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Assessing environmental factors associated with regional schistosomiasis prevalence in Anhui Province, Peoples' Republic of China using a geographical detector method.

Abstract Schistosomiasis is a water-borne disease caused by trematode worms belonging to genus Schistosoma, which is prevalent most of the developing world. Transmission of the disease is usually associated with multiple biological characteristics and social factors but also factors can play a role. Few studies have assessed the exact and interactive influence of each factor promoting schistosomiasis transmission.
PMID
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Authors

Mayor MeshTerms
Keywords

China

Environmental factors

Geographic information systems

Geographical detector

Schistosoma japonicum

Spatial variation analysis

Journal Title infectious diseases of poverty
Publication Year Start




PMID- 28416001
OWN - NLM
STAT- In-Process
DA  - 20170418
LR  - 20170421
IS  - 2049-9957 (Electronic)
IS  - 2049-9957 (Linking)
VI  - 6
IP  - 1
DP  - 2017 Apr 17
TI  - Assessing environmental factors associated with regional schistosomiasis
      prevalence in Anhui Province, Peoples' Republic of China using a geographical
      detector method.
PG  - 87
LID - 10.1186/s40249-017-0299-x [doi]
AB  - BACKGROUND: Schistosomiasis is a water-borne disease caused by trematode worms
      belonging to genus Schistosoma, which is prevalent most of the developing world. 
      Transmission of the disease is usually associated with multiple biological
      characteristics and social factors but also factors can play a role. Few studies 
      have assessed the exact and interactive influence of each factor promoting
      schistosomiasis transmission. METHODS: We used a series of different detectors
      (i.e., specific detector, risk detector, ecological detector and interaction
      detector) to evaluate separate and interactive effects of the environmental
      factors on schistosomiasis prevalence. Specifically, (i) specific detector
      quantifies the impact of a risk factor on an observed spatial disease pattern,
      which were ranked statistically by a value of Power of Determinate (PD)
      calculation; (ii) risk detector detects high risk areas of a disease on the
      condition that the study area is stratified by a potential risk factor; (iii)
      ecological detector explores whether a risk factor is more significant than
      another in controlling the spatial pattern of a disease; (iv) interaction
      detector probes whether two risk factors when taken together weaken or enhance
      one another, or whether they are independent in developing a disease. Infection
      data of schistosomiasis based on conventional surveys were obtained at the county
      level from the health authorities in Anhui Province, China and used in
      combination with information from Chinese weather stations and internationally
      available environmental data. RESULTS: The specific detector identified various
      factors of potential importance as follows: Proximity to Yangtze River (0.322) > 
      Land cover (0.285) > sunshine hours (0.256) > population density (0.109) >
      altitude (0.090) > the normalized different vegetation index (NDVI) (0.077) >
      land surface temperature at daytime (LSTday) (0.007). The risk detector indicated
      that areas of schistosomiasis high risk were located within a buffer distance of 
      50 km from Yangtze River. The ecological detector disclosed that the factors
      investigated have significantly different effects. The interaction detector
      revealed that interaction between the factors enhanced their main effects in most
      cases. CONCLUSION: Proximity to Yangtze River had the strongest effect on
      schistosomiasis prevalence followed by land cover and sunshine hours, while the
      remaining factors had only weak influence. Interaction between factors played an 
      even more important role in influencing schistosomiasis prevalence than each
      factor on its own. High risk regions influenced by strong interactions need to be
      targeted for disease control intervention.
FAU - Hu, Yi
AU  - Hu Y
AD  - Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 
      200032, China.
AD  - Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
AD  - Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan
      University, Shanghai, China.
AD  - Collaborative Innovation Center of Social Risks Governance in Health, School of
      Public Health, Fudan University, Shanghai, China.
FAU - Xia, Congcong
AU  - Xia C
AD  - Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 
      200032, China.
AD  - Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
AD  - Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan
      University, Shanghai, China.
AD  - Collaborative Innovation Center of Social Risks Governance in Health, School of
      Public Health, Fudan University, Shanghai, China.
FAU - Li, Shizhu
AU  - Li S
AD  - National Institute of Parasitic Diseases, Chinese Center for Disease Control and 
      Prevention, Key Laboratory of Parasite and Vector Biology, Ministry of Health;
      WHO Collaborating Center for Tropical diseases, Shanghai, People's Republic of
      China. [email protected]
AD  - , No.130 Dong'an Road, Xuhui District, Shanghai, 200032, China. [email protected]
FAU - Ward, Michael P
AU  - Ward MP
AD  - Faculty of Veterinary Science, The University of Sydney NSW, Sydney, Australia.
FAU - Luo, Can
AU  - Luo C
AD  - Department of Environmental Art and Architecture, Changsha Environmental
      Protection Vocational Technical College, Changsha, Hunan, People's Republic of
      China.
FAU - Gao, Fenghua
AU  - Gao F
AD  - Anhui Institute of Parasitic Diseases, Wuhu, People's Republic of China.
FAU - Wang, Qizhi
AU  - Wang Q
AD  - Anhui Institute of Parasitic Diseases, Wuhu, People's Republic of China.
FAU - Zhang, Shiqing
AU  - Zhang S
AD  - Anhui Institute of Parasitic Diseases, Wuhu, People's Republic of China.
FAU - Zhang, Zhijie
AU  - Zhang Z
AD  - Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 
      200032, China. [email protected]
AD  - Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
      [email protected]
AD  - Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan
      University, Shanghai, China. [email protected]
AD  - Collaborative Innovation Center of Social Risks Governance in Health, School of
      Public Health, Fudan University, Shanghai, China. [email protected]
AD  - , No.130 Dong'an Road, Xuhui District, Shanghai, 200032, China.
      [email protected]
LA  - eng
PT  - Journal Article
DEP - 20170417
PL  - England
TA  - Infect Dis Poverty
JT  - Infectious diseases of poverty
JID - 101606645
PMC - PMC5392949
OTO - NOTNLM
OT  - China
OT  - Environmental factors
OT  - Geographic information systems
OT  - Geographical detector
OT  - Schistosoma japonicum
OT  - Spatial variation analysis
EDAT- 2017/04/19 06:00
MHDA- 2017/04/19 06:00
CRDT- 2017/04/19 06:00
PHST- 2017/02/22 [received]
PHST- 2017/04/03 [accepted]
AID - 10.1186/s40249-017-0299-x [doi]
AID - 10.1186/s40249-017-0299-x [pii]
PST - epublish
SO  - Infect Dis Poverty. 2017 Apr 17;6(1):87. doi: 10.1186/s40249-017-0299-x.

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