{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T04:31:42Z","timestamp":1780547502575,"version":"3.54.1"},"reference-count":60,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2022,7,28]],"date-time":"2022-07-28T00:00:00Z","timestamp":1658966400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003786","name":"Hangzhou Science and Technology Development Plan","doi-asserted-by":"publisher","award":["20201203B141"],"award-info":[{"award-number":["20201203B141"]}],"id":[{"id":"10.13039\/501100003786","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003786","name":"Hangzhou Science and Technology Development Plan","doi-asserted-by":"publisher","award":["41101371"],"award-info":[{"award-number":["41101371"]}],"id":[{"id":"10.13039\/501100003786","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["20201203B141"],"award-info":[{"award-number":["20201203B141"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41101371"],"award-info":[{"award-number":["41101371"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Foodborne diseases are an increasing concern to public health; climate and socioeconomic factors influence bacterial foodborne disease outbreaks. We developed an \u201cexposure\u2013sensitivity\u2013adaptability\u201d vulnerability assessment framework to explore the spatial characteristics of multiple climatic and socioeconomic environments, and analyzed the risk of foodborne disease outbreaks in different vulnerable environments of Zhejiang Province, China. Global logistic regression (GLR) and geographically weighted logistic regression (GWLR) models were combined to quantify the influence of selected variables on regional bacterial foodborne diseases and evaluate the potential risk. GLR results suggested that temperature, total precipitation, road density, construction area proportions, and gross domestic product (GDP) were positively correlated with foodborne diseases. GWLR results indicated that the strength and significance of these relationships varied locally, and the predicted risk map revealed that the risk of foodborne diseases caused by Vibrio parahaemolyticus was higher in urban areas (60.6%) than rural areas (20.1%). Finally, distance from the coastline was negatively correlated with predicted regional risks. This study provides a spatial perspective for the relevant departments to prevent and control foodborne diseases.<\/jats:p>","DOI":"10.3390\/rs14153613","type":"journal-article","created":{"date-parts":[[2022,7,28]],"date-time":"2022-07-28T22:43:26Z","timestamp":1659048206000},"page":"3613","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Evaluating the Spatial Risk of Bacterial Foodborne Diseases Using Vulnerability Assessment and Geographically Weighted Logistic Regression"],"prefix":"10.3390","volume":"14","author":[{"given":"Wanchao","family":"Bian","sequence":"first","affiliation":[{"name":"Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou Normal University, Hangzhou 311121, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2444-133X","authenticated-orcid":false,"given":"Hao","family":"Hou","sequence":"additional","affiliation":[{"name":"Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou Normal University, Hangzhou 311121, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiang","family":"Chen","sequence":"additional","affiliation":[{"name":"Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Zhou","sequence":"additional","affiliation":[{"name":"Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou Normal University, Hangzhou 311121, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2593-9423","authenticated-orcid":false,"given":"Jianhong","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Earth and Planetary Sciences, Curtin University, Perth 6845, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shanjuan","family":"Xie","sequence":"additional","affiliation":[{"name":"Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou Normal University, Hangzhou 311121, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0389-2553","authenticated-orcid":false,"given":"Ting","family":"Liu","sequence":"additional","affiliation":[{"name":"Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou Normal University, Hangzhou 311121, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,28]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2008). Foodborne Disease Outbreaks: Guidelines for Investigation and Control, World Health Organization."},{"key":"ref_2","unstructured":"World Health Organization (2015). WHO Estimates of the Global Burden of Foodborne Diseases: Foodborne Disease Burden Epidemiology Reference Group 2007\u20132015, World Health Organization."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Chen, Y., Yan, W., Zhou, Y., Zhen, S., Zhang, R., Chen, J., Liu, Z., Cheng, H., Liu, H., and Duan, S. (2013). Burden of Self-reported Acute Gastrointestinal Illness in China: A Population-based Survey. BMC Public Health, 13.","DOI":"10.1186\/1471-2458-13-456"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.foodcont.2017.12.032","article-title":"National Molecular Tracing Network for Foodborne Disease Surveillance in China","volume":"88","author":"Li","year":"2018","journal-title":"Food Control"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1038\/s41597-020-00671-3","article-title":"A Database for Risk Assessment and Comparative Genomic Analysis of Foodborne Vibrio Parahaemolyticus in China","volume":"7","author":"Pang","year":"2020","journal-title":"Sci. Data"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Chen, L., Sun, L., Zhang, R., Liao, N., Qi, X., and Chen, J. (2022). Surveillance for Foodborne Disease Outbreaks in Zhejiang Province, China, 2015\u20132020. BMC Public Health, 22.","DOI":"10.1186\/s12889-022-12568-4"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1089\/fpd.2018.2592","article-title":"Laboratory Review of Foodborne Disease Investigations in Washington State 2007\u20132017","volume":"16","author":"Swoveland","year":"2019","journal-title":"Foodborne Pathog. Dis."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1089\/fpd.2015.2047","article-title":"Systemic Analysis of Foodborne Disease Outbreak in Korea","volume":"13","author":"Lee","year":"2016","journal-title":"Foodborne Pathog. Dis."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Chen, Y.J., Wen, Y.F., Song, J.G., Chen, B.F., Ding, S.S., Ding, L., and Dai, J.J. (2018). The Correlation Between Family Food Handling Behaviors and Foodborne Acute Gastroenteritis: A Community-oriented, Population-based Survey in Anhui, China. BMC Public Health, 18.","DOI":"10.1186\/s12889-018-6223-x"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1089\/fpd.2020.2913","article-title":"High-Efficiency Machine Learning Method for Identifying Foodborne Disease Outbreaks and Confounding Factors","volume":"18","author":"Zhang","year":"2021","journal-title":"Foodborne Pathog. Dis."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Wang, X.L., Zhou, M.Q., Jia, J.Z., Geng, Z., and Xiao, G.X. (2018). A Bayesian Approach to Real-Time Monitoring and Forecasting of Chinese Foodborne Diseases. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15081740"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1007\/s00003-021-01346-w","article-title":"Time Series Analysis of Foodborne Diseases During 2012\u20132018 in Shenzhen, China","volume":"17","author":"Li","year":"2021","journal-title":"J. Consum. Prot. Food Saf."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Lesiv, M., Moltchanova, E., Schepaschenko, D., See, L., Shvidenko, A., Comber, A., and Fritz, S. (2016). Comparison of Data Fusion Methods Using Crowdsourced Data in Creating a Hybrid Forest Cover Map. Remote Sens., 8.","DOI":"10.3390\/rs8030261"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Yasuo, K., and Nishiura, H. (2019). Spatial Epidemiological Determinants of Severe Fever with Thrombocytopenia Syndrome in Miyazaki, Japan: A GWLR Modeling Study. BMC Infect. Dis., 19.","DOI":"10.1186\/s12879-019-4111-3"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1080\/10106049.2019.1614100","article-title":"Geo-spatially Modelling Dengue Epidemics in Urban Cities: A Case Study of Lahore, Pakistan","volume":"36","author":"Imran","year":"2021","journal-title":"Geocarto. Int."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Manyangadze, T., Mavhura, E., Mudavanhu, C., and Pedzisai, E. (2021). An Exploratory Analysis of the Spatial Variation of Malaria Cases and Associated Household Socio-economic Factors in Flood-prone Areas of Mbire district, Zimbabwe. GeoJournal, 1\u201316.","DOI":"10.1007\/s10708-021-10505-3"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1291","DOI":"10.1017\/S0950268815002666","article-title":"Geographical variations of risk factors associated with HCV infection in drug users in southwestern China","volume":"144","author":"Zhou","year":"2016","journal-title":"Epidemiol. Infect."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1080\/01944363.2014.954464","article-title":"Climate Change 2014: Impacts, Adaptation, and Vulnerability","volume":"80","author":"Birch","year":"2014","journal-title":"J. Am. Plann. Assoc."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Rathi, S.K., Chakraborty, S., Mishra, S.K., Dutta, A., and Nanda, L. (2022). A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Urbanites of Four Cities of India. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph19010283"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1186\/s40249-020-00717-z","article-title":"Climate Change Induced Vulnerability and Adaption for Dengue Incidence in Colombo and Kandy Districts: The Detailed Investigation in Sri Lanka","volume":"9","author":"Udayanga","year":"2020","journal-title":"Infect. Dis. Poverty"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1016\/j.scitotenv.2018.02.271","article-title":"Vulnerability Assessment Including Tangible and Intangible Components in the Index Composition: An Amazon Case Study of Flooding and Flash Flooding","volume":"630","author":"Szlafsztein","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"e2021GH000461","DOI":"10.1029\/2021GH000461","article-title":"Population Vulnerability to the SARS-CoV-2 Virus Infection. A County-Level Geographical-Methodological Approach in Romania","volume":"5","author":"Mitrica","year":"2021","journal-title":"GeoHealth"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ahmad, I., Wang, X., Waseem, M., Zaman, M., Aziz, F., Khan, R.Z.N., and Ashraf, M. (2022). Flood Management, Characterization and Vulnerability Analysis Using an Integrated RS-GIS and 2D Hydrodynamic Modelling Approach: The Case of Deg Nullah, Pakistan. Remote Sens., 14.","DOI":"10.3390\/rs14092138"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1016\/j.gloenvcha.2006.02.006","article-title":"Vulnerability","volume":"16","author":"Adger","year":"2006","journal-title":"Glob. Environ. Change"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Shen, J., and Li, Y. (2018). Atmospheric Environment Vulnerability Cause Analysis for the Beijing-Tianjin-Hebei Metropolitan Region. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15010128"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"102939","DOI":"10.1016\/j.scs.2021.102939","article-title":"Examining Social Vulnerability to Flood of Affordable Housing Communities in Nanjing, China: Building Long-term Disaster Resilience of Low-income Communities","volume":"71","author":"Chen","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"107206","DOI":"10.1016\/j.ecolind.2020.107206","article-title":"Dynamics of Exposure, Sensitivity, Adaptive Capacity and Agricultural Vulnerability at District Scale for Maharashtra, India","volume":"121","author":"Swami","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1016\/j.envint.2019.01.057","article-title":"Exploring the Mechanisms of Heat Wave Vulnerability at the Urban Scale Based on the Application of Big Data and Artificial Societies","volume":"127","author":"He","year":"2019","journal-title":"Environ. Int."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1016\/j.envint.2018.10.003","article-title":"Weather and Gastrointestinal Disease in Spain: A Retrospective Time Series Regression Study","volume":"121","author":"Villanueva","year":"2018","journal-title":"Environ. Int."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.foodres.2014.03.023","article-title":"Correlations Between Climatic Conditions and Foodborne Disease","volume":"68","author":"Kim","year":"2015","journal-title":"Food Res. Int."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"264","DOI":"10.3136\/nskkk.55.264","article-title":"Impact of Climate Change on Foodborne Pathogens and Diseases","volume":"55","author":"Bari","year":"2008","journal-title":"J. Jpn. Soc. Food. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"e200","DOI":"10.1017\/S0950268818003126","article-title":"Sex and Age Distributions of Persons in Foodborne Disease Outbreaks and Associations with Food Categories","volume":"147","author":"Strassle","year":"2019","journal-title":"Epidemiol. Infect."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"494","DOI":"10.4315\/0362-028X.JFP-18-163","article-title":"Food Handling Behaviors Associated with Reported Acute Gastrointestinal Disease That May Have Been Caused by Food","volume":"82","author":"Chen","year":"2019","journal-title":"J. Food Prot."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Osei-Tutu, B., and Anto, F. (2016). Trends of Reported Foodborne Diseases at the Ridge Hospital, Accra, Ghana: A Retrospective Review of Routine Data from 2009\u20132013. BMC Infect. Dis., 16.","DOI":"10.1186\/s12879-016-1472-8"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"445","DOI":"10.32394\/pe.73.42","article-title":"Foodborne Botulism in Poland in 2017","volume":"73","author":"Czerwinski","year":"2019","journal-title":"Prz. Epidemiol."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Xiao, G.X., Xu, C.D., Wang, J.F., Yang, D.Y., and Wang, L. (2014). Spatial-temporal Pattern and Risk Factor Analysis of Bacillary Dysentery in the Beijing-Tianjin-Tangshan Urban Region of China. BMC Public Health, 14.","DOI":"10.1186\/1471-2458-14-998"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.foodcont.2017.02.004","article-title":"Epidemiology of Foodborne Disease Outbreaks Caused by Vibrio Parahaemolyticus During 2010\u20132014 in Zhejiang Province, China","volume":"77","author":"Chen","year":"2017","journal-title":"Food Control"},{"key":"ref_38","unstructured":"National Bureau of Statistics of China (2021, December 22). Provisions on the Statistical Division of Urban and Rural Areas (for Trial Implementation), Available online: http:\/\/www.stats.gov.cn\/tjsj\/pcsj\/rkpc\/5rp\/html\/append7.htm."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Bai, H.M., Shi, Y.L., Seong, M.S., Gao, W.K., and Li, Y.H. (2022). Influence of Spatial Resolution on Satellite-Based PM2.5 Estimation: Implications for Health Assessment. Remote Sens., 14.","DOI":"10.3390\/rs14122933"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"548","DOI":"10.3109\/1040841X.2014.972335","article-title":"Effects of Climate Change on the Persistence and Dispersal of Foodborne Bacterial Pathogens in the Outdoor Environment: A review","volume":"42","author":"Hellberg","year":"2016","journal-title":"Crit. Rev. Microbiol."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Prinsen, G., Benschop, J., Cleaveland, S., Crump, J.A., French, N.P., Hrynick, T.A., Mariki, B., Mmbaga, B.T., Sharp, J.P., and Swai, E.S. (2020). Meat Safety in Tanzania\u2019s Value Chain: Experiences, Explanations and Expectations in Butcheries and Eateries. Int. J. Environ. Res. Public Health, 17.","DOI":"10.3390\/ijerph17082833"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2301","DOI":"10.1073\/pnas.0710375105","article-title":"Temporal and Spatial Changes in Social Vulnerability to Natural Hazards","volume":"105","author":"Cutter","year":"2008","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.apgeog.2012.10.012","article-title":"Comparison of Spatial and Non-spatial Logistic Regression Models for Modeling the Occurrence of Cloud Cover in North-eastern Puerto Rico","volume":"37","author":"Wu","year":"2013","journal-title":"Appl. Geogr."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1111\/j.2041-210X.2009.00001.x","article-title":"A Protocol for Data Exploration to Avoid Common Statistical Problems","volume":"1","author":"Zuur","year":"2010","journal-title":"Methods Ecol. Evol."},{"key":"ref_45","first-page":"e00894","article-title":"Investigating Spatial Non-stationary Environmental Effects on the Distribution of Giant Pandas in the Qinling Mountains, China","volume":"21","author":"Ye","year":"2020","journal-title":"Glob. Ecol. Conserv."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1080\/13658816.2013.865739","article-title":"Geographically Weighted Regression with a Non-Euclidean Distance Metric: A Case Study Using Hedonic House Price Data","volume":"28","author":"Lu","year":"2014","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1007\/s11629-016-4118-9","article-title":"Selecting Suitable Sites for Mountain Ginseng (Panax ginseng) Cultivation by Using Geographically Weighted Logistic Regression","volume":"14","author":"Han","year":"2017","journal-title":"J. Mt. Sci."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Yang, L., Yu, K., Ai, J., Liu, Y., Yang, W., and Liu, J. (2022). Dominant Factors and Spatial Heterogeneity of Land Surface Temperatures in Urban Areas: A Case Study in Fuzhou, China. Remote Sens., 14.","DOI":"10.3390\/rs14051266"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Hsiao, H.I., Jan, M.S., and Chi, H.J. (2016). Impacts of Climatic Variability on Vibrio Parahaemolyticus Outbreaks in Taiwan. Int. J. Environ. Res. Public Health, 13.","DOI":"10.3390\/ijerph13020188"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Shih, Y.J., Chen, J.S., Chen, Y.J., Yang, P.Y., Kuo, Y.J., Chen, T.H., and Hsu, B.M. (2021). Impact of Heavy precipitation Events on Pathogen Occurrence in Estuarine Areas of the Puzi River in Taiwan. PLoS ONE, 16.","DOI":"10.1371\/journal.pone.0256266"},{"key":"ref_51","first-page":"309","article-title":"Epidemiological Characteristics and Spatio-temporal Patterns of Foodborne Diseases in Jinan, Northern China","volume":"32","author":"Yang","year":"2019","journal-title":"Biomed. Environ. Sci."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Zhang, L., Wei, Y., and Meng, R. (2017). Spatiotemporal Dynamics and Spatial Determinants of Urban Growth in Suzhou, China. Sustainability, 9.","DOI":"10.3390\/su9030393"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/S2542-5196(18)30066-4","article-title":"Use of Geographically Weighted Logistic Regression to Quantify Spatial Variation in the Environmental and Sociodemographic Drivers of Leptospirosis in Fiji: A Modelling Study","volume":"2","author":"Mayfield","year":"2018","journal-title":"Lancet Planet. Health"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.ecolind.2017.06.032","article-title":"Urbanization Impact on Landscape Patterns in Beijing City, China: A Spatial Heterogeneity Perspective","volume":"82","author":"Li","year":"2017","journal-title":"Ecol. Indic."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"837","DOI":"10.1093\/aje\/kww073","article-title":"The Local Food Environment and Fruit and Vegetable Intake: A Geographically Weighted Regression Approach in the ORiEL Study","volume":"184","author":"Clary","year":"2016","journal-title":"Am. J. Epidemiol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"345","DOI":"10.3389\/fvets.2020.00345","article-title":"Spatial Trends in Salmonella Infection in Pigs in Spain","volume":"7","author":"Teng","year":"2020","journal-title":"Front. Vet. Sci."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1550","DOI":"10.1530\/EC-21-0418","article-title":"Iodine Nutritional Status, the Prevalence of Thyroid Goiter and Nodules in Rural and Urban Residents: A Cross-sectional Study from Guangzhou, China","volume":"10","author":"Yan","year":"2021","journal-title":"Endocr. Connect."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1155\/2003\/936084","article-title":"A Descriptive Study of Human Salmonella Serotype Typhimurium Infections Reported in Ontario from 1990 to 1998","volume":"14","author":"Ford","year":"2003","journal-title":"Can. J. Infect. Dis. Med. Microbiol."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"2237","DOI":"10.1017\/S0950268814001897","article-title":"Impact of Seafood Regulations for Vibrio Parahaemolyticus Infection and Verification by Analyses of Seafood Contamination and Infection","volume":"142","author":"Kumagai","year":"2014","journal-title":"Epidemiol. Infect."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"17","DOI":"10.3389\/fmicb.2016.00549","article-title":"Prevalence, Molecular Characterization, and Antibiotic Susceptibility of Vibrio Parahaemolyticus from Ready-to-Eat Foods in China","volume":"7","author":"Xie","year":"2016","journal-title":"Front. Microbiol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/15\/3613\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:58:24Z","timestamp":1760140704000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/15\/3613"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,28]]},"references-count":60,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2022,8]]}},"alternative-id":["rs14153613"],"URL":"https:\/\/doi.org\/10.3390\/rs14153613","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,28]]}}}