ABSTRACT In this review, we discuss dengue surveillance, prevention, and control measures in Brazil. Data on dengue epidemics between 2000 and 2024 indicates an increase in the number of dengue cases and deaths. Global climate change is a key driver of this growth. Over the past 25 years, nearly 18 million Brazilians have been infected with the dengue virus, and the highest number of dengue cases in Brazil's history is projected to reach 2024. Dengue mortality in Brazil increased geographically over time. As of June, there were approximately 6 million probable cases and 4,000 confirmed deaths in Brazil, which represents the greatest dengue epidemic to date. Several technologies have been developed to control Aedes aegypti, including the deployment of Wolbachia-infected mosquitoes, indoor residual spraying, sterile insect techniques, and mosquito-disseminated insecticides. The Ministry of Health recommends integrating these technologies into health services. Brazil is the first country to incorporate the Takeda vaccine into its public health system, and the Butantan vaccine is currently undergoing Phase 3 clinical trials. Increasing the vaccination coverage and implementing novel Ae. aegypti control technologies could reduce the number of dengue cases in Brazil in the coming years. Community activities such as home cleaning and elimination of potential mosquito breeding sites, facilitated by social media and health education initiatives, must continue to achieve this reduction. Ultimately, a multisectoral approach encompassing sanitary improvements, mosquito control, vaccination, and community mobilization is crucial in the fight against dengue epidemics. review surveillance prevention 200 202 growth 2 years 1 virus Brazils s time June 4000 4 000 4,00 date Wolbachiainfected Wolbachia mosquitoes spraying techniques mosquitodisseminated disseminated insecticides services system trials Ae sites initiatives reduction Ultimately improvements 20 400 00 4,0 40 0 4,

ABSTRACT Deforestation and high human mobility due to mining activities have been key to the increase in malaria cases in the Americas. Here, we review the epidemiological and control aspects of malaria in the Amazon mining areas. Epidemiological evidence shows: 1) a positive correlation between illegal mining activity and malaria incidence, mostly in the Amazon region; 2) most Brazilian miners are males aged 15-29 years who move between states and even countries; 3) miners do not fear the disease and rely on medical care, diagnosis, and medication when they become ill; 4) illegal mining has emerged as the most reported anthropogenic activity within indigenous lands and is identified as a major cause of malaria outbreaks among indigenous people in the Amazon; and 5) because mining is largely illegal, most areas are not covered by any healthcare facilities or activities, leading to little assistance in the diagnosis and treatment of malaria. Our review identified five strategies for reducing the malaria incidence in areas with mining activities: 1) reviewing legislation to control deforestation and mining expansion, particularly in indigenous lands; 2) strengthening malaria surveillance by expanding the network of community health agents to support rapid diagnosis and treatment; 3) reinforcing vector control strategies, such as the use of insecticide-treated nets; 4) integrating deforestation alerts into the national malaria control program; and 5) implementing multi-sectoral activities and providing prompt assistance to indigenous populations. With this roadmap, we can expect a decrease in malaria incidence in the Amazonian mining areas in the future. Americas Here shows 1 region 2 1529 15 29 15-2 countries 3 care ill 4 5 expansion insecticidetreated insecticide treated nets program multisectoral multi sectoral populations roadmap future 152 15-

ABSTRACT Background: Domiciliation by Triatoma sordida is a public health concern in South America. This study aimed to evaluate the morphometric changes in the domestic and peridomestic populations of T. sordida. Methods: Specimen hemelytra were mounted, digitized, and processed for geometric morphometric analyses. Results: The specimens captured in houses were smaller than those captured in peridomiciles. A large size reduction effect was observed in female peridomicile populations compared with female house populations. Conclusions: T. sordida house populations were smaller than peridomestic populations. Wing geometric morphometry can be used as a tool to indicate T. sordida domiciliation. Background America T Methods mounted digitized analyses Results peridomiciles Conclusions domiciliation

ABSTRACT Background: Chagas disease is a silent illness with high mortality burden in many Latin American countries, such as Brazil. Bahia has the fourth highest mortality rate in Brazil. This study analyzed the temporal trends and regional differences in the mortality rate of Chagas disease in Bahia State from 2008 to 2018. Methods: A time-series analysis of Chagas disease-related deaths was conducted using data from the Mortality Information System of Brazil. We compared the mortality rate due to Chagas disease as the primary cause and mention of the disease in the death certificate, standardized by age and health macroregion/residence municipality, and mapped hot and coldspots. Results: The Chagas Disease Mortality Rate in Bahia during the study period revealed a stationary trend, ranging from 5.34 (2008) to 5.33 (2018) deaths per 100,000 inhabitants. However, the four health macroregions showed an upward trend in mortality rates. The mortality rate (age-adjusted) ranged from 4.3 to 5.1 deaths per 100,000 inhabitants between 2008 and 2018. We observed a upward trend in the mortality rate among individuals aged ≥70 years and a higher incidence of death among men than among women. Of the total number of deaths (8,834), 79.3% had Chagas disease as the primary cause and the death certificates of 20.7% mentioned the disease. Cardiac complications were reported in 85.1% of the deaths due to Chagas disease. Conclusions: The regional and individual differences in the mortality rate of Chagas disease highlighted in this study may support health planning that considers the peculiarities of the territory. Background countries Brazil 200 2018 Methods timeseries time series diseaserelated related certificate macroregionresidence macroregion residence municipality coldspots Results 534 5 34 5.3 (2008 533 33 (2018 100000 100 000 100,00 However rates ageadjusted adjusted (age-adjusted 43 4 3 4. 51 1 5. 70 ≥7 women 8,834, 8834 8,834 , 8 834 (8,834) 793 79 79.3 207 20 7 20.7 851 85 85.1 Conclusions territory 201 53 (200 (201 10000 10 00 100,0 ≥ 883 8,83 83 (8,834 79. 2 20. 85. (20 1000 0 100, 88 8,8 (8,83 (2 8, (8,8 ( (8, (8

Resumo As matas de galeria abrigam mamíferos e flebotomíneos que podem estar envolvidos na transmissão de Leishmania. Caracterizar os ciclos enzoóticos de Leishmania spp. é essencial para entender a dinâmica da transmissão. Foi analisada a presença de Leishmania spp. em mamíferos e flebotomíneos em matas de galeria durante a estação seca no Cerrado. Quatro matas de galeria foram investigadas nos meses de maio e setembro. Nosso esforço de captura foi de 1.280 armadilhas-noite HP e 16 armadilhas-noite Shannon para flebotomíneos e 5.120 armadilhas-noite para mamíferos. Depois de identificar as espécies, realizamos PCRs direcionadas aos genes SSU rRNA e ITS-1 para detectar Leishmania spp. Capturou-se um total de 1.209 flebotomíneos pertencentes a 13 espécies, principalmente Bichromomyia flaviscutellata. Não foi detectado DNA de Leishmania spp. nas fêmeas de flebotomíneos analisadas. A PCR de 153 mamíferos revelou Leishmania spp. em 20 amostras (13%) em maio (início da estação seca), quando a taxa de infecção alcançou 31% em uma mata de galeria. Os hospedeiros pertenciam as espécies Rhipidomys macrurus, Gracilinanus agilis e Didelphis albiventris. Observou-se uma baixa frequência de mamíferos infectados por Leishmania spp., que não foi detectada em flebotomíneos. Os resultados indicam que a infecção por Leishmania spp. nos mamíferos é maior durante o início da estação seca nas matas de galeria do Cerrado. spp Cerrado setembro 1280 1 280 1.28 armadilhasnoite armadilhas noite 5120 5 120 5.12 ITS1 ITS ITS- Capturouse Capturou se 1209 209 1.20 flaviscutellata analisadas 15 2 13% (13% seca, , seca) 31 macrurus albiventris Observouse Observou 128 28 1.2 512 12 5.1 (13 3 1. 51 5. (1 (

Abstract Gallery forests harbor mammals and sand flies that may be involved in the transmission of Leishmania spp. parasites. Characterizing the enzootic cycles of Leishmania spp. is essential for understanding its transmission dynamics. We analyzed the presence of Leishmania spp. in mammals and sand flies in gallery forests during the dry season in the Cerrado. Four gallery forests were investigated in May and September 2014. Our capture effort included 1,280 HP trap-nights, 16 Shannon trap-nights for sand flies, and 5,120 trap-nights for mammals. After identifying the mammalian and sand fly species, SSU rRNA and ITS-1 polymerase chain reaction (PCR) were used to detect Leishmania spp. A total of 1,209 sand flies belonging to 13 species were captured, mainly Bichromomyia flaviscutellata. Leishmania spp. DNA was not detected in the analyzed sand fly females. PCR analysis of 153 mammals revealed Leishmania spp. in 20 samples (13%) in May (early dry season), when the infection rate was 31% in one gallery forest. The host species were Rhipidomys macrurus, Gracilinanus agilis, and Didelphis albiventris. We observed a low frequency of mammals infected with Leishmania spp., which was not detected in sand flies. Our results indicate that Leishmania spp. infection is higher in mammals during the early dry season in Cerrado gallery forests. spp parasites dynamics 2014 1280 1 280 1,28 trapnights, trapnights trap nights, nights 5120 5 120 5,12 ITS1 ITS ITS- (PCR 1209 209 1,20 captured flaviscutellata females 15 2 13% (13% season, , season) 31 forest macrurus agilis albiventris 201 128 28 1,2 512 12 5,1 (13 3 1, 51 5, (1 (

ABSTRACT Background: This paper reports the occurrence of Panstrongylus guentheri Berg, 1879 in the State of Mato Grosso (MT). Methods: Triatomines were captured in rural environments in municipalities of MT. Specimens were identified, and Trypanosoma cruzi infection was investigated. Results: Nineteen specimens of Panstrongylus guentheri were found, primarily inside houses. The geographical distribution of this species was recorded in nine municipalities of Mato Grosso, and parasitological tests did not detect T. cruzi on P. guentheri. Conclusions: The distribution of this species in Brazil has been recently updated. Background Berg 187 MT . (MT) Methods identified investigated Results found houses T P Conclusions updated 18 (MT 1

ABSTRACT Background: Neglected tropical diseases are a growing threat to global health, and endemic Chagas disease has emerged as one of the most important health problems in America. The main strategy to prevent Trypanosoma cruzi transmission is chemical control of vectors. This study presents a descriptive analysis of synanthropic triatomines before and after the implementation of a vector-control program in Bahia, Brazil. Methods: Descriptive analysis and geospatial statistics were performed on triatomine data, (1) the relative abundance and (2) proportional spatial distribution, from Bahia during two periods: (A) 1957 to 1971 and (B) 2006 to 2019. Results: We observed a decrease in the relative abundance of Panstrongylus megistus (A: n=22.032, 61.9%; B: n=1.842, 1.0%) and Triatoma infestans (A: n=1.310, 3.7%; B: n=763, 0.43%), as well as an increase in the relative abundance of T. sordida (A: n=8.314, 23.4%, B: n=146.901, 81.6%) and T. pseudomaculata (A: n=894, 2.5%, B: n=16.717, 9.3%). Conclusions: Our results indicate a clear reduction in the occurrence of P. megistus and T. infestans (last record in 2015) and an increase in the relative abundance and geographical distribution of T. sordida and T. pseudomaculata after 40 years of the vector-control program. The high frequency of other triatomine species in the municipalities of the state of Bahia and their abundance in recent years highlight the need to reinforce permanent entomological surveillance actions to prevent Chagas disease.

Abstract INTRODUCTION: We aimed to study intraspecific variation in Triatoma costalimai, a potential vector of Chagas disease present in Brazil and Bolivia. METHODS: We analyzed phenotypic (connexivum color patterns, wing morphometrics) and genetic variation (16S mtDNA) of three Brazilian T. costalimai populations. We compared 16S sequences with those of putative Bolivian T. costalimai and its sister species, T. jatai. RESULTS: Brazilian populations had different connexivum color patterns and forewing shapes. A 16S mtDNA haplotype network showed a clear separation of Brazilian T. costalimai from both T. jatai and Bolivian T. costalimai. CONCLUSIONS: We report considerable variability in T. costalimai populations.

RESUMO Deep Learning é uma técnica de aprendizado de máquina na qual o programa computacional aprende padrões diretamente a partir de imagens classificadas previamente. O presente ensaio objetivou apresentar essa técnica e algumas de suas aplicações para diagnóstico de doenças e identificação de insetos vetores para incentivar profissionais da saúde que não tenham conhecimento aprofundado em informática e que desejem utilizar a ferramenta para realizar análises automatizadas. Deep Learning tem sido aplicado para diagnóstico de câncer, fibrose cardíaca, tuberculose, detecção de parasitos como Plasmodium e Leishmania e ainda para identificação de insetos vetores. Na Universidade de Brasília, a técnica tem sido aplicada para desenvolver uma ferramenta para identificar lesões ulceradas de leishmaniose em diagnóstico diferencial e para detectar Leishmania em lâminas de estudos histopatológicos. Além disso, Deep Learning tem sido usado para identificar as espécies de vetores da doença de Chagas – o que é importante para auxiliar na vigilância epidemiológica. O uso da tecnologia envolve desafios éticos e procedimentais que são discutidos no presente ensaio. O ensaio aponta perspectivas de desenvolvimento de aplicativos que auxiliem os profissionais de saúde no diagnóstico de Leishmaniose e de vetores da doença de Chagas, o que vai ao encontro dos objetivos da pesquisa translacional.

ABSTRACT Deep Learning is a machine learning technique in which the computational algorithm learns patterns directly from images previously classified. The present essay aims to show some of its applications for clinical diagnosis and identification of insect vectors to encourage health professionals who do not have deep knowledge of computer science and who wish to use the tool to perform automated analyzes. Deep Learning has been applied to the diagnosis of cancer, cardiac fibrosis, tuberculosis, detection of parasites such as Plasmodium and Leishmania, and to identify insect vectors. At the University of Brasília, Deep Learning has been used to develop a tool to identify ulcers caused by leishmaniasis, as well as to detect Leishmania parasites. Moreover, Deep Learning was applied to identify the species of vectors of Chagas disease, an important contribution to the epidemiological surveillance of the disease. The use of Deep Learning involves some ethical and procedural issues that are discussed in this paper. Finally, the essay points out perspectives of development of apps that assist health professionals in the diagnosis of Leishmaniasis and Chagas disease vectors, which meets the goals of translational research.

RESUMO Deep Learning é uma técnica de aprendizado de máquina na qual o programa computacional aprende padrões diretamente a partir de imagens classificadas previamente. O presente ensaio objetivou apresentar essa técnica e algumas de suas aplicações para diagnóstico de doenças e identificação de insetos vetores para incentivar profissionais da saúde que não tenham conhecimento aprofundado em informática e que desejem utilizar a ferramenta para realizar análises automatizadas. Deep Learning tem sido aplicado para diagnóstico de câncer, fibrose cardíaca, tuberculose, detecção de parasitos como Plasmodium e Leishmania e ainda para identificação de insetos vetores. Na Universidade de Brasília, a técnica tem sido aplicada para desenvolver uma ferramenta para identificar lesões ulceradas de leishmaniose em diagnóstico diferencial e para detectar Leishmania em lâminas de estudos histopatológicos. Além disso, Deep Learning tem sido usado para identificar as espécies de vetores da doença de Chagas – o que é importante para auxiliar na vigilância epidemiológica. O uso da tecnologia envolve desafios éticos e procedimentais que são discutidos no presente ensaio. O ensaio aponta perspectivas de desenvolvimento de aplicativos que auxiliem os profissionais de saúde no diagnóstico de Leishmaniose e de vetores da doença de Chagas, o que vai ao encontro dos objetivos da pesquisa translacional.

ABSTRACT Deep Learning is a machine learning technique in which the computational algorithm learns patterns directly from images previously classified. The present essay aims to show some of its applications for clinical diagnosis and identification of insect vectors to encourage health professionals who do not have deep knowledge of computer science and who wish to use the tool to perform automated analyzes. Deep Learning has been applied to the diagnosis of cancer, cardiac fibrosis, tuberculosis, detection of parasites such as Plasmodium and Leishmania, and to identify insect vectors. At the University of Brasília, Deep Learning has been used to develop a tool to identify ulcers caused by leishmaniasis, as well as to detect Leishmania parasites. Moreover, Deep Learning was applied to identify the species of vectors of Chagas disease, an important contribution to the epidemiological surveillance of the disease. The use of Deep Learning involves some ethical and procedural issues that are discussed in this paper. Finally, the essay points out perspectives of development of apps that assist health professionals in the diagnosis of Leishmaniasis and Chagas disease vectors, which meets the goals of translational research.

ABSTRACT Consumption of ready-to-eat (RTE) vegetables is quick, easy and healthy, especially when eaten without cooking. However, they might be a source of foodborne pathogenic microorganisms. The objective of this study was to evaluate the microbiological and parasitological contamination of fresh RTE vegetables produced in agroindustries in the Federal District of Brazil (FD), and to correlate contamination with good manufacturing practices (GMP). One hundred and three samples of RTE vegetables were collected from six agroindustries for microbiology and parasitology analyses and correlate with GMP; 54 samples were collected from three hypermarkets for parasitological evaluation. None of the samples analyzed were positive for Salmonella sp. and for thermotolerant coliforms, but they were contaminated with total coliforms. All analyzed samples were contaminated with at least one species of enteroparasistes or commensals, which were identified as Ascaris sp., Balantidium coli, Entamoeba histolytica/dispar, Hookworm, Strongyloides sp., Trichuris sp., Entamoeba sp., eggs and larvae of Nematoda, insects and fungi. Agroindustries that adopted GMP showed less contamination with helminths. RTE vegetables sold in hypermarkets of the FD are unfit for human consumption. It is important to guide farmers in the FD on the need to adopt good practices in the production and processing of vegetables to reduce the microbial contamination.

Abstract We report an Acanthamoeba keratitis case associated with the use of contact lens in a 28-year-old female from Brasília, Brazil. Samples from corneal scraping and contact lens case were used for culture establishment, PCR amplification, and partial sequencing (fragments of ~400kb) of small subunit rDNA; both culture and PCR were positive. The sequence analyses of the cornea and of isolates from the contact lens case showed similarity with the T4 genotype. To the best of our knowledge, this is the first report of T4 Acanthamoeba keratitis case from the Midwest region of Brazil.