This is a stratified, cluster sample. (If you have never heard these words before, you are probably not prepared to handle the project... sorry, but that's what it is; you may want to seek a consulting statistician to do this; Statistics without Borders may be able to help.)
Your strata are regions: all six are in the sample, and samples are to be taken independently across them.
Your clusters, or primary sampling units (PSUs), are municipalities. I would select them with probabilities proportional to size. In R, this is to be done with
library(sampling)... I would use
sampling::UPmaxentropy() as the method that is closest to SRS in its statistical properties (and hence harder to screw up at the analysis stage, vs. say systematic sampling).
Then if you have the list of people in that municipality (which would really impress me), you could take a simple random sample from that list. If you don't have that list, then you need to add another sampling stage which would depend on census or other population data on sizes of cities and towns and villages within the municipality (and probably some administrative divisions within the larger cities). You would again take a PPS sample at that stage, aiming to get to areas of 2,000-5,000 people that could be managed by field enumerators. (In the U.S., areas of this size are referred to as census tracts; they are artificial geographic entities that mainly exist for the purposes of other data collections.) And once you enumerate dwellings/households at that last step, you can draw your sample of 30 people (which would probably be 10 people in 3 "census tracts"). If you don't have detailed data, you'd probably have to rely on maps, and drawing units on the map pretty much by hand (well... "by hand" these days means in a GIS program).
One of the problems I have encountered many times in international work is that once you took the sample, you (or your local contractors) destroyed all the records that you had used. This makes the data nearly unusable. To analyze the data properly (
library(survey) in R; I wrote a chapter on this recently, as well), you need selection probabilities (and to construct these, you need the population counts at every stage) and identifiers of the strata and sampling units. You need to make absolutely sure that this information travels into your final data set.