The Health Office of Pontianak City, West Kalimantan Province reported that there were 387 confirmed cases of COVID-19 per July 2020 and 4 of them died. Unfortunately, the use of Geographic Information System (GIS) for planning, monitoring, and decision-making to support surveillance program by local- health managers has not been well documented, particularly in the distribution of COVID-19. The utilization of GIS is required as a method for public health surveillance and monitoring. This study aimed to analyze the distribution of COVID-19 cases with a spatial approach to support the epidemiological surveillance program in Pontianak City between March 2020 to July 2020. This research was a cross- sectional study. The dependent variable was cases COVID-19 (suspect and confirmation) and the independent variables included ages, sex, and patient’s status. A total of 332 cases of COVID-19 in Pontianak City were collected from six districts. The results showed that males were more likely to suffer from COVID-19 than females, the age group of 31-40 years was more vulnerable, and some patients were cured. The study also revealed the spread of one district with a Clustered type of COVID-19. The presence of spatial autocorrelation was explored using global and local Moran's I statistics. The global Moran's I revealed a negative but statistically significant spatial autocorrelation COVID-19 incident rate (I = 0,000). The mapping of COVID-19 cases using GIS can facilitate the epidemiology programmer in Pontianak City Health Office and Public Health Centre in intervening the social determinant of health to identify the spread of COVID-19 disease.