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Coronavirus disease 2019 (COVID-19) has been spread globally and brought health and socioeconomic issues. Jakarta tried to accommodate health and economic interests through the Large-Scale Social Restriction (LSSR) policy that should be assessed. This study aims to (1) visualize the spatial patterns of confirmed Covid-19 cases and the locations of potential risk of transmission, and (2) determine the spatial processes underlying the spatial patterns of Covid-19 cases. The emerging hot spot analysis and space-time scan statistic were employed to analyze the dynamic of infected cases and transmission risk. A Geographical Weighted Regression (GWR) model was developed to define factors that influence the spatial transmission. The result shows that spatial transmission keeps continuing, despite a decline in the aggregate pandemic curve during LSSR implementation. This was likely affected by settlements types and population density distribution, and transportation networks. Spatial analysis supports the aggregate pandemic curve to increase the pandemic surveillance effectiveness.

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