Surveillance and molecular characterization of human sapovirus in patients with acute gastroenteritis in Brazil, 2010 to 2017.

BACKGROUND: Human sapoviruses (HuSaV) are associated with acute gastroenteritis (AGE), causing sporadic cases and outbreaks in patients worldwide. In Brazil, however, there are few reports describing the prevalence of HuSaV in patients with AGE. OBJECTIVE: Describing the diversity of HuSaV in Brazil by detecting and molecularly characterizing HuSaV among patients with AGE during an 8-year period (2010-2017). STUDY DESIGN: A total of 3974 stool samples, testing negative for rotavirus (RVA), norovirus (NoV) and human adenovirus (HAdV), were selected and screened for the presence of HuSaV. Nested RT-PCR were performed for a partial region of VP1, sequenced and genetic analyzed for genotyping the positive samples. RESULTS: In the current study, the HuSaV prevalence was determined to be 3.7% (149/3974). A higher prevalence, 5.7% (118/2074), was observed in children under 2 years of age. During the surveillance period, 13 outbreaks were detected: 12 outbreaks in children under 3 years old and one outbreak in adults. Among the 149 HuSaV positive cases, 106 samples (71%) were successfully sequenced. The most prevalent genotype found was GI.1 (44.3%), followed by GI.2 (21.7%), GI.3 (3.8%), GI.6 (2.8%), GII.1 (5.7%), GII.2 (8.5%), GII.3 (2.8%), GII.4 (2.8%), GII.5 (5.7%) and GIV.1 (1.9%). Two GIV.1 strains characterized in this study are, to date, the only strains of this genotype reported in Brazil. CONCLUSIONS: The present study elucidated the circulation of HuSaV in Brazil and highlight that HuSaV has not assumed an epidemiological importance in the country after the introduction of the RVA vaccine.

Genomic Surveillance of Yellow Fever Virus Epizootic in São Paulo, Brazil, 2016 - 2018.

São Paulo, a densely inhabited state in southeast Brazil that contains the fourth most populated city in the world, recently experienced its largest yellow fever virus (YFV) outbreak in decades. YFV does not normally circulate extensively in São Paulo, so most people were unvaccinated when the outbreak began. Surveillance in non-human primates (NHPs) is important for determining the magnitude and geographic extent of an epizootic, thereby helping to evaluate the risk of YFV spillover to humans. Data from infected NHPs can give more accurate insights into YFV spread than when using data from human cases alone. To contextualise human cases, identify epizootic foci and uncover the rate and direction of YFV spread in São Paulo, we generated and analysed virus genomic data and epizootic case data from NHPs in São Paulo. We report the occurrence of three spatiotemporally distinct phases of the outbreak in São Paulo prior to February 2018. We generated 51 new virus genomes from YFV positive cases identified in 23 different municipalities in São Paulo, mostly sampled from NHPs between October 2016 and January 2018. Although we observe substantial heterogeneity in lineage dispersal velocities between phylogenetic branches, continuous phylogeographic analyses of generated YFV genomes suggest that YFV lineages spread in São Paulo at a mean rate of approximately 1km per day during all phases of the outbreak. Viral lineages from the first epizootic phase in northern São Paulo subsequently dispersed towards the south of the state to cause the second and third epizootic phases there. This alters our understanding of how YFV was introduced into the densely populated south of São Paulo state. Our results shed light on the sylvatic transmission of YFV in highly fragmented forested regions in São Paulo state and highlight the importance of continued surveillance of zoonotic pathogens in sentinel species.

Genomic Surveillance of Yellow Fever Virus Epizootic in São Paulo, Brazil, 2016 ­ 2018

São Paulo, a densely inhabited state in southeast Brazil that contains the fourth most populated city in the world, recently experienced its largest yellow fever virus (YFV) outbreak in decades. YFV does not normally circulate extensively in São Paulo, so most people were unvaccinated when the outbreak began. Surveillance in non-human primates (NHPs) is important for determining the magnitude and geographic extent of an epizootic, thereby helping to evaluate the risk of YFV spillover to humans. Data from infected NHPs can give more accurate insights into YFV spread than when using data from human cases alone. To contextualise human cases, identify epizootic foci and uncover the rate and direction of YFV spread in São Paulo, we generated and analysed virus genomic data and epizootic case data from NHPs in São Paulo. We report the occurrence of three spatiotemporally distinct phases of the outbreak in São Paulo prior to February 2018. We generated 51 new virus genomes from YFV positive cases identified in 23 different municipalities in São Paulo, mostly sampled from NHPs between October 2016 and January 2018. Although we observe substantial heterogeneity in lineage dispersal velocities between phylogenetic branches, continuous phylogeographic analyses of generated YFV genomes suggest that YFV

Fatal Brazilian Spotted Fever Associated with Dogs and Amblyomma aureolatum Ticks, Brazil, 2013.

In São Paulo metropolitan area, Brazil, Amblyomma aureolatum ticks are the main vector of Rickettsia rickettsii, which causes Brazilian spotted fever. In 2013, a boy in São Paulo died of Brazilian spotted fever associated with household dogs and A. aureolatum ticks. Prompt recognition and treatment of this illness might prevent deaths.

Rickettsia sp. Strain Atlantic Rainforest Infection in a Patient from a Spotted Fever-Endemic Area in Southern Brazil.

Santa Catarina State in southern Brazil is the state with the second highest number of laboratory-confirmed cases of spotted fever illness in Brazil. However, all these cases were confirmed solely by serological analysis (seroconversion to spotted fever group rickettsiae), which has not allowed identification of the rickettsial agent. Here, a clinical case of spotted fever illness from Santa Catarina is shown by seroconversion and molecular analysis to be caused by Rickettsia sp. strain Atlantic rainforest. This is the third confirmed clinical case due to this emerging rickettsial agent in Brazil. Like the previous two cases, the patient presented an inoculation eschar at the tick bite site. Our molecular diagnosis was performed on DNA extracted from the crust removed from the eschar. These results are supported by previous epidemiological studies in Santa Catarina, which showed that nearly 10% of the most common human-biting ticks were infected by Rickettsia sp. strain Atlantic rainforest.

Genetic identification of rickettsial isolates from fatal cases of Brazilian spotted fever and comparison with Rickettsia rickettsii isolates from the American continents.

Fifteen bacterial isolates from spotted fever group rickettsiosis in Brazil were genetically identified as Rickettsia rickettsii. In a phylogenetic analysis with other R. rickettsii isolates from GenBank, the Central/South American isolates showed low polymorphism and formed a clade distinct from two North American clades, with the North American clades having greater in-branch polymorphism.

Features of Brazilian spotted fever in two different endemic areas in Brazil.

Brazilian spotted fever (BSF) caused by Rickettsia rickettsii is the most important rickettsiosis and the only reportable tick-borne disease in Brazil. In Brazil, the hard tick Amblyomma cajennense is the most important BSF vector; however, in São Paulo State, A. aureolatum was also recognized as a vector species in remaining Atlantic forest areas near the metropolitan area of São Paulo city. We analyzed clinical and epidemiological features of BSF cases from two distinct areas where A. cajennense (Area 1) and A. aureolatum (Area 2) are the incriminated vectors. The clinical features demonstrate the same severity pattern of BSF in both endemic areas. Differences in seasonality, patient characteristics (median age and gender), and epidemiological risk factors (animals host contact and vegetation characteristics) were observed and possibly could be attributed to the characteristics of each vector and their typical biological cycle (hosts and environment).