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Prospective time periodic geographical disease surveillance using a scan statistic

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Cited by:

  1. Shixin Wang & Wenjun Li & Yi Zhou & Fuli Yan & Futao Wang & Wenliang Liu, 2015. "Space–time evolution of historical drought hazards in eastern China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(3), pages 2027-2047, July.
  2. Marianne Frisén, 2014. "Spatial outbreak detection based on inference principles for multivariate surveillance," IISE Transactions, Taylor & Francis Journals, vol. 46(8), pages 759-769, August.
  3. Suparna Das & Jenevieve Opoku & Adam Allston & Michael Kharfen, 2018. "Detecting spatial clusters of HIV and hepatitis coinfections," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-13, September.
  4. Rohit Shenoi & Ned Levine & Marcella Marie Donaruma-Kwoh & Michelle A. Lyn & Jill V. Hunter & Angelo P. Giardino, 2013. "The Spatial Relationship of Child Homicides to Community Resources in a Large Metropolitan Area," SAGE Open, , vol. 3(2), pages 21582440134, April.
  5. Andrea J. Cook & Diane R. Gold & Yi Li, 2007. "Spatial Cluster Detection for Censored Outcome Data," Biometrics, The International Biometric Society, vol. 63(2), pages 540-549, June.
  6. Hadeel AlQadi & Majid Bani-Yaghoub & Sindhu Balakumar & Siqi Wu & Alex Francisco, 2021. "Assessment of Retrospective COVID-19 Spatial Clusters with Respect to Demographic Factors: Case Study of Kansas City, Missouri, United States," IJERPH, MDPI, vol. 18(21), pages 1-15, November.
  7. Lianjie Shu & Wei Jiang & Kwok‐Leung Tsui, 2012. "A standardized scan statistic for detecting spatial clusters with estimated parameters," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(6), pages 397-410, September.
  8. Loecher, Markus & Ropkins, Karl, 2015. "RgoogleMaps and loa: Unleashing R Graphics Power on Map Tiles," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i04).
  9. Felipa De Mello-Sampayo, 2022. "Spatial and Temporal Analysis of COVID-19 in the Elderly Living in Residential Care Homes in Portugal," IJERPH, MDPI, vol. 19(10), pages 1-14, May.
  10. Viergutz, Tim & Schulze-Ehlers, Birgit, 2018. "Exploring the Spatiotemporal Dynamics of Cooperative Members' Switching Decisions," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 9(5), January.
  11. Xufeng Fei & Zhaohan Lou & George Christakos & Qingmin Liu & Yanjun Ren & Jiaping Wu, 2016. "A Geographic Analysis about the Spatiotemporal Pattern of Breast Cancer in Hangzhou from 2008 to 2012," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-13, January.
  12. Yi Zhu, 2022. "Can bicycle sharing mitigate vehicle emission in Chinese large cities? Estimation based on mode shift analysis," Transportation, Springer, vol. 49(6), pages 1627-1648, December.
  13. Schiöler, Linus, 2010. "Modelling the spatial patterns of influenza incidence in Sweden," Research Reports 2010:1, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
  14. William H. Woodall & J Brooke Marshall & Michael D. Joner Jr & Shannon E Fraker & Abdel‐Salam G Abdel‐Salam, 2008. "On the use and evaluation of prospective scan methods for health‐related surveillance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 223-237, January.
  15. Sami Ullah & Hanita Daud & Sarat C Dass & Hadi Fanaee-T & Alamgir Khalil, 2018. "An Eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in Khyber-Pakhtunkhwa, Pakistan," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-13, June.
  16. Sami Ullah & Hanita Daud & Sarat C. Dass & Hadi Fanaee-T & Husnul Kausarian & Alamgir, 2020. "Space-Time Clustering Characteristics of Tuberculosis in Khyber Pakhtunkhwa Province, Pakistan, 2015–2019," IJERPH, MDPI, vol. 17(4), pages 1-10, February.
  17. Neill, Daniel B., 2009. "Expectation-based scan statistics for monitoring spatial time series data," International Journal of Forecasting, Elsevier, vol. 25(3), pages 498-517, July.
  18. Linus Schiöler & Marianne Fris�n, 2012. "Multivariate outbreak detection," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 223-242, April.
  19. Dong Ding & Axel Gandy & Georg Hahn, 2020. "A simple method for implementing Monte Carlo tests," Computational Statistics, Springer, vol. 35(3), pages 1373-1392, September.
  20. Jingnan Zhang & Yicheng Kang & Yang Yang & Peihua Qiu, 2015. "Statistical monitoring of the hand, foot and mouth disease in China," Biometrics, The International Biometric Society, vol. 71(3), pages 841-850, September.
  21. Lan Huang & Martin Kulldorff & David Gregorio, 2007. "A Spatial Scan Statistic for Survival Data," Biometrics, The International Biometric Society, vol. 63(1), pages 109-118, March.
  22. Sevvandi Kandanaarachchi & Rob J Hyndman & Kate Smith-Miles, 2020. "Early classification of spatio-temporal events using partial information," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-39, August.
  23. Fuyu Xu & Kate Beard, 2021. "A comparison of prospective space-time scan statistics and spatiotemporal event sequence based clustering for COVID-19 surveillance," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-23, June.
  24. Chih-Chieh Wu & Chien-Hsiun Chen & Sanjay Shete, 2017. "Assessing current temporal and space-time anomalies of disease incidence," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-10, November.
  25. Lyle Fearnley, 2008. "Signals Come and Go: Syndromic Surveillance and Styles of Biosecurity," Environment and Planning A, , vol. 40(7), pages 1615-1632, July.
  26. Assuno, Renato & Correa, Thais, 2009. "Surveillance to detect emerging space-time clusters," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2817-2830, June.
  27. Chenchen Yang & Han Zhang & Xunhua Li & Zongyi He & Junli Li, 2023. "Analysis of spatial and temporal characteristics of major natural disasters in China from 2008 to 2021 based on mining news database," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(3), pages 1881-1916, September.
  28. Toshiro Tango & Kunihiko Takahashi & Kazuaki Kohriyama, 2011. "A Space–Time Scan Statistic for Detecting Emerging Outbreaks," Biometrics, The International Biometric Society, vol. 67(1), pages 106-115, March.
  29. Arif Masrur & Manzhu Yu & Wei Luo & Ashraf Dewan, 2020. "Space-Time Patterns, Change, and Propagation of COVID-19 Risk Relative to the Intervention Scenarios in Bangladesh," IJERPH, MDPI, vol. 17(16), pages 1-22, August.
  30. Alexandre Rodrigues & Peter J. Diggle, 2012. "Bayesian Estimation and Prediction for Inhomogeneous Spatiotemporal Log-Gaussian Cox Processes Using Low-Rank Models, With Application to Criminal Surveillance," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 93-101, March.
  31. Ruth Benson & Jan Rigby & Christopher Brunsdon & Grace Cully & Lay San Too & Ella Arensman, 2022. "Quantitative Methods to Detect Suicide and Self-Harm Clusters: A Systematic Review," IJERPH, MDPI, vol. 19(9), pages 1-13, April.
  32. Frisén, Marianne, 2008. "Introduction to financial surveillance," Research Reports 2008:1, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
  33. Miao, Congcong & Chen, Xiang & Zhang, Chuanrong, 2024. "Assessing network-based traffic crash risk using prospective space-time scan statistic method," Journal of Transport Geography, Elsevier, vol. 119(C).
  34. Lele Deng & Yajun Han & Jinlong Wang & Haican Liu & Guilian Li & Dayan Wang & Guangxue He, 2023. "Epidemiological Characteristics of Notifiable Respiratory Infectious Diseases in Mainland China from 2010 to 2018," IJERPH, MDPI, vol. 20(5), pages 1-16, February.
  35. Yingqi Zhao & Donglin Zeng & Amy H. Herring & Amy Ising & Anna Waller & David Richardson & Michael R. Kosorok, 2011. "Detecting Disease Outbreaks Using Local Spatiotemporal Methods," Biometrics, The International Biometric Society, vol. 67(4), pages 1508-1517, December.
  36. Kunihiko Takahashi & Hideyasu Shimadzu, 2018. "Multiple-cluster detection test for purely temporal disease clustering: Integration of scan statistics and generalized linear models," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-15, November.
  37. Viergutz, Tim & Schulze-Ehlers, Birgit, 2016. "The Spatiotemporal Interrelatedness of Farmers’ Switching Decisions," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235882, Agricultural and Applied Economics Association.
  38. Mohammad Tabasi & Ali Asghar Alesheikh & Elnaz Babaie & Javad Hatamiafkoueieh, 2022. "Spatiotemporal Surveillance of COVID-19 Based on Epidemiological Features: Evidence from Northeast Iran," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
  39. Silva, Ivair R. & Assunção, Renato M., 2013. "Optimal generalized truncated sequential Monte Carlo test," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 33-49.
  40. Thais Paiva & Renato Assunção & Taynãna Simões, 2015. "Prospective space–time surveillance with cumulative surfaces for geographical identification of the emerging cluster," Computational Statistics, Springer, vol. 30(2), pages 419-440, June.
  41. Costa, Marcelo Azevedo & Ruiz-Cárdenas, Ramiro & Mineti, Leandro Brioschi & Prates, Marcos Oliveira, 2021. "Dynamic time scan forecasting for multi-step wind speed prediction," Renewable Energy, Elsevier, vol. 177(C), pages 584-595.
  42. Schiöler, Linus, 2009. "Explorative analysis of spatial patterns of influenza incidences in Sweden 1999—2008," Research Reports 2008:5, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
  43. M. R. Martines & R. V. Ferreira & R. H. Toppa & L. M. Assunção & M. R. Desjardins & E. M. Delmelle, 2021. "Detecting space–time clusters of COVID-19 in Brazil: mortality, inequality, socioeconomic vulnerability, and the relative risk of the disease in Brazilian municipalities," Journal of Geographical Systems, Springer, vol. 23(1), pages 7-36, January.
  44. Zhou, Ruoyu & Shu, Lianjie & Su, Yan, 2015. "An adaptive minimum spanning tree test for detecting irregularly-shaped spatial clusters," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 134-146.
  45. Ibrahim Musa & Hyun Woo Park & Lkhagvadorj Munkhdalai & Keun Ho Ryu, 2018. "Global Research on Syndromic Surveillance from 1993 to 2017: Bibliometric Analysis and Visualization," Sustainability, MDPI, vol. 10(10), pages 1-20, September.
  46. de Lima, Max Sousa & Duczmal, Luiz Henrique, 2014. "Adaptive likelihood ratio approaches for the detection of space–time disease clusters," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 352-370.
  47. Kieran Kalair & Colm Connaughton & Pierfrancesco Alaimo Di Loro, 2021. "A non‐parametric Hawkes process model of primary and secondary accidents on a UK smart motorway," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 80-97, January.
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