This project is maintained by aprotiva
Andrew Protiva
02-24-20
Tajikistan is a low-income country as deemed by the world bank. This is the lowest group of income. Similarly, they have many issues in other places, perhaps equality, education, health, hunger, or poverty. This paper will focus on studies related to the health services in Tajikistan. Lack of proper healthcare and health services is detrimental to development. Lack of proper health obviously leads to a higher death rate, but what most statistics do not include is the foregone work, progress, labor, and ideas that individuals would have otherwise. If a person is preoccupied with maintaining their health, or the health of others, it prevents them from engaging in something else. Suffering in health is a vicious cycle that prevents natural human development. Because of this, health is essential to improve in order to increase human development. It is important to recognize that problem is unique and different. The main cause of premature death in Tajikistan in 2017 is lower respiratory infection. It has increased by 10% since 2007. Uzbekistan, a nearby country, has lower respiratory infection as its second most cause of premature death, yet the rate in Uzbekistan has decreased by about 30% since 2007. Why has this rate not decreased in Tajikistan? Data science and data analysis in Tajikistan may be able to provide significant evidence. (“Tajikistan.” Institute for Health Metrics and Evaluation, 20 Sept. 2017, www.healthdata.org/tajikistan., “Uzbekistan.” Institute for Health Metrics and Evaluation, 20 Sept. 2017, www.healthdata.org/Uzbekistan.)
Heart disease is the leading cause of death in Tajikistan. Early detection and management of hypertension can reduce this. Despite increasing efforts to reduce hypertension since 2010, there a large gap in treatment now. They used survey data from routine health information systems, household surveys, and a World Bank funded impact evaluation to attempt to collect needed data. Using the information, they created fit-for-purpose solutions to the barriers they uncovered. Detection of hypertension is a necessary step toward proper health management in Tajikistan. Low priority was given hypertension screening, and there was little effort to reach rural communities. To combat this, they implemented the solutions to mobilize faith-based groups, scaling up screening through May Measurement Month, leveraging service user interactions with pharmacy, introducing job aids for providers, and task-shifting to increase provider supply. These solutions will provide benefit towards the third sustainable development goal, increasing good health and well-being. If Sen were to describe the increase of human development, he would say that these solutions increased the social opportunities. By increasing the freedom of social opportunities, individuals may turn their minds and resources away from health toward other objectives which will benefit the development of the country as a whole. The data used is compiled from regional sources and statistically analyzed, though no geospatial data is used. The human development process includes many different factors. When health is increased, infrastructure, communication, logistics and spatial designations, and more are increase. By increasing data about health, other human development process will increase. The overall questions that this article attempts to answer is how to decrease hypertension in Tajikistan.
This article seeks to determine the productiveness and sustainability of economic development. Many scholars agree that specific economic and social characteristics are relatively more important than others when determining competitiveness. There is a lack of standard methodology to determine these characteristics. In order to determine these characteristics, this paper uses institutional synergy and system approaches, using comparative analysis. Based on the results of this mapper, Mashokhida believes that the “Pattern” methods are most effective at determining the productiveness of Tajikistan. Determining proper indicators for the analysis of sustainability of economic development, then assessing the value of each indicator and its weight. The value and weight of each indicator is calculated using multidimensional comparative analysis, which is based on Euclidian distances method. The average is determined by category, and the score can be interpreted. This methodology was used to determine the public and private values of each indicator. The comparison reveals a relative assessment of regional sustainability. This article mainly focuses on Sens freedom of economic facilities. Sustainability in development lies within the institutions, thus sustainability is dependent on the institutions. The methods procured in this paper can relate and be used for many of the sustainable development goals. Most specifically applicable would be industry, innovation, and infrastructure, affordable and clean energy, clean water and sanitation, or even decent work and economic growth. The article does not focus on the solutions to the problems, but rather the best methods of identification of those problems. This means it specifically analyzes and determines the unfreedoms rather than creating possible solutions. This may be even more beneficial than attempting to create solutions because of the inherent dangers of data bias. The methodology used for analyzing the data is the institutional synergy and system approaches, pattern methods, and multidimensional comparative analysis. The authors are investigating developmental processes themselves. It seems to be a sort of meta-analysis of methods rather than a standard analysis of processes.
After urban growth, survey models become inaccurate and misrepresent the poorest. The health of urban poor is masked compared to that of the wealthier. This distorts resource allocation and processes associated with it. Gridded population data can more accurately determine population. In addition to misrepresentation, many aspects of health are underestimated as well, such as non-communicable diseases. The high-quality data available is also difficult for LMIC to use in planning decisions. They use three methods, gridded population sampling, enumeration using open-access online maps, and one-stage vs two-stage sampling. No results were finalized in this ongoing study. The article related to Sen’s definition by increasing the processes rather than opportunities of freedoms. This study simply provides a way to reduce sampling bias, which does not really connect to Sen’s 5 essential freedom types. This paper seeks to provide useful information for goal one, no poverty. Although this paper does not convey any results, its theory is consistent with Sen, Rosling, and many others. Solutions created from misinformation due to sampling bias or other bias can be even more detrimental than if no solutions were presented in the first place. Using data science to more accurately and currently produce data is the first step to implement effective sustainable development plans. Gridded population data specifically is much cheaper and significantly more up to date than old census data or survey data. More than just the first goal, most of the sustainable development goals can be improved, which is significantly more promising than simply improving one. Jahan and Rosling stated that many different factors are intertwined together in human development, and methods that allow for distributed growth over the different sustainable development goals seems to align with their ideas. In addition, the use of data science can provide insight to social class designations as well as population movement.
In Sub-Saharan Africa, there has been large progress in providing access and care for communicable disease. Increasing research is being made into other forms of care, such as for emergency services. Increasing access and care for emergency patients could decrease mortality by 45%. Currently, there is no real master health facility list, thus this article seeks to use geocoded assembly to compile and analyze emergency care access in Sub-Saharan Africa. After compiling data about health services from ministries of health, health management information systems, government statistical agencies, Humanitarian Data Exchange portal, UNICEF, and other datasets, the authors labeled each hospital with geographical location data. Then they obtained estimates of child-bearing-aged women through WorldPop data. Calculations were made to model travel time of these women to reach a hospital in a reasonable amount of time. Only 16 out of the 48 countries analyzed met the international standard of having more than 80% of the population within 2 hours of a hospital. This article seeks to help produce the third sustainable development goal, to increase good health and well-being. In addition to providing increased freedoms to those with poor health, or those whose life has been crippled or cut short due to illness, this solution also increases free agency. One of the main goals of this article is the compile emergency care facilities in Sub-Saharan Africa. This will make it easier for them to develop how they choose on whatever path their end up growing towards. Development is not a linear path, and the production of data and access to the data may help in development more than attempting to implement solutions. This source analyzes Africa, and I believe that the concepts presented in this article would be beneficial for Tajikistan as well. The studies I have looked at previously don’t use much data compared to this one. A statistical compilation and analysis of a broad set of data will allow for more agency in Tajikistan. A multitude of data sets are analyzed is this paper, including ministries of health, health management information systems, and government statistical agencies. This article focuses on the location and mapping of healthcare facilities. This will allow easier access for human development.
HIV is a high-risk threat in Tajikistan due to its location in central Asia and its poor status. Injected drug use accounts for 70% of cases. Currently, heterosexual transmission has been on the rise, accounting for around 45% of recent cases. The data used in this study was collected from Tajikistan Multiple Indicator Cluster Survey, focusing on women aged 15-49. Univariate analysis was used to analyze distribution, binary logistic regression was used was used to measure correlation between awareness, prevention, and transmission, and last the results were simulated using statistical software. The results show that although general knowledge of HIV/AIDS is increasing, so are misconceptions and myths. This article relates to sustainable development goal 4, education. Rather than attempting to actually implement solutions for the health problem identified, the main purpose of this article is to analyze the education around this health risk. Increasing education will lead to more free agency in social opportunities. The Tajikistan Multiple Indicator Cluster Survey was used as data, and the methods used were univariate analysis and binary logistic regression. The data used in this study is somewhat outdated, thus solutions created based on these results do fully represent reality today. This article also seeks to improve the third goal, good health and well-being. A clear shortcoming is the limitations of this study. The data used was relatively outdated, and the results produced do not represent the full picture. By using outdated sources, the findings and solutions created about the findings will become more out of touch with reality, and not effectively increase freedoms and free agency.
After doing this research, many noteworthy thoughts have come upon me. Not many of the sources truly use data science methods, and I believe that the scope and accuracy, as well as the results, could be more influential had the authors used bigger data. There seemed to be a lack of literature relating to Tajikistan, even though its development indexes are very significantly low. This prompts me to believe that there is a fairly large shortcoming the data science work being done in Tajikistan. Tajikistan seems to have data that is not used effectively, or able to be synthesized and used, which is a direction that I would like to explore in the next part of this assignment.