Using linear regression for geospatial data?

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Say, my database has three columns. A: county (300 rows with 300 counties as index), B: X (some independent variable in continuous scale, which is the average of everyone in that county), and C: Y (the percentage of people indicated "yes" in that county, thus continuous).

Since the majority of the counties are not available, and only 300 counties are, in the map you can see not all counties have adjacent neighbors. If I want to find if there is a significant correlation between X and Y, is simple univariate linear regression okay to use? Or should I still factor in the spatial factor?



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