With the continuous increase of COVID-19 cases in the Philippines, particularly in the National Capital Region, this study aims to explore one of the most important factors in preventing the spread of and curing those infected by the disease: the COVID-19 referral hospitals. Specifically, we want to know how accessible these referral hospitals actually are and how we can use network science and geospatial analysis to perform simulations, identify hospitals at full capacity, and consequently, the corresponding unserved population.
We approach this problem by performing a service area analysis and building a bipartite network to simulate the status of the capacity of each of the referral hospitals in the National Capital Region. As a result, we were able to identify unserved barangays which are not within a certain walking distance from COVID-19 referral hospitals. Additionally, we were also able to calculate for node redundancy using the bipartite network and were able to identify less redundant hospitals that may need additional support. Lastly, our simulation provided metrics that would assist in assessing the needs of hospitals and their service areas to ensure proper treatment and care of COVID-19 patients.