Multi-country model or single model
In the paper of Hinton - Distilling the knowledge of Neural Networks, the following is mentioned (Section 5) when defining specialist models:

When the number of classes is very large, it makes sense for the cumbersome model to be an ensemble that contains one generalist model trained on all the data and many “specialist” models, each of which is trained on data that is highly enriched in examples from a very confusable subset of the
classes (like different types of mushroom).

What they do is they use a general model first and then a specialist model each to focus on a different subset of the classes.
You could consider your problem something similar, instead of a specialist to classes, and specialist in countries. This way you could build a country(cluster of countries) specific ensemble of models.