Skip to main content
Top
Published in: BMC Infectious Diseases 1/2014

Open Access 01-12-2014 | Research article

Spatial pattern of severe acute respiratory syndrome in-out flow in 2003 in Mainland China

Authors: Chengdong Xu, Jinfeng Wang, Li Wang, Chunxiang Cao

Published in: BMC Infectious Diseases | Issue 1/2014

Login to get access

Abstract

Background

Severe acute respiratory syndrome (SARS) spread to 32 countries and regions within a few months in 2003. There were 5327 SARS cases from November 2002 to May 2003 in Mainland China, which involved 29 provinces, resulted in 349 deaths, and directly caused economic losses of $18.3 billion.

Methods

This study used an in-out flow model and flow mapping to visualize and explore the spatial pattern of SARS transmission in different regions. In-out flow is measured by the in-out degree and clustering coefficient of SARS. Flow mapping is an exploratory method of spatial visualization for interaction data.

Results

The findings were as follows. (1) SARS in-out flow had a clear hierarchy. It formed two main centers, Guangdong in South China and Beijing in North China, and two secondary centers, Shanxi and Inner Mongolia, both connected to Beijing. (2) “Spring Festival travel” strengthened external flow, but “SARS panic effect” played a more significant role and pushed the external flow to the peak. (3) External flow and its three typical kinds showed obvious spatial heterogeneity, such as self-spreading flow (spatial displacement of SARS cases only within the province or municipality of onset and medical locations); hospitalized flow (spatial displacement of SARS cases that had been seen by a hospital doctor); and migrant flow (spatial displacement of SARS cases among migrant workers). (4) Internal and external flow tended to occur in younger groups, and occupational differentiation was particularly evident. Low-income groups of male migrants aged 19–35 years were the main routes of external flow.

Conclusions

During 2002–2003, SARS in-out flow played an important role in countrywide transmission of the disease in Mainland China. The flow had obvious spatial heterogeneity, which was influenced by migrants’ behavior characteristics. In addition, the Chinese holiday effect led to irregular spread of SARS, but the panic effect was more apparent in the middle and late stages of the epidemic. These findings constitute valuable input to prevent and control future serious infectious diseases like SARS.
Appendix
Available only for authorised users
Literature
1.
go back to reference Mills CE, Robins JM, Lipsitch M: Transmissibility of 1918 pandemic influenza. Nature. 2004, 432 (7019): 904-906. 10.1038/nature03063.CrossRefPubMed Mills CE, Robins JM, Lipsitch M: Transmissibility of 1918 pandemic influenza. Nature. 2004, 432 (7019): 904-906. 10.1038/nature03063.CrossRefPubMed
2.
go back to reference McCloskey B, Zumla A, Stephens G, Heymann DL, Memish ZA: Applying lessons from SARS to a newly identified coronavirus. Lancet Infect Dis. 2013, 13 (5): 384-385. 10.1016/S1473-3099(13)70082-3.CrossRefPubMed McCloskey B, Zumla A, Stephens G, Heymann DL, Memish ZA: Applying lessons from SARS to a newly identified coronavirus. Lancet Infect Dis. 2013, 13 (5): 384-385. 10.1016/S1473-3099(13)70082-3.CrossRefPubMed
3.
go back to reference Alcorn T: As H7N9 spreads in China, experts watch and wait. Lancet. 2013, 381 (9875): 1347-10.1016/S0140-6736(13)60868-5.CrossRefPubMed Alcorn T: As H7N9 spreads in China, experts watch and wait. Lancet. 2013, 381 (9875): 1347-10.1016/S0140-6736(13)60868-5.CrossRefPubMed
5.
go back to reference Hu A, Li C: Analysis of SARS impact on China’s economy. 204th Xiangshan Science Conference workshop “SARS Prevention and Control” 2003., Hu A, Li C: Analysis of SARS impact on China’s economy. 204th Xiangshan Science Conference workshop “SARS Prevention and Control” 2003.,
6.
go back to reference Li Z, Cui H, Yang H, Li X: SI Models and Piecewise SI Model on SARS Forecasting. J Remote Sensing. 2003, 7 (5): 345-349. Li Z, Cui H, Yang H, Li X: SI Models and Piecewise SI Model on SARS Forecasting. J Remote Sensing. 2003, 7 (5): 345-349.
7.
go back to reference Wang JF, Meng B, Zheng X, Liu J, Han W, Wu J, Liu X, Li X, Song X: Analysis on the multi-distribution and the major influencing factors on severe acute respiratory syndrome in Beijing. Chinese J Epidemiol. 2005, 26 (3): 164- Wang JF, Meng B, Zheng X, Liu J, Han W, Wu J, Liu X, Li X, Song X: Analysis on the multi-distribution and the major influencing factors on severe acute respiratory syndrome in Beijing. Chinese J Epidemiol. 2005, 26 (3): 164-
8.
go back to reference Massad E, Burattini MN, Lopez LF, Coutinho FAB: Forecasting versus projection models in epidemiology: the case of the SARS epidemics. Med Hypotheses. 2005, 65 (1): 17-22. 10.1016/j.mehy.2004.09.029.CrossRefPubMed Massad E, Burattini MN, Lopez LF, Coutinho FAB: Forecasting versus projection models in epidemiology: the case of the SARS epidemics. Med Hypotheses. 2005, 65 (1): 17-22. 10.1016/j.mehy.2004.09.029.CrossRefPubMed
9.
go back to reference Lipsitch M, Cohen T, Cooper B, Robins JM, Ma S, James L, Gopalakrishna G, Chew SK, Tan CC, Samore MH: Transmission dynamics and control of severe acute respiratory syndrome. Science. 2003, 300 (5627): 1966-1970. 10.1126/science.1086616.CrossRefPubMedPubMedCentral Lipsitch M, Cohen T, Cooper B, Robins JM, Ma S, James L, Gopalakrishna G, Chew SK, Tan CC, Samore MH: Transmission dynamics and control of severe acute respiratory syndrome. Science. 2003, 300 (5627): 1966-1970. 10.1126/science.1086616.CrossRefPubMedPubMedCentral
10.
go back to reference Riley S, Fraser C, Donnelly CA, Ghani AC, Abu-Raddad LJ, Hedley AJ, Leung GM, Ho LM, Lam TH, Thach TQ, Chau P, Chan KP, Leung PY, Tsang T, Ho W, Lee KH, Lau EMC, Ferguson NM, Anderson RM: Transmission dynamics of the etiological agent of SARS in Hong Kong: impact of public health interventions. Science. 2003, 300 (5627): 1961-1966. 10.1126/science.1086478.CrossRefPubMed Riley S, Fraser C, Donnelly CA, Ghani AC, Abu-Raddad LJ, Hedley AJ, Leung GM, Ho LM, Lam TH, Thach TQ, Chau P, Chan KP, Leung PY, Tsang T, Ho W, Lee KH, Lau EMC, Ferguson NM, Anderson RM: Transmission dynamics of the etiological agent of SARS in Hong Kong: impact of public health interventions. Science. 2003, 300 (5627): 1961-1966. 10.1126/science.1086478.CrossRefPubMed
11.
go back to reference Wang JF, Christakos G, Han WG, Meng B: Data-driven exploration of ‘spatial pattern-time process-driving forces’ associations of SARS epidemic in Beijing. China J Public Health. 2008, 30 (3): 234-244. 10.1093/pubmed/fdn023.CrossRef Wang JF, Christakos G, Han WG, Meng B: Data-driven exploration of ‘spatial pattern-time process-driving forces’ associations of SARS epidemic in Beijing. China J Public Health. 2008, 30 (3): 234-244. 10.1093/pubmed/fdn023.CrossRef
12.
go back to reference Cao ZD, Zeng DJ, Zheng XL, Wang QY, Wang FY, Wang JF, Wang XL: Spatio-temporal evolution of Beijing 2003 SARS epidemic. Sci China Earth Sci. 2010, 53 (7): 1017-1028. 10.1007/s11430-010-0043-x.CrossRef Cao ZD, Zeng DJ, Zheng XL, Wang QY, Wang FY, Wang JF, Wang XL: Spatio-temporal evolution of Beijing 2003 SARS epidemic. Sci China Earth Sci. 2010, 53 (7): 1017-1028. 10.1007/s11430-010-0043-x.CrossRef
13.
go back to reference Fan XS, Ying LG: An exploratory spatial data analysis of SARS epidemic in China. Adv Earth Sci. 2005, 20 (3): 282-288. Fan XS, Ying LG: An exploratory spatial data analysis of SARS epidemic in China. Adv Earth Sci. 2005, 20 (3): 282-288.
14.
go back to reference Cao ZD, Wang JF, Gao YG, Han WG, Feng XL, Zeng G: Risk factors and autocorrelation characteristics on SARS in Guangzhou. Acta Geograph Sin. 2008, 63 (9): 981-993. Cao ZD, Wang JF, Gao YG, Han WG, Feng XL, Zeng G: Risk factors and autocorrelation characteristics on SARS in Guangzhou. Acta Geograph Sin. 2008, 63 (9): 981-993.
15.
go back to reference Yang H, Li X, Shi H, Zhao K, Han L: “ Fly dots” spreading model of SARS along transportation. J Remote Sensing-Beijing. 2003, 7 (4): 251-255. Yang H, Li X, Shi H, Zhao K, Han L: “ Fly dots” spreading model of SARS along transportation. J Remote Sensing-Beijing. 2003, 7 (4): 251-255.
16.
go back to reference Cao C, Li X, Yan J, Jin S: Geo-spatial information and analysis of SARS spread trend. J Remote Sensing. 2003, 7 (4): 241-244. Cao C, Li X, Yan J, Jin S: Geo-spatial information and analysis of SARS spread trend. J Remote Sensing. 2003, 7 (4): 241-244.
17.
go back to reference Peiris JSM, Chu CM, Cheng VCC, Chan KS, Hung IFN, Poon LLM, Law KI, Tang BSF, Hon TYW, Chan CS, Chan KH, Ng JSC, Zheng BJ, Ng WL, Lai RWM, Guan Y, Yuen KY, Hku Uch Sars Study Grp: Clinical progression and viral load in a community outbreak of coronavirus-associated SARS pneumonia: a prospective study. Lancet. 2003, 361 (9371): 1767-1772. 10.1016/S0140-6736(03)13412-5.CrossRefPubMed Peiris JSM, Chu CM, Cheng VCC, Chan KS, Hung IFN, Poon LLM, Law KI, Tang BSF, Hon TYW, Chan CS, Chan KH, Ng JSC, Zheng BJ, Ng WL, Lai RWM, Guan Y, Yuen KY, Hku Uch Sars Study Grp: Clinical progression and viral load in a community outbreak of coronavirus-associated SARS pneumonia: a prospective study. Lancet. 2003, 361 (9371): 1767-1772. 10.1016/S0140-6736(03)13412-5.CrossRefPubMed
18.
go back to reference Harris SR, Feil EJ, Holden MTG, Quail MA, Nickerson EK, Chantratita N, Gardete S, Tavares A, Day N, Lindsay JA: Evolution of MRSA during hospital transmission and intercontinental spread. Science. 2010, 327 (5964): 469-10.1126/science.1182395.CrossRefPubMedPubMedCentral Harris SR, Feil EJ, Holden MTG, Quail MA, Nickerson EK, Chantratita N, Gardete S, Tavares A, Day N, Lindsay JA: Evolution of MRSA during hospital transmission and intercontinental spread. Science. 2010, 327 (5964): 469-10.1126/science.1182395.CrossRefPubMedPubMedCentral
19.
go back to reference Eubank S, Guclu H, Kumar VSA, Marathe MV, Srinivasan A, Toroczkai Z, Wang N: Modelling disease outbreaks in realistic urban social networks. Nature. 2004, 429 (6988): 180-184. 10.1038/nature02541.CrossRefPubMed Eubank S, Guclu H, Kumar VSA, Marathe MV, Srinivasan A, Toroczkai Z, Wang N: Modelling disease outbreaks in realistic urban social networks. Nature. 2004, 429 (6988): 180-184. 10.1038/nature02541.CrossRefPubMed
20.
go back to reference Charleston B, Bankowski BM, Gubbins S, Chase-Topping ME, Schley D, Howey R, Barnett PV, Gibson D, Juleff ND, Woolhouse MEJ: Relationship between clinical signs and transmission of an infectious disease and the implications for control. Science. 2011, 332 (6030): 726-729. 10.1126/science.1199884.CrossRefPubMed Charleston B, Bankowski BM, Gubbins S, Chase-Topping ME, Schley D, Howey R, Barnett PV, Gibson D, Juleff ND, Woolhouse MEJ: Relationship between clinical signs and transmission of an infectious disease and the implications for control. Science. 2011, 332 (6030): 726-729. 10.1126/science.1199884.CrossRefPubMed
21.
go back to reference Wang JF, McMichael AJ, Meng B, Becker NG, Han WG, Glass K, Wu JL, Liu XH, Liu JY, Li LW, Zheng XY: Spatial dynamics of an epidemic of severe acute respiratory syndrome in an urban area. Bull World Health Organ. 2006, 84 (12): 965-968. 10.2471/BLT.06.030247.CrossRefPubMedPubMedCentral Wang JF, McMichael AJ, Meng B, Becker NG, Han WG, Glass K, Wu JL, Liu XH, Liu JY, Li LW, Zheng XY: Spatial dynamics of an epidemic of severe acute respiratory syndrome in an urban area. Bull World Health Organ. 2006, 84 (12): 965-968. 10.2471/BLT.06.030247.CrossRefPubMedPubMedCentral
22.
go back to reference Hu B, Gong J, Sun J, Zhou J: Exploring the epidemic transmission network of SARS in-out flow in mainland China. Chinese Sci Bull, 58(15):1818–1831., Hu B, Gong J, Sun J, Zhou J: Exploring the epidemic transmission network of SARS in-out flow in mainland China. Chinese Sci Bull, 58(15):1818–1831.,
23.
go back to reference Watts DJ, Strogatz SH: Collective dynamics of ‘small-world’ networks. Nature. 1998, 393 (6684): 440-442. 10.1038/30918.CrossRefPubMed Watts DJ, Strogatz SH: Collective dynamics of ‘small-world’ networks. Nature. 1998, 393 (6684): 440-442. 10.1038/30918.CrossRefPubMed
24.
go back to reference Boccaletti S, Latora V, Moreno Y, Chavez M, Hwang D-U: Complex networks: structure and dynamics. Phys Rep. 2006, 424 (4): 175-308. 10.1016/j.physrep.2005.10.009.CrossRef Boccaletti S, Latora V, Moreno Y, Chavez M, Hwang D-U: Complex networks: structure and dynamics. Phys Rep. 2006, 424 (4): 175-308. 10.1016/j.physrep.2005.10.009.CrossRef
25.
go back to reference Dye C, Gay N: Modeling the SARS epidemic. Science. 2003, 300 (5627): 1884-1885. 10.1126/science.1086925.CrossRefPubMed Dye C, Gay N: Modeling the SARS epidemic. Science. 2003, 300 (5627): 1884-1885. 10.1126/science.1086925.CrossRefPubMed
26.
go back to reference Boyandin I, Bertini E, Bak P, Lalanne D: Flowstrates: an approach for visual exploration of temporal origin–destination data. Comput Graph Forum. 2011, 30 (3): 971-980. 10.1111/j.1467-8659.2011.01946.x.CrossRef Boyandin I, Bertini E, Bak P, Lalanne D: Flowstrates: an approach for visual exploration of temporal origin–destination data. Comput Graph Forum. 2011, 30 (3): 971-980. 10.1111/j.1467-8659.2011.01946.x.CrossRef
27.
go back to reference Guo DS: Flow mapping and multivariate visualization of large spatial interaction data. Ieee T Vis Comput Gr. 2009, 15 (6): 1041-1048. 10.1109/TVCG.2009.143.CrossRef Guo DS: Flow mapping and multivariate visualization of large spatial interaction data. Ieee T Vis Comput Gr. 2009, 15 (6): 1041-1048. 10.1109/TVCG.2009.143.CrossRef
28.
go back to reference Wang JF: Spatial Analysis. Beijing: Science Press; 2006. Wang JF: Spatial Analysis. Beijing: Science Press; 2006.
29.
go back to reference Wei HK: Modern Regional Economics. Beijing: Economy & Management Publishing House; 2006. Wei HK: Modern Regional Economics. Beijing: Economy & Management Publishing House; 2006.
Metadata
Title
Spatial pattern of severe acute respiratory syndrome in-out flow in 2003 in Mainland China
Authors
Chengdong Xu
Jinfeng Wang
Li Wang
Chunxiang Cao
Publication date
01-12-2014
Publisher
BioMed Central
Published in
BMC Infectious Diseases / Issue 1/2014
Electronic ISSN: 1471-2334
DOI
https://doi.org/10.1186/s12879-014-0721-y

Other articles of this Issue 1/2014

BMC Infectious Diseases 1/2014 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.