20-Month monitoring of SARS-CoV-2 in wastewater of Curitiba, in Southern Brazil.

The COVID-19 pandemic resulted in the collapse of healthcare systems and led to the development and application of several approaches of wastewater-based epidemiology to monitor infected populations. The main objective of this study was to carry out a SARS-CoV-2 wastewater based surveillance in Curitiba, Southern Brazil Sewage samples were collected weekly for 20 months at the entrance of five treatment plants representing the entire city and quantified by qPCR using the N1 marker. The viral loads were correlated with epidemiological data. The correlation by sampling points showed that the relationship between the viral loads and the number of reported cases was best described by a cross-correlation function, indicating a lag between 7 and 14 days amidst the variables, whereas the data for the entire city presented a higher correlation (0.84) with the number of positive tests at lag 0 (sampling day). The results also suggest that the Omicron VOC resulted in higher titers than the Delta VOC. Overall, our results showed that the approach used was robust as an early warning system, even with the use of different epidemiological indicators or changes in the virus variants in circulation. Therefore, it can contribute to public decision-makers and health interventions, especially in vulnerable and low-income regions with limited clinical testing capacity. Looking toward the future, this approach will contribute to a new look at environmental sanitation and should even induce an increase in sewage coverage rates in emerging countries.

Tuberculosis in the Russian Federation: Dynamics of the Epidemic Indicators before and after COVID-19 Pandemic.

The measures taken against tuberculosis (TB) in recent years in the Russian Federation have been highly effective. Unfortunately, the COVID-19 pandemic may seriously undermine the progress that has been made in the fight against TB. The aim of this study was to assess changes in the epidemiological rates of tuberculosis in the Russian Federation before and after the COVID-19 pandemic. Materials and methods. The analysis was conducted by considering the main epidemiological indicators of tuberculosis, according to the federal statistics for the period from 2017 to 2021. The parameters were estimated according to the data received from 11 areas in the North-Western region. Statistical analysis was carried out using the free software computing environment R (v.3.5.1) and the commercial software package Statistical Package for the Social Sciences (SPSS Statistics for Windows, version 24.0, IBM Corp., 2016). Research results. We found a positive correlation between the incidence among the overall population and the incidence among children aged 0-17, inclusively (r = 0.55 in 2017, r = 0.60 in 2020, and r = 0.53 in 2021). Along with the received regularities, a different trend is shown in the data analysis of general incidence and health X-ray examination for tuberculosis among the general population. The correlation has decreased threefold from 2017 (r = 0.72) to 2020 (r = 0.32); this negative trend might be the result of factors such as the quality of X-ray screening examinations among the general population, and the reduced assessment objectivity of the tuberculosis incidence rate. Conclusions. In assessing the correlation between general incidence and incidence in children under 17 years of age, as well as between incidence and mortality in the Russian Federation, a positive correlation was found with an increasing trend. Such a discrepancy might be due to decreases in the occupational health examination coverage among the general population. Therefore, in the years ahead, we can expect epidemiological indicators to increase incidence and mortality, including child mortality, associated with the insufficient detection of tuberculosis among the population during the COVID-19 pandemic.

COVID-19 Vaccinating Russian Medical Students-Challenges and Solutions: A Cross-Sectional Study.

Background: The role of preventive measures increases significantly in the absence of effective specific COVID-19 treatment. Mass population immunization and the achievement of collective immunity are of particular importance. The future development of public attitudes towards SARS-CoV-2 immunization depends significantly on medical students, as future physicians. Therefore, it seemed relevant to determine the percentage of COVID-19-vaccinated medical students and to identify the factors significantly affecting this indicator. Methods: A total of 2890 medical students from years one to six, studying at nine leading Russian medical universities, participated in an anonymous sociological survey. The study was performed in accordance with the STROBE guidelines. Results: It was found that the percentage of vaccinated Russian medical students at the beginning of the academic year 2021 was 58.8 ± 7.69%, which did not significantly differ from the vaccination coverage of the general population in the corresponding regions (54.19 ± 4.83%). Student vaccination rate was largely determined by the region-specific epidemiological situation. The level of student vaccination coverage did not depend on the gender or student residence (in a family or in a university dormitory). The group of senior students had a higher number of COVID-19 vaccine completers than the group of junior students. The lack of reliable information about COVID-19 vaccines had a pronounced negative impact on the SARS-CoV-2 immunization process. Significant information sources influencing student attitudes toward vaccination included medical professionals, medical universities, academic conferences, and manuscripts, which at that time provided the least information. Conclusion: The obtained results make it possible to develop recommendations to promote SARS-CoV-2 immunoprophylaxis among students and the general population and to increase collective immunity.

Estudio transversal de una base de datos sobre casos de COVID-19 y aplicación de indicadores epidemiológicos básicos bajo la modalidad de taller / Cross-sectional study of a COVID-19 cases data base and application of basic epidemiological indicators in a workshop modality

Introducción. La pandemia por COVID-19 ha evidenciado la importancia de la metodología epidemiológica, por lo que es significativo fortalecer su aprendizaje en todos los niveles formativos del área de ciencias de la salud. Objetivo. Aplicar metodología epidemiológica de carácter descriptivo y analítico para el estudio de una base de datos de casos COVID-19 en la República Mexicana. Material y métodos. Se realizó una búsqueda de bases de datos en sitios web oficiales sobre los casos de COVID-19, y se recuperó un archivo en formato Excel con la información de 65,536 casos al día 10 de abril del 2021 a las 01:14hrs. Posteriormente, se realizó análisis estadístico de las diferentes variables mediante el programa SPSS, versión 21 en español, consistente en cálculo de prevalencias, razón de productos cruzados (RPC) y medidas de asociación, en lo cual participaron alumnos del cuarto semestre de enfermería. Resultados. La prevalencia para el género masculino fue de 53 %, y para el femenino de 47 %, con una media aritmética de edad de 35 años. La Chi cuadrada entre género y resultado de laboratorio positivo fue de 6527.9, con un 99 % de probabilidad de que haya asociación entre las variables. Asimismo, para la relación hipertensión y resultado de laboratorio positivo la Chi cuadrada fue de 51.97. La RPC para diabetes y resultado de laboratorio positivo fue de 1.4. Conclusiones. La aplicación de indicadores epidemiológicos básicos representa una herramienta importante para el fenómeno epidemiológico COVID-19, pues establece una caracterización de la epidemia en nuestro país.

Introduction: The COVID-19 pandemic has evidenced the importance of epidemiological methodology, so it is significant to strengthen its learning at all educational levels in the area of health sciences. Objetive. Apply descriptive and analytical epidemiological methodology for the study of a database of COVID-19 cases in the Mexican Republic. Material and methods: A search of databases on official websites on COVID-19 cases was carried out, and an Excel format file was recovered with the information of 65,536 cases as of April 10, 2021 at 01:14 a.m. Subsequently, a statistical analysis of the different variables was carried out using the SPSS program, version 21 in Spanish, consisting of calculation of prevalence, ratio of cross products (RPC) and measures of association, in which fourth semester nursing students participated. Results: The prevalence for the male gender was 53%, and for the female 47%, with an arithmetic mean age of 35 years. The Chi square between gender and positive laboratory result was 6527.9, with a 99% probability of an association between the variables. Likewise, for the relationship between hypertension and a positive laboratory result, the Chi square was 51.97. The RPC for diabetes and positive laboratory result was 1.4. Conclusions: The application of basic epidemiological indicators represents an important tool for the epidemiological phenomenon COVID-19, since it establishes a characterization of the epidemic in our country.

A Novel Matrix Profile-Guided Attention LSTM Model for Forecasting COVID-19 Cases in USA.

Background: The outbreak of the novel coronavirus disease 2019 (COVID-19) has been raging around the world for more than 1 year. Analysis of previous COVID-19 data is useful to explore its epidemic patterns. Utilizing data mining and machine learning methods for COVID-19 forecasting might provide a better insight into the trends of COVID-19 cases. This study aims to model the COVID-19 cases and perform forecasting of three important indicators of COVID-19 in the United States of America (USA), which are the adjusted percentage of daily admitted hospitalized COVID-19 cases (hospital admission), the number of daily confirmed COVID-19 cases (confirmed cases), and the number of daily death cases caused by COVID-19 (death cases). Materials and Methods: The actual COVID-19 data from March 1, 2020 to August 5, 2021 were obtained from Carnegie Mellon University Delphi Research Group. A novel forecasting algorithm was proposed to model and predict the three indicators. This algorithm is a hybrid of an unsupervised time series anomaly detection technique called matrix profile and an attention-based long short-term memory (LSTM) model. Several classic statistical models and the baseline recurrent neural network (RNN) models were used as the baseline models. All models were evaluated using a repeated holdout training and test strategy. Results: The proposed matrix profile-assisted attention-based LSTM model performed the best among all the compared models, which has the root mean square error (RMSE) = 1.23, 31612.81, 467.17, mean absolute error (MAE) = 0.95, 26259.55, 364.02, and mean absolute percentage error (MAPE) = 0.25, 1.06, 0.55, for hospital admission, confirmed cases, and death cases, respectively. Conclusion: The proposed model is more powerful in forecasting COVID-19 cases. It can potentially aid policymakers in making prevention plans and guide health care managers to allocate health care resources reasonably.

[Age-related macular degeneration and diabetic eye lesion. Socio-economic aspects]. / Vozrastnaya makulyarnaya degeneratsiya i diabeticheskoe porazhenie glaz. Sotsial'no-ekonomicheskie aspekty zabolevaemosti.

Diabetic retinopathy (DR) and age-related macular degeneration (AMD) comprise a significant socio-medical problem for Russia. The article presents an analysis aimed at identifying the prerequisites for further research on the socio-economic consequences of retinal pathology. Studying the epidemiological aspects of DR and AMD, as well as the conditions for receiving medical aid helped define the main approaches to assessing the economic burden of retinal diseases in Russia. It also revealed the problems associated with completeness of registration and accounting of patients, the disparity between the volume of medical aid required and funding, and between the required and provided assistance for patients with these pathologies in clinical practice. Analysis of the disease cost will allow not only to determine the socio-economic consequences of retinal diseases, but also to find further directions for improving the quality of medical care for patients with DR and AMD in order to reduce its economic cost for the state and society. Evidently, there is a need for comprehensive assessment of the total burden of retinal diseases in Russia that would serve as a basis for subsequent assessment of the economic effectiveness of prevention and treatment measures.

Towards unified and real-time analyses of outbreaks at country-level during pandemics.

The management of public health and the preparedness for health emergencies partly rely on the collection and analysis of surveillance data, which become crucial in the context of an emergency such as the pandemic caused by COVID-19. For COVID-19, typically, numerous national and global initiatives have been set up from this perspective. Here, we propose to develop a shared vision of the country-level outbreaks during a pandemic, by enhancing, at the international scale, the foundations of the analysis of surveillance data and by adopting a unified and real-time approach to monitor and forecast the outbreak across time and across the world. This proposal, rolled out as a web platform, should contribute to strengthen epidemiological understanding, sanitary democracy as well as global and local responses to pandemics.

Estimating the Prevalence and Mortality of Coronavirus Disease 2019 (COVID-19) in the USA, the UK, Russia, and India.

OBJECTIVE: The aim of this study is to apply the advanced error-trend-seasonal (ETS) framework to forecast the prevalence and mortality series of COVID-19 in the USA, the UK, Russia, and India, and the predictive performance of the ETS framework was compared with the most frequently used autoregressive integrated moving average (ARIMA) model. MATERIALS AND METHODS: The prevalence and mortality data of COVID-19 in the USA, the UK, Russia, and India between 20 February 2020 and 15 May 2020 were extracted from the WHO website. Then, the data subsamples between 20 February 2020 and 3 May 2020 were treated as the training horizon, and the others were used as the testing horizon to construct the ARIMA models and the ETS models. RESULTS: Based on the model evaluation criteria, the ARIMA (0,2,1) and ETS (M,MD,N), sparse coefficient ARIMA (0,2,(1,6)) and ETS (A,AD,M), ARIMA (1,1,1) and ETS (A,MD,A), together with ARIMA (2,2,1) and ETS (A,M,A) specifications were identified as the preferred ARIMA and ETS models for the prevalence data in the USA, the UK, Russia, and India, respectively; the ARIMA (0,2,1) and ETS (M,A,M), ARIMA (0,2,1) and ETS (M,A,N), ARIMA (0,2,1) and ETS (A,A,N), coupled with ARIMA (0,2,2) and ETS (M,M,N) specifications were selected as the optimal ARIMA and ETS models for the mortality data in these four countries, respectively. Among these best-fitting models, the ETS models produced smaller forecasting error rates than the ARIMA models in all the datasets. CONCLUSION: The ETS framework can be used to nowcast and forecast the long-term temporal trends of the COVID-19 prevalence and mortality in the USA, the UK, Russia, and India, and which provides a notable performance improvement over the most frequently used ARIMA model. Our findings can aid governments as a reference to prepare for and respond to the COVID-19 pandemic both in restricting the transmission of the disease and in lowering the disease-related deaths in the upcoming days.

A Correlation Study of the Colorectal Cancer Statistics and Economic Indicators in Selected Balkan Countries.

Colorectal cancer (CRC) is one of the most commonly diagnosed malignant neoplasms. The aim of the study was to evaluate and correlate most important epidemiological and economic indicators of CRC in 11 selected Balkan countries. The number of new CRC cases was 56,960, and the highest 5-year CRC prevalence was in Slovenia, Croatia, and Greece. Age-standardized CRC incidence rates were highest in Slovenia, Serbia, and Croatia, and age-standardized mortality rates were highest in Croatia, Serbia, and Bulgaria. Current Health Expenditure as % of Gross Domestic Product was the highest in Bosnia and Herzegovina and Serbia. The GDP per capita levels have shown positive correlation with the CRC incidence rate and prevalence. Absolute numbers of new and death-related CRC cases and 5-year prevalence in absolute numbers have shown strong positive correlation with GDP in million current US$. It has been shown that various economic indicators can be linked to the rate of incidence and prevalence of the CRC patients in the selected Balkan countries. Therefore, economic factors can influence the epidemiology of CRC, and heavy CRC burden in the Balkan region may be one of the indexes of the economic development.

[The epidemiologic study of the risk of autism spectrum disorders in children of 16-24 months in Russia, 2015-2016]. / Épidemiologiia riska vozniknoveniia rasstroistv autisticheskogo spektra u detei 16-24 mesiatsev zhizni (dannye po Rossii za 2015-2016 gg.).

AIM: To screen infants of the general population for the risk of autism spectrum disorders (ASD). MATERIAL AND METHODS: The survey was conducted by a total epidemiological method in primary health care facilities in the three largest regions in Russia (Volgograd, Novosibirsk, Chelyabinsk regions). For the period 2015-2016, 74191 parents of children aged 16-24 months were questioned. RESULTS AND CONCLUSION: The prevalence of risk of ASD (a condition of a pre-illness) was 103.5 cases per 1000 of children aged 16-24 months. Some of the children at ASD risk had a preventive consultation with a psychiatrist, 36 children (0.5 per 1000 peers) had severe clinical disorders classified as F84 - 'Pervasive developmental disorders' of ICD-10 (F84.0; F84.1; F84.8). From the perspective of predicative and preventive medicine, children at risk require complex measures to prevent the onset of a mental disorder or worsening of the mental state of the child.

Somatic cell counts as an indicator of mammary infection in periparturient cows / Contagem de células somáticas como indicador de infecção mamária em vacas periparturientes

The somatic cell count (SCC) is a screening test for the evaluation of intramammary infection; however, changes in mammary secretion during colostrogenesis can promote a physiological increase in the SCC, potentially reducing its reliability in the diagnosis of mastitis. Therefore, the aim of this study was to evaluate bovine colostrum SCC as an indicative parameter of breast infection in Holstein periparturient cows. A total of 80 samples were harvested from the first milking colostrum of 20 cows and were subjected to manual SCC and bacteriological examination. Bacterial growth was present in 36.62% of the crops; coagulase-negative Staphylococcus (CNS) was the predominant microorganism (76.92%). The median SCC in infected cows (1.8 × 106 cells/mL) was significantly higher than in uninfected cows (0.9 × 106 cells/mL) (p = 0.0451). The sensitivity (10015%), specificity (1002.2%), and false positive (1002.2%) of the SCC decreased gradually when thresholds of 0.210.0 × 106 cells/mL were adopted. In contrast, the proportion of false negatives (084.6%) revealed an opposite trend. The threshold of greatest concordance between SCC and bacteriological examination was 10.0 × 106 cells/mL; however, the sensitivity rates (15.4%), specificity (2.2%), and false positive (2.2%) were very low. Based on these results, we conclude that SCCs increased prior to the infectious processes of the mammary gland, particularly in the CNS group. However, physiological changes caused by colostrogenesis resulted in poor concordance between the SCC and bacteriological examination of the colostrum...

A contagem de células somáticas (CCS) é um teste de triagem para avaliação de infecção intramamária, porém, as alterações na composição do colostro observadas durante a colostrogênese podem promover o aumento fisiológico da CCS e inviabilizar o uso desta prova para diagnóstico da mastite. Assim, o objetivo desta pesquisa foi avaliar a CCS do colostro como parâmetro indicativo de infecção mamária em vacas Holandesas periparturientes. Para tanto, foram colhidas 80 amostras de colostro de primeira ordenha, provenientes de 20 vacas, para a CCS manual e exame bacteriológico (EB). Observou-se crescimento bacteriano em 36,62% dos cultivos, com predomínio de Staphylococcus coagulase-negativa (SCN) (76,92%). O valor mediano da CCS de vacas infectadas (1,8 x106 células/mL) foi maior do que o obtido para as vacas sadias (0,9 x106 células/mL) (P=0,0451). A sensibilidade (100 a 15%), especificidade (100 a 2,2%) e falso-positivo (100 a 2,2%) diminuíram gradativamente quando os limiares de 0,2 a 10,0 x106 células/mL foram adotados. Em contrapartida, a proporção de falso-negativo (0 a 84,6%) apresentou perfil inverso. O limiar de maior concordância entre a CCS e EB foi de 10,0 x106 células/mL, porém os índices de sensibilidade (15,4%), especificidade (2,2%) e falso-positivo (2,2%) foram muito baixos. Com base nos resultados encontrados, conclui-se que a CCS apresentou elevação diante dos processos infecciosos da glândula mamária (GM), causados especialmente por bactérias do grupo SCN. No entanto, as alterações fisiológicas decorrentes da colostrogênese resultaram em baixa concordância entre a CCS e o exame bacteriológico do colostro...

Leprosy in post-elimination era in India: difficult journey ahead.

Leprosy is a chronic inflammatory disease of skin and peripheral nerves. Elimination of leprosy as a public health problem was reached at the global level in the year 2000 and by India on 31(st) December, 2005. Thereafter, leprosy services in India have been integrated with General Health-Care System resulting in reduced focus and funds. Sustaining the gains made so far in controlling leprosy is a big challenge and there is no time for complacency. Pockets of high endemicity with prevalence rate of > 1 still exist in many states. Our data from a tertiary care center indicates poor epidemiological control and ongoing disease transmission. To combat this, dermatologists all over India should continue to play a central role in capacity building and training of undergraduate and post-graduate students, medical officers, and field workers.

Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet.

Infodemiology can be defined as the science of distribution and determinants of information in an electronic medium, specifically the Internet, or in a population, with the ultimate aim to inform public health and public policy. Infodemiology data can be collected and analyzed in near real time. Examples for infodemiology applications include the analysis of queries from Internet search engines to predict disease outbreaks (eg. influenza), monitoring peoples' status updates on microblogs such as Twitter for syndromic surveillance, detecting and quantifying disparities in health information availability, identifying and monitoring of public health relevant publications on the Internet (eg. anti-vaccination sites, but also news articles or expert-curated outbreak reports), automated tools to measure information diffusion and knowledge translation, and tracking the effectiveness of health marketing campaigns. Moreover, analyzing how people search and navigate the Internet for health-related information, as well as how they communicate and share this information, can provide valuable insights into health-related behavior of populations. Seven years after the infodemiology concept was first introduced, this paper revisits the emerging fields of infodemiology and infoveillance and proposes an expanded framework, introducing some basic metrics such as information prevalence, concept occurrence ratios, and information incidence. The framework distinguishes supply-based applications (analyzing what is being published on the Internet, eg. on Web sites, newsgroups, blogs, microblogs and social media) from demand-based methods (search and navigation behavior), and further distinguishes passive from active infoveillance methods. Infodemiology metrics follow population health relevant events or predict them. Thus, these metrics and methods are potentially useful for public health practice and research, and should be further developed and standardized.

Introducción a la esperanza de vida ajustada por discapacidad

Se presenta la justificación y el procedimiento de cálculo de la esperanza de vida ajustada por discapacidad, indicador que resume la salud de una población de una manera especialmente intuitiva. Se comenta la interdependencia entre este indicador y los años de vida ajustados por discapacidad (AVAD), los cuales se utilizan de manera creciente a nivel nacional e internacional para evaluar la carga de enfermedades y sus secuelas, y la carga de los principales factores de riesgo que propician esas enfermedades y secuelas. Se ilustra el procedimiento de cálculo mediante un ejemplo, y se comentan las posibles interpretaciones y análisis factibles de realizarse con este indicador. Finalmente, se discuten los principales requerimientos informativos que el cálculo adecuado y periódico de estos indicadores demanda.

The justification and the procedure of disability-adjusted life expectancy, an indicator that summarizes the health status of a population in a specially intuitive way, is presented. Coments are made on the interdependence between this indicator and the disability- adjusted life years (DALY), which are increasingly used at the national and international level to evaluate the burden of diseases and their sequelae, and the burden of the main risk factors propitiating these diseases and sequelae. The calculation procedure is illustrated by an example and the possible interpretations and analyses that can be made with this indicator are discussed. Finally, the main information requirements demanded by the adequate and periodical calculation of these indicators are dealt with..

The importance of surveillance in the control of influenza.

Surveillance of influenza has important practical uses for controlling the spread and the severity of epidemic episodes. The participation of sentinel practitioners directly involved in primary patient care is essential and can be promoted by active surveillance networks working in real time with a strong coordinating structure. The Groupes régionaux d'observation de la Grippe (grog) system, elaborated in France since 1984 on these principles, has allowed a short and middle term prevision of outbreaks and the isolation of a large number of influenza strains.