Using geostatistical modelling to explore smoking cessation in the Global South

I was drawn to this PhD project entitled 'Using geostatistical modelling to explore smoking cessation in the Global South' as it will further develop my statistical modelling experience and will also allow me to research my interests in smoking-related health behaviours and outcomes. This experience will provide me with new skills in multilevel modelling and synthetic estimations. These will be useful after I complete this PhD and enter a public health-related job, or remain in academia. Another aspect of the project that attracts me is that it would bring to attention the smoking-related health impacts in the Global South, which is subject to a shift in smoking prevalence rates from the Global North. The study of which would inform other researchers and interested parties of the viability of calculating synthetic estimations which could guide future tobacco control policies.
My academic experience during my undergraduate degree focused on enhancing my understanding of the effects of place on health behaviours and also developing my skills with software packages such as ArcMap, QGIS and IBM SPSS and Minitab which allows me to map and model quantitative datasets and perform analysis such as multiple and logistic regression. After completing my degree, I undertook a Masters in Research (MRes) at the University of Portsmouth. The aim of my research is to create a method that can web scrape geolocations of tobacco outlets in Portsmouth. This will be used to understand the impacts and risks of the geographies of tobacco retail on smoking prevalence and vulnerable populations.
My course has provided me with opportunities to further train and develop my skills by attending workshops. One of which was a day workshop at the University of Essex where I was made aware of a method, which I implemented in my own research, that involved the use of Application Programming Interfaces (API's) and Python Programming to web scrape locations from an online database. My work thus far has proven challenging but stimulating, as studying an untaught course is different from the structure I am used to. However, this gave me the opportunity to create my own structure which has further built upon my organisational skills, academic ability and confidence. Consequently, I believe I am the most suitable candidate for this project as my interest and experience with quantitative data of the place effects on health behaviour has been continuously enhanced throughout my MRes course and my undergraduate degree.
Although I have not studied multilevel (ML) modelling techniques, I am eager to learn about ML methods as part of the Masters and PhD training. This will be key to the PhD I wish to undertake as it will adopt a geostatistical modelling method to explore smoking cessation in the Global South by developing high-resolution estimates. My enthusiasm for studying and immersion into a course can be seen by my participation as an open day assistant for the geography department and the treasurer of the geography society at the University of Portsmouth.