30 research outputs found
Status of water, sanitation and hygiene services for childbirth and newborn care in seven countries in East Asia and the Pacific
No full textBackground:
Water, sanitation and hygiene (WASH) services are critical to providing quality maternal and neonatal care in health facilities. This study aimed to investigate availability of WASH policies, standards, and services for childbirth and newborn care in hospitals in East Asia and the Pacific.
Methods:
Descriptive analysis of survey data and observations of water, sanitation and hygiene services in maternity and neonatal care rooms and of deliveries in 147 hospitals in Cambodia, Lao People’s Democratic Republic, Mongolia, Papua New Guinea, Philippines, Solomon Islands, and Viet Nam. The main outcome measures were availability of national policies and standards; availability of water, sanitation, and hygiene services in maternity rooms and neonatal care units; and practice of hygiene at childbirth.
Results:
Three of seven countries had national WASH policies and three had standards for health facilities. Seventy-seven percent of hospitals had a sink with water and soap or alcohol hand rub in delivery rooms, 78% in neonatal care rooms and 42% in postnatal care rooms. Only 44% of hospitals had clean sinks with water, soap and hand drying methods in the delivery room, 40% in neonatal care units and 10% in postnatal care rooms. Flush toilets were available in or next to delivery rooms in 60% and neonatal care units in 50% of 10 hospitals with data. Countries with WASH standards had a higher proportion of hospitals with water and hand hygiene services. Appropriate hygiene was practiced by health workers in 65% of 371 deliveries observed, and more likely in delivery rooms with a sink, water and soap.
Conclusions:
Coverage of WASH services for maternal and newborn care must be improved to reduce risks of maternal and newborn morbidity and mortality
Cognitive Software Complexity Analysis
No full textabstract: A well-defined Software Complexity Theory which captures the Cognitive means of algorithmic information comprehension is needed in the domain of cognitive informatics & computing. The existing complexity heuristics are vague and empirical. Industrial software is a combination of algorithms implemented. However, it would be wrong to conclude that algorithmic space and time complexity is software complexity. An algorithm with multiple lines of pseudocode might sometimes be simpler to understand that the one with fewer lines. So, it is crucial to determine the Algorithmic Understandability for an algorithm, in order to better understand Software Complexity. This work deals with understanding Software Complexity from a cognitive angle. Also, it is vital to compute the effect of reducing cognitive complexity. The work aims to prove three important statements. The first being, that, while algorithmic complexity is a part of software complexity, software complexity does not solely and entirely mean algorithmic Complexity. Second, the work intends to bring to light the importance of cognitive understandability of algorithms. Third, is about the impact, reducing Cognitive Complexity, would have on Software Design and Development.Dissertation/ThesisMasters Thesis Computer Science 201
Tilted cross-entropy (TCE): Promoting fairness in semantic segmentation
No full textTraditional empirical risk minimization (ERM) for semantic segmentation can disproportionately advantage or disadvantage certain target classes in favor of an (unfair but) improved overall performance. Inspired by the recently introduced tilted ERM (TERM), we propose tilted cross-entropy (TCE) loss and adapt it to the semantic segmentation set-ting to minimize performance disparity among target classes and promote fairness. Through quantitative and qualitative performance analyses, we demonstrate that the proposed Stochastic TCE for semantic segmentation can offer improved overall fairness by efficiently minimizing the performance disparity among the target classes of Cityscapes.Electrical Engineering, Mathematics and Computer SciencePattern Recognition and Bioinformatic
Male sex workers who sell sex to men also engage in anal intercourse with women : evidence from Mombasa, Kenya
No full textObjective: To investigate self-report of heterosexual anal intercourse among male sex workers who sell sex to men, and to identify the socio-demographic characteristics associated with practice of the behavior.
Design: Two cross-sectional surveys of male sex workers who sell sex to men in Mombasa, Kenya.
Methods: Male sex workers selling sex to men were invited to participate in surveys undertaken in 2006 and 2008. A structured questionnaire administered by trained interviewers was used to collect information on socio-demographic characteristics, sexual behaviors, HIV and STI knowledge, and health service usage. Data were analyzed through descriptive and inferential statistics. Bivariate logistic regression, after controlling for year of survey, was used to identify socio-demographic characteristics associated with heterosexual anal intercourse.
Results: From a sample of 867 male sex workers, 297 men had sex with a woman during the previous 30 days - of whom 45% did so with a female client and 86% with a non-paying female partner. Within these groups, 66% and 43% of male sex workers had anal intercourse with a female client and non-paying partner respectively. Factors associated with reporting recent heterosexual anal intercourse in bivariate logistic regression after controlling for year of survey participation were being Muslim, ever or currently married, living with wife only, living with a female partner only, living with more than one sexual partner, self-identifying as basha/king/bisexual, having one's own children, and lower education.
Conclusions: We found unexpectedly high levels of self-reported anal sex with women by male sex workers, including selling sex to female clients as well as with their own partners. Further investigation among women in Mombasa is needed to understand heterosexual anal sex practices, and how HIV programming may respond
Recent (past 30 days) vaginal and/or oral sex and AI outcomes by selected socio-demographic characteristics in bivariate logistic regression after controlling for survey year, among male sex workers who sell sex to men in Mombasa.
No full text#<p>N = numerator, D = denominator, IQR = inter-quartile range.</p>†<p>Odds ratios calculated after controlling for year of survey in bivariate logistic regression.</p><p>°Ratio measures odds of recent vaginal/oral sex or recent AI for those whose age is above the median of 25 years.</p>*<p><i>P</i><0.05,</p>**<p><i>P</i><0.01,</p>***<p><i>P</i><0.001.</p
Socio-demographic characteristics and reported bisexual behaviours of male sex workers who sell sex to men in Mombasa.
No full text#<p>N = numerator, D = denominator, IQR = inter-quartile range.</p>*<p>Variables for which the P-value was statistically significant (<i>P</i><0.05) when testing for differences between values obtained in the 2006 and 2008 surveys. Wilcoxon rank-sum test used for median values, chi-squared tests for categorical variables.</p
Big data in global health: improving health in low- and middle-income countries
No full textOver the last decade, a massive increase in data collection and analysis has occurred in many fields. In the health sector, however, there has been relatively little progress in data analysis and application despite a rapid rise in data production. Given adequate governance, improvements in the quality, quantity, storage and analysis of health data could lead to substantial improvements in many health outcomes. In low- and middle-income countries in particular, the creation of an information feedback mechanism can move health-care delivery towards results-based practice and improve the effective use of scarce resources. We review the evolving definition of big data and the possible advantages of – and problems in – using such data to improve health-care delivery in low- and middle-income countries. The collection of big data as mobile-phone based services improve may mean that development phases required elsewhere can be skipped. However, poor infrastructure may prevent interoperability and the safe use of patient data. An appropriate governance framework must be developed and enforced to protect individuals and ensure that health-care delivery is tailored to the characteristics and values of the target communities
