Assignment 1. Annotated Bibliography
Sasan Faraj
February 13
Problem Statement
The Rotavirus vaccine has the lowest vaccination coverage in El Salvador, even though El Salvador is known for having good vaccination coverage (Suárez-Castaneda et al., 2013). The harm of this dilemma is extremely extensive, as lack of a vaccine is generally known to be a fatal diarrheal disease. In fact, the Mayo Clinic analyzes that there are over 200,000 deaths per year to rotavirus. This is extremely significant to the development of freedom. Relating this to Amartya Sen’s discussion of human development and freedom, if children, mainly babies, are denied the substantive freedom of life due to death, then human development loses potential, leading to a perpetual cycle of decreasing development. The inherency of this topic is what requires the most research. As will be discussed below, unsafe conditions and lack of resources relate to low vaccination coverage, but no research has been done to see if crime rates relate to vaccination coverage, curbing the need for vaccination data.
Annotations
Utazi, C.D., Thorley, J., Alegana, V. A., Ferrari, M.J., Takahashi, S., Metcalf, C. J. E., Lessler, J., & Tatem, A.J. (2018). High resolution age-structured mapping of childhood vaccination coverage in low and middle income countries. Vaccine, 36(12), 1583-1591. https://doi.org/10.1016/j.vaccine.2018.02.020
Utazi and the rest of the authors attempted to answer the general question of what was the vaccination coverage in Nigeria, Mozambique, and Cambodia and how could they produce the the highest resolution analysis. In order to do this, they attained survey data from Demographic and Health Surveys (DHS) which produce cluster-level data. Incorporating a Bayesian hierarchical model through Markov Chain Monte Carlo methodology, they created a 1 x 1km resolution map, displaying the vaccination coverage of children under the age of five, separating the age group into different categories/levels.
Utazi and the other authors specifically state that this form of a study is necessary so countries or organizations can help meet the sustainable development goals of the United Nations. Specifically, this article relates the most to the third SDG which is to ensure and promote healthy lives to people of all ages, though this study solely examines people under the age of 5. The harm that this article is trying to address is that lower- and middle-income countries generally have vaccination rates that are lower than what the United Nations desire, which is 90% vaccination coverage. So the researchers wanted to see if that was true and where the improvement needed to be. This topic can be difficult to analyze. For starters, there are many different diseases that children should be vaccinated for; however, the researchers decided to focus on the vaccination rates of Measles. Another inherent issue, which was directly written by the authors, is the way that DHS collects its data. In order to protect the random ability and privacy of its users, DHS uses cluster-level data, so the researchers needed to create a methodology in order to accurately determine where the clusters are, so they can have geographically correct data. If the researchers want to display where governments and organizations need to vaccinate, they must know the specific locations of where to go.
In relation to human development, health care, in many ways, dictates whether or not humans live. So by the inherent nature of the vaccine being able to save hundreds to thousands of lives, finding out where the vaccinations are needed the most can help increase human development by increasing the number of humans alive. This closely relates to Sen’s claims on human development, because he argues that human development relies on human capabilities. Being alive is the essence of human capability. If they are not alive, they cannot be capable of anything. The human development pattern/process that the researchers are looking at is how vaccination rates impact the quality of life of people. Though they do not explicitly state that is what they are looking at, by researching this topic and providing a map displaying vaccination rates, they are feeding into the overall discussion of vaccination rates and quality of life, because sickness dictates quality of life.
Niyibizi, I., Schamel, J., & Frew P. M. (2016). Neighborhood influences on seasonal influenza vaccination among older African Americans in Atlanta, Georgia. Journal of Immunological Techniques in Infectious Diseases, 5(2), 1-20. doi: 10.4172/2329-9541.1000139
The researchers sought to answer the question of how neighborhoods (or localized factors) impact the vaccination coverage in the vaccination rates for influenza among African American aged 50+ years, specifically looking at crime rates, housing vacancies, vehicle availability, and other demographic changes. The data in this study was not aquired through geospatial datasets, rather the researchers collected data of vaccination from 221 African Americans from 6 different predominately African American churches.
Though the study focused on a non lower- to middle-income country, it is relevant to my research because of its data science related methodology and justified through Amartya Sen’s definition of human development. For instance, the researchers acquired data on the neighborhood-level variables from census-level data. All the census were measures as per 1000 people (ie rate of violent crimes, percent of vacant houses, and neighborhood deprivation index). While analyzing the data, descriptive statistics were attained by using “IBM SPSS statistics, version 22” and a bivariate analyses to see the correlation between each variable and vaccination coverage. On the flip side, during Sen’s reading, he, and his data, strongly suggests that the quality of life, using life expectancy and other variables for analyses, were on par and sometimes worse than the quality of life in a low- or middle-income country. So focusing on a high-income country is okay as long as the subsection we are focusing on is comparable to other low- or middle income countries. Also, finding the correlation of neighborhood level variables to vaccination rates can help NGO’s or governments improve the quality of life because they know why the vaccination rate is low, so they will be able to counteract the reasons for a lack of vaccination. The idea of living would be a substantive freedom to human development because you need to live in order to be free. The source relates to Sustainable Development Goal 3 because it describes a way to find out if people are living a healthy life.
The authors saw multiple correlations within their results. The study found that perceiving the neighborhood as safe led the respondents to having friendlier attitudes towards vaccination. On the contrapositive, that might indicate that people with perceiving dangerous neighborhoods could view vaccinations negatively. Older age and less availability to vehicles per household had the same statistical significance as neighborhood security. Again, this shares the same development goal that I want to research which is to ensure healthy lives for everyone so they can develop in other sectors.
Wong, M. K, Yadav, R. P., Nishikiori, N., & Eang, M. T. (2013). The association between household poverty rates and tuberculosis case notifications rates in Cambodia, 2010. Western Pacific Survival and Response Journal, 4(1), 25 - 33. doi: 10.5365/WPSAR.2013.4.1.002
This article answers the question regarding what is the correlation between household poverty rates and tuberculosis case notification rates. Though, it is important to notice that the authors are investing the notifications rates rather than the people infected. When adjusting for “population density, distance to health care facilities, all basic vaccination coverage and HIV prevalence,” the researchers found a negative correlation between household poverty rates and septum positive tuberculosis notification rates, meaning as household poverty rates increased, the notification of people testing positive for tuberculosis decreased, contradicting the authors’ hypothesis.
In order to find an answer to their question, the researchers used Poisson regression models. In addition, researchers incorporated a univariate model to determine how household poverty rates affect sputum-positive tuberculosis notification rates. Though the researchers used this form of statistical analysis, they used ArcMap GIS software V.9.3.1 to map out their other covariates and help users visualize how all the covariates are related. In fact, they explicitly write that GIS is useful for visualization. The researchers acquired their data about tuberculosis through the “National TB Registry maintained by the National Centre for Tuberculosis and LeprosyControl ‘’. Data about household poverty was from the Commune Database which is ran by the National Committee for SubNational Democratic Development (Communes are the lowest level administrative level district in Cambodia).
The article relates to Amartya Sen’s definition of human development because of the discussion surrounding the basic health of citizens of lower socioeconomic status. For instance, Sen draws connections about the importance of income in being able to pursue what we enjoy and how our ability to be healthy impacts whether or not we are able to develop as a collective body. This study combines both those concepts because it tested whether or not having money, monitored by poverty rates, will increase their likelihood of being sick with TB, inevitably disabling them from both gaining money to pursue interests and exploring their own development. Holistically, this article relates to two Sustainable Development Goals: reducing poverty and ensuring healthy lives for all people. The article relates to reducing poverty because it aims to demonstrate the negative health effects of poverty, though it found that distance to facilities has a greater impact on health than poverty. It relates to improving overall health because it seeks to find out what may be causing people to live fatally unhealthy lives.
Wiysonge, C. S., Uthman, O. A., Ndumbe, P. M., & Hussey, G. D. (2012). Individual and contextual factors associated with low childhood immunisation coverage in sub-Saharan Africa: a multilevel analysis. Plos ONE, 7(5), 1-7. https://doi.org/10.1371/journal.pone.0037905
The authors of this study sought to answer the question of how do different levels of analysis (individual-, community-, and national-level) impact the immunization rate of children under five in sub-Saharan Africa. The research found a multitude of correlations. But the most important relationship was that both contextual factors (community and national) and individual factors influenced the vaccination coverage of the children. A few examples are children whose parents did not receive and education are likely to be not vaccinated for specific vaccines. Likewise, children in neighborhoods which have high illiteracy rates are likely to not be vaccinated.
For their data analysis, the researchers used a multilevel logistic regression to see how the different factors correlated with childhood immunization. They incorporated a total of five models, including, or not including, certain control factors. The researchers acquired their data from Demographic and Health Surveys (DHS), specifically from the MEASURE DHS project in sub-Saharan Africa. Also, the defined “unimmunized child” using the definition of the World Health Organization.
This article relates to Sen’s discussion of human development and freedom because the researchers take what Sen describes as important to freedom (literacy rates, average income, etc.) and correlates how those impact substantive freedoms, mainly health. Likewise, the researchers focus on the development pattern of children vaccination rates which can differ based on the community. So the researchers are clearly focusing on the third Sustainable Development Goal which is about ensuring healthy lives, regardless of external factors. However, it is critical to note that this article was made in response to the effectiveness of the Millennium Development Goals (MDGs), but it still relates to SDGs, even though it does not blatantly state that.
Menezes, T., Silveira-Neto, R., Monteiro, C., & Ratton, L. J. (2013). Spatial correlation between homicide rates and inequality: evidence from urban neighborhoods. Economic Letters, 120(1), 97-79. https://doi.org/10.1016/j.econlet.2013.03.040
The researchers of this article attempted to answer the questions of how socioeconomic and neighborhood characteristics influence homicide rates in specified Brazilian Neighborhoods. Overall, the researchers found a few correlations. Interestingly, if a neighborhood had low crime rates, its neighboring communities would have higher murder rates. Maybe most importantly, the researchers found that a low Gini coefficient correlated with a total decrease in the neighborhood’s homicide rates, meaning lower income inequality indicated lower homicide rates.
The data representing the tested variables were from the Brazilian Demographic Census from the Brazilian Bureau of Statistics. The method of spatial regression they used was the “spatial autoregressive (SAR) model in the notation of LeSage and Pace.”
This article relates to Sen’s discussion of human development and freedom because it describes the basic influence of inequality on the most foundational substantive freedom, life. They wanted to find out what is influencing people’s ability to be alive which directly impacts their ability to be alive. Unlike the previous source, this source does not relate to the third Sustainable Development goal. This most relates to the first Sustainable Development Goal of ending poverty because the study shows the negative impact of income inequality. In fact, the study illustrates the common human development pattern of income inequality and how it influences people’s lives.