Background: Allocation of adequate healthcare facilities is one of the most important factors that public health policymakers consider when preparing for infectious disease outbreaks. Negative pressure isolation rooms (NPIRs) are one of the critical resources for control of infectious respiratory diseases, such as the novel coronavirus disease 2019 (COVID-19) outbreak. However, there is insufficient attention to efficient allocation of NPIR-equipped hospitals. Methods: We aim to explore any insufficiency and spatial disparity of NPIRs in South Korea in response to infectious disease outbreaks based on a simple analytic approach. We examined the history of installing NPIRs in South Korea between the severe acute respiratory syndrome (SARS) outbreak in 2003 and the Middle East respiratory syndrome coronavirus (MERS-Cov) in 2015 to evaluate the allocation process and spatial distribution of NPIRs across the country. Then, for two types of infectious diseases (a highly contagious disease like COVID-19 vs. a hospital-based transmission like MERS-Cov), we estimated the level of disparity between NPIR capacity and demand at the sub-regional level in South Korea by applying the two-step floating catchment area (2SFCA) method. Results: Geospatial information system (GIS) mapping reveals a substantial shortage and misallocation of NPIRs, indicating that the Korean government should consider a simple but evidence-based spatial method to identify the areas that need NPIRs most and allocate funds wisely. The 2SFCA method suggests that, despite the recent addition of NPIRs across the country, there should still be more NPIRs regardless of the spread pattern of the disease. It also illustrates high levels of regional disparity in allocation of those facilities in preparation for an infectious disease, due to the lack of evidence-based approach. Conclusion: These findings highlight the importance of evidence-based decision-making processes in allocating public health facilities, as misallocation of facilities could impede the responsiveness of the public health system during an epidemic. This study provides some evidence to be used to allocate the resources for NPIRs, the urgency of which is heightened in the face of rapidly evolving threats from the novel COVID-19 outbreak.

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Researchers are able to adopt a text scrapping method to collect data from news articles when data are not available due to privacy protections. This study introduces the processes of text scrapping and analyzing texts of news articles from a local news server in Jeju-do. Since the Jeju government regularly discards the path information of COVID-19 patients, researchers who want to explore characteristics of places where a high number of confirmed cases occurred have predicaments in collecting relevant information. To overcome this challenge for social researchers, this study shows a text analysis process including pre-processing, calculating TF-IDF, creating word clouds, and conducting a word network analysis. The results from analyzing 4500 news articles confirm that there was a serial correlation between the number of daily COVID-19 cases and the number of articles and explore specific features of the places where COVID-19 patients went through. The article would help social researchers to use big data and text mining methods in order to overcome the difficulties of data collection in public administration.