A descriptive analysis of the Spatio-temporal distribution of intestinal infectious diseases in China.
Adult
Child
China
/ epidemiology
Communicable Diseases
/ epidemiology
Dysentery
/ epidemiology
Epidemics
Hand, Foot and Mouth Disease
/ epidemiology
Hepatitis E
/ epidemiology
Humans
Incidence
Intestinal Diseases
/ epidemiology
Intraabdominal Infections
/ epidemiology
Prevalence
Seasons
Spatial Analysis
Spatio-Temporal Analysis
China
Intestinal infectious diseases
Long-term trend
Moran’s I
Seasonal trend
Spatial epidemiology
Journal
BMC infectious diseases
ISSN: 1471-2334
Titre abrégé: BMC Infect Dis
Pays: England
ID NLM: 100968551
Informations de publication
Date de publication:
02 Sep 2019
02 Sep 2019
Historique:
received:
30
12
2018
accepted:
23
08
2019
entrez:
4
9
2019
pubmed:
4
9
2019
medline:
15
11
2019
Statut:
epublish
Résumé
Intestinal infectious diseases (IIDs) have caused numerous deaths worldwide, particularly among children. In China, eight IIDs are listed as notifiable infectious diseases, including cholera, poliomyelitis, dysentery, typhoid and paratyphoid (TAP), viral Hepatitis A, viral Hepatitis E, hand-foot-mouth disease (HFMD) and other infectious diarrhoeal diseases (OIDDs). The aim of the study is to analyse the spatio-temporal distribution of IIDs from 2006 to 2016. Data on the incidence of IIDs from 2006 to 2016 were collected from the public health science data centre issued by the Chinese Center for Disease Control and Prevention. This study applied seasonal decomposition analysis, spatial autocorrelation analysis and space-time scan analysis. Plots and maps were constructed to visualize the spatio-temporal distribution of IIDs. Regarding temporal analysis, the incidence of HFMD and Hepatitis E showed a distinct increasing trend, while the incidence of TAP, dysentery, and Hepatitis A presented decreasing trends over the last decade. The incidence of OIID remained steady. Summer is the season with the greatest number of cases of different IIDs. Regarding the spatial distribution, approximately all p values for the global Moran's I from 2006 to 2016 were less than 0.05, indicating that the incidences of the epidemics were unevenly distributed throughout the country. The high-risk areas for HFMD and OIDD were located in the Beijing-Tianjin-Tangshan (BTT) region and south China. The high-risk areas for TAP were located in some parts of southwest China. A higher incidence rates for dysentery and Hepatitis A were observed in the BTT region and some west provincial units. The high-risk areas for Hepatitis E were the BTT region and the Yangtze River Delta area. Based on our temporal and spatial analysis of IIDs, we identified the high-risk periods and clusters of regions for the diseases. HFMD and OIDD exhibited high incidence rates, which reflected the negligence of Class C diseases by the government. At the same time, the incidence rate of Hepatitis E gradually surpassed Hepatitis A. The authorities should pay more attention to Class C diseases and Hepatitis E. Regardless of the various distribution patterns of IIDs, disease-specific, location-specific, and disease-combined interventions should be established.
Sections du résumé
BACKGROUND
BACKGROUND
Intestinal infectious diseases (IIDs) have caused numerous deaths worldwide, particularly among children. In China, eight IIDs are listed as notifiable infectious diseases, including cholera, poliomyelitis, dysentery, typhoid and paratyphoid (TAP), viral Hepatitis A, viral Hepatitis E, hand-foot-mouth disease (HFMD) and other infectious diarrhoeal diseases (OIDDs). The aim of the study is to analyse the spatio-temporal distribution of IIDs from 2006 to 2016.
METHODS
METHODS
Data on the incidence of IIDs from 2006 to 2016 were collected from the public health science data centre issued by the Chinese Center for Disease Control and Prevention. This study applied seasonal decomposition analysis, spatial autocorrelation analysis and space-time scan analysis. Plots and maps were constructed to visualize the spatio-temporal distribution of IIDs.
RESULTS
RESULTS
Regarding temporal analysis, the incidence of HFMD and Hepatitis E showed a distinct increasing trend, while the incidence of TAP, dysentery, and Hepatitis A presented decreasing trends over the last decade. The incidence of OIID remained steady. Summer is the season with the greatest number of cases of different IIDs. Regarding the spatial distribution, approximately all p values for the global Moran's I from 2006 to 2016 were less than 0.05, indicating that the incidences of the epidemics were unevenly distributed throughout the country. The high-risk areas for HFMD and OIDD were located in the Beijing-Tianjin-Tangshan (BTT) region and south China. The high-risk areas for TAP were located in some parts of southwest China. A higher incidence rates for dysentery and Hepatitis A were observed in the BTT region and some west provincial units. The high-risk areas for Hepatitis E were the BTT region and the Yangtze River Delta area.
CONCLUSIONS
CONCLUSIONS
Based on our temporal and spatial analysis of IIDs, we identified the high-risk periods and clusters of regions for the diseases. HFMD and OIDD exhibited high incidence rates, which reflected the negligence of Class C diseases by the government. At the same time, the incidence rate of Hepatitis E gradually surpassed Hepatitis A. The authorities should pay more attention to Class C diseases and Hepatitis E. Regardless of the various distribution patterns of IIDs, disease-specific, location-specific, and disease-combined interventions should be established.
Identifiants
pubmed: 31477044
doi: 10.1186/s12879-019-4400-x
pii: 10.1186/s12879-019-4400-x
pmc: PMC6721277
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
766Subventions
Organisme : National Social Science Fund of China
ID : 17ZDA079
Références
J Microbiol Immunol Infect. 2011 Aug;44(4):265-73
pubmed: 21524954
PLoS Negl Trop Dis. 2013;7(3):e2112
pubmed: 23516653
Epidemiol Infect. 2014 Aug;142(8):1751-62
pubmed: 24139426
Lancet Infect Dis. 2014 Apr;14(4):308-318
pubmed: 24485991
Curr Top Microbiol Immunol. 2014;379:117-44
pubmed: 24827501
PLoS One. 2014 Jul 18;9(7):e102020
pubmed: 25036182
Zhonghua Yu Fang Yi Xue Za Zhi. 2014 Sep;48(9):753-5
pubmed: 25492283
Exp Ther Med. 2015 Mar;9(3):811-816
pubmed: 25667633
Biometrics. 2015 Sep;71(3):841-50
pubmed: 25832170
Sci Rep. 2015 Oct 15;5:15264
pubmed: 26469274
PLoS One. 2016 Jan 25;11(1):e0147054
pubmed: 26808311
Int J Infect Dis. 2016 Jul;48:7-13
pubmed: 27094249
Int J Environ Res Public Health. 2016 May 10;13(5):
pubmed: 27171104
Emerg Microbes Infect. 2016 Jun 22;5:e62
pubmed: 27329848
Int J Biometeorol. 2017 Feb;61(2):335-348
pubmed: 27492630
BMC Public Health. 2016 Oct 21;16(1):1109
pubmed: 27769194
BMC Infect Dis. 2016 Nov 18;16(1):685
pubmed: 27863468
Zhonghua Liu Xing Bing Xue Za Zhi. 2017 Apr 10;38(4):424-430
pubmed: 28468056
Zhonghua Liu Xing Bing Xue Za Zhi. 2017 Jun 10;38(6):754-758
pubmed: 28647977
BMC Public Health. 2017 Sep 25;17(1):743
pubmed: 28946856
Int J Environ Res Public Health. 2018 Apr 02;15(4):
pubmed: 29614809
BMC Infect Dis. 2018 Apr 3;18(1):158
pubmed: 29614964
Medicine (Baltimore). 2018 Aug;97(34):e11787
pubmed: 30142765
Am J Epidemiol. 1997 Jul 15;146(2):161-70
pubmed: 9230778