Abstract
The World Health Organization (WHO) treated at least 350 million
persons with antiparasitic medicines globally, in an effort to
control and eliminate onchocerciasis (oncho), lymphatic filariasis
(LF), and other Neglected Tropical Diseases (NTDs). Unintended side
effects, however, occurred for people in regions endemic with
loiasis, with thousands of Serious Adverse Events (SAEs) that
occurred solely as a result of the WHO's strategy, and 85% reported
in Cameroon. To mitigate these undesired consequences, Schluter, et
al. (2016) developed a probability model to gauge a village's
average intensity of loiasis by calculating the population's
average microfilariae count within a milliliter of blood (mf/ml),
and generating a recommendation output whether or not to administer
antiparasitics. This project aims to reduce SAEs by making this
statistical tool more accessible through a graphical user interface
(GUI) and aid global policymakers in their decisions about
dispersing the antiparasitic tablet, ivermectin. Data were
collected in September 2016 in Cameroon and captured demographic
information, as well as test results for oncho and LF prevalence,
loiasis mf/ml intensity, and the Schluter, et al., (2016)
probabilities. 2,700 persons were tested within 27 villages. 93% of
the villages were found to have loiasis with a mean of 4,009 mf/ml,
as well as an 89% prevalence on oncho, and a 30% prevalence of LF.
Approximately half of these villages, according the Schluter, et
al. (2016) test, were found to have too high of a loiasis intensity
to merit mass treatment of ivermectin. These findings were then
programmed into a GUI that depended on the RStudio Shiny
application, which provides source code to make statistical tools
accessible as a user interface. This application generated a
successful GUI that allows anyone with a Microsoft Excel file (CSV)
to upload a spreadsheet, and instantly view the statistical model's
prediction with a useful graphic ('Thumbs up' for treating the
village with ivermectin sans pre-testing; 'Thumbs Down' for not
treating). With this innovation, steps towards approximating
loiasis in Cameroon, and other African counties, can be made more
accessible to a wider array of global health stakeholders.
Table of Contents
CHAPTER 1. INTRODUCTION 4 CHAPTER 2. LITERATURE REVIEW 5 Literature
Review Part I: NTD Elimination and Loiasis 5 Literature Review Part
II: eHealth History and Implementation 13 CHAPTER 3. PROJECT
CONTENT 21 Methods 21 Results and the GUI Prototype 25 CHAPTER 4.
DISCUSSION 27 CHAPTER 5. ADDITIONAL PAGES 33 Public Health
Implications 33 Tables 34 Figures 36 References 45
About this Master's Thesis
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