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.

The health burden of natural and technological disasters in Brazil from 2013 to 2021.

Disasters deeply impact the health of the affected population and the economy of a country. The health burden of disasters in Brazil is underestimated and more studies are needed to underpin policies and actions for disaster risk reduction. This study analyzes and describes disasters that occurred in Brazil from 2013 to 2021. The Integrated Disaster Information System (S2iD) was accessed to obtain demographic data, disaster data according to Brazilian Classification and Codification of Disasters (COBRADE), and health outcome data (number of dead, injured, sick, unsheltered, displaced, and missing individuals and other outcomes). Database preparation and analysis were performed in Tableau. In total, 98.62% (50,481) of the disasters registered in Brazil from 2013 to 2021 are natural, with a significant increase in 2020 and 2021 due to the COVID-19 pandemic, a biological disaster. This disaster group also caused the highest number of deaths (321,111), as well as injured (208,720) and sick (7,041,099) people. By analyzing data for each geographic region, we observed differences regarding disasters frequency and their health outcomes. In Brazil, climatological disasters are the most frequent (23,452 events) and occur mainly in the Northeast region. Geological disasters have the highest lethality, which are more common in the Southeast; however, the most common disasters in the South and Southeast are those of the meteorological and hydrological groups. Therefore, since the greatest health outcomes are associated with disasters predicted in time and space, public policies for the prevention and management of disasters can reduce the impacts of these events.

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.

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.

The health burden of natural and technological disasters in Brazil from 2013 to 2021 / A carga de saúde dos desastres naturais e tecnológicos no Brasil de 2013 a 2021 / La carga sanitaria de los desastres naturales y tecnológicos en Brasil de 2013 a 2021

Disasters deeply impact the health of the affected population and the economy of a country. The health burden of disasters in Brazil is underestimated and more studies are needed to underpin policies and actions for disaster risk reduction. This study analyzes and describes disasters that occurred in Brazil from 2013 to 2021. The Integrated Disaster Information System (S2iD) was accessed to obtain demographic data, disaster data according to Brazilian Classification and Codification of Disasters (COBRADE), and health outcome data (number of dead, injured, sick, unsheltered, displaced, and missing individuals and other outcomes). Database preparation and analysis were performed in Tableau. In total, 98.62% (50,481) of the disasters registered in Brazil from 2013 to 2021 are natural, with a significant increase in 2020 and 2021 due to the COVID-19 pandemic, a biological disaster. This disaster group also caused the highest number of deaths (321,111), as well as injured (208,720) and sick (7,041,099) people. By analyzing data for each geographic region, we observed differences regarding disasters frequency and their health outcomes. In Brazil, climatological disasters are the most frequent (23,452 events) and occur mainly in the Northeast region. Geological disasters have the highest lethality, which are more common in the Southeast; however, the most common disasters in the South and Southeast are those of the meteorological and hydrological groups. Therefore, since the greatest health outcomes are associated with disasters predicted in time and space, public policies for the prevention and management of disasters can reduce the impacts of these events.

Desastres afetam profundamente a saúde da população afetada e a economia de um país. A carga de saúde dos desastres no Brasil é subestimada e mais estudos são necessários para fundamentar políticas e ações para a redução do risco de desastres. Este estudo analisa e descreve desastres ocorridos no Brasil entre 2013 e 2021. O Sistema Integrado de Informações sobre Desastres (S2iD) foi acessado para obtenção de dados demográficos, dados de desastres, de acordo com a Classificação e Codificação Brasileira de Desastres (COBRADE), e dados de resultados de saúde (mortos, feridos, doentes, desabrigados, deslocados, desaparecidos e outros afetados). A preparação e a análise do banco de dados foram realizadas no Tableau. O estudo mostra que 98,62% (50.481) dos desastres registrados no Brasil entre 2013 e 2021 foram naturais, com um aumento significativo em 2020 e 2021 por causa da pandemia de COVID-19, que é um desastre biológico. Este grupo de desastres também causou o maior número de mortes (321.111), bem como de feridos (208.720) e doentes (7.041.099). Ao analisar os dados para cada região geográfica, observaram-se diferenças em relação à frequência e aos resultados de saúde dos desastres. Por exemplo, enquanto os desastres climatológicos são os mais frequentes no país (23.452 eventos) e ocorrem principalmente na Região Nordeste, a maior letalidade é observada para desastres geológicos, que são mais comuns no Sudeste. No Sul e Sudeste, os desastres mais comuns são meteorológicos e hidrológicos. Este estudo mostra que os maiores resultados de saúde estão associados a desastres previstos no tempo e no espaço e, portanto, os impactos podem ser reduzidos com políticas públicas de prevenção e gestão de desastres.

Los desastres afectan profundamente la salud de la población y la economía de un país. La carga sanitaria de los desastres en Brasil está subestimada, y se necesitan más estudios para elaborar políticas y acciones para reducir el riesgo de desastres. Este estudio analiza y describe los desastres ocurridos en Brasil entre 2013 y 2021. Del Sistema Integrado de Información de Desastres (S2iD) se recogió datos demográficos, datos de desastres, según la Clasificación y Codificación Brasileña de Desastres (COBRADE), y datos de resultados de salud (muertos, heridos, enfermos, personas sin hogar, desplazados, desaparecidos y otros afectados). La preparación y análisis de los datos se realizó en Tableau. El estudio muestra que ocurrieron el 98,62% (50.481) de los desastres registrados en Brasil entre 2013 y 2021 fueron naturales, con un aumento significativo en 2020 y 2021 a causa de la pandemia del COVID-19, considerada un desastre biológico. Este grupo de desastre también causó el mayor número de muertos (321.111), así como el mayor número de heridos (208.720) y enfermos (7.041.099). Al analizar los datos de cada región del país, se constataron diferencias en cuanto a la frecuencia y los resultados en salud de los desastres. Mientras los desastres climatológicos son los más frecuentes en el país (23.452 eventos) y ocurren principalmente en la región Nordeste, los desastres geológicos frecuentes en el Sudeste son los más letales. En el Sur y Sudeste del país, los desastres más comunes son los meteorológicos e hidrológicos. Este estudio muestra que los mayores resultados en salud se asocian con los desastres previstos en tiempo y espacio, y que los impactos pueden reducirse con las políticas públicas de prevención y gestión de desastres.

The health burden of natural and technological disasters in Brazil from 2013 to 2021 / A carga de saúde dos desastres naturais e tecnológicos no Brasil de 2013 a 2021 / La carga sanitaria de los desastres naturales y tecnológicos en Brasil de 2013 a 2021

Disasters deeply impact the health of the affected population and the economy of a country. The health burden of disasters in Brazil is underestimated and more studies are needed to underpin policies and actions for disaster risk reduction. This study analyzes and describes disasters that occurred in Brazil from 2013 to 2021. The Integrated Disaster Information System (S2iD) was accessed to obtain demographic data, disaster data according to Brazilian Classification and Codification of Disasters (COBRADE), and health outcome data (number of dead, injured, sick, unsheltered, displaced, and missing individuals and other outcomes). Database preparation and analysis were performed in Tableau. In total, 98.62% (50,481) of the disasters registered in Brazil from 2013 to 2021 are natural, with a significant increase in 2020 and 2021 due to the COVID-19 pandemic, a biological disaster. This disaster group also caused the highest number of deaths (321,111), as well as injured (208,720) and sick (7,041,099) people. By analyzing data for each geographic region, we observed differences regarding disasters frequency and their health outcomes. In Brazil, climatological disasters are the most frequent (23,452 events) and occur mainly in the Northeast region. Geological disasters have the highest lethality, which are more common in the Southeast; however, the most common disasters in the South and Southeast are those of the meteorological and hydrological groups. Therefore, since the greatest health outcomes are associated with disasters predicted in time and space, public policies for the prevention and management of disasters can reduce the impacts of these events.

Desastres afetam profundamente a saúde da população afetada e a economia de um país. A carga de saúde dos desastres no Brasil é subestimada e mais estudos são necessários para fundamentar políticas e ações para a redução do risco de desastres. Este estudo analisa e descreve desastres ocorridos no Brasil entre 2013 e 2021. O Sistema Integrado de Informações sobre Desastres (S2iD) foi acessado para obtenção de dados demográficos, dados de desastres, de acordo com a Classificação e Codificação Brasileira de Desastres (COBRADE), e dados de resultados de saúde (mortos, feridos, doentes, desabrigados, deslocados, desaparecidos e outros afetados). A preparação e a análise do banco de dados foram realizadas no Tableau. O estudo mostra que 98,62% (50.481) dos desastres registrados no Brasil entre 2013 e 2021 foram naturais, com um aumento significativo em 2020 e 2021 por causa da pandemia de COVID-19, que é um desastre biológico. Este grupo de desastres também causou o maior número de mortes (321.111), bem como de feridos (208.720) e doentes (7.041.099). Ao analisar os dados para cada região geográfica, observaram-se diferenças em relação à frequência e aos resultados de saúde dos desastres. Por exemplo, enquanto os desastres climatológicos são os mais frequentes no país (23.452 eventos) e ocorrem principalmente na Região Nordeste, a maior letalidade é observada para desastres geológicos, que são mais comuns no Sudeste. No Sul e Sudeste, os desastres mais comuns são meteorológicos e hidrológicos. Este estudo mostra que os maiores resultados de saúde estão associados a desastres previstos no tempo e no espaço e, portanto, os impactos podem ser reduzidos com políticas públicas de prevenção e gestão de desastres.

Los desastres afectan profundamente la salud de la población y la economía de un país. La carga sanitaria de los desastres en Brasil está subestimada, y se necesitan más estudios para elaborar políticas y acciones para reducir el riesgo de desastres. Este estudio analiza y describe los desastres ocurridos en Brasil entre 2013 y 2021. Del Sistema Integrado de Información de Desastres (S2iD) se recogió datos demográficos, datos de desastres, según la Clasificación y Codificación Brasileña de Desastres (COBRADE), y datos de resultados de salud (muertos, heridos, enfermos, personas sin hogar, desplazados, desaparecidos y otros afectados). La preparación y análisis de los datos se realizó en Tableau. El estudio muestra que ocurrieron el 98,62% (50.481) de los desastres registrados en Brasil entre 2013 y 2021 fueron naturales, con un aumento significativo en 2020 y 2021 a causa de la pandemia del COVID-19, considerada un desastre biológico. Este grupo de desastre también causó el mayor número de muertos (321.111), así como el mayor número de heridos (208.720) y enfermos (7.041.099). Al analizar los datos de cada región del país, se constataron diferencias en cuanto a la frecuencia y los resultados en salud de los desastres. Mientras los desastres climatológicos son los más frecuentes en el país (23.452 eventos) y ocurren principalmente en la región Nordeste, los desastres geológicos frecuentes en el Sudeste son los más letales. En el Sur y Sudeste del país, los desastres más comunes son los meteorológicos e hidrológicos. Este estudio muestra que los mayores resultados en salud se asocian con los desastres previstos en tiempo y espacio, y que los impactos pueden reducirse con las políticas públicas de prevención y gestión de desastres.

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.

Severe acute respiratory infection surveillance in Brazil: the role of public, private and philanthropic healthcare units.

Epidemiological surveillance and notification of respiratory infections are important for management and control of epidemics and pandemics. Fact-based decisions, like social distancing policies and preparation of hospital beds, are taken based on several factors, including case numbers; hence, health authorities need quick access to reliable and well-analysed data. We aimed to analyse the role of the Brazilian public health system in the notification and hospitalization of patients with severe acute respiratory infection (SARI). Data of SARI cases in Brazil (2013-20) were obtained from SIVEP-Gripe platform, and legal status of each healthcare unit (HCU) responsible for case notification and hospitalization was obtained from the National Registry of Health Facilities (CNES) database. HCUs that are part of the hospital network were classified as 'Public Administration', 'Business Entities', 'Philanthropic Entities' or 'Individuals'. SARI notification data from Brazilian macro-regions (North, Northeast, Midwest, Southeast and South) were analysed and compared between administrative spheres. This study reveals that hospitalizations due to SARI increased significantly in Brazil during the coronavirus disease 2019 (COVID-19) pandemic, especially in HCUs of Public Administration. In the Southeast and South, where incidence of SARI is high, philanthropic HCUs also contribute to hospitalization of SARI cases and attend up to 7.4% of the cases notified by the Public Administration. The number of cases is usually lower in other regions, but in 2020 the Northeast showed more hospitalizations than the South. In the South, SARI season occurs later; however, in 2020, an early peak was observed because of COVID-19. Notably, the contribution of each administrative sphere that manages hospital networks in Brazil in the control and management of SARI varies between regions. Our approach will allow managers to assess the use of public resources, given that there are different profiles of healthcare in each region of Brazil and that the public health system has a major role in notifying and attending SARI cases.

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.

Gene expression evaluation of antioxidant enzymes in patients with hepatocellular carcinoma: RT-qPCR and bioinformatic analyses.

Any condition leading to chronic liver disease is a potential oncogenic agent for hepatocellular carcinoma (HCC). Alterations in the expression of antioxidant enzymes could alter the redox balance. Our aim was to evaluate the expression of the genes GPX1, GPX4, SEP15, SELENOP, SOD1, SOD2, GSR, CAT, and NFE2L2 in patients with HCC. Differential gene expression analysis was performed using RNA-Seq data from the TCGA and GTEx databases, and RT-qPCR data from HCC patient samples. Bioinformatic analysis revealed significant differential expression in most genes. GPX4 expression was significantly increased (p=0.02), while SOD2 expression was significantly decreased (p=0.04) in experimental data. In TCGA samples, alpha-fetoprotein levels (mg/dL) were negatively correlated with the expression of SEP15 (p<0.001), SELENOP (p<0.001), SOD1 (p<0.001), SOD2 (p<0.001), CAT (p<0.001), and NFE2L2 (p=0.004). Alpha-fetoprotein levels were positively correlated with the expression of GPX4 (p=0.02) and SELENOP (p=0.01) in the experimental data. Low expression of GPX1 (p=0.006), GPX4 (p=0.01), SELENOP (p=0.006), SOD1 (p=0.007), CAT (p<0.001), and NFE2L2 (p<0.001), and higher levels of GSR, were associated with low overall survival at 12 months. These results suggest a significant role for these antioxidant enzymes in HCC pathogenesis and severity.

Control and prevention of infectious diseases from a One Health perspective.

The ongoing COVID-19 pandemic has caught the attention of the global community and rekindled the debate about our ability to prevent and manage outbreaks, epidemics, and pandemics. Many alternatives are suggested to address these urgent issues. Some of them are quite interesting, but with little practical application in the short or medium term. To realistically control infectious diseases, human, animal, and environmental factors need to be considered together, based on the One Health perspective. In this article, we highlight the most effective initiatives for the control and prevention of infectious diseases: vaccination; environmental sanitation; vector control; social programs that encourage a reduction in the population growth; control of urbanization; safe sex stimulation; testing; treatment of sexually and vertically transmitted infections; promotion of personal hygiene practices; food safety and proper nutrition; reduction of the human contact with wildlife and livestock; reduction of social inequalities; infectious disease surveillance; and biodiversity preservation. Subsequently, this article highlights the impacts of human genetics on susceptibility to infections and disease progression, using the SARS-CoV-2 infection as a study model. Finally, actions focused on mitigation of outbreaks and epidemics and the importance of conservation of ecosystems and translational ecology as public health strategies are also discussed.

Epidemiology of human adenovirus associated with respiratory infection in southern Brazil.

Human adenoviruses (HAdVs) are associated with respiratory infection in the human population worldwide, but HAdV is underreported and less studied than other respiratory viruses. We investigated HAdV in patients with respiratory infection in Rio Grande do Sul (RS), Brazil, between 2004 and 2018. The frequency and seasonality of HAdV, clinical symptoms and underlying diseases were analysed. Respiratory samples from outpatients with acute respiratory illness (ARI) who attended sentinel units and from inpatients with severe acute respiratory infection (SARI) were collected for HAdV detection by immunofluorescence assay; demographic and clinical data were analysed. In total, 43,514 cases of respiratory infection were analysed, of which 8,901 were ARI (20.5%), and 34,613 (79.5%) were SARI. Respiratory viruses were detected in 35.8% of the cases. The frequency of HAdV in relation to respiratory viruses was 2.8%. HAdV circulated year-round, with higher frequency during winter and early spring; increases in the average monthly temperature were associated with decreases in HAdV infections (p = 0.013). Most hospitalized patients with HAdV were male (p = 0.003). HAdV infection showed association with age (p < 0.001), and children between 1 and 5 years old accounted for 30.8% of the outpatients, whereas among cases of SARI, 88.2% were paediatric patients. Among inpatients with HAdV, 3% died, and of these, the majority had at least one underlying condition, such as cardiopathy and immunosuppression. HAdV infection of the respiratory tract causes morbidity and mortality, and individuals with heart diseases and the immunocompromised are at higher risk of fatality.

More than just a common cold: endemic coronaviruses OC43, HKU1, NL63, and 229E associated with severe acute respiratory infection and fatality cases among healthy adults

Respiratory viral infection can cause severe disease and hospitalization, especially among children, the elderly, and patients with comorbidities. In Brazil, the official surveillance system of severe acute respiratory infection (SARI) investigates influenza A (IAV) and B (IBV) viruses, respiratory syncytial virus (RSV), adenovirus (HAdV), and parainfluenza viruses (hPIV 1­3). In Rio Grande do Sul (RS), Brazil, many fatalities associated with SARI between 2013 and 2017 occurred among patients without underlying diseases and for whom the causative agent had not been identified using official protocols. This cross­sectional study analyzed the presence of coronaviruses (HCoV), bocavirus (HBoV), metapneumovirus (hMPV), and rhinovirus in patients who died of SARI despite not having comorbidities, and that were negative for IAV, IBV, RSV, HAdV, and hPIV. Nasopharyngeal aspirates/swabs from patients were used for nucleic acid extraction. The presence of HCoVs OC43, HKU1, NL63, and 229E; HBoV; hMPV; and rhinovirus was assessed by quantitative reverse transcription­polymerase chain reaction. Clinical data were also analyzed. Between 2013 and 2017, 16 225 cases of SARI were reported in RS; 9.8% of the patients died; 20% of all fatal cases were patients without comorbidities and for whom no pathogen was detected using standard protocols. Analysis of 271 of these cases identified HCoV in nine cases; HBoV, hMPV, and rhinovirus were detected in 3, 3, and 10 cases, respectively. Of note, patients infected with HCoV were adults. Results reinforce the importance of including coronaviruses in diagnostic panels used by official surveillance systems because besides their pandemic potential, endemic HCoVs are associated to severe disease in healthy adults.

A 12-year study of fungal infections in Rio Grande do Sul, Southern Brazil / Infecciones fúngicas en Rio Grande do Sul, Brasil: estudio de 12 años

Background: The number of fungal infections has increased in recent years in Rio Grande do Sul (RS), Brazil. Epidemiological studies are important for proper control of infections. Aims: To evaluate the etiology of fungal infections in patients in RS, from 2003 to 2015. Methods: This is a retrospective and longitudinal study carried out at Mycology Department of Central Laboratory of RS; 13,707 samples were evaluated. The variables sex, age, site of infection, and etiologic agent were analyzed. Susceptibility of Candida to fluconazole was tested in isolates from samples collected in 2015 from 51 outpatients. Results: Of the 13,707 samples, 840 cases (6.12%) of fungal infections were found and included in the analyses; female gender accounted for the 55.9% of the cases. The main fungus was Candida albicans (450 cases, 53.38%; p < 0.001). Onychomycosis was the most frequent infection in superficial mycoses. Systemic mycoses accounted for 54.05% of the cases, from which 68.8% occurred in males, mainly HIV-positive (33.11%), and the main etiologic agent in these cases was Cryptococcus neoformans (73.13%). Among 51 samples tested for susceptibility to fluconazole, 78.43% of Candida isolates were susceptible; 5.88% were susceptible in a dose-dependent manner, and 15.69% were resistant. Conclusions: C. albicans is a common cause of fungal infections in RS, accounting for half of the cases; resistance to antifungals was found in non-hospitalized patients. In addition, women seem to be more susceptible to fungal infections than men, however men show more systemic mycoses than women. The nails are the most common site of infection

Antecedentes: El número de casos de infecciones fúngicas ha aumentado en los últimos años en Rio Grande do Sul (RS), Brasil. Los estudios epidemiológicos son importantes para el control de estas infecciones. Objetivos: Evaluar la etiología de las infecciones fúngicas en pacientes de RS desde 2003 hasta 2015. Métodos: Este es un estudio retrospectivo y longitudinal realizado en el Departamento de Micología del Laboratorio Central de RS; se evaluaron 13.707 casos de infecciones. Se analizaron las variables sexo, edad, lugar de infección y agente etiológico. La sensibilidad de Candida al fluconazol se analizó en 51 aislamientos de muestras recogidas en el año 2015. Resultados: De las 13.707 muestras, 840 casos (6,12%) de infecciones fúngicas se incluyeron en el análisis; el 55,9% correspondieron a mujeres. El hongo predominante fue Candida albicans (450 casos, 53,38%; p < 0,001). La onicomicosis fue la infección más frecuente de las micosis superficiales. Las micosis sistémicas representaron el 54,05% de los casos; de estos, el 68,8% tuvieron lugar en hombres, principalmente VIH-positivos (33,11%), y el principal agente etiológico en estos casos fue Cryptococcus neoformans (73,13%). Entre las 51 muestras analizadas para determinar la sensibilidad al fluconazol, el 78,43% de los aislamientos de Candida fueron sensibles; el 5,88% fueron sensibles de forma dosis-dependiente y el 15,69% fueron resistentes. Conclusiones: C. albicans es una causa común de infecciones fúngicas en RS, pues representa la mitad de los casos; su resistencia a los antifúngicos se encontró entre pacientes ambulatorios. Además, parece que las mujeres son más susceptibles a las infecciones fúngicas que los hombres, mientras que los hombres presentan más micosis sistémicas que las mujeres; las uñas son el lugar más frecuente de infección

A 12-year study of fungal infections in Rio Grande do Sul, Southern Brazil.

BACKGROUND: The number of fungal infections has increased in recent years in Rio Grande do Sul (RS), Brazil. Epidemiological studies are important for proper control of infections. AIMS: To evaluate the etiology of fungal infections in patients in RS, from 2003 to 2015. METHODS: This is a retrospective and longitudinal study carried out at Mycology Department of Central Laboratory of RS; 13,707 samples were evaluated. The variables sex, age, site of infection, and etiologic agent were analyzed. Susceptibility of Candida to fluconazole was tested in isolates from samples collected in 2015 from 51 outpatients. RESULTS: Of the 13,707 samples, 840 cases (6.12%) of fungal infections were found and included in the analyses; female gender accounted for the 55.9% of the cases. The main fungus was Candida albicans (450 cases, 53.38%; p<0.001). Onychomycosis was the most frequent infection in superficial mycoses. Systemic mycoses accounted for 54.05% of the cases, from which 68.8% occurred in males, mainly HIV-positive (33.11%), and the main etiologic agent in these cases was Cryptococcus neoformans (73.13%). Among 51 samples tested for susceptibility to fluconazole, 78.43% of Candida isolates were susceptible; 5.88% were susceptible in a dose-dependent manner, and 15.69% were resistant. CONCLUSIONS: C. albicans is a common cause of fungal infections in RS, accounting for half of the cases; resistance to antifungals was found in non-hospitalized patients. In addition, women seem to be more susceptible to fungal infections than men, however men show more systemic mycoses than women. The nails are the most common site of infection.

A 28-year study of human parainfluenza in Rio Grande do Sul, Southern Brazil.

PROBLEM: Human parainfluenza virus (hPIV) is an important pathogen in respiratory infections, however the health burden of hPIV is underestimated. This study describes the infections by hPIV1-3 in Rio Grande do Sul, Brazil, from 1990 to 2017, providing data of the frequency and seasonality of cases and associated clinical symptoms. METHOD OF STUDY: Nasopharyngeal samples of patients with respiratory infection were collected, clinical data were analyzed, and immunofluorescence was used to detect hPIV. RESULTS: Respiratory viruses were detected in 33.63% of respiratory infections. In a total of 11 606 cases of viral respiratory infection, 781 were positive for hPIV; hPIV prevalence ranged from 2.14% to 27% of viral respiratory infections. hPIV1 circulates mainly during fall; hPIV3 circulation, in turn, starts in fall and peaks during spring; and cases of hPIV2 are reported along the year, with peaks in fall and early spring. The most affected age group was children, with hPIV prevalence of 74.23% in patients for less than 1 year. A higher proportion of girls were infected than boys, however, no difference by sex was observed considering all age groups. The most frequent type was hPIV3, especially in hospitalized patients. Both hPIV1 and 3 were associated with dyspnea, while hPIV2 caused mild symptoms mainly in nonhospitalized patients. Nineteen fatalities occurred, 89.5% of them associated with risk factors (prematurity; chronic diseases; age, <1 or >60 years). CONCLUSION: hPIV causes a high number of respiratory infections, leading to hospitalization especially in children; epidemiological and surveillance studies are important for the control and management of respiratory infections.

A 12-year study of fungal infections in Rio Grande do Sul, southern Brazil

Background: The number of fungal infections has increased in recent years in Rio Grande do Sul (RS), Brazil. Epidemiological studies are important for proper control of infections. Aims: To evaluate the etiology of fungal infections in patients in RS, from 2003 to 2015. Methods: This is a retrospective and longitudinal study carried out at Mycology Department of Central Laboratory of RS; 13,707 samples were evaluated. The variables sex, age, site of infection, and etiologic agent were analyzed. Susceptibility of Candida to fluconazole was tested in samples collected in 2015from 51 outpatients. Results: Of the 13,707 samples, 840 cases (6.12%) of fungal infections were found and included in the analyses; female gender accounted for the 55.9% of the cases. The main fungus was Candida albicans (450 cases, 53.38%; p < 0.001). Onychomycosis was the most frequent infection in superficial mycoses. Systemic mycoses accounted for 54.05% of the cases, from which 68.8% occurred in males, mainly HIVpositive (33.11%), and the main etiologic agent in these cases was Cryptococcus neoformans (73.13%). Among 51 samples tested for susceptibility to fluconazole, 78.43% of Candida isolates were susceptible; 5.88% were susceptible in a dose-dependent manner, and 15.69% were resistant. Conclusions: C. albicans is a common cause of fungal infections in RS, accounting for half of the cases;resistance to antifungals was found in non-hospitalized patients. In addition, women seem to be moresusceptible to fungal infections than men, however men show more systemic mycoses than women. Thenails are the most common site of infection. (AU)

Comparison of the nasopharynx microbiome between influenza and non­influenza cases of severe acute respiratory infections: a pilot study

Aims: Influenza A virus (IAV) can cause severe acute respiratory infection (SARI), and disease outcome may be associated with changes in the microbiome of the nasopharynx. This is a pilot study to characterize the microbiome of the nasopharynx in patients hospitalized with SARI, infected and not infected by IAV. Methods and Results: Using target sequencing of the 16S rRNA gene, we assessed the bacterial community of nasopharyngeal aspirate samples and compared the microbiome of patients infected with IAV with the microbiome of patients who were negative for IAV. We observed differences in the relative abundance of Proteobacteria and Firmicutes between SARI patients, with Streptococcus being enriched and Pseudomonas underrepresented in IAV patients compared with patients who were not infected with IAV. Conclusion: Pseudomonas taxon seems to be in high frequency on the nasopharynx of SARI patients with non­IAV infection and might present a negative association with Streptococcus taxon. Microbial profile appears to be different between SARI patients infected or not infected with IAV.