Identifying determinants for the seropositive rate of schistosomiasis in Hunan province, China: A multi-scale geographically weighted regression model
Schistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis elimination and the need for precision prevention and control, identifying determinants at a fine scale is urgent and necessary, especially for resource deploy...
Saved in:
| Published in | PLoS neglected tropical diseases Vol. 17; no. 7; p. e0011466 |
|---|---|
| Main Authors | , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
01.07.2023
|
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | Schistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis elimination and the need for precision prevention and control, identifying determinants at a fine scale is urgent and necessary, especially for resource deployment in practice. Our study aimed to identify the determinants for the seropositive rate of schistosomiasis at the village level and to explore their spatial variations in local space.
The seropositive rates of schistosomiasis were collected from 1714 villages or communities in Human Province, and six spatial regression models including ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), robust GWR (RGWR) and multiscale GWR (MGWR) were used to fit the data.
MGWR was the best-fitting model (R2: 0.821, AICc:2727.092). Overall, the nearest distance from the river had the highest mean negative correlation, followed by proportion of households using well water and the annual average daytime surface temperature. The proportions of unmodified toilets showed the highest mean positive correlation, followed by the snail infested area, and the number of cattle. In spatial variability, the regression coefficients for the nearest distance from the river, annual average daytime surface temperature and the proportion of unmodified toilets were significant in all villages or communities and varied little in local space. The other significant determinants differed substantially in local space and had significance ratios ranging from 41% to 70%, including the number of cattle, the snail infested area and the proportion of households using well water.
Our study shows that MGWR was well performed for the spatial variability of schistosomiasis in Hunan province. The spatial variability was different for different determinants. The findings for the determinants for the seropositive rate and mapped variability for some key determinants at the village level can be used for developing precision intervention measure for schistosomiasis control. |
|---|---|
| AbstractList | Background Schistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis elimination and the need for precision prevention and control, identifying determinants at a fine scale is urgent and necessary, especially for resource deployment in practice. Our study aimed to identify the determinants for the seropositive rate of schistosomiasis at the village level and to explore their spatial variations in local space. Methodology The seropositive rates of schistosomiasis were collected from 1714 villages or communities in Human Province, and six spatial regression models including ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), robust GWR (RGWR) and multiscale GWR (MGWR) were used to fit the data. Principal/Findings MGWR was the best-fitting model (R.sup.2 : 0.821, AICc:2727.092). Overall, the nearest distance from the river had the highest mean negative correlation, followed by proportion of households using well water and the annual average daytime surface temperature. The proportions of unmodified toilets showed the highest mean positive correlation, followed by the snail infested area, and the number of cattle. In spatial variability, the regression coefficients for the nearest distance from the river, annual average daytime surface temperature and the proportion of unmodified toilets were significant in all villages or communities and varied little in local space. The other significant determinants differed substantially in local space and had significance ratios ranging from 41% to 70%, including the number of cattle, the snail infested area and the proportion of households using well water. Conclusions/Significance Our study shows that MGWR was well performed for the spatial variability of schistosomiasis in Hunan province. The spatial variability was different for different determinants. The findings for the determinants for the seropositive rate and mapped variability for some key determinants at the village level can be used for developing precision intervention measure for schistosomiasis control. Schistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis elimination and the need for precision prevention and control, identifying determinants at a fine scale is urgent and necessary, especially for resource deployment in practice. Our study aimed to identify the determinants for the seropositive rate of schistosomiasis at the village level and to explore their spatial variations in local space. The seropositive rates of schistosomiasis were collected from 1714 villages or communities in Human Province, and six spatial regression models including ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), robust GWR (RGWR) and multiscale GWR (MGWR) were used to fit the data. Our study shows that MGWR was well performed for the spatial variability of schistosomiasis in Hunan province. The spatial variability was different for different determinants. The findings for the determinants for the seropositive rate and mapped variability for some key determinants at the village level can be used for developing precision intervention measure for schistosomiasis control. Background Schistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis elimination and the need for precision prevention and control, identifying determinants at a fine scale is urgent and necessary, especially for resource deployment in practice. Our study aimed to identify the determinants for the seropositive rate of schistosomiasis at the village level and to explore their spatial variations in local space. Methodology The seropositive rates of schistosomiasis were collected from 1714 villages or communities in Human Province, and six spatial regression models including ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), robust GWR (RGWR) and multiscale GWR (MGWR) were used to fit the data. Principal/Findings MGWR was the best-fitting model (R2: 0.821, AICc:2727.092). Overall, the nearest distance from the river had the highest mean negative correlation, followed by proportion of households using well water and the annual average daytime surface temperature. The proportions of unmodified toilets showed the highest mean positive correlation, followed by the snail infested area, and the number of cattle. In spatial variability, the regression coefficients for the nearest distance from the river, annual average daytime surface temperature and the proportion of unmodified toilets were significant in all villages or communities and varied little in local space. The other significant determinants differed substantially in local space and had significance ratios ranging from 41% to 70%, including the number of cattle, the snail infested area and the proportion of households using well water. Conclusions/Significance Our study shows that MGWR was well performed for the spatial variability of schistosomiasis in Hunan province. The spatial variability was different for different determinants. The findings for the determinants for the seropositive rate and mapped variability for some key determinants at the village level can be used for developing precision intervention measure for schistosomiasis control. Schistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis elimination and the need for precision prevention and control, identifying determinants at a fine scale is urgent and necessary, especially for resource deployment in practice. Our study aimed to identify the determinants for the seropositive rate of schistosomiasis at the village level and to explore their spatial variations in local space.BACKGROUNDSchistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis elimination and the need for precision prevention and control, identifying determinants at a fine scale is urgent and necessary, especially for resource deployment in practice. Our study aimed to identify the determinants for the seropositive rate of schistosomiasis at the village level and to explore their spatial variations in local space.The seropositive rates of schistosomiasis were collected from 1714 villages or communities in Human Province, and six spatial regression models including ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), robust GWR (RGWR) and multiscale GWR (MGWR) were used to fit the data.METHODOLOGYThe seropositive rates of schistosomiasis were collected from 1714 villages or communities in Human Province, and six spatial regression models including ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), robust GWR (RGWR) and multiscale GWR (MGWR) were used to fit the data.MGWR was the best-fitting model (R2: 0.821, AICc:2727.092). Overall, the nearest distance from the river had the highest mean negative correlation, followed by proportion of households using well water and the annual average daytime surface temperature. The proportions of unmodified toilets showed the highest mean positive correlation, followed by the snail infested area, and the number of cattle. In spatial variability, the regression coefficients for the nearest distance from the river, annual average daytime surface temperature and the proportion of unmodified toilets were significant in all villages or communities and varied little in local space. The other significant determinants differed substantially in local space and had significance ratios ranging from 41% to 70%, including the number of cattle, the snail infested area and the proportion of households using well water.PRINCIPAL/FINDINGSMGWR was the best-fitting model (R2: 0.821, AICc:2727.092). Overall, the nearest distance from the river had the highest mean negative correlation, followed by proportion of households using well water and the annual average daytime surface temperature. The proportions of unmodified toilets showed the highest mean positive correlation, followed by the snail infested area, and the number of cattle. In spatial variability, the regression coefficients for the nearest distance from the river, annual average daytime surface temperature and the proportion of unmodified toilets were significant in all villages or communities and varied little in local space. The other significant determinants differed substantially in local space and had significance ratios ranging from 41% to 70%, including the number of cattle, the snail infested area and the proportion of households using well water.Our study shows that MGWR was well performed for the spatial variability of schistosomiasis in Hunan province. The spatial variability was different for different determinants. The findings for the determinants for the seropositive rate and mapped variability for some key determinants at the village level can be used for developing precision intervention measure for schistosomiasis control.CONCLUSIONS/SIGNIFICANCEOur study shows that MGWR was well performed for the spatial variability of schistosomiasis in Hunan province. The spatial variability was different for different determinants. The findings for the determinants for the seropositive rate and mapped variability for some key determinants at the village level can be used for developing precision intervention measure for schistosomiasis control. Schistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis elimination and the need for precision prevention and control, identifying determinants at a fine scale is urgent and necessary, especially for resource deployment in practice. Our study aimed to identify the determinants for the seropositive rate of schistosomiasis at the village level and to explore their spatial variations in local space. The seropositive rates of schistosomiasis were collected from 1714 villages or communities in Human Province, and six spatial regression models including ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), robust GWR (RGWR) and multiscale GWR (MGWR) were used to fit the data. MGWR was the best-fitting model (R2: 0.821, AICc:2727.092). Overall, the nearest distance from the river had the highest mean negative correlation, followed by proportion of households using well water and the annual average daytime surface temperature. The proportions of unmodified toilets showed the highest mean positive correlation, followed by the snail infested area, and the number of cattle. In spatial variability, the regression coefficients for the nearest distance from the river, annual average daytime surface temperature and the proportion of unmodified toilets were significant in all villages or communities and varied little in local space. The other significant determinants differed substantially in local space and had significance ratios ranging from 41% to 70%, including the number of cattle, the snail infested area and the proportion of households using well water. Our study shows that MGWR was well performed for the spatial variability of schistosomiasis in Hunan province. The spatial variability was different for different determinants. The findings for the determinants for the seropositive rate and mapped variability for some key determinants at the village level can be used for developing precision intervention measure for schistosomiasis control. The elimination of schistosomiasis depends critically on the identification of a set of determinants. A site-specific analysis of the determinants allows organizers to adjust and clarify the focus areas for the next round. This analysis, based on anecdotal evidence and investigations specific to a narrow geographic area at a fine scale, would enhance our understanding of the determinants. Especially for areas where elimination goals are to be achieved, local spatial variation in determinants is worth exploring in depth. In this analysis we included the seropositive rates of schistosomiasis from 1714 villages or communities and established six spatial regression models. Benefiting from determinants with different bandwidths, MGWR was good at simulating schistosomiasis. We also explored the spatial variability of multiple determinants and mapped variability for some key determinants at the village level. We hope the findings will be used for developing precision intervention measure for schistosomiasis control. Background Schistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis elimination and the need for precision prevention and control, identifying determinants at a fine scale is urgent and necessary, especially for resource deployment in practice. Our study aimed to identify the determinants for the seropositive rate of schistosomiasis at the village level and to explore their spatial variations in local space. Methodology The seropositive rates of schistosomiasis were collected from 1714 villages or communities in Human Province, and six spatial regression models including ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), robust GWR (RGWR) and multiscale GWR (MGWR) were used to fit the data. Principal/Findings MGWR was the best-fitting model (R2: 0.821, AICc:2727.092). Overall, the nearest distance from the river had the highest mean negative correlation, followed by proportion of households using well water and the annual average daytime surface temperature. The proportions of unmodified toilets showed the highest mean positive correlation, followed by the snail infested area, and the number of cattle. In spatial variability, the regression coefficients for the nearest distance from the river, annual average daytime surface temperature and the proportion of unmodified toilets were significant in all villages or communities and varied little in local space. The other significant determinants differed substantially in local space and had significance ratios ranging from 41% to 70%, including the number of cattle, the snail infested area and the proportion of households using well water. Conclusions/Significance Our study shows that MGWR was well performed for the spatial variability of schistosomiasis in Hunan province. The spatial variability was different for different determinants. The findings for the determinants for the seropositive rate and mapped variability for some key determinants at the village level can be used for developing precision intervention measure for schistosomiasis control. |
| Audience | Academic |
| Author | Zhou, Jie Zhou, Yibiao Yin, Jiangfan Tong, Yixin Jiang, Honglin Chen, Yue Xia, Meng Wang, Jiamin Jiang, Qingwu Huang, Junhui Tang, Ling Hu, Benjiao Li, Guangping Xu, Ning |
| AuthorAffiliation | 4 Hunan Institute for Schistosomiasis Control, Yueyang, China 3 Fudan University Center for Tropical Disease Research, Shanghai, China 5 School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada 1 Fudan University School of Public Health, Shanghai, China 2 Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China Federal University of Agriculture Abeokuta, NIGERIA |
| AuthorAffiliation_xml | – name: 1 Fudan University School of Public Health, Shanghai, China – name: 3 Fudan University Center for Tropical Disease Research, Shanghai, China – name: 2 Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China – name: 4 Hunan Institute for Schistosomiasis Control, Yueyang, China – name: 5 School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada – name: Federal University of Agriculture Abeokuta, NIGERIA |
| Author_xml | – sequence: 1 givenname: Yixin orcidid: 0000-0002-8188-7031 surname: Tong fullname: Tong, Yixin – sequence: 2 givenname: Ling surname: Tang fullname: Tang, Ling – sequence: 3 givenname: Meng surname: Xia fullname: Xia, Meng – sequence: 4 givenname: Guangping surname: Li fullname: Li, Guangping – sequence: 5 givenname: Benjiao surname: Hu fullname: Hu, Benjiao – sequence: 6 givenname: Junhui surname: Huang fullname: Huang, Junhui – sequence: 7 givenname: Jiamin surname: Wang fullname: Wang, Jiamin – sequence: 8 givenname: Honglin surname: Jiang fullname: Jiang, Honglin – sequence: 9 givenname: Jiangfan surname: Yin fullname: Yin, Jiangfan – sequence: 10 givenname: Ning surname: Xu fullname: Xu, Ning – sequence: 11 givenname: Yue surname: Chen fullname: Chen, Yue – sequence: 12 givenname: Qingwu surname: Jiang fullname: Jiang, Qingwu – sequence: 13 givenname: Jie surname: Zhou fullname: Zhou, Jie – sequence: 14 givenname: Yibiao orcidid: 0000-0002-4635-0802 surname: Zhou fullname: Zhou, Yibiao |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37440524$$D View this record in MEDLINE/PubMed |
| BookMark | eNp9kt-K1DAYxYusuH_0DUQDgnjhjE2TtM3eyDCou7DgjV6HTPO1zZImY5KOzIv4vKZsR2aWRXqRJv2dk_TkXGZn1lnIstc4X2JS4U_3bvRWmuXWRrXMc4xpWT7LLjAnbFFUhJ0dvZ9nlyHc5znjrMYvsnNSUZqzgl5kf24V2KjbvbYdUhDBD9pKGwNqnUexBxTAu60LOuodIC8jINei0PQ6RBfcoGXQAWmLbsakQ1vvdto28BGt-2R0jVZoGE3Ui9BIA6gD13m57XWamT36DbrrIyjkofMQgnYWDU6BeZk9b6UJ8Goer7KfX7_8WN8s7r5_u12v7hYNYzwuIC9LXJJaNRvJlNoozltKN4xzqBipWyoJkXWVKwI8B6gLQjGQpsKFqmuVkrnK3j74bo0LYo40iKJmmKeMKE_E55kYNwOoJqXlpRFbrwfp98JJLU6_WN2Lzu0EzgklmJLk8GF28O7XCCGKQYcGjJEW3DhtRuoiXR4vE_ruEfr0kWaqS5EKbVuXNm4mU7GqGCeUczJ5LZ-g0qNg0E3qUqvT-ong_ZGgB2liH5wZY7qVcAq-OY7kXxaHViXg-gFovAvBQysaHeXkk46gTYpGTBU-_JyYKizmCicxfSQ--P9X9hczR_pf |
| CitedBy_id | crossref_primary_10_1007_s00436_024_08331_w crossref_primary_10_1371_journal_pntd_0012466 |
| Cites_doi | 10.1111/j.0002-9092.2004.600_2.x 10.1016/j.parepi.2022.e00256 10.4269/ajtmh.22-0238 10.1016/j.pt.2003.10.019 10.1186/1756-3305-7-138 10.1016/S1473-3099(22)00221-3 10.1016/j.envpol.2021.118324 10.1097/COH.0b013e328351b9e3 10.1371/journal.pntd.0005733 10.3389/fimmu.2020.574136 10.4135/9781412985888 10.1371/journal.pntd.0000250 10.1080/24694452.2017.1352480 10.1016/j.scitotenv.2020.138884 10.1080/00045600903550378 10.1016/j.jtbi.2017.08.015 10.1016/j.scitotenv.2022.158628 10.1016/j.actatropica.2020.105743 10.1016/S0140-6736(12)61689-4 10.1016/j.scitotenv.2021.152126 10.1186/s13071-022-05465-7 10.1080/00365540902756505 10.1016/S0140-6736(06)69440-3 10.1016/j.actatropica.2016.03.028 10.1186/s13071-021-04720-7 10.1016/j.apgeog.2022.102671 10.1016/S1473-3099(15)00066-3 10.1186/s13071-016-1418-4 10.1016/j.ijpara.2014.05.005 10.1016/bs.apar.2016.03.001 10.1186/1756-3305-7-216 10.3390/rs10091428 10.1186/s40249-021-00919-z 10.1186/1756-3305-6-249 10.1371/journal.pntd.0009578 10.1016/S0140-6736(18)32279-7 10.1111/j.1435-5957.2012.00480.x 10.1016/j.ijpara.2004.11.002 10.1017/S003118200999206X 10.1186/s12866-020-01963-9 10.1016/j.scitotenv.2022.158834 10.1371/journal.pntd.0010410 10.4081/gh.2007.255 10.1016/j.scs.2020.102627 10.3389/fpubh.2022.1032668 10.1186/1756-3305-7-95 10.1016/j.actatropica.2013.12.007 10.1016/j.envres.2022.114151 10.1093/trstmh/trab174 10.1186/s13071-020-04188-x 10.1371/journal.pone.0004058 |
| ContentType | Journal Article |
| Copyright | Copyright: © 2023 Tong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. COPYRIGHT 2023 Public Library of Science 2023 Tong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2023 Tong et al 2023 Tong et al |
| Copyright_xml | – notice: Copyright: © 2023 Tong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. – notice: COPYRIGHT 2023 Public Library of Science – notice: 2023 Tong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: 2023 Tong et al 2023 Tong et al |
| DBID | AAYXX CITATION NPM 3V. 7QL 7SS 7T2 7T7 7U9 7X7 7XB 88E 8C1 8FD 8FI 8FJ 8FK ABUWG AEUYN AFKRA AZQEC BENPR C1K CCPQU COVID DWQXO F1W FR3 FYUFA GHDGH H94 H95 H97 K9. L.G M0S M1P M7N P64 PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQQKQ PQUKI PRINS 7X8 5PM |
| DOI | 10.1371/journal.pntd.0011466 |
| DatabaseName | CrossRef PubMed ProQuest Central (Corporate) Bacteriology Abstracts (Microbiology B) Entomology Abstracts (Full archive) Health and Safety Science Abstracts (Full archive) Industrial and Applied Microbiology Abstracts (Microbiology A) Virology and AIDS Abstracts Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Public Health Database Technology Research Database Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest One Sustainability ProQuest Central UK/Ireland ProQuest Central Essentials ProQuest Central Environmental Sciences and Pollution Management ProQuest One Coronavirus Research Database ProQuest Central Korea ASFA: Aquatic Sciences and Fisheries Abstracts Engineering Research Database Proquest Health Research Premium Collection Health Research Premium Collection (Alumni) AIDS and Cancer Research Abstracts Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality ProQuest Health & Medical Complete (Alumni) Aquatic Science & Fisheries Abstracts (ASFA) Professional ProQuest Health & Medical Collection Medical Database Algology Mycology and Protozoology Abstracts (Microbiology C) Biotechnology and BioEngineering Abstracts ProQuest Central Premium ProQuest One Academic (New) ProQuest Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China MEDLINE - Academic PubMed Central (Full Participant titles) |
| DatabaseTitle | CrossRef PubMed Publicly Available Content Database Aquatic Science & Fisheries Abstracts (ASFA) Professional Technology Research Database ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Central China Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality Environmental Sciences and Pollution Management ProQuest Central ProQuest One Sustainability Health Research Premium Collection Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) Health & Medical Research Collection AIDS and Cancer Research Abstracts Health & Safety Science Abstracts Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources Industrial and Applied Microbiology Abstracts (Microbiology A) ProQuest Central (New) ProQuest Medical Library (Alumni) ProQuest Public Health Virology and AIDS Abstracts ProQuest One Academic Eastern Edition Coronavirus Research Database ProQuest Hospital Collection Health Research Premium Collection (Alumni) ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts Entomology Abstracts ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ASFA: Aquatic Sciences and Fisheries Abstracts Engineering Research Database ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | Publicly Available Content Database MEDLINE - Academic PubMed |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine Public Health |
| DocumentTitleAlternate | Determinants for the seropositive rate of schistosomiasis |
| EISSN | 1935-2735 |
| ExternalDocumentID | 2851974449 PMC10343143 A759349936 37440524 10_1371_journal_pntd_0011466 |
| Genre | Journal Article |
| GeographicLocations | China Hunan China |
| GeographicLocations_xml | – name: China – name: Hunan China |
| GrantInformation_xml | – fundername: ; grantid: 2121SK2032 |
| GroupedDBID | --- 123 29O 2WC 53G 5VS 7X7 88E 8C1 8FI 8FJ AAFWJ AAUCC AAWOE AAYXX ABDBF ABUWG ACGFO ACIHN ACPRK ACUHS ADBBV AEAQA AENEX AEUYN AFKRA AFPKN AFRAH AHMBA ALIPV ALMA_UNASSIGNED_HOLDINGS AOIJS BAWUL BCNDV BENPR BPHCQ BVXVI BWKFM CCPQU CITATION CS3 DIK DU5 E3Z EAP EAS EBD ECGQY EMOBN ESX F5P FPL FYUFA GROUPED_DOAJ GX1 HMCUK HYE IAO IHR IHW ITC KQ8 M1P M48 O5R O5S OK1 OVT P2P PGMZT PHGZM PHGZT PIMPY PQQKQ PROAC PSQYO PV9 RNS RPM RZL SV3 TR2 TUS UKHRP 3V. ADRAZ H13 IPNFZ M~E NPM RIG WOQ PMFND 7QL 7SS 7T2 7T7 7U9 7XB 8FD 8FK AZQEC C1K COVID DWQXO F1W FR3 H94 H95 H97 K9. L.G M7N P64 PJZUB PKEHL PPXIY PQEST PQUKI PRINS 7X8 5PM AAPBV ABPTK |
| ID | FETCH-LOGICAL-c559t-e0661638dcba5ddbd99f44b599e7538f4a33a870d3e90ee82341e3c712d88d273 |
| IEDL.DBID | M48 |
| ISSN | 1935-2735 1935-2727 |
| IngestDate | Sun Sep 03 00:14:44 EDT 2023 Thu Aug 21 18:36:50 EDT 2025 Fri Jul 11 08:41:42 EDT 2025 Fri Jul 25 04:33:34 EDT 2025 Tue Jun 17 21:26:13 EDT 2025 Tue Jun 10 21:30:33 EDT 2025 Thu May 22 21:16:12 EDT 2025 Wed Feb 19 02:23:56 EST 2025 Thu Apr 24 23:13:02 EDT 2025 Tue Jul 01 00:44:17 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 7 |
| Language | English |
| License | Copyright: © 2023 Tong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Creative Commons Attribution License |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c559t-e0661638dcba5ddbd99f44b599e7538f4a33a870d3e90ee82341e3c712d88d273 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 The authors have declared that no competing interests exist. |
| ORCID | 0000-0002-8188-7031 0000-0002-4635-0802 |
| OpenAccessLink | http://journals.scholarsportal.info/openUrl.xqy?doi=10.1371/journal.pntd.0011466 |
| PMID | 37440524 |
| PQID | 2851974449 |
| PQPubID | 1436337 |
| ParticipantIDs | plos_journals_2851974449 pubmedcentral_primary_oai_pubmedcentral_nih_gov_10343143 proquest_miscellaneous_2838246696 proquest_journals_2851974449 gale_infotracmisc_A759349936 gale_infotracacademiconefile_A759349936 gale_healthsolutions_A759349936 pubmed_primary_37440524 crossref_citationtrail_10_1371_journal_pntd_0011466 crossref_primary_10_1371_journal_pntd_0011466 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2023-07-01 |
| PublicationDateYYYYMMDD | 2023-07-01 |
| PublicationDate_xml | – month: 07 year: 2023 text: 2023-07-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | United States |
| PublicationPlace_xml | – name: United States – name: San Francisco – name: San Francisco, CA USA |
| PublicationTitle | PLoS neglected tropical diseases |
| PublicationTitleAlternate | PLoS Negl Trop Dis |
| PublicationYear | 2023 |
| Publisher | Public Library of Science |
| Publisher_xml | – name: Public Library of Science |
| References | DX Tran (pntd.0011466.ref028) 2022; 808 C Xue (pntd.0011466.ref046) 2023; 855 DD Lin (pntd.0011466.ref013) 2011; 23 Q Su (pntd.0011466.ref049) 2022; 116 AS Fotheringham (pntd.0011466.ref040) 2017; 107 H Yu (pntd.0011466.ref041) 2019 Lung-Fei Lee (pntd.0011466.ref035) 2002; 18 C Tupps (pntd.0011466.ref056) 2022; 16 KA Alene (pntd.0011466.ref017) 2022; 10 L Yang (pntd.0011466.ref062) 2022; 853 C Brunsdon (pntd.0011466.ref036) 2010 FY Li (pntd.0011466.ref026) 2020; 11 AM Deelder (pntd.0011466.ref066) 1994; 46 SY Xie (pntd.0011466.ref015) 2014; 7 M Qu (pntd.0011466.ref038) 2022; 292 ZG Cao (pntd.0011466.ref020) 2016; 92 WX Peng (pntd.0011466.ref022) 2010; 137 LJ Zhang (pntd.0011466.ref027) 2019; 31 P Harris (pntd.0011466.ref039) 2010; 100 CJ Murray (pntd.0011466.ref004) 2012; 380 L Mari (pntd.0011466.ref024) 2017; 432 by Review (pntd.0011466.ref029) 1996 W Wang (pntd.0011466.ref009) 2013; 6 D. P. McMillen (pntd.0011466.ref037) 2004; 86 C Zhao (pntd.0011466.ref045) 2018; 10 AS Akinwumiju (pntd.0011466.ref032) 2022; 141 OG Oso (pntd.0011466.ref055) 2022; 18 RK Assaré (pntd.0011466.ref007) 2020; 13 B Gryseels (pntd.0011466.ref001) 2006; 368 RJC Fornillos (pntd.0011466.ref047) 2019; 36 AD James SL (pntd.0011466.ref002) 2018; 392 Y Yang (pntd.0011466.ref048) 2022; 214 Prevention and control of schistosomiasis and soil-transmitted helminthiasis (pntd.0011466.ref057) 2002; 912 AE Phillips (pntd.0011466.ref058) 2022; 15 B Barda (pntd.0011466.ref012) 2020; 20 NC Lo (pntd.0011466.ref021) 2022; 22 T Manyangadze (pntd.0011466.ref016) 2016; 159 G Byrne (pntd.0011466.ref063) 2009 H Liu (pntd.0011466.ref044) 2021 DJ Gray (pntd.0011466.ref018) 2008; 3 A Mollalo (pntd.0011466.ref023) 2020; 728 MJ Doenhoff (pntd.0011466.ref064) 2004; 20 YS Lai (pntd.0011466.ref005) 2015; 15 C Lv (pntd.0011466.ref014) 2016; 9 MV da Silva (pntd.0011466.ref042) 2011; 2 P Steinmann (pntd.0011466.ref065) 2007; 2 XH Wang (pntd.0011466.ref019) 2008; 2 T Manyangadze (pntd.0011466.ref050) 2021; 14 WE Secor (pntd.0011466.ref008) 2012; 7 M Ward (pntd.0011466.ref030) 2008 C Lv (pntd.0011466.ref061) 2023; 8 OG Ajakaye (pntd.0011466.ref053) 2017; 11 Y Chen (pntd.0011466.ref043) 2022; 10 S Mansour (pntd.0011466.ref034) 2021; 65 DJ Gray (pntd.0011466.ref059) 2014; 44 RG Scholte (pntd.0011466.ref054) 2014; 132 JY Wu (pntd.0011466.ref025) 2014; 7 YC Cai (pntd.0011466.ref067) 2014; 7 LM Duus (pntd.0011466.ref068) 2009; 41 L. Anselin (pntd.0011466.ref033) 1990; 85 GJ Yang (pntd.0011466.ref052) 2005; 35 C Chen (pntd.0011466.ref011) 2021; 213 W Wang (pntd.0011466.ref010) 2021; 15 L Anselin (pntd.0011466.ref031) 2013; 92 J Utzinger (pntd.0011466.ref060) 2005; 96 R. Barnett (pntd.0011466.ref006) 2018; 392 D Rinaldo (pntd.0011466.ref003) 2021; 10 Y Zheng (pntd.0011466.ref051) 2022; 107 |
| References_xml | – volume: 96 start-page: 69 issue: 2–3 year: 2005 ident: pntd.0011466.ref060 article-title: Conquering schistosomiasis in China: the long march publication-title: Acta Trop – volume: 86 start-page: 554 issue: 2 year: 2004 ident: pntd.0011466.ref037 article-title: Geographically Weighted Regression: The Analysis of Spatially Varying Relationships publication-title: American Journal of Agricultural Economics doi: 10.1111/j.0002-9092.2004.600_2.x – year: 2021 ident: pntd.0011466.ref044 article-title: Impacts of the evolving urban development on intra-urban surface thermal environment: Evidence from 323 Chinese cities publication-title: Science of The Total Environment – volume: 18 start-page: e00256 year: 2022 ident: pntd.0011466.ref055 article-title: Models for predicting bulinids species habitats in southwestern Nigeria. publication-title: Parasite Epidemiol Control doi: 10.1016/j.parepi.2022.e00256 – volume: 10 issue: 4 year: 2022 ident: pntd.0011466.ref017 article-title: Analysis of Schistosomiasis in Hunan and Jiangxi Provinces in the People’s Republic of China publication-title: SpatialDiseases – volume: 107 start-page: 1178 issue: 6 year: 2022 ident: pntd.0011466.ref051 article-title: Environmental Determinants for Snail Density in Dongting Lake Region: An Ecological Study Incorporating Spatial Regression publication-title: Am J Trop Med Hyg doi: 10.4269/ajtmh.22-0238 – volume: 20 start-page: 35 issue: 1 year: 2004 ident: pntd.0011466.ref064 article-title: Specific and sensitive diagnosis of schistosome infection: can it be done with antibodies? publication-title: Trends Parasitol doi: 10.1016/j.pt.2003.10.019 – volume: 7 start-page: 138 year: 2014 ident: pntd.0011466.ref067 article-title: Field comparison of circulating antibody assays versus circulating antigen assays for the detection of schistosomiasis japonica in endemic areas of China. publication-title: Parasit Vectors doi: 10.1186/1756-3305-7-138 – volume: 912 start-page: i year: 2002 ident: pntd.0011466.ref057 publication-title: World Health Organ Tech Rep Ser – volume: 22 start-page: e327 issue: 11 year: 2022 ident: pntd.0011466.ref021 article-title: Review of 2022 WHO guidelines on the control and elimination of schistosomiasis publication-title: Lancet Infect Dis doi: 10.1016/S1473-3099(22)00221-3 – volume: 292 start-page: 118324 year: 2022 ident: pntd.0011466.ref038 article-title: Additional sampling using in-situ portable X-ray fluorescence (PXRF) for rapid and high-precision investigation of soil heavy metals at a regional scale publication-title: Environmental Pollution doi: 10.1016/j.envpol.2021.118324 – volume: 7 start-page: 254 issue: 3 year: 2012 ident: pntd.0011466.ref008 article-title: The effects of schistosomiasis on HIV/AIDS infection, progression and transmission. publication-title: Curr Opin HIV AIDS doi: 10.1097/COH.0b013e328351b9e3 – year: 2010 ident: pntd.0011466.ref036 publication-title: Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity Spatial – volume: 11 start-page: e0005733 issue: 7 year: 2017 ident: pntd.0011466.ref053 article-title: Modeling the risk of transmission of schistosomiasis in Akure North Local Government Area of Ondo State, Nigeria using satellite derived environmental data. publication-title: PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0005733 – volume: 46 start-page: 233 issue: 4 Spec No year: 1994 ident: pntd.0011466.ref066 article-title: Quantitative diagnosis of Schistosoma infections by measurement of circulating antigens in serum and urine publication-title: Trop Geogr Med – volume: 11 start-page: 574136 year: 2020 ident: pntd.0011466.ref026 article-title: Current Status of Schistosomiasis Control and Prospects for Elimination in the Dongting Lake Region of the People’s Republic of China publication-title: Front Immunol doi: 10.3389/fimmu.2020.574136 – year: 2008 ident: pntd.0011466.ref030 publication-title: Spatial Regression Models doi: 10.4135/9781412985888 – volume: 2 start-page: e250 issue: 6 year: 2008 ident: pntd.0011466.ref019 article-title: Bayesian spatio-temporal modeling of Schistosoma japonicum prevalence data in the absence of a diagnostic ’gold’ standard. publication-title: PLoS Negl Trop Dis doi: 10.1371/journal.pntd.0000250 – volume: 85 start-page: 160 issue: 411 year: 1990 ident: pntd.0011466.ref033 article-title: Spatial Econometrics: Methods and Models publication-title: Journal of the American Statistical Association – volume: 107 start-page: 1247 issue: 6 year: 2017 ident: pntd.0011466.ref040 article-title: Multiscale Geographically Weighted Regression (MGWR). publication-title: Annals of the American Association of Geographers doi: 10.1080/24694452.2017.1352480 – volume: 728 start-page: 138884 year: 2020 ident: pntd.0011466.ref023 article-title: GIS-based spatial modeling of COVID-19 incidence rate in the continental United States publication-title: Sci Total Environ doi: 10.1016/j.scitotenv.2020.138884 – volume: 100 start-page: 286 issue: 2 year: 2010 ident: pntd.0011466.ref039 article-title: Robust Geographically Weighted Regression: A Technique for Quantifying Spatial Relationships Between Freshwater Acidification Critical Loads and Catchment Attributes publication-title: Annals of the Association of American Geographers doi: 10.1080/00045600903550378 – volume: 432 start-page: 87 year: 2017 ident: pntd.0011466.ref024 article-title: Heterogeneity in schistosomiasis transmission dynamics publication-title: J Theor Biol doi: 10.1016/j.jtbi.2017.08.015 – volume: 18 issue: 02 year: 2002 ident: pntd.0011466.ref035 article-title: CONSISTENCY AND EFFICIENCY OF LEAST SQUARES ESTIMATION FOR MIXED REGRESSIVE, SPATIAL AUTOREGRESSIVE MODELS publication-title: Econometric Theory. – volume: 853 start-page: 158628 year: 2022 ident: pntd.0011466.ref062 article-title: Elucidating the spatial determinants of heavy metals pollution in different agricultural soils using geographically weighted regression publication-title: Sci Total Environ doi: 10.1016/j.scitotenv.2022.158628 – volume: 8 issue: 2 year: 2023 ident: pntd.0011466.ref061 article-title: The Current Distribution of Oncomelania hupensis Snails in the People’s Republic of China Based on a Nationwide Survey publication-title: Trop Med Infect Dis – volume: 213 start-page: 105743 year: 2021 ident: pntd.0011466.ref011 article-title: Reviews and advances in diagnostic research on Schistosoma japonicum publication-title: Acta Trop doi: 10.1016/j.actatropica.2020.105743 – volume: 380 start-page: 2197 issue: 9859 year: 2012 ident: pntd.0011466.ref004 article-title: Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010 publication-title: Lancet doi: 10.1016/S0140-6736(12)61689-4 – volume: 808 start-page: 152126 year: 2022 ident: pntd.0011466.ref028 article-title: Quantifying spatial non-stationarity in the relationship between landscape structure and the provision of ecosystem services: An example in the New Zealand hill country publication-title: Sci Total Environ doi: 10.1016/j.scitotenv.2021.152126 – volume: 15 start-page: 410 issue: 1 year: 2022 ident: pntd.0011466.ref058 article-title: Association between water, sanitation, and hygiene access and the prevalence of soil-transmitted helminth and schistosome infections in Wolayita, Ethiopia publication-title: Parasit Vectors doi: 10.1186/s13071-022-05465-7 – volume: 41 start-page: 285 issue: 4 year: 2009 ident: pntd.0011466.ref068 article-title: The schistosoma-specific antibody response after treatment in non-immune travellers publication-title: Scand J Infect Dis doi: 10.1080/00365540902756505 – volume: 23 start-page: 642 issue: 6 year: 2011 ident: pntd.0011466.ref013 article-title: Evaluation on application of common diagnosis methods for schistosomiasis japonica in endemic areas of China. III. Analysis and evaluation of underestimation of prevalence of Schistosoma japonicum infection by routine Kato-Katz technique]. publication-title: Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi – volume: 368 start-page: 1106 issue: 9541 year: 2006 ident: pntd.0011466.ref001 article-title: Human schistosomiasis publication-title: Lancet doi: 10.1016/S0140-6736(06)69440-3 – volume: 392 start-page: 2431 issue: 10163 year: 2018 ident: pntd.0011466.ref006 article-title: Schistosomiasis Lancet. – volume: 159 start-page: 176 year: 2016 ident: pntd.0011466.ref016 article-title: Risk factors and micro-geographical heterogeneity of Schistosoma haematobium in Ndumo area, uMkhanyakude district, KwaZulu-Natal publication-title: South Africa. Acta Trop doi: 10.1016/j.actatropica.2016.03.028 – volume: 14 start-page: 222 issue: 1 year: 2021 ident: pntd.0011466.ref050 article-title: Spatial and seasonal distribution of Bulinus globosus and Biomphalaria pfeifferi in Ingwavuma, uMkhanyakude district, KwaZulu-Natal, South Africa: Implications for schistosomiasis transmission at micro-geographical scale. publication-title: Parasit Vectors. doi: 10.1186/s13071-021-04720-7 – volume: 141 start-page: 102671 year: 2022 ident: pntd.0011466.ref032 article-title: Geospatial evaluation of COVID-19 mortality: Influence of socio-economic status and underlying health conditions in contiguous USA publication-title: Appl Geog doi: 10.1016/j.apgeog.2022.102671 – volume: 15 start-page: 927 issue: 8 year: 2015 ident: pntd.0011466.ref005 article-title: Spatial distribution of schistosomiasis and treatment needs in sub-Saharan Africa: a systematic review and geostatistical analysis publication-title: Lancet Infect Dis doi: 10.1016/S1473-3099(15)00066-3 – volume: 9 start-page: 135 year: 2016 ident: pntd.0011466.ref014 article-title: Evaluation of recombinant multi-epitope proteins for diagnosis of goat schistosomiasis by enzyme-linked immunosorbent assay publication-title: Parasit Vectors doi: 10.1186/s13071-016-1418-4 – volume: 44 start-page: 659 issue: 9 year: 2014 ident: pntd.0011466.ref059 article-title: A multi-component integrated approach for the elimination of schistosomiasis in the People’s Republic of China: design and baseline results of a 4-year cluster-randomised intervention trial publication-title: Int J Parasitol doi: 10.1016/j.ijpara.2014.05.005 – volume: 92 start-page: 269 year: 2016 ident: pntd.0011466.ref020 article-title: Towards the Elimination of Schistosomiasis japonica through Control of the Disease in Domestic Animals in The People’s Republic of China: A Tale of over 60Years. publication-title: Adv Parasitol. doi: 10.1016/bs.apar.2016.03.001 – volume: 7 start-page: 216 year: 2014 ident: pntd.0011466.ref025 article-title: Identification of optimum scopes of environmental factors for snails using spatial analysis techniques in Dongting Lake Region, China publication-title: Parasit Vectors doi: 10.1186/1756-3305-7-216 – volume: 10 start-page: 1428 issue: 9 year: 2018 ident: pntd.0011466.ref045 article-title: A Geographically Weighted Regression Analysis of the Underlying Factors Related to the Surface Urban Heat Island Phenomenon publication-title: Remote Sensing doi: 10.3390/rs10091428 – volume: 10 start-page: 134 issue: 1 year: 2021 ident: pntd.0011466.ref003 article-title: The economic impact of schistosomiasis publication-title: Infect Dis Poverty doi: 10.1186/s40249-021-00919-z – volume: 6 start-page: 249 issue: 1 year: 2013 ident: pntd.0011466.ref009 article-title: African schistosomiasis in mainland China: risk of transmission and countermeasures to tackle the risk. publication-title: Parasit Vectors doi: 10.1186/1756-3305-6-249 – year: 1996 ident: pntd.0011466.ref029 article-title: Applied Logistic Regression Analysis. by S. Menard publication-title: Journal of the Royal Statistical Society – volume: 15 start-page: e0009578 issue: 8 year: 2021 ident: pntd.0011466.ref010 article-title: Elimination of schistosomiasis in China: Current status and future prospects. publication-title: PLoS Negl Trop Dis doi: 10.1371/journal.pntd.0009578 – volume: 2 start-page: 112 year: 2011 ident: pntd.0011466.ref042 article-title: Box-Cox Transformation and Random Regression Models for Fecal egg Count Data publication-title: Front Genet – volume: 392 start-page: 1789 issue: 10159 year: 2018 ident: pntd.0011466.ref002 article-title: Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017 publication-title: Lancet doi: 10.1016/S0140-6736(18)32279-7 – volume: 92 start-page: 3 issue: 1 year: 2013 ident: pntd.0011466.ref031 article-title: Spatial Fixed Effects and Spatial Dependence publication-title: Papers in Regional Science doi: 10.1111/j.1435-5957.2012.00480.x – volume: 35 start-page: 155 issue: 2 year: 2005 ident: pntd.0011466.ref052 article-title: A Bayesian-based approach for spatio-temporal modeling of county level prevalence of Schistosoma japonicum infection in Jiangsu province, China publication-title: Int J Parasitol doi: 10.1016/j.ijpara.2004.11.002 – volume: 137 start-page: 1099 issue: 7 year: 2010 ident: pntd.0011466.ref022 article-title: Identifying high-risk areas of schistosomiasis and associated risk factors in the Poyang Lake region publication-title: China. Parasitology doi: 10.1017/S003118200999206X – volume: 20 start-page: 298 issue: 1 year: 2020 ident: pntd.0011466.ref012 article-title: Comparison of real-time PCR and the Kato-Katz method for the diagnosis of soil-transmitted helminthiasis and assessment of cure in a randomized controlled trial publication-title: BMC Microbiol doi: 10.1186/s12866-020-01963-9 – volume: 855 start-page: 158834 year: 2023 ident: pntd.0011466.ref046 article-title: Modeling the spatially heterogeneous relationships between tradeoffs and synergies among ecosystem services and potential drivers considering geographic scale in Bairin Left Banner, China publication-title: Sci Total Environ doi: 10.1016/j.scitotenv.2022.158834 – volume: 36 start-page: 402 issue: 2 year: 2019 ident: pntd.0011466.ref047 article-title: Infection rate of Schistosoma japonicum in the snail Oncomelania hupensis quadrasi in endemic villages in the Philippines: Need for snail surveillance technique. publication-title: Trop Biomed – volume: 16 start-page: e0010410 issue: 5 year: 2022 ident: pntd.0011466.ref056 article-title: Community-wide prevalence and intensity of soil-transmitted helminthiasis and Schistosoma mansoni in two districts of Sierra Leone. publication-title: PLoS Negl Trop Dis doi: 10.1371/journal.pntd.0010410 – volume: 31 start-page: 576 issue: 6 year: 2019 ident: pntd.0011466.ref027 article-title: Endemic status of schistosomiasis in People’s Republic of China in 2018 publication-title: Chinese Journal of Schistosomiasis Control – volume: 2 start-page: 59 issue: 1 year: 2007 ident: pntd.0011466.ref065 article-title: Spatial risk profiling of Schistosoma japonicum in Eryuan county, Yunnan province, China. publication-title: Geospat Health doi: 10.4081/gh.2007.255 – year: 2009 ident: pntd.0011466.ref063 article-title: Multiple Dependent Hypothesis Tests in Geographically Weighted Regression publication-title: Giscience & Remote Sensing – volume: 65 start-page: 102627 year: 2021 ident: pntd.0011466.ref034 article-title: Sociodemographic determinants of COVID-19 incidence rates in Oman: Geospatial modelling using multiscale geographically weighted regression (MGWR). publication-title: Sustain Cities Soc doi: 10.1016/j.scs.2020.102627 – volume: 10 start-page: 1032668 year: 2022 ident: pntd.0011466.ref043 article-title: Street centrality and vitality of a healthy catering industry: A case study of Jinan, China publication-title: Front Public Health doi: 10.3389/fpubh.2022.1032668 – volume: 7 start-page: 95 year: 2014 ident: pntd.0011466.ref015 article-title: Immune responses result in misdiagnosis of Schistosoma japonicum by immunodiagnosis kits in egg-positive patients living in a low schistosomiasis transmission area of China publication-title: Parasit Vectors doi: 10.1186/1756-3305-7-95 – issue: 1 year: 2019 ident: pntd.0011466.ref041 article-title: Inference in Multiscale Geographically Weighted Regression. publication-title: Geographical Analysis. – volume: 132 start-page: 57 year: 2014 ident: pntd.0011466.ref054 article-title: Predictive risk mapping of schistosomiasis in Brazil using Bayesian geostatistical models publication-title: Acta Trop doi: 10.1016/j.actatropica.2013.12.007 – volume: 214 start-page: 114151 issue: Pt 4 year: 2022 ident: pntd.0011466.ref048 article-title: Monitoring spatiotemporal characteristics of land-use carbon emissions and their driving mechanisms in the Yellow River Delta: A grid-scale analysis publication-title: Environ Res doi: 10.1016/j.envres.2022.114151 – volume: 116 start-page: 555 issue: 6 year: 2022 ident: pntd.0011466.ref049 article-title: A comparison of modelling the spatio-temporal pattern of disease: a case study of schistosomiasis japonica in Anhui Province, China publication-title: Trans R Soc Trop Med Hyg doi: 10.1093/trstmh/trab174 – volume: 13 start-page: 337 issue: 1 year: 2020 ident: pntd.0011466.ref007 article-title: Characteristics of persistent hotspots of Schistosoma mansoni in western Côte d’Ivoire publication-title: Parasit Vectors doi: 10.1186/s13071-020-04188-x – volume: 3 start-page: e4058 issue: 12 year: 2008 ident: pntd.0011466.ref018 article-title: Transmission dynamics of Schistosoma japonicum in the lakes and marshlands of China. publication-title: PLoS One doi: 10.1371/journal.pone.0004058 |
| SSID | ssj0059581 |
| Score | 2.3952725 |
| Snippet | Schistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis elimination and... Background Schistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis... The elimination of schistosomiasis depends critically on the identification of a set of determinants. A site-specific analysis of the determinants allows... Background Schistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis... |
| SourceID | plos pubmedcentral proquest gale pubmed crossref |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source |
| StartPage | e0011466 |
| SubjectTerms | Behavior Biology and Life Sciences Cattle Coefficients Correlation Data collection Daytime Development and progression Diagnosis Disease Distance Earth Sciences Ecology and Environmental Sciences Households Infections Intervention Medicine and Health Sciences Physical Sciences Public health Regression analysis Regression coefficients Regression models Regressions Rivers Robustness (mathematics) Schistosomiasis Social Sciences Spatial variations Surface temperature Toilets Towns Tropical diseases Variability Villages Well water |
| SummonAdditionalLinks | – databaseName: Health & Medical Collection dbid: 7X7 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwhV3db9MwELegSAgJIRgfKwwwEhIvhCWxU9u8oAoxVUjjiUl9i_zVrVJJytJu4h_h7-XOdrMFTfBan9M4d7bv83eEvJWuzLWaFJmdMJ9xr01mhMkz2Epyop2xLvQiOP42mZ3wr_NqnhxuXUqr3J2J4aB2rUUf-WEpscSSc64-rX9m2DUKo6uphcZtcgehyzClS8x7g6uCX4oYVca6q1Kk0jkmisPEqQ_rZuNCNIIHnMSrqykd0KP1qu1u0j7_TqK8disdPSQPkjpJp5H_j8gt3-yRu8cpYL5H7ke3HI3VRo_J71iYG4qbqLuWCkNBeaWgDFIQyTZmcl14ijgStF1QMIERgqBrfyx1t-zosqGzLcyj0SNh_XsaGnF_pFMaUhSzDnjv6WlssY7pHqvVL3oZ_LDe0XN_GvNvGxpa8TwhJ0dfvn-eZak1Q2bBBNlkHjQV1OScNbpyzjilFpybSikP9o9ccM2YhqPAMa9y72UJl6VnVhSlkyAegj0lo6Zt_D6huZNskSvDRQDa0boQthIG7KxSOlPmY8J2XKltwi3H9hmrOgTjBNgv8VvXyMs68XJMsn7WOuJ2_If-NTK8jtWn_bavp6JSDKxCBhTvAgVufPh_q1P9AqwCIbQGlAcDStiwdjC8j0K1e42uvhJtmLkTtJuH3_TD-FDMj2t8u0UaJktYhoKnP4ty2S-bIQZkVfIxkQOJ7QkQYXw40izPAtJ4kTNQMDl7_u_3ekHulaD7xSzmAzLanG_9S9DVNuZV2JB_ABYtQds priority: 102 providerName: ProQuest |
| Title | Identifying determinants for the seropositive rate of schistosomiasis in Hunan province, China: A multi-scale geographically weighted regression model |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/37440524 https://www.proquest.com/docview/2851974449 https://www.proquest.com/docview/2838246696 https://pubmed.ncbi.nlm.nih.gov/PMC10343143 http://dx.doi.org/10.1371/journal.pntd.0011466 |
| Volume | 17 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwhV3da9swEBdtCmMwxtZ9NFuXaTDYy1xsS7akwRhZaQmDlDEWyJuRLKULeHYaJ936j-zv3UmyTT1S9uIX3cmWdGf9TroPhN5yHYdSpFGQp8QE1EgVKKbCAFSJp1KrXLtaBNOLdDKjX-bJfA-1NVubCax3mna2ntRsXZz8vrr5BAr_0VVtYFHLdLIqN9rdLNA03UcHsDcxq6pT2t0rJCLhURNAdxdnb4NqftODVVHVuzDov66Ut_am80foYQMq8dhLwWO0Z8pDdG_aXJsfogf-cA77mKMn6I8Pz3UhTljfcojBAGExQEIMgll5f65rg202CVwtMMyWTURQVz-Xsl7WeFniyRb4sD-XyM177Mpxf8Bj7BwVgxokwOBLX2jdOn0UxQ3-5U5jjcZrc-m9cEvsCvI8RbPzs--nk6Ap0BDkYIhsAgN4xeI5nSuZaK20EAtKVSKEASuIL6gkRMIPQRMjQmN4DFumITmLYs1BSBh5hgZlVZojhEPNySIUijKXbkfKiOUJU2BtxVyrOBwi0q5KljfZy20RjSJzV3IMrBg_15ldy6xZyyEKOq6Vz97xH_rXdsEzH4PaKX82ZokgYBsSoHjnKKxAwvtz2UQxwChsIq0e5XGPEtQ27zUfWaFqP6POYm5jiCmlAjhbQdvd_KZrtp1aL7nSVFtLQ3gMwxDQ-3Mvl92wic0EmcR0iHhPYjsCm2e831Iuf7h841FIAGZS8uLuT36J7seA_rwf8zEabNZb8wrQ2kaN0D6bM3jy02iEDj6fXXz9NnInHyOnmn8BPitINw |
| linkProvider | Scholars Portal |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1bb9MwFLZGkQAJIRiXFQYzEogXwlLbqWMkhCpg6ti6p03qWxZfOiqVpCwt0_4IP4PfyDl2kq1ogqc9-9iNey7-jn0uhLxKLYtz1e9Fps9dJFyuIy11HIEqpf3camN9L4LRQX94JL6Ok_Ea-d3kwmBYZWMTvaG2pcE78m2WYoqlEEJ9nP-IsGsUvq42LTSCWOy58zNw2aoPu5-Bv68Z2_ly-GkY1V0FIgPoeRE5OGQRhFij88RabZWaCKETpRxA93Qics5zkGLLnYqdSxnYeceN7DGbws4kh3VvkJtw8MaoUXLcOniJSnxTVMBEmOfFZJ2qx2Vvu5aMd_NiYf3rh_B1GS-OwvpA6MxnZXUV2v07aPPSKbhzn9yr4SsdBHl7QNZcsU5ujeoH-nVyN1wD0pDd9JD8ConAPpmK2kuhNxTAMgXwSUEFyhA59tNRrFtBywkFlxtLHlTl92leTSs6LehwCfNouAEx7i31jb_f0wH1IZFRBbLm6Elo6Y7hJbPZOT3z977O0lN3EuJ9C-pb_zwiR9fCtMekU5SF2yA0timfxEoL6Qv75HlPmkRq8OtYajWLu4Q3XMlMXScd23XMMv_4J8FfCv91hrzMal52SdTOmoc6If-h30KGZyHbtTUz2UAmioMXyoHijadAQwO_b_I6XwJ2gSW7Vig3VyjBQJiV4Q0UquYzquxClWBmI2hXD79sh3FRjMcrXLlEGp4y2IaC1Z8EuWy3zbHmZMJEl6QrEtsSYEXz1ZFi-s1XNu_FHPRK8Kf__q4tcnt4ONrP9ncP9p6ROwxwZ4ig3iSdxenSPQecuNAvvHJScnzd1uAPT8t-WA |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1bb9MwFLZGkSYkhGBcVhjMSCBeCE1sp46REKoYVcfYxAOT-pbFsTsqdUm3tEz7I_wYfh3n2Em2ogme9uxjN-65-Dv2uRDyKjEszFQ_CvI-t4GwmQ601GEAqpT0M6Nz43oR7B_0R4fiyzger5HfTS4MhlU2NtEZalPmeEfeYwmmWAohVG9Sh0V82xl-nJ8G2EEKX1qbdhpeRPbsxTm4b9WH3R3g9WvGhp-_fxoFdYeBIAckvQgsHLgISEyus9gYbZSaCKFjpSzA-GQiMs4zkGjDrQqtTRjYfMtzGTGTwC4lh3VvkduSxxHqmBy3zl6sYtcgFfAR5nwxWaftcRn1ail5Ny8Wxr2ECFej8fJYrA-HznxWVtch378DOK-ciMP75F4NZenAy94DsmaLDbK-Xz_Wb5C7_kqQ-kynh-SXTwp2iVXUXAnDoQCcKQBRCupQ-iiyn5ZiDQtaTii431j-oCpPplk1rei0oKMlzKP-NiS3b6lrAv6eDqgLjwwqkDtLj317dww1mc0u6Lm7A7aGntljH_tbUNcG6BE5vBGmPSadoizsJqGhSfgkVFpIV-QnyyKZx1KDj8cSo1nYJbzhSprXNdOxdccsdQ-BEnwn_1-nyMu05mWXBO2sua8Z8h_6bWR46jNfW5OTDmSsOHikHCjeOAo0OvD7eVbnTsAusHzXCuXWCiUYi3xleBOFqvmMKr1UK5jZCNr1wy_bYVwUY_MKWy6RhicMtqFg9SdeLtttc6w_GTPRJcmKxLYEWN18daSY_nBVzqOQA7gV_Om_v2ubrIMdSL_uHuw9I3cYQFAfTL1FOouzpX0OkHGhXzjdpOTopo3BHxO4go4 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Identifying+determinants+for+the+seropositive+rate+of+schistosomiasis+in+Hunan+province%2C+China%3A+A+multi-scale+geographically+weighted+regression+model&rft.jtitle=PLoS+neglected+tropical+diseases&rft.au=Yixin+Tong+https%3A%2F%2Forcid.org%2F0000-0002-8188-7031&rft.au=Tang%2C+Ling&rft.au=Xia%2C+Meng&rft.au=Li%2C+Guangping&rft.date=2023-07-01&rft.pub=Public+Library+of+Science&rft.eissn=1935-2735&rft.volume=17&rft.issue=7&rft_id=info:doi/10.1371%2Fjournal.pntd.0011466&rft.externalDocID=2851974449 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1935-2735&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1935-2735&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1935-2735&client=summon |