Compromise optimum allocation in neutrosophic multi-character survey under stratified random sampling using neutrosophic fuzzy programming.

Survey sampling has wide range of applications in social and scientific investigation to draw inference about the unknown parameter of interest. In complex surveys, the sample information about the study variable cannot be expressed by a precise number under uncertain environment due fuzziness and indeterminacy. Therefore, this information is expressed by neutrosophic numbers rather than the classical numbers. The neutrosophic statistics, which is generalization of classical statistics, deals with the neutrosophic data that has some degree of indeterminacy and fuzziness. In this study, we investigate the compromise optimum allocation problem for estimating the population means of the neutrosophic study variables in a multi-character stratified random sampling under uncertain per unit measurement cost. We proposed the intuitionistic fuzzy cost function, modeling the fuzzy uncertainty in stratum per unit measurement cost. The compromise optimum allocation problem is formulated as a multi-objective intuitionistic fuzzy optimization problem. The solution methodology is suggested using neutrosophic fuzzy programming and intuitionistic fuzzy programming approaches. A numerical study includes the means estimation of atmospheric variables is presented to explore the real-life application, explain the mathematical formulation, and efficiency comparison with some existing methods. The results show that the suggested methods produce more precise estimates with less utilization of survey resources as compared to some existing methods. The Python is used for statistical analysis, graphical designing and numerical optimization problems are solved using GAMS.

Improved estimation of population variance in stratified successive sampling using calibrated weights under non-response.

This paper introduces a new method to estimate the population variance of a study variable in stratified successive sampling over two occasions, while accounting for random non-response. The method uses a logarithmic type estimator and leverages information from a highly positively correlated auxiliary variable. The paper also presents calibrated weights for the new estimator and examines its properties through numerical and simulation studies. The results indicate that the suggested estimator is more effective than the standard estimator for estimating the population variance.

Filling the agronomic data gap through a minimum data collection approach.

Context: Agronomic data such as applied inputs, management practices, and crop yields are needed for assessing productivity, nutrient balances, resource use efficiency, as well as other aspects of environmental and economic performance of cropping systems. In many instances, however, these data are only available at a coarse level of aggregation or simply do not exist. Objectives: Here we developed an approach that identifies sites for agronomic data collection for a given crop and country, seeking a balance between minimizing data collection efforts and proper representation of the main crop producing areas. Methods: The developed approach followed a stratified sampling method based on a spatial framework that delineates major climate zones and crop area distribution maps, which guides selection of sampling areas (SA) until half of the national harvested area is covered. We provided proof of concept about the robustness of the approach using three rich databases including data on fertilizer application rates for maize, wheat, and soybean in Argentina, soybean in the USA, and maize in Kenya, which were collected via local experts (Argentina) and field surveys (USA and Kenya). For validation purposes, fertilizer rates per crop and nutrient derived at (sub-) national level following our approach were compared against those derived using all data collected from the whole country. Results: Application of the approach in Argentina, USA, and Kenya resulted in selection of 12, 28, and 10 SAs, respectively. For each SA, three experts or 20 fields were sufficient to give a robust estimate of average fertilizer rates applied by farmers. Average rates at national level derived from our approach compared well with those derived using the whole database ( ± 10 kg N, ± 2 kg P, ± 1 kg S, and ± 5 kg K per ha) requiring less than one third of the observations. Conclusions: The developed minimum crop data collection approach can fill the agronomic data gaps in a cost-effective way for major crop systems both in large- and small-scale systems. Significance: The proposed approach is generic enough to be applied to any crop-country combination to guide collection of key agricultural data at national and subnational levels with modest investment especially for countries that do not currently collect data.

Sequestration of imaging studies in MIDRC: stratified sampling to balance demographic characteristics of patients in a multi-institutional data commons.

Purpose: The Medical Imaging and Data Resource Center (MIDRC) is a multi-institutional effort to accelerate medical imaging machine intelligence research and create a publicly available image repository/commons as well as a sequestered commons for performance evaluation and benchmarking of algorithms. After de-identification, approximately 80% of the medical images and associated metadata become part of the open commons and 20% are sequestered from the open commons. To ensure that both commons are representative of the population available, we introduced a stratified sampling method to balance the demographic characteristics across the two datasets. Approach: Our method uses multi-dimensional stratified sampling where several demographic variables of interest are sequentially used to separate the data into individual strata, each representing a unique combination of variables. Within each resulting stratum, patients are assigned to the open or sequestered commons. This algorithm was used on an example dataset containing 5000 patients using the variables of race, age, sex at birth, ethnicity, COVID-19 status, and image modality and compared resulting demographic distributions to naïve random sampling of the dataset over 2000 independent trials. Results: Resulting prevalence of each demographic variable matched the prevalence from the input dataset within one standard deviation. Mann-Whitney U test results supported the hypothesis that sequestration by stratified sampling provided more balanced subsets than naïve randomization, except for demographic subcategories with very low prevalence. Conclusions: The developed multi-dimensional stratified sampling algorithm can partition a large dataset while maintaining balance across several variables, superior to the balance achieved from naïve randomization.

Polygon Simplification for the Efficient Approximate Analytics of Georeferenced Big Data.

The unprecedented availability of sensor networks and GPS-enabled devices has caused the accumulation of voluminous georeferenced data streams. These data streams offer an opportunity to derive valuable insights and facilitate decision making for urban planning. However, processing and managing such data is challenging, given the size and multidimensionality of these data. Therefore, there is a growing interest in spatial approximate query processing depending on stratified-like sampling methods. However, in these solutions, as the number of strata increases, response time grows, thus counteracting the benefits of sampling. In this paper, we originally show the design and realization of a novel online geospatial approximate processing solution called GeoRAP. GeoRAP employs a front-stage filter based on the Ramer-Douglas-Peucker line simplification algorithm to reduce the size of study area coverage; thereafter, it employs a spatial stratified-like sampling method that minimizes the number of strata, thus increasing throughput and minimizing response time, while keeping the accuracy loss in check. Our method is applicable for various online and batch geospatial processing workloads, including complex geo-statistics, aggregation queries, and the generation of region-based aggregate geo-maps such as choropleth maps and heatmaps. We have extensively tested the performance of our prototyped solution with real-world big spatial data, and this paper shows that GeoRAP can outperform state-of-the-art baselines by an order of magnitude in terms of throughput while statistically obtaining results with good accuracy.

Unmatched spatially stratified controls: A simulation study examining efficiency and precision using spatially-diverse controls and generalized additive models.

Unmatched spatially stratified random sampling (SSRS) of non-cases selects geographically balanced controls by dividing the study area into spatial strata and randomly selecting controls from all non-cases within each stratum. The performance of SSRS control selection was evaluated in a case study spatial analysis of preterm birth in Massachusetts. In a simulation study, we fit generalized additive models using controls selected by SSRS or simple random sample (SRS) designs. We compared mean squared error (MSE), bias, relative efficiency (RE), and statistically significant map results to the model results with all non-cases. SSRS designs had lower average MSE (0.0042-0.0044) and higher RE (77-80%) compared to SRS designs (MSE: 0.0072-0.0073; RE across designs: 71%). SSRS map results were more consistent across simulations, reliably identifying statistically significant areas. SSRS designs improved efficiency by selecting controls that are geographically distributed, particularly from low population density areas, and may be more appropriate for spatial analyses.

scHi-CSim: a flexible simulator that generates high-fidelity single-cell Hi-C data for benchmarking.

Single-cell Hi-C technology provides an unprecedented opportunity to reveal chromatin structure in individual cells. However, high sequencing cost impedes the generation of biological Hi-C data with high sequencing depths and multiple replicates for downstream analysis. Here, we developed a single-cell Hi-C simulator (scHi-CSim) that generates high-fidelity data for benchmarking. scHi-CSim merges neighboring cells to overcome the sparseness of data, samples interactions in distance-stratified chromosomes to maintain the heterogeneity of single cells, and estimates the empirical distribution of restriction fragments to generate simulated data. We demonstrated that scHi-CSim can generate high-fidelity data by comparing the performance of single-cell clustering and detection of chromosomal high-order structures with raw data. Furthermore, scHi-CSim is flexible to change sequencing depth and the number of simulated replicates. We showed that increasing sequencing depth could improve the accuracy of detecting topologically associating domains. We also used scHi-CSim to generate a series of simulated datasets with different sequencing depths to benchmark scHi-C clustering methods.

Efficient Evaluation of Prediction Rules in Semi-Supervised Settings under Stratified Sampling.

In many contemporary applications, large amounts of unlabeled data are readily available while labeled examples are limited. There has been substantial interest in semi-supervised learning (SSL) which aims to leverage unlabeled data to improve estimation or prediction. However, current SSL literature focuses primarily on settings where labeled data is selected uniformly at random from the population of interest. Stratified sampling, while posing additional analytical challenges, is highly applicable to many real world problems. Moreover, no SSL methods currently exist for estimating the prediction performance of a fitted model when the labeled data is not selected uniformly at random. In this paper, we propose a two-step SSL procedure for evaluating a prediction rule derived from a working binary regression model based on the Brier score and overall misclassification rate under stratified sampling. In step I, we impute the missing labels via weighted regression with nonlinear basis functions to account for stratified sampling and to improve efficiency. In step II, we augment the initial imputations to ensure the consistency of the resulting estimators regardless of the specification of the prediction model or the imputation model. The final estimator is then obtained with the augmented imputations. We provide asymptotic theory and numerical studies illustrating that our proposals outperform their supervised counterparts in terms of efficiency gain. Our methods are motivated by electronic health record (EHR) research and validated with a real data analysis of an EHR-based study of diabetic neuropathy.

Germplasm variability-assisted near infrared reflectance spectroscopy chemometrics to develop multi-trait robust prediction models in rice.

Rice is a major staple food across the world in which wide variations in nutrient composition are reported. Rice improvement programs need germplasm accessions with extreme values for any nutritional trait. Near infrared reflectance spectroscopy (NIRS) uses electromagnetic radiations in the NIR region to rapidly measure the biochemical composition of food and agricultural products. NIRS prediction models provide a rapid assessment tool but their applicability is limited by the sample diversity, used for developing them. NIRS spectral variability was used to select a diverse sample set of 180 accessions, and reference data were generated using association of analytical chemists and standard methods. Different spectral pre-processing (up to fourth-order derivatization), scatter corrections (SNV-DT, MSC), and regression methods (partial least square, modified partial least square, and principle component regression) were employed for each trait. Best-fit models for total protein, starch, amylose, dietary fiber, and oil content were selected based on high RSQ, RPD with low SEP(C) in external validation. All the prediction models had ratio of prediction to deviation (RPD) > 2 amongst which the best models were obtained for dietary fiber and protein with R 2 = 0.945 and 0.917, SEP(C) = 0.069 and 0.329, and RPD = 3.62 and 3.46. A paired sample t-test at a 95% confidence interval was performed to ensure that the difference in predicted and laboratory values was non-significant.

Clinical practice of Helicobacter pylori infection management by gastroenterologists in secondary and tertiary hospitals: A stratified sampling cross-sectional survey.

OBJECTIVE: To investigate the management of Helicobacter pylori (H. pylori) infection by gastroenterologists from secondary and tertiary hospitals in Shandong Province, China, where there is a high prevalence of H. pylori infection. METHODS: A questionnaire-based, stratified sampling survey was conducted from June 1 to August 30, 2021. The ratio of secondary to tertiary hospitals was set at 2:1. An electronic questionnaire was sent to the gastroenterologists via the WeChat platform. RESULTS: A total of 89.09% (1053/1182) gastroenterologists were included. Overall, 34.19% and 60.59% of gastroenterologists recommended screening for and treating H. pylori infection in patients without any competing factors. The most preferred testing method in secondary and tertiary hospitals was the 13 C-urea breath test (53.92% and 80.48%), but the reexamination rate of results close to the cut-off value was low (55.10% and 59.48%). Gastroenterologists preferred bismuth-containing quadruple therapy (secondary and tertiary hospitals: 96.67% and 98.53%), but the antibiotic combination prescribed for patients with penicillin allergy was suboptimal in secondary hospitals. The overall post-treatment follow-up rate was 64.58%, and gastroenterologists in secondary hospitals were more proactive than those in tertiary hospitals (69.41% vs 60.04%, P = 0.001). Less than 80% of gastroenterologists emphasized the importance of post-treatment reexamination to their patients. Only a minority of gastroenterologists in secondary and tertiary hospitals (30.79% and 34.36%) achieved acceptable eradication rates (exceeding 80%). CONCLUSIONS: Deficiencies exist in gastroenterologists from secondary and tertiary hospitals, and the H. pylori eradication rate is relatively low. Training programs for gastroenterologists are warranted to strengthen their comprehension of guidelines.

Survey design and analysis considerations when utilizing misclassified sampling strata.

BACKGROUND: A large multi-center survey was conducted to understand patients' perspectives on biobank study participation with particular focus on racial and ethnic minorities. In order to enrich the study sample with racial and ethnic minorities, disproportionate stratified sampling was implemented with strata defined by electronic health records (EHR) that are known to be inaccurate. We investigate the effect of sampling strata misclassification in complex survey design. METHODS: Under non-differential and differential misclassification in the sampling strata, we compare the validity and precision of three simple and common analysis approaches for settings in which the primary exposure is used to define the sampling strata. We also compare the precision gains/losses observed from using a disproportionate stratified sampling scheme compared to using a simple random sample under varying degrees of strata misclassification. RESULTS: Disproportionate stratified sampling can result in more efficient parameter estimates of the rare subgroups (race/ethnic minorities) in the sampling strata compared to simple random sampling. When sampling strata misclassification is non-differential with respect to the outcome, a design-agnostic analysis was preferred over model-based and design-based analyses. All methods yielded unbiased parameter estimates but standard error estimates were lowest from the design-agnostic analysis. However, when misclassification is differential, only the design-based method produced valid parameter estimates of the variables included in the sampling strata. CONCLUSIONS: In complex survey design, when the interest is in making inference on rare subgroups, we recommend implementing disproportionate stratified sampling over simple random sampling even if the sampling strata are misclassified. If the misclassification is non-differential, we recommend a design-agnostic analysis. However, if the misclassification is differential, we recommend using design-based analyses.

[Prevalence of frailty and its related factors in community-dwelling middle-aged and elderly adults in Settsu and Hannan cities in Osaka prefecture].

Objectives　The purpose of this study was to examine the prevalence of frailty and its associated factors in community-dwelling middle-aged and elderly adults in Settsu and Hannan cities, which are located in the north and south of Osaka prefecture, respectively.Methods　We conducted a mailed, self-administered, questionnaire survey of individuals aged 40 years and older in Settsu city in 2019 and Hannan city in 2020. There are 10 primary school districts in Settsu city and 8 districts in Hannan city, from each of which 1,000 people were selected according to the age and sex structures of the districts. We included 5,134 individuals from Settsu city and 3,939 individuals from Hannan city. We defined frailty using self-reported questionnaires, the Kihon Checklist (KCL), and Simple Frailty Index (SFI). Multivariate logistic regression analysis was performed for each city to examine the association of frailty with age, sex, body mass index (BMI), family structure, subjective health, economic status, subjective physical fitness, sleeping status, smoking history, alcohol use, meal frequency and awareness of the word "frailty."Results　The average age (standard deviation) of participants was 62.7 (12.5) years in Settsu city and 63.4 (12.2) years in Hannan city. The prevalence of frailty by KCL was 18.7% and 17.9% for participants in their 40s, 18.2% and 14.6% for those in their 50s, 17.0% and 15.7% for those in their 60s, 25.4% and 20.8% for those in their 70s, 39.7% and 36.1% for those 80 years and older from Settsu and Hannan cities, respectively. Using SFI, the prevalence of frailty was 16.2% and 13.5% for participants in their 40s, 15.0% and 11.9% for those in their 50s, 12.5% and 10.0% for those in their 60s, 14.6% and 12.3% for those in their 70s, and 24.7% and 22.3% for those aged 80 years and older in Settsu and Hannan cities, respectively. Significant common independent variables associated with frailty as defined using the KCL and SFI in Settsu and Hannan cities were age, subjective health, economic status, subjective physical fitness, sleeping status, and awareness of the word "frailty."Conclusion　This study found some participants to be frail as early as their 40s or 50s. Thus, efforts must be made to prevent frailty in working-age populations, including those aged 40 years and older. Six factors were associated with frailty. Longitudinal or interventional studies are required to examine their causal relationships and public health significance.

Sampling plan and methodological aspects: a household healthcare survey in Piauí / Plano de amostragem e aspectos metodológicos: inquérito de saúde domiciliar no Piauí

ABSTRACT OBJECTIVE To describe the methodological aspects of the Piauí home healthcare survey (ISAD-PI) and assess the relation between sampling plan, precision, and design effects, assuming that population health surveys are relevant instruments for health monitoring. METHODS ISAD-PI was a population-based cross-sectional study that analyzed the living conditions and health status of the population residing in urban areas in the municipalities of Teresina and Picos, in Piauí. Sampling was carried out by conglomerates in two stages: Primary Sampling Units and households. To calculate the sample size, we considered the stratification of the population in both cities, according to the age of the individuals. We evaluated the "non-response" rate (NRR) and estimated the proportions according to sex and age, as well as the prevalence of social determinants of health in order to assess the compliance of the sampling plan. Analyses related to the precision according to the coefficient of proportion variation of the standard error (Cv-pˆ) and the design effect (deff). Cv-pˆ less than 20% and deff less than 1.5 were considered adequate. The total NRR of households was 38.2% in Teresina and 38.3% in Picos. We carried out twenty-four proportion estimates in relation to age and sex and 48 prevalence of social and health determinants estimates, totaling 72 estimates. Among them, 71 had Cv-pˆ less than 20% and 61 had deff less than or equal to 1.5. CONCLUSION Data generated from the ISAD-PI may contribute to the assessment of health and morbidity conditions in the population. Furthermore, methodological aspects employed in this research may serve as a basis for studies carried out in other cities in Brazil.

RESUMO OBJETIVO Descrever os aspectos metodológicos do Inquérito de Saúde Domiciliar no Piauí (ISAD-PI), bem como avaliar a conformidade do plano amostral em relação à precisão e aos efeitos do desenho, dado que os inquéritos populacionais de saúde constituem instrumentos importantes para o monitoramento da situação de saúde da população. MÉTODOS O ISAD-PI foi um estudo de base populacional, transversal, que analisou as condições de vida e situação de saúde da população residente nas áreas urbanas dos municípios de Teresina e Picos, no Piauí. A amostragem foi realizada por conglomerados, em dois estágios: Unidades Primárias de Amostragem e domicílios. Para o cálculo do tamanho da amostra, considerou-se a estratificação da população de ambas as cidades, de acordo com a idade dos indivíduos, para ambos os sexos. Para avaliação da conformidade do plano amostral, foi avaliada a taxa de "não-resposta" (TNR) e, além disso, as estimativas de proporções segundo sexo e idade, bem como as prevalências de determinantes sociais de saúde, que foram analisadas em relação à precisão por meio do coeficiente de variação da proporção do erro padrão (Cv-pˆ) e do efeito do delineamento (deff). Foram considerados adequados Cv-pˆ menores que 20%, e deff menores que 1,5. A TNR-Total dos domicílios foi de 38,2% em Teresina e de 38,3% em Picos. Foram realizadas 24 estimativas de proporção em relação à idade e ao sexo e 48 estimativas de prevalência de determinantes sociais e de saúde, totalizando 72 estimativas, das quais 71 apresentaram Cv-pˆ menor que 20% e 61 apresentaram deff menor ou igual a 1,5. CONCLUSÃO Dados gerados a partir do ISAD-PI poderão contribuir para a avaliação das condições de saúde e morbidade na população. Ademais, aspectos metodológicos empregados nesta pesquisa poderão servir de base para estudos realizados em outras cidades do Brasil.

Sampling plan and methodological aspects: a household healthcare survey in Piauí / Plano de amostragem e aspectos metodológicos: inquérito de saúde domiciliar no Piauí

ABSTRACT OBJECTIVE To describe the methodological aspects of the Piauí home healthcare survey (ISAD-PI) and assess the relation between sampling plan, precision, and design effects, assuming that population health surveys are relevant instruments for health monitoring. METHODS ISAD-PI was a population-based cross-sectional study that analyzed the living conditions and health status of the population residing in urban areas in the municipalities of Teresina and Picos, in Piauí. Sampling was carried out by conglomerates in two stages: Primary Sampling Units and households. To calculate the sample size, we considered the stratification of the population in both cities, according to the age of the individuals. We evaluated the "non-response" rate (NRR) and estimated the proportions according to sex and age, as well as the prevalence of social determinants of health in order to assess the compliance of the sampling plan. Analyses related to the precision according to the coefficient of proportion variation of the standard error (Cv-pˆ) and the design effect (deff). Cv-pˆ less than 20% and deff less than 1.5 were considered adequate. The total NRR of households was 38.2% in Teresina and 38.3% in Picos. We carried out twenty-four proportion estimates in relation to age and sex and 48 prevalence of social and health determinants estimates, totaling 72 estimates. Among them, 71 had Cv-pˆ less than 20% and 61 had deff less than or equal to 1.5. CONCLUSION Data generated from the ISAD-PI may contribute to the assessment of health and morbidity conditions in the population. Furthermore, methodological aspects employed in this research may serve as a basis for studies carried out in other cities in Brazil.

RESUMO OBJETIVO Descrever os aspectos metodológicos do Inquérito de Saúde Domiciliar no Piauí (ISAD-PI), bem como avaliar a conformidade do plano amostral em relação à precisão e aos efeitos do desenho, dado que os inquéritos populacionais de saúde constituem instrumentos importantes para o monitoramento da situação de saúde da população. MÉTODOS O ISAD-PI foi um estudo de base populacional, transversal, que analisou as condições de vida e situação de saúde da população residente nas áreas urbanas dos municípios de Teresina e Picos, no Piauí. A amostragem foi realizada por conglomerados, em dois estágios: Unidades Primárias de Amostragem e domicílios. Para o cálculo do tamanho da amostra, considerou-se a estratificação da população de ambas as cidades, de acordo com a idade dos indivíduos, para ambos os sexos. Para avaliação da conformidade do plano amostral, foi avaliada a taxa de "não-resposta" (TNR) e, além disso, as estimativas de proporções segundo sexo e idade, bem como as prevalências de determinantes sociais de saúde, que foram analisadas em relação à precisão por meio do coeficiente de variação da proporção do erro padrão (Cv-pˆ) e do efeito do delineamento (deff). Foram considerados adequados Cv-pˆ menores que 20%, e deff menores que 1,5. A TNR-Total dos domicílios foi de 38,2% em Teresina e de 38,3% em Picos. Foram realizadas 24 estimativas de proporção em relação à idade e ao sexo e 48 estimativas de prevalência de determinantes sociais e de saúde, totalizando 72 estimativas, das quais 71 apresentaram Cv-pˆ menor que 20% e 61 apresentaram deff menor ou igual a 1,5. CONCLUSÃO Dados gerados a partir do ISAD-PI poderão contribuir para a avaliação das condições de saúde e morbidade na população. Ademais, aspectos metodológicos empregados nesta pesquisa poderão servir de base para estudos realizados em outras cidades do Brasil.

The conditions for women's autonomy: Statistical data for Valle del Cauca.

In this article, we describe the data set on theconditions for women's autonomy in the municipalities of Cali, Buenaventura, Yumbo, and Jamundí (Colombia). The database was developed by the Observatoriopara la Equidad de las Mujeres (OEM), an entity resulting from an alliancebetween Universidad Icesi and Fundación WWB Colombia. The OEM's purpose is toconstruct measurements that make it possible to account for women's autonomy,based on three main dimensions: physical autonomy (associated with aspects ofpersonal and family life), economic and financial autonomy (the type of work,income, decision-making with respect to these aspects, entrepreneurship orbusiness units, among others), and leadership and public participation(electoral practices, type of participation, relation to institutions, etc.),while fundamentally, considering women's capacity to make decisions onthese  aspects, based on both theirperception and their actions. As well as helping to overcome the limitations ofexisting information, this primary data collection is aimed at generatingvalid, reliable and high-quality inputs to formulate local and national publicpolicies to improve the living conditions of women in Colombia's Pacificregion. The survey, designed and applied by the OEM, was first implemented inOctober and November 2018 through multi-stage probability sampling. The samplesize was 1,507 women in the four mentioned municipalities.

Approximation rates for neural networks with general activation functions.

We prove some new results concerning the approximation rate of neural networks with general activation functions. Our first result concerns the rate of approximation of a two layer neural network with a polynomially-decaying non-sigmoidal activation function. We extend the dimension independent approximation rates previously obtained to this new class of activation functions. Our second result gives a weaker, but still dimension independent, approximation rate for a larger class of activation functions, removing the polynomial decay assumption. This result applies to any bounded, integrable activation function. Finally, we show that a stratified sampling approach can be used to improve the approximation rate for polynomially decaying activation functions under mild additional assumptions.

Methodological design for the macro-location of a micropollutants monitoring network in tropical rivers: a case study in Cauca River.

Establishing scientifically the macro-location of a micropollutants monitoring network in tropical Andean rivers is a complex process, because information gathering is restricted by high-cost of analysis and limited availability of analytical techniques, which lead to inadequate sampling strategies that hinder the representativeness of samples. Thus, this work proposes a methodology for determining the number of representative sampling sections in a micropollutant monitoring network to characterise the ecological risk in tropical Andean torrential rivers. The proposed methodology consists of four stages: identification of the potential sampling units by Spline interpolation; calculation of the number of representative sections for a stratified sampling with an acceptable level of confidence and error; spatial allocation of the potential sampling units into sections by hierarchical cluster analysis; and representation of the spatial distribution of the sampling sections through a geographic information system (GIS). The proposed methodology is dynamic, and therefore, it can be revisited as more data are obtained in the subsequent years; it has the possibility of being applied to other inter-Andean valley rivers that interact with the tropical Andean sloppy mountains and serves as a tool for decision making by environmental authorities regarding the optimisation of the existing monitoring networks in terms of micropollutants to promote sustainable management of water resources. The proposed methodology is applied in the Upper Cauca River Basin (UCRB), which is located in southwest Colombia, South America.

Common Comorbidities of Stroke in the Canadian Population.

OBJECTIVES: Although comorbidity increases the health care and community support needs for patients, and the burden for the health care system, there are few population-based studies on comorbidity in patients with stroke. This study aims to evaluate the occurrence of important comorbidities among stroke patients in the Canadian population. METHODS: Data from the population-based 2011-2012 Canadian Community Health Survey containing responses from 124,929 participants covering about 98% of the Canadian population when weighted were examined and analyzed by means of logistic regression models. RESULTS: There was a statistically significant association between stroke history and multiple comorbid risk factors. Stroke prevalence increased in individuals with heart disease (odds ratio (OR): 3.80, 95% confidence interval (CI): 3.77-3.84), hypertension (OR: 1.97, 95% CI: 1.95-1.99), diabetes (OR: 1.74, 95% CI: 1.72-1.75), mood disorder (OR: 2.14, 95% CI: 2.12-2.17), and chronic obstructive pulmonary disease (COPD) (OR: 1.46, 95% CI: 1.44-1.48) compared to others without the condition. Of 2067 participants with stroke, 1680 (81.3%) had one or more comorbid conditions (heart disease, hypertension, diabetes, mood disorder, or COPD) that coexist with stroke and 48% had two or more. Comorbidity increased with age, and two-thirds of stroke patients with comorbid medical conditions were 60 years of age or older. CONCLUSION: This population-based study provides evidence of comorbidity between stroke and other conditions that include heart disease, hypertension, diabetes, mood disorder, and COPD. Canadian individuals with stroke have a high burden of comorbidity. Health care systems need to recognize and respond to the strong association of comorbidity and stroke occurrence. This key factor should be considered when allocating resources.

Analyzing the distribution of rabies clinics and achievements of standardized rabies clinics implementation in mainland China.

BACKGROUND: For rabies prevention and treatment, the Chinese government has been establishing standardized rabies clinics since 2016. This study aimed to investigate the distribution of rabies clinics and the achievements of newly-implemented standardized rabies clinics in mainland China, for the purpose of providing further rabies control strategies. METHODS: The number of rabies clinics, including per million inhabitants in each region, was determined. We sampled 1200 clinics from 8 provinces by multi-stage stratified sampling, and a questionnaire survey was carried out to record each clinic's achievements. Data collected from 1185 questionnaires were analyzed. RESULTS: We found that rabies clinics were mostly located in the southwest, central, and eastern regions of China; these accounted for 67.1% of all clinics. The eastern and south regions showed the lowest number of rabies clinics per million inhabitants (0.15 and 0.12, respectively). The total standard-reaching rate of rabies clinics in mainland China was only 11.0%, with significant differences in the rate among regions (X2 = 33.004, p <  0.001). Specifically, the qualified rates of supporting facilities and functional areas were 13.9% (X2 = 34.003, p <  0.001) and 56.1% (X2 = 9.943, p = 0.019), respectively. Vaccines with 2 different substrates and professional flushing equipment were provided by 40.5% (X2 = 27.935, p = 0.001) and 37.7% (X2 = 54.922, p = 0.001) of clinics, respectively. CONCLUSION: Regional differences do exist in the distribution of rabies clinics in mainland China, with relative low number per million population in south and eastern China. There are few standardized rabies clinics in mainland China. Efforts are needed to establish supporting facilities, especially for wound treatment and vaccination. Future research should focus on the improvement of rabies clinics standardization.

Estratificación de riesgo de tuberculosis pulmonar en consejos populares del municipio Abreus. Cienfuegos, 2015 / Pulmonary tuberculosis risk stratification in communities of the Abreus municipality. Cienfuegos, 2015

RESUMEN Fundamento: La tuberculosis es un tema de investigación prioritario en Cuba, dada la necesidad de un fortalecimiento de la capacidad de respuesta para su eliminación como problema de salud. Objetivo: estratificar el riesgo de tuberculosis pulmonar en consejos populares del municipio Abreus. Métodos: se realizó un estudio descriptivo, en los siete consejos populares del municipio Abreus, provincia Cienfuegos, durante el año 2015. La información se obtuvo de los departamentos de estadística de las áreas de salud y la Unidad Municipal de Higiene y Epidemiología. Fue utilizado el método de distribución de riesgo absoluto. El criterio para la estratificación que se tuvo en cuenta para definir los estratos de alto, mediano y bajo riesgo, fue la media de la prevalencia de los factores de riesgo según dispensarización del año 2015. Los factores de riesgo analizados fueron: población mayor de 60 años, tasa de contactos de pacientes con tuberculosis pulmonar, prevalencia de virus de inmunodeficiencia adquirida/sida, alcohólicos, casos sociales, fumadores, y diabéticos. Se utilizó el programa MapInfo 7.5. Resultados: la prevalencia del hábito de fumar fue elevada, con 5 consejos populares ubicados en el estrato de mediano riesgo, uno en el estrato de bajo riesgo, y otro (Cieneguitas) en el de alto riesgo. Los consejos populares Abreus, Charca, Cieneguita y Yaguaramas presentaron el mayor porcentaje de factores ubicados en el estrato de alto riesgo. Conclusión: Las características clínico epidemiológicas de los casos notificados con tuberculosis pulmonar en el decenio 2006-2015, en Abreus, muestran evidencias del riesgo potencial de infección tuberculosa en la comunidad.

ABSTRACT Foundation: Tuberculosis is a priority research topic in Cuba, given the need to strengthen the response capacity for its elimination as a health problem. Objective: to stratify the risk of pulmonary tuberculosis in communities of the Abreus municipality. Methods: a descriptive study was carried out in the seven communities of the Abreus municipality, Cienfuegos province, during 2015. The information was obtained from the statistical departments of the health areas and the Municipal Hygiene and Epidemiology Unit. The absolute risk distribution method was used. The criterion for the stratification taken into account to define the high, medium and low risk strata was the average prevalence of risk factors according to the identified patients in 2015. The risk analyzed factors were: population over 60 years, contact rate of patients with pulmonary tuberculosis, prevalence of acquired immunodeficiency virus/AIDS, alcoholics, social hardship cases, smokers, and diabetics. The MapInfo 7.5 program was used. Results: the prevalence of smoking was high, with 5 communities located in the medium riskstratum, one in the low risk stratum, and another (Cieneguitas) in the high risk stratum. Communities of Abreus, Charca, Cieneguita and Yaguaramas presented the highest percentage of factors located in the high risk stratum. Conclusion: Clinical epidemiological characteristics of the cases reported with pulmonary tuberculosis in the decade 2006-2015, in Abreus, show evidence of the potential risk of tuberculosis infection in the community.