Currently writing a research paper on if dengue, a disease transmitted by mosquitoes, is more common due to urbanization of human populations. I believe an effective and accurate spatial analysis technique will help my research because it will allow me to track and record the areas that are affected by dengue.
This depends on the nature of the data sets that you have. Do you intend to develop a model between georeferenced dengue incidence data and potential determinants? What is the spatial scale you intend to map the results at?
In general, there are many approaches in spatial modelling such as Geographically Weighted Regression (Fotheringham et al. 2003), Spatial Lag Models (Anselin, 2001) all of which you can find and apply in open acess software (R, QGIS, Python). Machine learning algorithms such as Random Forest have can also describe spatial processes very well. Be aware that they may very well not be needed, sometimes a simple regression is more appropriate.
In regards to your research topic, i doubt that vector transmitted diseases are more common in urban environments but i would argue that dengue prevalence and incidence can persist and even show increases i in an urban context because of various factors (vector adaptation to urban environments, rural-urban migration dynamics, most vector control initiatives are done in rural areas).
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