Publications by authors named "Rafael De Castro Catao"
Dengue is hyperendemic in Brazil, with outbreaks affecting all regions. Previous studies identified geographical barriers to dengue transmission in Brazil, beyond which certain areas, such as South Brazil and the Amazon rainforest, were relatively protected from outbreaks. Recent data shows these barriers are being eroded.
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- The study analyzed the spread of yellow fever in Espírito Santo, Brazil, during the 2017 epidemic, focusing on its geographic and temporal distribution.
- Using ArcGIS software, the research found an incidence rate of 4.85 cases per 100,000 people, with a case-fatality rate of 29.74%, affecting 34 out of 78 municipalities.
- The analysis showed that yellow fever initially spread from municipalities near Minas Gerais and moved eastward, primarily affecting Central and Metropolitan regions rich in Atlantic Forest, indicating a pattern of contagion.
Background: Temperature and rainfall patterns are known to influence seasonal patterns of dengue transmission. However, the effect of severe drought and extremely wet conditions on the timing and intensity of dengue epidemics is poorly understood. In this study, we aimed to quantify the non-linear and delayed effects of extreme hydrometeorological hazards on dengue risk by level of urbanisation in Brazil using a spatiotemporal model.
View Article and Find Full Text PDFPublic 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.
View Article and Find Full Text PDFTwo 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.
View Article and Find Full Text PDFIs it time to talk about the end of social distancing? A joinpoint analysis of COVID-19 time series in Brazilian capitals.
Rev Soc Bras Med Trop
September 2020
Article Synopsis
- Monitoring COVID-19 infections and deaths in Brazil remains controversial as calls for easing social distancing grow, despite no consistent evidence of reduced cases.
- A segmented regression analysis revealed a mostly exponential rise in COVID-19 cases across Brazilian capital cities, with only 8 out of 20 cities showing a significant decline in cases later on.
- The findings suggest that any relaxation of restrictions should be approached with caution due to the potential for a resurgence in infections.
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.
View Article and Find Full Text PDFObjective 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.
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- A prototype dengue early warning system was created to forecast dengue risk three months prior to the 2014 World Cup in Brazil.
- The evaluation showed that this forecast model outperformed a null model based on seasonal averages, achieving a hit rate of 57% compared to 33%.
- This early warning framework could be valuable for public health services to manage dengue epidemics both before large events and during the peak transmission season.