[Spatial-temporal diffusion of yellow fever in a state in Southeast Brazil in 2017]. / Difusão espaço-temporal da febre amarela silvestre em um estado do Sudeste do Brasil, 2017.

The objective was to analyze the diffusion of cases of yellow fever in time and space in the epidemic of 2017 in the state of Espírito Santo, Brazil. An ecological observational study was performed with spatial analysis of yellow fever cases. Georeferencing of information and spatial analysis used the digital grid for the state of Espírito Santo, divided into 78 municipalities (counties), using the Arcgis software, 10.3. Geostatistical analysis was performed using the ordinary kriging function. The study found an incidence of 4.85/100,000 inhabitants of sylvatic yellow fever in Espírito Santo in 2017, with 29.74% case-fatality. Sylvatic yellow fever cases were distributed across 34 of the state's 78 municipalities, representing 43% of its territory. The temporal distribution of reported yellow fever cases in the current study occurred from the 1st to the 19th Epidemiological Weeks (EW). The geostatistical spatial analysis via ordinary kriging demonstrated spatial diffusion by yellow fever contagion among the municipalities in the state of Espírito Santo, with spatial continuity. The disease emerged in the state in the EW 1 through municipalities bordering on the state of Minas Gerais. Geoprocessing showed that yellow fever reached the state of Espírito Santo through the municipalities bordering on the state of Minas Gerais, moving eastward in the state and reaching the Atlantic coastline. There was a higher concentration of cases and persistence in the state's Central and Metropolitan regions, which have areas of Atlantic Forest, showing a pattern of diffusion continuity by contagion.

O objetivo foi analisar a difusão dos casos de febre amarela no tempo e no espaço, na epidemia de 2017, no Estado do Espírito Santo, Brasil. Estudo observacional ecológico, com análise espacial da difusão dos casos de febre amarela. Para o georreferenciamento das informações e a análise espacial, utilizou-se a malha digital do Estado do Espírito Santo, dividida em 78 municípios, por meio do software ArcGIS 10.3. Realizou-se uma análise de geoestatística utilizando a função krigagem ordinária. Nosso estudo mostrou uma incidência de 4,85/100 mil habitantes de febre amarela silvestre no Espírito Santo, no período de 2017, perfazendo uma letalidade de 29,74%. Os casos de febre amarela silvestre estão distribuídos em 34 municípios dos 78 que compõem o estado, representando 43% do território. A distribuição temporal dos casos de febre amarela registrados no presente estudo encontrava-se entre a 1ª e a 19ª Semana Epidemiológica (SE). Por meio da análise espacial de geoestatística por krigagem ordinária, foi possível demonstrar a difusão espacial por contágio da doença amarílica entre os municípios no Estado do Espírito Santo, com uma continuidade espacial. A doença surgiu no estado na SE 1 pelos municípios que realizam divisa com o Estado de Minas Gerais. O geoprocessamento demonstrou que a doença amarílica chegou ao Espírito Santo pelos municípios vizinhos ao Estado de Minas Gerais, seguindo em direção leste do estado, atingindo o litoral. Apresentou uma maior concentração de casos e tempo de permanência nas regiões Central e Metropolitana, que possuem áreas de Mata Atlântica, mostrando um padrão de continuidade da difusão por contágio.

El objetivo fue analizar la difusión de los casos de fiebre amarilla en el tiempo y espacio, en la epidemia de 2017 en el estado de Espírito Santo, Brasil. Estudio observacional ecológico, con análisis espacial de la difusión de los casos de fiebre amarilla. Para la georreferencia de la información y análisis espacial se utilizó la red digital del estado de Espírito Santo, dividida en 78 municipios, a través del software Arcgis 10.3. Se realizó un análisis de geoestadístico, utilizando la función krigagem ordinaria. Nuestro estudio mostró una incidencia de 4,85/100 mil habitantes de fiebre amarilla silvestre en Espírito Santo durante el período de 2017, ocasionando una letalidad de 29,74%. Los casos de fiebre amarilla silvestre están distribuidos en 34 municipios, de los 78 en los que se compone el estado, representando un 43% del territorio. La distribución temporal de los casos de febre amarela registrados en el presente estudio se encontraba entre la 1ª y la 19ª Semana Epidemiológica (SE). A través del análisis espacial de geoestadística por krigagem ordinaria fue posible demostrar la difusión espacial por contagio de la enfermedad amarílica entre los municipios en el estado de Espírito Santo, con una continuidad espacial. La enfermedad surgió en el estado en la SE 1, a través de los municipios que tienen frontera con el estado de Minas Gerais. El geoprocesamiento demostró que la enfermedad amarílica llegó al estado de Espírito Santo a través de los municipios vecinos al estado de Minas Gerais, siguiendo en dirección al este del estado, alcanzando el litoral. Presentó una mayor concentración de casos y tiempo de permanencia en las regiones Central y Metropolitana, que poseen areas de mata atlántica, presentando un patrón de continuidad de la difusión por contagio.

The use of health geography modeling to understand early dispersion of COVID-19 in São Paulo, Brazil.

Public health policies to contain the spread of COVID-19 rely mainly on non-pharmacological measures. Those measures, especially social distancing, are a challenge for developing countries, such as Brazil. In São Paulo, the most populous state in Brazil (45 million inhabitants), most COVID-19 cases up to April 18th were reported in the Capital and metropolitan area. However, the inner municipalities, where 20 million people live, are also at risk. As governmental authorities discuss the loosening of measures for restricting population mobility, it is urgent to analyze the routes of dispersion of COVID-19 in São Paulo territory. We hypothesize that urban hierarchy is the main responsible for the disease spreading, and we identify the hotspots and the main routes of virus movement from the metropolis to the inner state. In this ecological study, we use geographic models of population mobility to check for patterns for the spread of SARS-CoV-2 infection. We identify two patterns based on surveillance data: one by contiguous diffusion from the capital metropolitan area, and the other hierarchical with long-distance spread through major highways that connects São Paulo city with cities of regional relevance. This knowledge can provide real-time responses to support public health strategies, optimizing the use of resources in order to minimize disease impact on population and economy.

Difusão espaço-temporal da febre amarela silvestre em um estado do Sudeste do Brasil, 2017 / Spatial-temporal diffusion of yellow fever in a state in Southeast Brazil in 2017 / Difusión espacio-temporal de la fiebre amarilla en un estado de la Región Sudeste de Brasil, 2017

O objetivo foi analisar a difusão dos casos de febre amarela no tempo e no espaço, na epidemia de 2017, no Estado do Espírito Santo, Brasil. Estudo observacional ecológico, com análise espacial da difusão dos casos de febre amarela. Para o georreferenciamento das informações e a análise espacial, utilizou-se a malha digital do Estado do Espírito Santo, dividida em 78 municípios, por meio do software ArcGIS 10.3. Realizou-se uma análise de geoestatística utilizando a função krigagem ordinária. Nosso estudo mostrou uma incidência de 4,85/100 mil habitantes de febre amarela silvestre no Espírito Santo, no período de 2017, perfazendo uma letalidade de 29,74%. Os casos de febre amarela silvestre estão distribuídos em 34 municípios dos 78 que compõem o estado, representando 43% do território. A distribuição temporal dos casos de febre amarela registrados no presente estudo encontrava-se entre a 1ª e a 19ª Semana Epidemiológica (SE). Por meio da análise espacial de geoestatística por krigagem ordinária, foi possível demonstrar a difusão espacial por contágio da doença amarílica entre os municípios no Estado do Espírito Santo, com uma continuidade espacial. A doença surgiu no estado na SE 1 pelos municípios que realizam divisa com o Estado de Minas Gerais. O geoprocessamento demonstrou que a doença amarílica chegou ao Espírito Santo pelos municípios vizinhos ao Estado de Minas Gerais, seguindo em direção leste do estado, atingindo o litoral. Apresentou uma maior concentração de casos e tempo de permanência nas regiões Central e Metropolitana, que possuem áreas de Mata Atlântica, mostrando um padrão de continuidade da difusão por contágio.

The objective was to analyze the diffusion of cases of yellow fever in time and space in the epidemic of 2017 in the state of Espírito Santo, Brazil. An ecological observational study was performed with spatial analysis of yellow fever cases. Georeferencing of information and spatial analysis used the digital grid for the state of Espírito Santo, divided into 78 municipalities (counties), using the Arcgis software, 10.3. Geostatistical analysis was performed using the ordinary kriging function. The study found an incidence of 4.85/100,000 inhabitants of sylvatic yellow fever in Espírito Santo in 2017, with 29.74% case-fatality. Sylvatic yellow fever cases were distributed across 34 of the state's 78 municipalities, representing 43% of its territory. The temporal distribution of reported yellow fever cases in the current study occurred from the 1st to the 19th Epidemiological Weeks (EW). The geostatistical spatial analysis via ordinary kriging demonstrated spatial diffusion by yellow fever contagion among the municipalities in the state of Espírito Santo, with spatial continuity. The disease emerged in the state in the EW 1 through municipalities bordering on the state of Minas Gerais. Geoprocessing showed that yellow fever reached the state of Espírito Santo through the municipalities bordering on the state of Minas Gerais, moving eastward in the state and reaching the Atlantic coastline. There was a higher concentration of cases and persistence in the state's Central and Metropolitan regions, which have areas of Atlantic Forest, showing a pattern of diffusion continuity by contagion.

El objetivo fue analizar la difusión de los casos de fiebre amarilla en el tiempo y espacio, en la epidemia de 2017 en el estado de Espírito Santo, Brasil. Estudio observacional ecológico, con análisis espacial de la difusión de los casos de fiebre amarilla. Para la georreferencia de la información y análisis espacial se utilizó la red digital del estado de Espírito Santo, dividida en 78 municipios, a través del software Arcgis 10.3. Se realizó un análisis de geoestadístico, utilizando la función krigagem ordinaria. Nuestro estudio mostró una incidencia de 4,85/100 mil habitantes de fiebre amarilla silvestre en Espírito Santo durante el período de 2017, ocasionando una letalidad de 29,74%. Los casos de fiebre amarilla silvestre están distribuidos en 34 municipios, de los 78 en los que se compone el estado, representando un 43% del territorio. La distribución temporal de los casos de febre amarela registrados en el presente estudio se encontraba entre la 1ª y la 19ª Semana Epidemiológica (SE). A través del análisis espacial de geoestadística por krigagem ordinaria fue posible demostrar la difusión espacial por contagio de la enfermedad amarílica entre los municipios en el estado de Espírito Santo, con una continuidad espacial. La enfermedad surgió en el estado en la SE 1, a través de los municipios que tienen frontera con el estado de Minas Gerais. El geoprocesamiento demostró que la enfermedad amarílica llegó al estado de Espírito Santo a través de los municipios vecinos al estado de Minas Gerais, siguiendo en dirección al este del estado, alcanzando el litoral. Presentó una mayor concentración de casos y tiempo de permanencia en las regiones Central y Metropolitana, que poseen areas de mata atlántica, presentando un patrón de continuidad de la difusión por contagio.

Two hundred days of COVID-19 in São Paulo State, Brazil.

Two hundred days after the first confirmed case of COVID-19 in Brazil, the epidemic has rapidly spread in metropolitan areas and advanced throughout the countryside. We followed the temporal epidemic pattern at São Paulo State, the most populous of the country, the first to have a confirmed case of COVID-19, and the one with the most significant number of cases until now. We analysed the number of new cases per day in each regional health department and calculated the effective reproduction number (Rt) over time. Social distance measures, along with improvement in testing and isolating positive cases, general population mask-wearing and standard health security protocols for essential and non-essential activities, were adopted and impacted on slowing down epidemic velocity but were insufficient to stop transmission.

Is it time to talk about the end of social distancing? A joinpoint analysis of COVID-19 time series in Brazilian capitals.

INTRODUCTION: Monitoring coronavirus disease (COVID-19)-related infections and deaths in Brazil is controversial, with increasing pressure to ease social distance measures. However, no evidence of a sustained, widespread fall in cases exists. METHODS: We used segmented (joinpoint) regression analysis to describe the behavior of COVID-19 infections in Brazilian capital cities. RESULTS: All capitals showed an exponential or a near-exponential increase in cases through May. A decline in reported cases was subsequently noted in 20 cities but was only significant for 8 (29.6%) and was followed in two by a renewed increase. CONCLUSIONS: Caution is warranted when considering the relaxation of restrictions.

Increasing molecular diagnostic capacity and COVID-19 incidence in Brazil.

Different countries have adopted strategies for the early detection of SARS-CoV-2 since the declaration of community transmission by the World Health Organization (WHO) and timely diagnosis has been considered one of the major obstacles for surveillance and healthcare. Here, we report the increase of the number of laboratories to COVID-19 diagnosis in Brazil. Our results demonstrate an increase and decentralisation of certified laboratories, which does not match the much higher increase in the number of COVID-19 cases. Also, it becomes clear that laboratories are irregularly distributed over the country, with a concentration in the most developed state, São Paulo.

Completeness of yellow fever notification forms in the state of Espírito Santo, Brazil, 2017. / Completude das fichas de notificação de febre amarela no estado do Espírito Santo, 2017.

Objective to describe the completeness of data on yellow fever notification forms in the municipalities of the state of Espírito Santo, Brazil, in 2017. Methods this is a descriptive ecological study with data from the Notifiable Health Conditions Information System (SINAN); form completeness was categorized as poor (<70.0%), regular (70-89.9%) or excellent (≥90.0%); thematic maps were prepared. Results 53.1% of the municipalities had poor or regular classification for many notification form variables, especially case Final Classification (57.1%), Confirmation/Dismissal Criterion (63.2%) and Closure Date (26.5%), which are required fields. Conclusion completeness was poor or regular for several variables, pointing to the need for a systematic assessment of information on yellow fever held on SINAN.

Is it time to talk about the end of social distancing? A joinpoint analysis of COVID-19 time series in Brazilian capitals

Abstract INTRODUCTION: Monitoring coronavirus disease (COVID-19)-related infections and deaths in Brazil is controversial, with increasing pressure to ease social distance measures. However, no evidence of a sustained, widespread fall in cases exists. METHODS We used segmented (joinpoint) regression analysis to describe the behavior of COVID-19 infections in Brazilian capital cities. RESULTS All capitals showed an exponential or a near-exponential increase in cases through May. A decline in reported cases was subsequently noted in 20 cities but was only significant for 8 (29.6%) and was followed in two by a renewed increase. CONCLUSIONS Caution is warranted when considering the relaxation of restrictions.

Completude das fichas de notificação de febre amarela no estado do Espírito Santo, 2017 / Completitud de las fichas de notificación de fiebre amarilla en el estado de Espírito Santo, Brasil, 2017 / Completeness of yellow fever notification forms in the state of Espírito Santo, Brazil, 2017

Objetivo: descrever a completude de dados das fichas de notificação de febre amarela nos municípios do estado do Espírito Santo, Brasil, em 2017. Métodos: trata-se de um estudo ecológico descritivo, com dados do Sistema de Informação de Agravos de Notificação (Sinan); a completude no preenchimento da ficha foi classificada como ruim (<70,0%), regular (70-89,9%) ou ótima (≥90,0%); foram elaborados mapas temáticos. Resultados: 53,1% dos municípios enquadraram-se na classificação ruim ou regular, para muitas variáveis da ficha de notificação dos casos de febre amarela, especialmente Classificação Final (57,1%), Critério de Confirmação/Descarte (63,2%) e Data do Encerramento (26,5%), campos de preenchimento obrigatório. Conclusão: a completude no preenchimento foi ruim ou regular para diversas variáveis, apontando a necessidade de uma avaliação sistemática das informações sobre febre amarela no Sinan.

Objetivo: describir la completitud de los datos en los formularios de notificación de fiebre amarilla en los municipios del Estado de Espírito Santo, Brasil, en 2017. Métodos: este es un estudio ecológico descriptivo con datos del Sistema de Información de Agravamientos de Notificación (Sinan); las proporciones de la completitud se clasificaron como pobres (<70,0%), regulares (70-89,9%) o excelentes (≥90,0%); se prepararon mapas temáticos. Resultados: 53,1% de los municipios tenía una clasificación pobre o regular para muchas variables en el formulario de notificación, como la Clasificación final de casos (57,1%), Criterios de confirmación/Descarte (63,2%) y la Fecha de cierre (26,5%), considerados campos obligatorios. Conclusión: la finalización fue pobre o regular para diversas variables, lo que indica la necesidad de una evaluación sistemática de la información sobre la fiebre amarilla en Sinan.

Objective: to describe the completeness of data on yellow fever notification forms in the municipalities of the state of Espírito Santo, Brazil, in 2017. Methods: this is a descriptive ecological study with data from the Notifiable Health Conditions Information System (SINAN); form completeness was categorized as poor (<70.0%), regular (70-89.9%) or excellent (≥90.0%); thematic maps were prepared. Results: 53.1% of the municipalities had poor or regular classification for many notification form variables, especially case Final Classification (57.1%), Confirmation/Dismissal Criterion (63.2%) and Closure Date (26.5%), which are required fields. Conclusion: completeness was poor or regular for several variables, pointing to the need for a systematic assessment of information on yellow fever held on SINAN.

Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil.

Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model framework to a null model, based on seasonal averages of previously observed dengue incidence. When considering the ability of the two models to predict high dengue risk across Brazil, the forecast model produced more hits and fewer missed events than the null model, with a hit rate of 57% for the forecast model compared to 33% for the null model. This early warning model framework may be useful to public health services, not only ahead of mass gatherings, but also before the peak dengue season each year, to control potentially explosive dengue epidemics.