Diversity of Anal HPV and Non-HPV Sexually Transmitted Infections and Concordance with Genital Infections in HIV-Infected and HIV-Uninfected Women in the Tapajós Region, Amazon, Brazil.

The aim of this study was to classify the diversity of anal HPV and non-HPV sexually transmitted infections (STIs) and compare the concordance between anal and genital infections in HIV-infected and uninfected women living in the Tapajós region, Amazon, Brazil. A cross-sectional study was performed with 112 HIV-uninfected and 41 HIV-infected nonindigenous women. Anal and cervical scrapings were collected and analyzed for HPV, Chlamydia trachomatis (CT), Neisseria gonorrheae (NG), Trichomonas vaginalis (TV), Mycoplasma genitalium (MG), and Human alphaherpesvirus 2 (HSV-2). The Kappa test evaluated the concordance between anal and genital infections. The overall prevalence of anal HPV infection was 31.3% in HIV-uninfected and 97.6% in HIV-infected women. The most frequent anal high-risk HPV (hrHPV) types were HPV18 and HPV16 in HIV-uninfected women and HPV51, HPV59, HPV31, and HPV58 in HIV-infected women. Anal HPV75 Betapapillomavirus was also identified. Anal non-HPV STIs were identified in 13.0% of all participants. The concordance analysis was fair for CT, MG, and HSV-2, almost perfect agreement for NG, moderate for HPV, and variable for the most frequent anal hrHPV types. Thus, a high prevalence of anal HPV infection with moderate and fair concordance between anal and genital HPV and non-HPV STIs was observed in our study.

COVID-PA Bulletin: reports on artificial intelligence-based forecasting in coping with COVID-19 pandemic in the state of Pará, Brazil. / Boletim COVID-PA: relatos sobre projeções baseadas em inteligência artificial no enfrentamento da pandemia de COVID-19 no estado do Pará.

OBJECTIVE: To report the university extension research result entitled 'The COVID-PA Bulletin', which presented forecasts on the behavior of the pandemic in the state of Pará, Brazil. METHODS: The artificial intelligence technique also known as 'artificial neural networks' was used to generate 13 bulletins with short-term forecasts based on historical data from the State Department of Public Health information system. RESULTS: After eight months of predictions, the technique generated reliable results, with an average accuracy of 97% (observed for147 days) for confirmed cases, 96% (observed for 161 days) for deaths and 86% (observed for 72 days) for Intensive Care Unit bed occupancy. CONCLUSION: These bulletins have become a useful decision-making tool for public managers, assisting in the reallocation of hospital resources and optimization of COVID-19 control strategies in various regions of the state of Pará.

Boletim COVID-PA: Reports on artificial intelligence-based forecasting to the facing of pandemic COVID-19 in the state of Pará, Brazil / Boletín COVID-PA: Informes de proyecciones basadas en inteligencia artificial para enfrentar la pandemia COVID-19 en el estado de Pará, Brasil / Boletim COVID-PA: relatos sobre projeções baseadas em inteligência artificial no enfrentamento da pandemia de COVID-19 no estado do Pará

Objective: Report the university research and extension product denominated 'Boletim COVID-PA' which presented projections about the pandemic in the State of Pará, Brazil, with practical, mathematically rigorous and computationally efficient approaches. Methods: The artificial intelligence technique known as Artificial Neural Networks was used to generate thirteen bulletins with short-term projections based on historical data from the State Department of Public Health system. Results: After eight months of projections, the technique generated reliable results with an average accuracy of 97% (147 days observed) for confirmed cases, 96% (161 observed days) for deaths and 86% (72 days observed) for occupancy of intensive care unit beds. Conclusion: These bulletins have become a useful tool for decision making by public managers, assisting in reallocating hospital resources and optimizing COVID-19 control strategies for the various regions of the State of Pará.

Objetivo: Relatar o produto de pesquisa e extensão universitária denominado Boletim COVID-PA, que apresentou projeções sobre o comportamento da pandemia no estado do Pará, Brasil. Métodos: Utilizou-se da técnica de inteligência artificial conhecida como 'redes neurais artificiais', para gerar 13 boletins com projeções de curto prazo baseadas nos dados históricos do sistema da Secretaria de Estado de Saúde Pública. Resultados: Após oito meses de projeções, a técnica gerou resultados confiáveis, com precisão média de 97% (147 dias observados) para casos confirmados, 96% (161 dias observados) para óbitos e 86% (72 dias observados) para ocupação de leitos de unidade de terapia intensiva. Conclusão: Esses boletins tornaram-se um instrumento útil para a tomada de decisão de gestores públicos, auxiliando na realocação de recursos hospitalares e otimização das estratégias de controle da COVID-19 nas diversas regiões do estado do Pará.

Prevalence of High Risk HPV in HIV-Infected Women From Belém, Pará, Amazon Region of Brazil: A Cross-Sectional Study.

Human papillomavirus (HPV) is the most common sexually transmitted infection in the world. Several studies have shown a higher prevalence of HPV infection in HIV-infected women. The aim of this study was to determine the prevalence and the genotype diversity of HPV infection in HIV-infected women. From April 2010 to December 2012 cervical specimens were collected from 169 HIV-infected women who screening for cervical cancer at Reference Unit in Belém. The detection of HPV infection was performed by nested PCR and HPV type was performed using a commercial system. The prevalence of HPV infection was 63.3%. Of the 47 genotyped samples, 40.4% was found positive for high risk-HPV 16 and 12.8% for high risk-HPV 52. HPV infection was predominant in the group of women with no incidence of cytological abnormalities and more prevalent in women of reproductive age, unmarried, low education level, and who reported use condoms during sexual intercourse. It was observed an association between HPV infection and independent variables, such as condom use, multiple sexual partners, and history of sexually transmitted diseases. High-risk types of HPV infection were prevalent in our study. Infection with multiple high-risk HPV genotypes may potentiate the development of cervical cancer in HIV-infected women.

Artificial neural networks for short-term forecasting of cases, deaths, and hospital beds occupancy in the COVID-19 pandemic at the Brazilian Amazon.

The first case of the novel coronavirus in Brazil was notified on February 26, 2020. After 21 days, the first case was reported in the second largest State of the Brazilian Amazon. The State of Pará presented difficulties in combating the pandemic, ranging from underreporting and a low number of tests to a large territorial distance between cities with installed hospital capacity. Due to these factors, mathematical data-driven short-term forecasting models can be a promising initiative to assist government officials in more agile and reliable actions. This study presents an approach based on artificial neural networks for the daily and cumulative forecasts of cases and deaths caused by COVID-19, and the forecast of demand for hospital beds. Six scenarios with different periods were used to identify the quality of the generated forecasting and the period in which they start to deteriorate. Results indicated that the computational model adapted capably to the training period and was able to make consistent short-term forecasts, especially for the cumulative variables and for demand hospital beds.

Boletim COVID-PA: relatos sobre projeções baseadas em inteligência artificial no enfrentamento da pandemia de COVID-19 no estado do Pará / Boletín COVID-PA: informes de proyecciones basadas en inteligencia artificial para enfrentar la pandemia COVID-19 en el estado de Pará, Brasil / COVID-PA Bulletin: reports on artificial intelligence-based forecasting in coping with COVID-19 pandemic in the state of Pará, Brazil

Objetivo: Relatar o produto de pesquisa e extensão universitária denominado Boletim COVID-PA, que apresentou projeções sobre o comportamento da pandemia no estado do Pará, Brasil. Métodos: Utilizou-se da técnica de inteligência artificial conhecida como 'redes neurais artificiais', para geração de 13 boletins com projeções de curto prazo baseadas nos dados históricos do sistema da Secretaria de Estado de Saúde Pública. Resultados: Após oito meses de projeções, a técnica gerou resultados confiáveis, com precisão média de 97% (147 dias observados) para casos confirmados, 96% (161 dias observados) para óbitos e 86% (72 dias observados) para ocupação de leitos de unidade de terapia intensiva. Conclusão: Esses boletins tornaram-se um instrumento útil para a tomada de decisão de gestores públicos, auxiliando na realocação de recursos hospitalares e otimização das estratégias de controle da COVID-19 nas diversas regiões do estado do Pará.

Objetivo: Reporte el resultado de la investigación y extensión universitaria denominada 'Boletim COVID-PA' que presentó proyecciones sobre el comportamiento de la pandemia en el estado de Pará, con un enfoque práctico y computacionalmente eficiente. Métodos: Fue utilizada una técnica de inteligencia artificial denominadas Redes Neurales para generar trece boletines con proyecciones basado en datos históricos del sistema de la Secretaría de Salud Pública. Resultados: Después de ocho meses de previsiones, la técnica genero resultados confiables con una precisión promedio de 97% (147 días observados) para casos confirmados, 96% (161 días observados) para los fallecimientos y 86% (72 días observados) para la ocupación de camas en las unidades de cuidados intensivos. Conclusión: Estos boletines se convirtieron en una herramienta para la toma de decisiones, auxiliando en la redistribución de recursos en los hospitales en el estado de Pará.

Objective: To report the university extension research result entitled 'The COVID-PA Bulletin', which presented forecasts on the behavior of the pandemic in the state of Pará, Brazil. Methods: The artificial intelligence technique also known as 'artificial neural networks' was used to generate 13 bulletins with short-term forecasts based on historical data from the State Department of Public Health information system. Results: After eight months of predictions, the technique generated reliable results, with an average accuracy of 97% (observed for147 days) for confirmed cases, 96% (observed for 161 days) for deaths and 86% (observed for 72 days) for Intensive Care Unit bed occupancy. Conclusion: These bulletins have become a useful decision-making tool for public managers, assisting in the reallocation of hospital resources and optimization of COVID-19 control strategies in various regions of the state of Pará.