Skip to main content
Top
Published in: BMC Infectious Diseases 1/2021

Open Access 01-12-2021 | Research

Spatio-temporal analysis of bacillary dysentery in Sichuan province, China, 2011–2019

Authors: Yao Zhang, Mengyuan Zhang, Dianju Kang, Wei Sun, Changhong Yang, Rongjie Wei

Published in: BMC Infectious Diseases | Issue 1/2021

Login to get access

Abstract

Background

Bacillary dysentery (BD) is a common infectious disease in China and causes enormous economic burdens. The purpose of this study was to describe the epidemiological characteristics of BD and to identify its possible hot spots and potentially high-risk areas in Sichuan province of China.

Methods

In this study, we collected monthly BD incidence reports of 181 counties in Sichuan province, China, from January 2011 to December 2019. Descriptive statistics were used to evaluate the epidemic characteristics of BD. Moran’s I index was applied to investigate the yearly patterns of the spatial distribution. And spatio-temporal scanning statistics with the spatial unit set as county and the temporal unit set as month were used to investigate the possible high-risk region. Meanwhile, the circular moving windows were also employed in the spatio-temporal scanning to scan the study areas.

Results

The annual incidence of BD ranged between 16.13/100,000 and 6.17/100,000 person-years from 2011 to 2019 in Sichuan. The majority of the cases were children aged 5 years or younger. For the descriptive statistics, a peak from May to October was observed in temporal analysis, the epidemics were mainly concentrated in the northwest and southwest of Sichuan in spatial analysis. After 2016, the scope of BD significantly narrowed and severe epidemic areas were relatively stable. For the spatial autocorrelation analysis, a high global autocorrelation was observed at the county level, and the high–high clusters mainly distributed in the northwest and southwest of Sichuan. For the spatio-temporal scanning, the spatiotemporal clusters of BD occurred every year from 2011 to 2019. The most likely cluster areas mainly distributed in the southwest and northwest of Sichuan at the beginning, and then gradually concentrated in the southwest. The secondary cluster mainly concentrated in the northwest and its surrounding areas. Moreover, the 2nd secondary cluster was relatively small and mainly distributed in the central area. No clusters were noted in eastern Sichuan.

Conclusions

Based on our current analysis, BD is still a common challenge in Sichuan, especially for counties in the southwest and northwest in summer and autumn. More disease prevention and control measures should be taken in such higher-risk susceptible areas at a certain time to allocate the public health resources rationally, and finally reduce the spread of BD.
Literature
1.
go back to reference Fried M. Acute gastrointestinal infections. Gastroenterologe. 2007;2(3):159–60.CrossRef Fried M. Acute gastrointestinal infections. Gastroenterologe. 2007;2(3):159–60.CrossRef
4.
go back to reference Zhang Z, Lai S, Yu J, Geng Q, Yang W, Yu C, Wu J, Jing H, Yang W, Li Z. Etiology of acute diarrhea in the elderly in China: a six-year observational study. PLoS ONE. 2017;12(3):e0173881.CrossRef Zhang Z, Lai S, Yu J, Geng Q, Yang W, Yu C, Wu J, Jing H, Yang W, Li Z. Etiology of acute diarrhea in the elderly in China: a six-year observational study. PLoS ONE. 2017;12(3):e0173881.CrossRef
5.
go back to reference Kotloff KL, Nataro JP, Blackwelder WC, Nasrin D, Farag TH. Burden and aetiology of diarrhoeal disease in infants and young children in developing countries (the Global Enteric Multicenter Study, GEMS): a prospective, case–control study. Lancet London. 2013;382(9888):209–22.CrossRef Kotloff KL, Nataro JP, Blackwelder WC, Nasrin D, Farag TH. Burden and aetiology of diarrhoeal disease in infants and young children in developing countries (the Global Enteric Multicenter Study, GEMS): a prospective, case–control study. Lancet London. 2013;382(9888):209–22.CrossRef
6.
go back to reference Meng Q, Liu X, Xie J, Xiao D, Wang Y, Deng D. Epidemiological characteristics of bacillary dysentery from 2009 to 2016 and its incidence prediction model based on meteorological factors. Environ Health Prev Med. 2019;24(1):82.CrossRef Meng Q, Liu X, Xie J, Xiao D, Wang Y, Deng D. Epidemiological characteristics of bacillary dysentery from 2009 to 2016 and its incidence prediction model based on meteorological factors. Environ Health Prev Med. 2019;24(1):82.CrossRef
7.
go back to reference Taneja N, Mewara A. Shigellosis: epidemiology in India. Indian J Med Res. 2016;143(5):565–76.CrossRef Taneja N, Mewara A. Shigellosis: epidemiology in India. Indian J Med Res. 2016;143(5):565–76.CrossRef
8.
go back to reference Ma Y, Zhang T, Liu L, Lv Q, Yin F. Spatio-temporal pattern and socio-economic factors of bacillary dysentery at county level in Sichuan province, China. Sci Rep. 2015;5:15264.CrossRef Ma Y, Zhang T, Liu L, Lv Q, Yin F. Spatio-temporal pattern and socio-economic factors of bacillary dysentery at county level in Sichuan province, China. Sci Rep. 2015;5:15264.CrossRef
9.
go back to reference Ministry of health of the PRC: Diagnostic criteria for bacillary dysentery and amoebic dysentery. 2008; WS 287-2008. Ministry of health of the PRC: Diagnostic criteria for bacillary dysentery and amoebic dysentery. 2008; WS 287-2008.
10.
go back to reference Tobler WR. A computer movie simulating urban growth in the Detroit region. Econ Geogr. 1970;46:234–40.CrossRef Tobler WR. A computer movie simulating urban growth in the Detroit region. Econ Geogr. 1970;46:234–40.CrossRef
11.
go back to reference Flahaut B, Mouchart M, Martin ES, Thomas I. The local spatial autocorrelation and the kernel method for identifying black zones: a comparative approach. Accid Anal Prev. 2003;35(6):991–1004.CrossRef Flahaut B, Mouchart M, Martin ES, Thomas I. The local spatial autocorrelation and the kernel method for identifying black zones: a comparative approach. Accid Anal Prev. 2003;35(6):991–1004.CrossRef
12.
go back to reference Mattsson BJ, Zipkin EF, Gardner B, Blank PJ, Sauer JR, Royle JA. Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage. PLoS ONE. 2013;8:e55097.CrossRef Mattsson BJ, Zipkin EF, Gardner B, Blank PJ, Sauer JR, Royle JA. Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage. PLoS ONE. 2013;8:e55097.CrossRef
13.
go back to reference Viladomat J, Mazumder R, Mcinturff A, McCauley DJ, Hastie T. Assessing the significance of global and local correlations under spatial autocorrelation: a nonparametric approach. Biometrics. 2014;70(2):409–18.CrossRef Viladomat J, Mazumder R, Mcinturff A, McCauley DJ, Hastie T. Assessing the significance of global and local correlations under spatial autocorrelation: a nonparametric approach. Biometrics. 2014;70(2):409–18.CrossRef
14.
go back to reference Tillé Y, Dickson MM, Espa G, Giuliani D. Measuring the spatial balance of a sample: a new measure based on the Moran’s I index. Spat Stat. 2018;23:182–92.CrossRef Tillé Y, Dickson MM, Espa G, Giuliani D. Measuring the spatial balance of a sample: a new measure based on the Moran’s I index. Spat Stat. 2018;23:182–92.CrossRef
16.
go back to reference Wu X, Hu S, Kwaku AB, Li Q, Luo K, Zhou Y, Tan H. Spatio-temporal clustering analysis and its determinants of hand, foot and mouth disease in Hunan, China, 2009–2015. BMC Infect Dis. 2017;17(1):645.CrossRef Wu X, Hu S, Kwaku AB, Li Q, Luo K, Zhou Y, Tan H. Spatio-temporal clustering analysis and its determinants of hand, foot and mouth disease in Hunan, China, 2009–2015. BMC Infect Dis. 2017;17(1):645.CrossRef
17.
go back to reference Zhu B, Fu Y, Liu J, Ying M. Notifiable sexually transmitted infections in China: epidemiologic trends and spatial changing patterns. Sustainability. 2017;9(10):1784.CrossRef Zhu B, Fu Y, Liu J, Ying M. Notifiable sexually transmitted infections in China: epidemiologic trends and spatial changing patterns. Sustainability. 2017;9(10):1784.CrossRef
18.
go back to reference Waldhör T. The spatial autocorrelation coefficient Moran’s I under heteroscedasticity. Stat Med. 2010;15(7–9):887–92. Waldhör T. The spatial autocorrelation coefficient Moran’s I under heteroscedasticity. Stat Med. 2010;15(7–9):887–92.
19.
go back to reference Anselin L. Local Indicator of Spatial Association—LISA. Geogr Anal. 2010;27(2):93–115.CrossRef Anselin L. Local Indicator of Spatial Association—LISA. Geogr Anal. 2010;27(2):93–115.CrossRef
20.
go back to reference Anselin L. Local Indicator of Spatial Association—LISA. Geogr Anal. 1995;27:93-115. CrossRef Anselin L. Local Indicator of Spatial Association—LISA. Geogr Anal. 1995;27:93-115. CrossRef
21.
go back to reference Kulldorff M. A spatial scan statistic. Commun Stat Theory Methods. 1997;26:1481–96.CrossRef Kulldorff M. A spatial scan statistic. Commun Stat Theory Methods. 1997;26:1481–96.CrossRef
22.
go back to reference Kulldorff M, Heffernan R, Hartman J, Assunçao R, Mostashari F. A space–time permutation scan statistic for disease outbreak detection. PLoS Med. 2005;2(3):e59.CrossRef Kulldorff M, Heffernan R, Hartman J, Assunçao R, Mostashari F. A space–time permutation scan statistic for disease outbreak detection. PLoS Med. 2005;2(3):e59.CrossRef
23.
go back to reference Kulldorff M, Huang L, Pickle L, Duczmal L. An elliptic spatial scan statistic. Stat Med. 2006;25(22):3929–43.CrossRef Kulldorff M, Huang L, Pickle L, Duczmal L. An elliptic spatial scan statistic. Stat Med. 2006;25(22):3929–43.CrossRef
24.
go back to reference Kleinman KP, Abrams AM, Kulldorff M, Platt R. A model-adjusted space–time scan statistic with an application to syndromic surveillance. Epidemiol Infect. 2005;133(3):409–19.CrossRef Kleinman KP, Abrams AM, Kulldorff M, Platt R. A model-adjusted space–time scan statistic with an application to syndromic surveillance. Epidemiol Infect. 2005;133(3):409–19.CrossRef
25.
go back to reference Zhu B, Liu J, Fu Y, Zhang B, Mao Y. Spatio-temporal epidemiology of viral hepatitis in China (2003–2015): implications for prevention and control policies. Int J Environ Res Public Health. 2018;15(4):661.CrossRef Zhu B, Liu J, Fu Y, Zhang B, Mao Y. Spatio-temporal epidemiology of viral hepatitis in China (2003–2015): implications for prevention and control policies. Int J Environ Res Public Health. 2018;15(4):661.CrossRef
26.
go back to reference Kulldorff M, Feuer EJ, Miller BA, Freedman LS. Breast cancer clusters in the northeast United States: a geographic analysis. Am J Epidemiol. 1997;146(2):161–70.CrossRef Kulldorff M, Feuer EJ, Miller BA, Freedman LS. Breast cancer clusters in the northeast United States: a geographic analysis. Am J Epidemiol. 1997;146(2):161–70.CrossRef
27.
go back to reference Abolfazl M, Abbas A, Mostafa K. Spatial and spatio-temporal analysis of human brucellosis in Iran. Trans R Soc Trop Med Hyg. 2014;11:721–8. Abolfazl M, Abbas A, Mostafa K. Spatial and spatio-temporal analysis of human brucellosis in Iran. Trans R Soc Trop Med Hyg. 2014;11:721–8.
28.
go back to reference He-Yan WU, Xiao WH, Guang-Zhi LU. Rural environmental sanitation in Guangdong, 2011–2016. Mod Prev Med. 2018;45(15):2713–8. He-Yan WU, Xiao WH, Guang-Zhi LU. Rural environmental sanitation in Guangdong, 2011–2016. Mod Prev Med. 2018;45(15):2713–8.
29.
go back to reference Wei XY, Tian KC, You LU. Epidemic characteristics and etiological analysis of bacillary dysentery in Guizhou province during the period of 2007–2010. Pract Prev Med. 2012;19(08):1185–6. Wei XY, Tian KC, You LU. Epidemic characteristics and etiological analysis of bacillary dysentery in Guizhou province during the period of 2007–2010. Pract Prev Med. 2012;19(08):1185–6.
30.
go back to reference Wang X, Zhang Y, Xing DG, Wen T, Meng QY, Tang L. Analysis on the epidemiological characteristics and temporal-spatial clusters of bacillary dysentery incidence in Chongqing from 2005 to 2015. Chin J Dis Control Prev. 2018;22(06):594–8. Wang X, Zhang Y, Xing DG, Wen T, Meng QY, Tang L. Analysis on the epidemiological characteristics and temporal-spatial clusters of bacillary dysentery incidence in Chongqing from 2005 to 2015. Chin J Dis Control Prev. 2018;22(06):594–8.
31.
go back to reference Liu D, Qiu L, Shi Y. Epidemiological analysis of spatio-temporal distribution of bacterial dysentery in Shaanxi Province, 2004–2017. Chin J Health Stat. 2019;36(02):176–80. Liu D, Qiu L, Shi Y. Epidemiological analysis of spatio-temporal distribution of bacterial dysentery in Shaanxi Province, 2004–2017. Chin J Health Stat. 2019;36(02):176–80.
32.
go back to reference Gao L. Current status of research on bacterial dysentery. Occup Health. 2017;33(02):277–81. Gao L. Current status of research on bacterial dysentery. Occup Health. 2017;33(02):277–81.
33.
go back to reference Cui CY, Wei Z, Office C. Epidemiological characteristics of bacillary dysentery in Xi’an City from 2012–2017. Occup Health. 2019;35(09):1232–4. Cui CY, Wei Z, Office C. Epidemiological characteristics of bacillary dysentery in Xi’an City from 2012–2017. Occup Health. 2019;35(09):1232–4.
34.
go back to reference Xu C, Xiao G, Wang J, Zhang X, Liang J. Spatiotemporal risk of bacillary dysentery and sensitivity to meteorological factors in Hunan Province, China. Int J Environ Res Public Health. 2018;15(1):47.CrossRef Xu C, Xiao G, Wang J, Zhang X, Liang J. Spatiotemporal risk of bacillary dysentery and sensitivity to meteorological factors in Hunan Province, China. Int J Environ Res Public Health. 2018;15(1):47.CrossRef
35.
go back to reference Chen Y, Liu X, Kong Q, Huang Y. Epidemiological characteristics of bacillary dysentery in Xicheng District of Beijing from 2014 to 2017. J Med Pest Control. 2019;35(07):645–7. Chen Y, Liu X, Kong Q, Huang Y. Epidemiological characteristics of bacillary dysentery in Xicheng District of Beijing from 2014 to 2017. J Med Pest Control. 2019;35(07):645–7.
36.
go back to reference Dongyu XU, Liu B, Zheng L, Lou Y, Department C. Hierarchical clustering analysis on the incidence of five types of common intestinal infectious diseases in China. J Prev Med Inf. 2018;34(01):9-12. Dongyu XU, Liu B, Zheng L, Lou Y, Department C. Hierarchical clustering analysis on the incidence of five types of common intestinal infectious diseases in China. J Prev Med Inf. 2018;34(01):9-12.
37.
go back to reference Von Seidlein L, Kim DR, Ali M, Lee H, Wang XY, Thiem VD, Canh DG, Chaicumpa W, Agtini MD, Hossain A. A multicentre study of Shigella diarrhoea in six Asian countries: disease burden, clinical manifestations, and microbiology. PLoS Med. 2006;3(9):e353.CrossRef Von Seidlein L, Kim DR, Ali M, Lee H, Wang XY, Thiem VD, Canh DG, Chaicumpa W, Agtini MD, Hossain A. A multicentre study of Shigella diarrhoea in six Asian countries: disease burden, clinical manifestations, and microbiology. PLoS Med. 2006;3(9):e353.CrossRef
38.
go back to reference Chang ZR, Sun QZ, Pei YX, Zhang J, Sun JL. Surveillance for bacillary dysentery in China, 2012. Dis Surveill. 2014;29(07):528–32. Chang ZR, Sun QZ, Pei YX, Zhang J, Sun JL. Surveillance for bacillary dysentery in China, 2012. Dis Surveill. 2014;29(07):528–32.
39.
go back to reference Wang XY, Tao F, Xiao D, Lee H, Deen J, Gong J, Zhao Y, Zhou W, Li W, Shen B. Trend and disease burden of bacillary dysentery in China (1991–2000). Bull World Health Organ. 2006;84(7):561.CrossRef Wang XY, Tao F, Xiao D, Lee H, Deen J, Gong J, Zhao Y, Zhou W, Li W, Shen B. Trend and disease burden of bacillary dysentery in China (1991–2000). Bull World Health Organ. 2006;84(7):561.CrossRef
40.
go back to reference Wang X, Zhang Y, Shi Q. Spatial distribution of hot spots of bacterial dysentery and related environmental factors in southwestern China. Dis Surveill. 2018;33(7):573–9. Wang X, Zhang Y, Shi Q. Spatial distribution of hot spots of bacterial dysentery and related environmental factors in southwestern China. Dis Surveill. 2018;33(7):573–9.
41.
go back to reference Wang X, Zhang Y, Ma J. Factors influencing the incidence of bacterial dysentery in parts of southwest China, using data from the geodetector. Chin J Epidemiol. 2019;40(8):953–9. Wang X, Zhang Y, Ma J. Factors influencing the incidence of bacterial dysentery in parts of southwest China, using data from the geodetector. Chin J Epidemiol. 2019;40(8):953–9.
Metadata
Title
Spatio-temporal analysis of bacillary dysentery in Sichuan province, China, 2011–2019
Authors
Yao Zhang
Mengyuan Zhang
Dianju Kang
Wei Sun
Changhong Yang
Rongjie Wei
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Infectious Diseases / Issue 1/2021
Electronic ISSN: 1471-2334
DOI
https://doi.org/10.1186/s12879-021-06738-9

Other articles of this Issue 1/2021

BMC Infectious Diseases 1/2021 Go to the issue
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.