RESUMO: Objetivo: Descrever, de forma retrospectiva, os casos graves de pacientes hospitalizados e os óbitos relacionados à epidemia de COVID-19 no estado de São Paulo, desde a data do primeiro registro, com início de sintomas em 10 de fevereiro de 2020 até registros disponíveis em 20 de maio de 2021. Métodos: Trata-se de um estudo descritivo realizado por meio da base de dados do Sistema de Vigilância Epidemiológica da Gripe. Foram calculadas as taxas de incidência, mortalidade e incidência acumulada no período, estratificadas por faixa etária e agrupadas de acordo com cada Departamento Regional de Saúde. Os casos graves foram geocodificados para a análise de seu espalhamento pelo estado e foi calculado o R efetivo, que estima o potencial de propagação de um vírus em uma população. Resultados: Houve aumento significativo dos casos graves e óbitos registrados no período de um ano, e as taxas de incidência e mortalidade foram heterogêneas no estado. Os períodos mais críticos em relação à incidência de casos graves ocorreram entre maio e julho de 2020 e entre março e abril de 2021. Os Departamentos Regionais de Saúde de São José do Rio Preto, Grande São Paulo e Araçatuba concentraram as maiores taxas de incidência e mortalidade. Os casos graves e óbitos foram mais frequentes nos homens e na população acima de 60 anos, e as principais condições de risco relacionadas aos óbitos foram cardiopatia (59%) e diabetes (42,8%). Conclusões: Espera-se que esses resultados ofereçam embasamento e possam contribuir para uma ação de controle mais eficiente da COVID-19, além de permitir o entendimento histórico de sua evolução no estado.

The Middle Paranapanema River region of São Paulo, Brazil is home to significant diversity of Biomphalaria species and is very vulnerable to health and environmental impacts such as schistosomiasis. This study updates freshwater malacological surveys for ecosystems in one portion of the Middle Paranapanema River Basin, with emphasis on the genus Biomphalaria. Snails were collected from 114 distinct bodies of water between 2015 and 2018. Biomphalaria specimens were identified according to morphological and molecular characteristics, while animals in other genera (Drepanotrema, Lymnaea, Melanoides, Physa and Pomacea) were identified solely according to shell characteristics. A geographic information system was used to update intermediate host colonization sites and consequently assist in identifying probable hotspots for intermediate hosts of schistosomiasis. The sequences of the COI gene relating to the DNA barcode stretch were tested for similarity against sequences found in GenBank, for monophyly through Maximum Likelihood phylogenetic inference, and analyzed in ABDG, bPTP and GMYC for the delimitation of putative species. Of the 10,722 snails collected, 86.7% were in the Planorbidae family (75.5% Biomphalaria and 11.2% Drepanotrema) and 13.3% were other non-Planorbidae species (Lymnaea, Melanoides, Physa and Pomacea). The taxonomic COI reference sequences in the NCBI nucleotide database used for DNA sequence comparison, and phylogenetic analysis used to test the monophyly of the groups, resulted in more reliable taxonomic units than delimitation of the COI sequences in MOTUs using statistical taxonomic models. Analysis of the species distribution shows that B. glabrata and B. tenagophila are heterogeneously distributed in the study area. B. glabrata colonizes only five water bodies, in the study area, most of them in Ourinhos, while B. tenagophila predominates in water bodies in Ipaussu. Contrasting with this, B. straminea, B. occidentalis and B. peregrina are evenly distributed throughout the study area.

DNA barcoding and morphological characters were used to identify adult snails belonging to the genus Biomphalaria from 17 municipalities in the state of São Paulo, Brazil. The DNA barcode analysis also included twenty-nine sequences retrieved from GenBank. The final data set of 104 sequences of the mitochondrial cytochrome oxidase I (COI) gene was analyzed for K2P intraspecific and interspecific divergences, through tree-reconstruction methods (Neighbor-Joining, Maximum Likelihood and Bayesian inference), and by applying different models (ABGD, bPTP, GMYC) to partition the sequences according to the pattern of genetic variation. Twenty-seven morphological parameters of internal organs were used to identify specimens. The molecular taxonomy of Biomphalaria agreed with the morphological identification of specimens from the same collection locality. DNA barcoding may therefore be a useful supporting tool for identifying Biomphalaria snails in areas at risk for schistosomiasis.

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