveillance of other pathogens, due to its ability to detect, prior to sequencing, samples suggestive of new variants, selecting them more assertively and earlier for whole genome sequencing when compared to random screening.

Influenza A(H3N2) infection followed by separate COVID-19 infection

[ABSTRACT]. This study describes the case of a health professional infected first by influenza virus A(H3N2) and then by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 11 days later. Respiratory samples and clinical data were collected from the patient and from close contacts. RNA was extracted from samples and reverse transcription–quantitative polymerase chain reaction (RT-qPCR) was used to investigate the viruses. The patient presented with two different illness events: the first was characterized by fever, chest and body pain, prostration and tiredness, which ceased on the ninth day; RT-qPCR was positive only for influenza virus A(H3N2). Eleven days after onset of the first symptoms, the patient presented with sore throat, nasal con- gestion, coryza, nasal itching, sneezing and coughing, and a second RT-qPCR test was positive only for SARS-CoV-2; in the second event, symptoms lasted for 11 days. SARS-CoV-2 sequencing identified the Omi- cron BA.1 lineage. Of the patient’s contacts, one was coinfected with influenza A(H3N2) and SARS-CoV-2 lineage BA.1.15 and the other two were infected only with SARS-CoV-2, one also with Omicron BA.1.15 and the other with BA.1.1. Our findings reinforce the importance of testing for different viruses in cases of suspected respiratory viral infection during routine epidemiological surveillance because common clinical manifestations of COVID-19 mimic those of other viruses, such as influenza.

[RESUMEN]. Este estudio describe el caso de un profesional de la salud que contrajo la infección primero por el virus de la gripe A (H3N2) y a continuación por el coronavirus 2 del síndrome respiratorio agudo grave (SARS-CoV-2) 11 días después. Se recogieron muestras respiratorias y datos clínicos del paciente y sus contactos cercanos. Se extrajo ARN de muestras y se utilizó la reacción en cadena de la polimerasa cuantitativa con transcripción inversa (RT-qPCR, por su sigla en inglés) para investigar los virus. El paciente presentó dos procesos infecciosos distintos: el primero se caracterizó por fiebre, dolor corporal y torácico, postración y cansancio, que cesó en el noveno día. La prueba mediante RT-qPCR solo fue positiva en el virus de la gripe A (H3N2). Once días después del inicio de los primeros síntomas, el paciente manifestó dolor de garganta, congestión nasal, catarro, picazón nasal, estornudos y tos. Una segunda prueba mediante RT-qPCR solo fue positiva para el SARS-CoV-2 y durante este segundo proceso los síntomas duraron 11 días. La secuenciación del SARS-CoV-2 identificó el linaje ómicron BA.1. De los contactos del paciente, uno presentaba una coinfección por el virus de la gripe A (H3N2) y el linaje BA.1.15 del SARS-COV-2, y los otros dos presentaban infecciones únicamente por SARS-CoV-2, uno también del linaje ómicron BA.1.15 y el otro de BA.1.1. Estos hallazgos refuerzan la importancia de realizar pruebas para detectar diferentes virus en casos de sospecha de infección viral respiratoria durante la vigilancia epidemiológica de rutina porque las manifestaciones clínicas comunes de COVID-19 son similares a las de otros virus, como en el caso de la gripe.

[RESUMO]. Este estudo descreve o caso de uma profissional de saúde infectada primeiro pelo vírus influenza A (H3N2) e, 11 dias depois, pelo coronavírus da síndrome respiratória aguda grave 2 (SARS-CoV-2). Amostras respiratórias e dados clínicos foram coletados da paciente e de contatos próximos. RNA foi extraído das amostras, e o método de reação em cadeia da polimerase via transcriptase reversa quantitativa (RT-qPCR) foi utilizado para investigar os vírus. A paciente apresentou dois quadros clínicos distintos. O primeiro foi caracterizado por febre, dor no peito e no corpo, prostração e fadiga, que cessou no nono dia. A RT-qPCR foi positiva apenas para o vírus da influenza A (H3N2). Onze dias após o início dos primeiros sintomas, a paciente apresentou dor de garganta, congestão nasal, coriza, prurido nasal, espirros e tosse. Um segundo teste de RT-qPCR foi positivo apenas para SARS-CoV-2. No segundo evento, os sintomas duraram 11 dias. O sequenciamento do SARS-CoV-2 identificou a cepa Ômicron BA.1. Dentre os contatos da paciente, um teve coinfeção por influenza A (H3N2) e SARS-COV-2 (cepa BA.1.15), e os outros dois foram infectados apenas por SARS-CoV-2 (um também pela cepa Ômicron BA.1.15 e o outro pela BA.1.1). Nossos achados reforçam a importância de testes para a detecção de diferentes vírus em casos de suspeita de infecção viral respiratória durante a vigilância epidemiológica de rotina, visto que as manifestações clínicas comuns da COVID-19 imitam as de outros vírus, como o vírus influenza.

Genomic characterization and molecular evolution of SARS-CoV-2 in Rio Grande do Sul State, Brazil.

SARS-CoV-2 is the virus responsible for the COVID-19 and has afflicted the world since the end of 2019. Different lineages have been discovered and the Gamma lineage, which started the second wave of infections, was first described in Brazil, one of the most affected countries by pandemic. Therefore, this study analyzed SARS-CoV-2 sequenced genomes from Esteio city in Rio Grande do Sul, Southern Brazil. We also comparatively analyzed genomes of the two first years of the pandemic from Rio Grande do Sul state for understanding their genomic and evolutionary patterns. The phylogenomic analysis showed monophyletic groups for Alpha, Gamma, Delta and Omicron, as well as for other circulating lineages in the state. Molecular evolutionary analysis identified several sites under adaptive selection in membrane and nucleocapsid proteins which could be related to a prevalent stabilizing effect on membrane protein structure, as well as majoritarily destabilizing effects on C-terminal nucleocapsid domain.

Incipient Parallel Evolution of SARS-CoV-2 Deltacron Variant in South Brazil.

With the coexistence of multiple lineages and increased international travel, recombination and gene flow are likely to become increasingly important in the adaptive evolution of SARS-CoV-2. These processes could result in genetic introgression and the incipient parallel evolution of multiple recombinant lineages. However, identifying recombinant lineages is challenging, and the true extent of recombinant evolution in SARS-CoV-2 may be underestimated. This study describes the first SARS-CoV-2 Deltacron recombinant case identified in Brazil. We demonstrate that the recombination breakpoint is at the beginning of the Spike gene. The 5' genome portion (circa 22 kb) resembles the AY.101 (Delta), and the 3' genome portion (circa 8 kb nucleotides) is most similar to the BA.1.1 (Omicron). Furthermore, evolutionary genomic analyses indicate that the new strain emerged after a single recombination event between lineages of diverse geographical locations in December 2021 in South Brazil. This Deltacron, AYBA-RS, is one of the dozens of recombinants described in 2022. The submission of only four sequences in the GISAID database suggests that this lineage had a minor epidemiological impact. However, the recent emergence of this and other Deltacron recombinant lineages (XD, XF, and XS) suggests that gene flow and recombination may play an increasingly important role in the COVID-19 pandemic. We explain the evolutionary and population genetic theory that supports this assertion, concluding that this stresses the need for continued genomic surveillance. This monitoring is vital for countries where multiple variants are present, as well as for countries that receive significant inbound international travel.

SARS-CoV-2 laboratory surveillance during the first year of the COVID-19 pandemic in southern Brazil.

BACKGROUND: Brazil has one of the highest numbers of COVID-19 cases and deaths. Rio Grande do Sul (RS) in southern Brazil is one of the leading states in terms of case numbers. As part of the national public health network, the State Central Laboratory (LACEN-RS) changed its routine in 2020 to focus on the diagnosis of COVID-19. This study evaluated the laboratory surveillance of COVID-19 suspected cases analyzed at the LACEN-RS in 2020. METHODS: Viral detection was performed using RT-qPCR in samples from patients with respiratory infection who met the study criteria. Viral RNA was isolated using commercial manual kits or automated extractors, and SARS-CoV-2 RT-qPCR was performed using the Bio-Manguinhos/Rio de Janeiro, IBMP/Paraná, or Allplex 2019-nCoV assay. In total, 360 representative SARS-CoV-2 samples were sequenced using the Illumina platform. RESULTS: In total, 31,197 of 107,578 (positivity rate = 29%) tested positive for SARS-CoV-2. The number of RT-qPCR tests performed per month followed the COVID-19 epidemic curve observed for the state, with peaks in July-August and December. Females accounted for 63% of the samples, whereas the positivity rate was higher among males (33.1% males vs. 26.5% females). The positivity rate was higher in adults aged 50-79 years compared to the overall positivity rate. The majority of cases were observed in the capital, Porto Alegre, and the metropolitan region. Ten distinct lineages were identified, with B.1.1.28, B.1.1.33, and P.2 being the most frequent. CONCLUSIONS: Here, we describe laboratory surveillance of COVID-19 to identify priorities for epidemiological surveillance actions in RS.

SARS-CoV-2 laboratory surveillance during the first year of the COVID-19 pandemic in southern Brazil

ABSTRACT Background: Brazil has one of the highest numbers of COVID-19 cases and deaths. Rio Grande do Sul (RS) in southern Brazil is one of the leading states in terms of case numbers. As part of the national public health network, the State Central Laboratory (LACEN-RS) changed its routine in 2020 to focus on the diagnosis of COVID-19. This study evaluated the laboratory surveillance of COVID-19 suspected cases analyzed at the LACEN-RS in 2020. Methods: Viral detection was performed using RT-qPCR in samples from patients with respiratory infection who met the study criteria. Viral RNA was isolated using commercial manual kits or automated extractors, and SARS-CoV-2 RT-qPCR was performed using the Bio-Manguinhos/Rio de Janeiro, IBMP/Paraná, or Allplex 2019-nCoV assay. In total, 360 representative SARS-CoV-2 samples were sequenced using the Illumina platform. Results: In total, 31,197 of 107,578 (positivity rate = 29%) tested positive for SARS-CoV-2. The number of RT-qPCR tests performed per month followed the COVID-19 epidemic curve observed for the state, with peaks in July-August and December. Females accounted for 63% of the samples, whereas the positivity rate was higher among males (33.1% males vs. 26.5% females). The positivity rate was higher in adults aged 50-79 years compared to the overall positivity rate. The majority of cases were observed in the capital, Porto Alegre, and the metropolitan region. Ten distinct lineages were identified, with B.1.1.28, B.1.1.33, and P.2 being the most frequent. Conclusions: Here, we describe laboratory surveillance of COVID-19 to identify priorities for epidemiological surveillance actions in RS.

Multiple introductions and country-wide spread of DENV-2 genotype II (Cosmopolitan) in Brazil.

Dengue virus serotype 2, genotype Cosmopolitan (DENV-2-GII), is one of the most widespread DENV strains globally. In the USA, DENV-2 epidemics have been dominated by DENV-2 genotype Asian-American (DENV-2-GIII), and the first cases of DENV-2-GII were only described in 2019, in Peru, and in 2021 in Brazil. To gain new information about the circulation of DENV-2-GII in Brazil, we sequenced 237 DENV-2 confirmed cases sampled between March 2021 and March 2023 and revealed that DENV-2-GII is already present in all geographic regions of Brazil. The phylogeographic analysis inferred that DENV-2-GII was introduced at least four times in Brazil, between May 2020 and August 2022, generating multiple clades that spread throughout the country with different success. Despite multiple introductions of DENV-2-GII, analysis of the country-wide laboratory surveillance data showed that the Brazilian dengue epidemic in 2022 was dominated by DENV-1 in most states. We hypothesize that massive circulation of DENV-2-GIII in previous years in Brazil might have created a population immune barrier against symptomatic homotypic reinfections by DENV-2-GII, leading to sustained cryptic circulation in asymptomatic cases and localized outbreaks of this new genotype. In summary, our study stresses the importance of arboviral genomic surveillance to close monitoring and better understanding the potential impact of DENV-2-GII in the coming years.

Influenza A(H3N2) infection followed by separate COVID-19 infection / Infección por el virus de la gripe A (H3N2) seguida de infección separada por el virus causante de la COVID-19 / Infecção por influenza A (H3N2) seguida de infecção independente por COVID-19

ABSTRACT This study describes the case of a health professional infected first by influenza virus A(H3N2) and then by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 11 days later. Respiratory samples and clinical data were collected from the patient and from close contacts. RNA was extracted from samples and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to investigate the viruses. The patient presented with two different illness events: the first was characterized by fever, chest and body pain, prostration and tiredness, which ceased on the ninth day; RT-qPCR was positive only for influenza virus A(H3N2). Eleven days after onset of the first symptoms, the patient presented with sore throat, nasal congestion, coryza, nasal itching, sneezing and coughing, and a second RT-qPCR test was positive only for SARS-CoV-2; in the second event, symptoms lasted for 11 days. SARS-CoV-2 sequencing identified the Omicron BA.1 lineage. Of the patient's contacts, one was coinfected with influenza A(H3N2) and SARS-CoV-2 lineage BA.1.15 and the other two were infected only with SARS-CoV-2, one also with Omicron BA.1.15 and the other with BA.1.1. Our findings reinforce the importance of testing for different viruses in cases of suspected respiratory viral infection during routine epidemiological surveillance because common clinical manifestations of COVID-19 mimic those of other viruses, such as influenza.

RESUMEN Este estudio describe el caso de un profesional de la salud que contrajo la infección primero por el virus de la gripe A (H3N2) y a continuación por el coronavirus 2 del síndrome respiratorio agudo grave (SARS-CoV-2) 11 días después. Se recogieron muestras respiratorias y datos clínicos del paciente y sus contactos cercanos. Se extrajo ARN de muestras y se utilizó la reacción en cadena de la polimerasa cuantitativa con transcripción inversa (RT-qPCR, por su sigla en inglés) para investigar los virus. El paciente presentó dos procesos infecciosos distintos: el primero se caracterizó por fiebre, dolor corporal y torácico, postración y cansancio, que cesó en el noveno día. La prueba mediante RT-qPCR solo fue positiva en el virus de la gripe A (H3N2). Once días después del inicio de los primeros síntomas, el paciente manifestó dolor de garganta, congestión nasal, catarro, picazón nasal, estornudos y tos. Una segunda prueba mediante RT-qPCR solo fue positiva para el SARS-CoV-2 y durante este segundo proceso los síntomas duraron 11 días. La secuenciación del SARS-CoV-2 identificó el linaje ómicron BA.1. De los contactos del paciente, uno presentaba una coinfección por el virus de la gripe A (H3N2) y el linaje BA.1.15 del SARS-COV-2, y los otros dos presentaban infecciones únicamente por SARS-CoV-2, uno también del linaje ómicron BA.1.15 y el otro de BA.1.1. Estos hallazgos refuerzan la importancia de realizar pruebas para detectar diferentes virus en casos de sospecha de infección viral respiratoria durante la vigilancia epidemiológica de rutina porque las manifestaciones clínicas comunes de COVID-19 son similares a las de otros virus, como en el caso de la gripe.

RESUMO Este estudo descreve o caso de uma profissional de saúde infectada primeiro pelo vírus influenza A (H3N2) e, 11 dias depois, pelo coronavírus da síndrome respiratória aguda grave 2 (SARS-CoV-2). Amostras respiratórias e dados clínicos foram coletados da paciente e de contatos próximos. RNA foi extraído das amostras, e o método de reação em cadeia da polimerase via transcriptase reversa quantitativa (RT-qPCR) foi utilizado para investigar os vírus. A paciente apresentou dois quadros clínicos distintos. O primeiro foi caracterizado por febre, dor no peito e no corpo, prostração e fadiga, que cessou no nono dia. A RT-qPCR foi positiva apenas para o vírus da influenza A (H3N2). Onze dias após o início dos primeiros sintomas, a paciente apresentou dor de garganta, congestão nasal, coriza, prurido nasal, espirros e tosse. Um segundo teste de RT-qPCR foi positivo apenas para SARS-CoV-2. No segundo evento, os sintomas duraram 11 dias. O sequenciamento do SARS-CoV-2 identificou a cepa Ômicron BA.1. Dentre os contatos da paciente, um teve coinfeção por influenza A (H3N2) e SARS-COV-2 (cepa BA.1.15), e os outros dois foram infectados apenas por SARS-CoV-2 (um também pela cepa Ômicron BA.1.15 e o outro pela BA.1.1). Nossos achados reforçam a importância de testes para a detecção de diferentes vírus em casos de suspeita de infecção viral respiratória durante a vigilância epidemiológica de rotina, visto que as manifestações clínicas comuns da COVID-19 imitam as de outros vírus, como o vírus influenza.

Chikungunya virus infection in the southernmost state of Brazil was characterised by self-limited transmission (2017-2019) and a larger 2021 outbreak

BACKGROUND Chikungunya is a mosquito-borne virus that has been causing large outbreaks in the Americas since 2014. In Brazil, Asian-Caribbean (AC) and East-Central-South-African (ECSA) genotypes have been detected and lead to large outbreaks in several Brazilian states. In Rio Grande do Sul (RS), the southernmost state of Brazil, the first cases were reported in 2016. OBJECTIVES AND METHODS We employed genome sequencing and epidemiological investigation to characterise the Chikungunya fever (CHIKF) burden in RS between 2017-2021. FINDINGS We detected an increasing CHIKF burden linked to travel associated introductions and communitary transmission of distinct lineages of the ECSA genotype during this period. MAIN CONCLUSIONS Until 2020, CHIKV introductions were most travel associated and transmission was limited. Then, in 2021, the largest outbreak occurred in the state associated with the introduction of a new ECSA lineage. CHIKV outbreaks are likely to occur in the near future due to abundant competent vectors and a susceptible population, exposing more than 11 million inhabitants to an increasing infection risk.

Low prevalence of influenza A strains with resistance markers in Brazil during 2017-2019 seasons.

The influenza A virus (IAV) is of a major public health concern as it causes annual epidemics and has the potential to cause pandemics. At present, the neuraminidase inhibitors (NAIs) are the most widely used anti-influenza drugs, but, more recently, the drug baloxavir marboxil (BXM), a polymerase inhibitor, has also been licensed in some countries. Mutations in the viral genes that encode the antiviral targets can lead to treatment resistance. Worldwide, a low prevalence of antiviral resistant strains has been reported. Despite that, this situation can change rapidly, and resistant strain surveillance is a priority. Thus, the aim of this was to evaluate Brazilian IAVs antiviral resistance from 2017 to 2019 through the identification of viral mutations associated with reduced inhibition of the drugs and by testing the susceptibility of IAV isolates to oseltamivir (OST), the most widely used NAI drug in the country. Initially, we analyzed 282 influenza A(H1N1)pdm09 and 455 A(H3N2) genetic sequences available on GISAID. The amino acid substitution (AAS) NA:S247N was detected in one A(H1N1)pdm09 strain. We also identified NA:I222V (n = 6) and NA:N329K (n = 1) in A(H3N2) strains. In addition, we performed a molecular screening for NA:H275Y in 437 A(H1N1)pdm09 samples, by pyrosequencing, which revealed a single virus harboring this mutation. Furthermore, the determination of OST IC50 values for 222 A(H1N1)pdm09 and 83 A(H3N2) isolates revealed that all isolates presented a normal susceptibility profile to the drug. Interestingly, we detected one A(H3N2) virus presenting with PA:E119D AAS. Moreover, the majority of the IAV sequences had the M2:S31N adamantanes resistant marker. In conclusion, we show a low prevalence of Brazilian IAV strains with NAI resistance markers, in accordance with what is reported worldwide, indicating that NAIs still remain an option for the treatment of influenza infections in Brazil. However, surveillance of influenza resistance should be strengthened in the country for improving the representativeness of investigated viruses and the robustness of the analysis.

Molecular characterization of a new SARS-CoV-2 recombinant cluster XAG identified in Brazil.

Recombination events have been described in the Coronaviridae family. Since the beginning of the SARS-CoV-2 pandemic, a variable degree of selection pressure has acted upon the virus, generating new strains with increased fitness in terms of viral transmission and antibody scape. Most of the SC2 variants of concern (VOC) detected so far carry a combination of key amino acid changes and indels. Recombination may also reshuffle existing genetic profiles of distinct strains, potentially giving origin to recombinant strains with altered phenotypes. However, co-infection and recombination events are challenging to detect and require in-depth curation of assembled genomes and sequencing reds. Here, we present the molecular characterization of a new SARS-CoV-2 recombinant between BA.1.1 and BA.2.23 Omicron lineages identified in Brazil. We characterized four mutations that had not been previously described in any of the recombinants already identified worldwide and described the likely breaking points. Moreover, through phylogenetic analysis, we showed that the newly named XAG lineage groups in a highly supported monophyletic clade confirmed its common evolutionary history from parental Omicron lineages and other recombinants already described. These observations were only possible thanks to the joint effort of bioinformatics tools auxiliary in genomic surveillance and the manual curation of experienced personnel, demonstrating the importance of genetic, and bioinformatic knowledge in genomics.

Possible Occupational Infection of Healthcare Workers with Monkeypox Virus, Brazil.

We evaluated epidemiologic and molecular characteristics of monkeypox virus (MPXV) infections sampled from 2 healthcare nurses. Five days after collecting samples from an infected patient, the nurses showed typical MPXV manifestations; quantitative PCR and whole-genome sequencing confirmed MPXV infection, most likely transmitted through contact with fomites.

Unusual SARS-CoV-2 intrahost diversity reveals lineage superinfection.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has infected almost 200 million people worldwide by July 2021 and the pandemic has been characterized by infection waves of viral lineages showing distinct fitness profiles. The simultaneous infection of a single individual by two distinct SARS-CoV-2 lineages may impact COVID-19 disease progression and provides a window of opportunity for viral recombination and the emergence of new lineages with differential phenotype. Several hundred SARS-CoV-2 lineages are currently well phylogenetically defined, but two main factors have precluded major coinfection/codetection and recombination analysis thus far: (i) the low diversity of SARS-CoV-2 lineages during the first year of the pandemic, which limited the identification of lineage defining mutations necessary to distinguish coinfecting/recombining viral lineages; and the (ii) limited availability of raw sequencing data where abundance and distribution of intrasample/intrahost variability can be accessed. Here, we assembled a large sequencing dataset from Brazilian samples covering a period of 18 May 2020 to 30 April 2021 and probed it for unexpected patterns of high intrasample/intrahost variability. This approach enabled us to detect nine cases of SARS-CoV-2 coinfection with well characterized lineage-defining mutations, representing 0.61 % of all samples investigated. In addition, we matched these SARS-CoV-2 coinfections with spatio-temporal epidemiological data confirming its plausibility with the cocirculating lineages at the timeframe investigated. Our data suggests that coinfection with distinct SARS-CoV-2 lineages is a rare phenomenon, although it is certainly a lower bound estimate considering the difficulty to detect coinfections with very similar SARS-CoV-2 lineages and the low number of samples sequenced from the total number of infections.

SARS-CoV-2 introduction and lineage dynamics across three epidemic peaks in Southern Brazil: massive spread of P.1.

Genomic surveillance of SARS-CoV-2 is paramount for understanding viral dynamics, contributing to disease control. This study analyzed SARS-CoV-2 genomic diversity in Rio Grande do Sul (RS), Brazil, including the first reported case in each Regional Health Coordination and cases from three epidemic peaks. Ninety SARS-CoV-2 genomes from RS were sequenced and analyzed through comparison with SARS-CoV-2 datasets available in GISAID for phylogenetic inference and mutation analysis. Among the first reported cases, we found the following lineages: B.1 (33.3%), B.1.1.28 (26.7%), B.1.1 (13.3%), B.1.1.33 (10.0%), and A (6.7%), evidencing SARS-CoV-2 introduction by both international origin and community-driven transmission. We found predominance of B.1.1.33 (50.0%) and B.1.1.28 (35.0%) during the first epidemic peak (July-August 2020), emergence of P.2 (55.6%) in the second peak (November-December 2020), and massive spread of P.1 and related sequences (78.4%), such as P.1-like-II, P.1.1 and P.1.2 in the third peak (February-April, 2021). Eighteen novel mutation combinations were found among P.1 genomes, and 22 different spike mutations and/or deletions among P.1 and related sequences. This study shows the dispersion of SARS-CoV-2 lineages in Southern Brazil and describes SARS-CoV-2 diversity during three epidemic peaks, highlighting the spread of P.1 and the high genetic diversity of currently circulating lineages. Genomic monitoring of SARS-CoV-2 is essential to guide health authorities' decisions to control COVID-19 in Brazil.