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Correlations Between the Incidence of National Notifiable Infectious Diseases and Public Open Data, Including Meteorological Factors and Medical Facility Resources

OBJECTIVES: This study was performed to investigate the relationship between the incidence of national notifiable infectious diseases (NNIDs) and meteorological factors, air pollution levels, and hospital resources in Korea. METHODS: We collected and stored 660 000 pieces of publicly available data...

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Detalles Bibliográficos
Autores principales: Jang, Jin-Hwa, Lee, Ji-Hae, Je, Mi-Kyung, Cho, Myeong-Ji, Bae, Young Mee, Son, Hyeon Seok, Ahn, Insung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society for Preventive Medicine 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4542299/
https://www.ncbi.nlm.nih.gov/pubmed/26265666
http://dx.doi.org/10.3961/jpmph.14.057
Descripción
Sumario:OBJECTIVES: This study was performed to investigate the relationship between the incidence of national notifiable infectious diseases (NNIDs) and meteorological factors, air pollution levels, and hospital resources in Korea. METHODS: We collected and stored 660 000 pieces of publicly available data associated with infectious diseases from public data portals and the Diseases Web Statistics System of Korea. We analyzed correlations between the monthly incidence of these diseases and monthly average temperatures and monthly average relative humidity, as well as vaccination rates, number of hospitals, and number of hospital beds by district in Seoul. RESULTS: Of the 34 NNIDs, malaria showed the most significant correlation with temperature (r=0.949, p<0.01) and concentration of nitrogen dioxide (r=-0.884, p<0.01). We also found a strong correlation between the incidence of NNIDs and the number of hospital beds in 25 districts in Seoul (r=0.606, p<0.01). In particular, Geumcheon-gu was found to have the lowest incidence rate of NNIDs and the highest number of hospital beds per patient. CONCLUSIONS: In this study, we conducted a correlational analysis of public data from Korean government portals that can be used as parameters to forecast the spread of outbreaks.