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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society for Preventive Medicine
2015
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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 |
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author | Jang, Jin-Hwa Lee, Ji-Hae Je, Mi-Kyung Cho, Myeong-Ji Bae, Young Mee Son, Hyeon Seok Ahn, Insung |
author_facet | Jang, Jin-Hwa Lee, Ji-Hae Je, Mi-Kyung Cho, Myeong-Ji Bae, Young Mee Son, Hyeon Seok Ahn, Insung |
author_sort | Jang, Jin-Hwa |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4542299 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Korean Society for Preventive Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-45422992015-08-24 Correlations Between the Incidence of National Notifiable Infectious Diseases and Public Open Data, Including Meteorological Factors and Medical Facility Resources Jang, Jin-Hwa Lee, Ji-Hae Je, Mi-Kyung Cho, Myeong-Ji Bae, Young Mee Son, Hyeon Seok Ahn, Insung J Prev Med Public Health Original Article 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. Korean Society for Preventive Medicine 2015-07 2015-07-27 /pmc/articles/PMC4542299/ /pubmed/26265666 http://dx.doi.org/10.3961/jpmph.14.057 Text en Copyright © 2015 The Korean Society for Preventive Medicine This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Jang, Jin-Hwa Lee, Ji-Hae Je, Mi-Kyung Cho, Myeong-Ji Bae, Young Mee Son, Hyeon Seok Ahn, Insung Correlations Between the Incidence of National Notifiable Infectious Diseases and Public Open Data, Including Meteorological Factors and Medical Facility Resources |
title | Correlations Between the Incidence of National Notifiable Infectious Diseases and Public Open Data, Including Meteorological Factors and Medical Facility Resources |
title_full | Correlations Between the Incidence of National Notifiable Infectious Diseases and Public Open Data, Including Meteorological Factors and Medical Facility Resources |
title_fullStr | Correlations Between the Incidence of National Notifiable Infectious Diseases and Public Open Data, Including Meteorological Factors and Medical Facility Resources |
title_full_unstemmed | Correlations Between the Incidence of National Notifiable Infectious Diseases and Public Open Data, Including Meteorological Factors and Medical Facility Resources |
title_short | Correlations Between the Incidence of National Notifiable Infectious Diseases and Public Open Data, Including Meteorological Factors and Medical Facility Resources |
title_sort | correlations between the incidence of national notifiable infectious diseases and public open data, including meteorological factors and medical facility resources |
topic | Original Article |
url | 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 |
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