Click on any of the links to go the specific section.
General Statistical Theory, Bernoulli and Poisson Models
Kulldorff M. A spatial scan statistic. Communications in Statistics: Theory and Methods, 1997; 26:1481-1496. [view]
Spatial Scan Statistic, Bernoulli Model
Kulldorff M, Nagarwalla N. Spatial disease clusters: Detection and Inference. Statistics in Medicine, 1995; 14:799-810. [view]
Retrospective Space-Time Scan Statistic
Kulldorff M, Athas W, Feuer E, Miller B, Key C. Evaluating cluster alarms: A space-time scan statistic and brain cancer in Los Alamos. American Journal of Public Health, 1998; 88:1377-1380. [view]
Prospective Space-Time Scan Statistic
Kulldorff M. Prospective time-periodic geographical disease surveillance using a scan statistic. Journal of the Royal Statistical Society, 2001; A164:61-72. [view]
Space-Time Permutation Model
Kulldorff M, Heffernan R, Hartman J, Assunção RM, Mostashari F. A space-time permutation scan statistic for the early detection of disease outbreaks. PLoS Medicine, 2005; 2:216-224. [view]
Jung I, Kulldorff M, Richard OJ. A spatial scan statistic for multinomial data. Statistics in Medicine, 2010, epub. [view]
Jung I, Kulldorff M, Klassen A. A spatial scan statistic for ordinal data. Statistics in Medicine, 2007; 26:1594-1607 [view]
Huang L, Kulldorff M, Gregorio D. A spatial scan statistic for survival data. Biometrics, 2007, 63:109-118. [view]
Kulldorff M, Huang L, Konty K. A scan statistic for continuous data based on the normal probability model. International Journal of Health Geographics, 2009, 8:58. [view]
Weighted Normal Model
Huang L, Huang L, Tiwari R, Zuo J, Kulldorff M, Feuer E. Weighted normal spatial scan statistic for heterogeneous population data. Journal of the American Statistical Association, 2009, 104:886-898. [view]
Spatial Variation in Temporal Trends
Manuscript in preparation.
Multivariate Scan Statistic
Kulldorff M, Mostashari F, Duczmal L, Yih K, Kleinman K, Platt R. Multivariate spatial scan statistics for disease surveillance. Statistics in Medicine, 2007, 26:1824-1833. [view]
Elliptic Scanning Window
Kulldorff M, Huang L, Pickle L, Duczmal L. An elliptic spatial scan statistic. Statistics in Medicine, 2006, 25:3929-3943. [view]
Isotonic Spatial Scan Statistic
Kulldorff M. An isotonic spatial scan statistic for geographical disease surveillance. Journal of the National Institute of Public Health, 1999;48:94-101. [view]
Fernando LP Oliveira, Gustavo de Souza, Andre LF Cançado, Gladston JP Moreira and Martin Kulldorff. Border Analysis for Spatial Clusters. manuscript in preparation 2017
Boscoe's Cluster Restriction by Risk level
Boscoe FP, McLaughlin C, Schymura MJ, Kielb CL. Visualization of the spatial scan statistic using nested circles. Healtrh and Place, 2003; 9:273-277.
Monte Carlo Hypothesis Testing
Dwass M. Modified randomization tests for nonparametric hypotheses. Annals of Mathematical Statistics, 1957; 28:181-187.
Besag J, Clifford J. Sequential Monte Carlo p-values. Biometrika, 1991; 78:301-330.
Silva I, Assunção RM, Costa M. Power of the sequential Monte Carlo test. Sequential Analysis, 2009; 28:163-174.
Abrams A, Kleinman K, Kulldorff M. Gumbel based p-value approximations for spatial scan statistics. International Journal of Health Geographics 2010, 9:61.Manuscript, 2008. [view]
Read S, Bath PA, Willett P, Maheswaran R. A study on the use of Gumbel approximation with the Bernoulli spatial scan statistic. Statistics in Medicine, 2013.
Jung I, Park G. p-value approximations for spatial scan statistics using extreme value distributions. Statistics in Medicine, 34:504-514, 2015.
Kleinman K, Lazarus R, Platt R. A generalized linear mixed models approach for detecting incident clusters of disease in small areas, with an application to biological terrorism. American Journal of Epidemiology, 159:217-24, 2004.
Adjusting for Covariates
Kulldorff M. A spatial scan statistic. Communications in Statistics: Theory and Methods, 26:1481-1496, 1997. [ view]
Kulldorff M, Feuer EJ, Miller BA, Freedman LS. Breast cancer clusters in Northeastern United States: A geographic analysis. American Journal of Epidemiology, 146:161-170, 1997. [view]
Kleinman K, Abrams A, Kulldorff M, Platt R. A model-adjusted space-time scan statistic with an application to syndromic surveillance. Epidemiology and Infection, 2005, 133:409-419.
Klassen A, Kulldorff M, Curriero F. Geographical clustering of prostate cancer grade and stage at diagnosis, before and after adjustment for risk factors. International Journal of Health Geographics, 2005, 4:1. [view]
Huang L, Kulldorff M, Gregorio D. A spatial scan statistic for survival data. Biometrics, 2006, in press. [ view]
Iterative Scan Statistics, Adjusting for More Likely Clusters
Zhang Z, Kulldorff M, Assunção R. Spatial scan statistics adjusted for multiple clusters. Journal of Probability and Statistics, 2010, 642379.
Kulldorff M. Spatial scan statistics: Models, calculations and applications. In Balakrishnan and Glaz (eds), Recent Advances on Scan Statistics and Applications. Boston, USA: Birkhäuser, 1999. [view]
Random Number Generator
Lehmer DH. Mathematical methods in large-scale computing units. In Proceedings of the second symposium on large scale digital computing machinery. Cambridge, USA: Harvard Univ. Press, 1951.
Park SK, Miller KW. Random number generators: Good ones are hard to find. Communications of the ACM, 31:1192-1201, 1988.
Abrams AM, Kleinman KP. A SaTScan (TM) macro accessory for cartography (SMAC) package implemented with SAS (R) software. International Journal of Health Geographics, 6:6,2007. [view]
Reporting, Visualization and Mapping
Boscoe FP, McLaughlin C, Schymura MJ, Kielb CL. Visualization of the spatial scan statistic using nested circles. Health and Place, 9:273-277, 2003.
Chen J, Roth RE, Naito AT, Lengerich EJ, MacEachern AM. Geovisual analytics to enhance spatial scan statistic interpretation: ananalysis of US cervical cancer mortality. International Journal of Health Geographics, 7:57, 2008. [view]
North American Association of Central Cancer Registries, SaTScan to Google Earth Conversion Tool. [view GIS Resources]
Han J, Zhu L, Kulldorff M, Hostovich S, Tatalovich Z, Lewis D, Feuer E. Determining optimal cluster reporting sizes for spatial scan statistics. Manuscript, 2015, submitted.
Methods Evaluations and Comparisons
Kulldorff M, Tango T, Park P. Power comparisons for disease clustering tests. Computational Statistics and Data Analysis, 42:665-684, 2003.
Song C, Kulldorff M. Power evaluation of disease clustering tests. International Journal of Health Geographics, 2:9, 2003. [view]
Kulldorff M, Zhang Z, Hartman J, Heffernan R, Huang L, Mostashari F. Evaluating disease outbreak detection methods: Benchmark data and power calculations. Morbidity and Mortality Weekly Report, 53:144-151, 2004. [view]
Nordin J, Goodman M, Kulldorff M, Ritzwoller D, Abrams A, Kleinman K, Levitt MJ, Donahue J, Platt R. Using modeled anthrax attacks on the Mall of America to assess sensitivity of syndromic surveillance. Emerging Infectious Diseases, 11:1394-1398, 2005. [view]
Ozdenerol E, Williams BL, Kang SY, Magsumbol MS. Comparison of spatial scan statistic and spatial filtering in estimating low birth weight clusters. International Journal of Health Geographics, 4:19, 2005. [view]
Costa MA, Assunção RM. A fair comparison between the spatial scan and Besag-Newell disease clustering tests. Environmental and Ecological Statistics, 12:301-319, 2005.
Tango T, Takahashi K. A flexibly shaped spatial scan statistic for detecting clusters. International Journal of Health Geographics, 4:11, 2005. [view]
Kulldorff M, Song C, Gregorio D, Samociuk H, DeChello L. Cancer map patterns: Are they random or not? American Journal of Preventive Medicine, 30:S37-49, 2006. [view]
Duczmal L, Kulldorff M, Huang L. Evaluation of spatial scan statistics for irregular shaped clusters. Journal of Computational and Graphical Statistics, 15:428-442, 2006.
Aamodt G, Samuelsen SO, Skrondal A. A simulation study of three methods for detecting disease clusters. International Journal of Health Geographics, 5:15, 2006. [view]
Jackson MC, Huang L, Luo J, Hachey M, Feuer E. Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers. International Journal of Health Geographics 2009;8:55. [view]
Wheeler DC. A comparison of spatial clustering and cluster detection techniques for childhood leukemia incidence in Ohio, 1996-2003. International Journal of Health Geographics 2007;6:13. [view]
Goujon-Bellec S, Demoury C, Guyot-Goubin A, Hémon D, Clavel J. Detection of clusters of a rare disease over a large territory: performance of cluster detection methods. International Journal of Health Geographics. 2011:10:53. [view]
Selected Applications by Field of Study
Airborne Infectious Diseases: Coronavirus
Adegboye OA, Gayawan E, Hanna F. Spatial modelling of contribution of individual level risk factors for mortality from Middle East respiratory syndrome coronavirus in the Arabian Peninsula. PloS one. 12:e0181215, 2017. [view]
Greene SK, Peterson ER, Balan D, Jones L, Culp GM, Kulldorff M. Detecting Emerging COVID-19 Community Outbreaks at High Spatiotemporal Resolution-New York City, June 2020. medRxiv, 2020. [view]
Desjardins MR, Hohl A, Delmelle EM. Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters. Applied Geography, 102202, 2020. [view]
Kim S, Castro MC. Spatiotemporal pattern of COVID-19 and government response in South Korea (as of May 31, 2020). International Journal of Infectious Diseases, 98:328-33, 2020. [view]
Amin R, Hall T, Church J, Schlierf D, Kulldorff M. Geographical surveillance of COVID-19: Diagnosed cases and death in the United States. medRxiv, 2020. [view]
Masrur A, Yu M, Luo W, Dewan A. Space-time patterns, change, and propagation of COVID-19 risk relative to the intervention scenarios in Bangladesh. International Journal of Environmental Research and Public Health, 17:5911, 2020. [view]
Leal-Neto OB, Santos FA, Lee JY, Albuquerque JO, Souza WV. Prioritizing COVID-19 tests based on participatory surveillance and spatial scanning. International Journal of Medical Informatics, 143:104263, 2020. [view]
Benita F, Gasca-Sanchez F. On the main factors influencing COVID-19 spread and deaths in Mexico: A comparison between Phase I and II. medRxiv, 2020. [view]
Ballesteros P, Salazar E, Sánchez D, Bolanos C. Spatial and spatiotemporal clustering of the COVID19 pandemic in Ecuador. Revista de la Facultad de Medicina. 69, 2020. [view]
Hohl A, Delmelle EM, Desjardins MR, Lan Y. Daily surveillance of COVID-19 using the prospective space-time scan statistic in the United States. Spatial and Spatio-temporal Epidemiology, 34:100354, 2020. [view]
Andersen LM, Harden SR, Sugg MM, Runkle JD, Lundquist TE. Analyzing the spatial determinants of local Covid-19 transmission in the United States. Science of the Total Environment. 754:142396, 2020. [view]
Cordes J, Castro MC. Spatial analysis of COVID-19 clusters and contextual factors in New York City. Spatial and Spatio-temporal Epidemiology, 34:100355, 2020. [view]
Acharya BK, Khanal L, Mahyoub AS, Ruan Z, Yang Y, Adhikari SK, Pandit S, Neupane BK, Paudel BK, Lin H. Execution of intervention matters more than strategy: A lesson from the spatiotemporal assessment of COVID-19 clusters in Nepal. medRxiv, 2020. [view]
Martines MR, Ferreira RV, Toppa RH, Assuncao L, Desjardins MR, Delmelle EM. Detecting space-time clusters of COVID-19 in Brazil: mortality, inequality, socioeconomic vulnerability, and the relative risk of the disease in Brazilian municipalities. MedRxiv, 2020. [view]
Chow TE, Choi Y, Yang M, Mills D, Yue R. Geographic pattern of human mobility and COVID-19 before and after Hubei lockdown. Annals of GIS, 2020. [view]
Alkhamis MA, Al Youha S, Khajah MM, Haider NB, Alhardan S, Nabeel A, Al Mazeedi S, Al-Sabah SK. Spatiotemporal dynamics of the COVID-19 pandemic in the State of Kuwait. International Journal of Infectious Diseases, 98:153-60, 2020. [view]
Azmach NN, Tesfahannes TG, Abdulsemed SA, Hamza TA. Prospective Time Periodic Geographical Covid-19 Surveillance in Ethiopia Using a Space-time Scan Statistics: Detecting and Evaluating Emerging Clusters. Research Square; 2020. [view]
Prendecki M, Clarke C, Cairns T, Cook T, Roufosse C, Thomas D, Willicombe M, Pusey CD, McAdoo SP. Anti-glomerular basement membrane disease during the COVID-19 pandemic. Kidney International, 2020. [view]
Gomes DS, Andrade LA, Ribeiro CJ, Peixoto MV, Lima SV, Duque AM, Cirilo TM, Góes MA, Lima AG, Santos MB, Araú jo KC. Risk clusters of COVID-19 transmission in northeastern Brazil: prospective space-time modelling. Epidemiology & Infection, 148, 2020. [view]
Qi C, Zhu YC, Li CY, Hu YC, Liu LL, Zhang DD, Wang X, She KL, Jia Y, Liu TX, Li XJ. Epidemiological characteristics and spatial-temporal analysis of COVID-19 in Shandong Province, China. Epidemiology & Infection, 148, 2020. [view]
Moreira RD. COVID-19: intensive care units, mechanical ventilators, and latent mortality profiles associated with case-fatality in Brazil. Cadernos de Saúde Pública, 36:e00080020, 2020. [view]
Tchole AI, Li ZW, Wei JT, Ye RZ, Wang WJ, Du WY, Wang HT, Yin CN, Ji XK, Xue FZ, Bachir AM. Epidemic and control of COVID-19 in Niger: quantitative analyses in a least developed country. Journal of Global Health, 10, 2020. [view]
Andrade LA, Gomes DS, Lima SV, Duque AM, Melo MS, Góes MA, Ribeiro CJ, Peixoto MV, Souza CD, Santos AD. COVID-19 Mortality in an area of northeast Brazil: epidemiological characteristics and prospective spatiotemporal modeling. Epidemiology & Infection, 148,e288,1-7, 2020. [view]
Bonnet E, Le Marcis F, Faye A, Sambieni E, Fournet F, Boyer F, Coulibaly A, Kadio K, Diongue FB, Ridde V. The COVID-19 Pandemic in Francophone West Africa: From the First Cases to Responses in Seven Countries. Research Square, 2020. [view]
Durán Morera N, Botello Ramírez E. Detección de conglomerados «activos» emergentes de altas tasas de incidencia, para la vigilancia rápida de la COVID-19. Medicentro Electrónica, 24:642-655, 2020. [view]
Leveau CM. Variaciones espacio-temporales de la mortalidad por COVID-19 en barrios de la Ciudad Autónoma de Buenos Aires, Argentina. Scielo Preprints, 2020. [view]
Badaloni C, Asta F, Michelozzi P, Mataloni F, Di Rosa E, Scognamiglio P, Vairo F, Davoli M, Leone M. Spatial analysis for detecting clusters of cases during the COVID-19 emergency in Rome and in the Lazio Region. Epidemiologia & Prevenzione, 44:144-151, 2020. [view]
Paul S, Bhattacharya S, Mandal B, Haldar S, Mandal S, Kundu S, Biswas A. Dynamics and risk assessment of SARS-CoV-2 in urban areas: a geographical assessment on Kolkata Municipal Corporation, India. Spatial Information Research, 2020. [view]
Airborne Infectious Diseases: Other
Bakker MI, Hatta M, Kwenang A, Faber WR, van Beers SM, Klatser PR, Oskam L. Population survey to determine risk factors for Mycobacterium leprae transmission and infection. International Journal of Epidemiology, 33: 1329-1336, 2004.
Andrade AL, Silva SA, Martelli CM, Oliveira RM, Morais Neto OL, Siqueira Junior JB, Melo LK, Di Fabio JL. Population-based surveillance of pediatric pneumonia: use of spatial analysis in an urban area of Central Brazil. Cadernos de Saúde Pública. 20: 411-421, 2004. [view]
Moore GE, Ward MP, Kulldorff M, Caldanaro RJ, Guptill LF, Lewis HB, Glickman LT. Identification of a space-time cluster of canine rabies vaccine-associated adverse events using a very large veterinary practice database. Vaccine, epub ahead of print, 2005.
Elias J, Harmsen D, Claus H, Hellenbrand W, Frosch M, Vogel U. Spatiotemporal analysis of invasive meningococcal disease, Germany. Emerging Infectious Diseases, 12:1689-1695, 2006. [view]
Oeltmann JE, Varma JK, Ortega L, Liu Y, O'Rourke T, Cano M, Harrington T, Toney S, Jones W, Karuchit S, Diem L, Rienthong D, Tappero JW, Ijaz K, Maloney, S. Multidrug-Resistant Tuberculosis Outbreak among US-bound Hmong Refugees, Thailand, 2005. Emerging Infectious Diseases, 14:1715-1721, 2008. [view]
Fischer EAJ, Pahan D, Chowdhury SK, Oskam L, Richardus JH. The spatial distribution of leprosy in four villages in Bangladesh: An observational study. BMC Infectious Diseases, 8:125, 2008.
Liang L, Xu B, Chen Y, Liu Y, Cao W, Fang L, Feng L, Goodchild MF, Gong P. Combining spatial-temporal and phylogenetic analysis approaches for improved understanding on global H5N1 transmission. PLoS One. 5:e13575, 2010. [view]
Kammerer JS, Shang N, Althomsons SP, Haddad MB, Grant J, Navin TR. Using statistical methods and genotyping to detect tuberculosis outbreaks. International Journal of Health Geographics, 12:15, 2013. [view]
Chen JH, Weng C, Chnag HG. Using space-time scan statistic to detect pertussis and shigellosis outbreaks. CSTE Annual Conference, 2013. [view]
Ratnayake R1, Allard R. Challenges to the surveillance of meningococcal disease in an era of declining incidence in Montréal, Québec. Canadian Journal of Public Health, 104:e335-9, 2013. [view]
Nana Yakam A, Noeske J, Dambach P. Spatial analysis of tuberculosis in Douala, Cameroon: clustering and links with socio-economic status. The International Journal of Tuberculosis and Lung Disease, 18:292-297, 2014.
Shea KM, Kammerer JS, Winston CA, Navin TR, Horsburgh CR. Estimated rate of reactivation of latent tuberculosis infection in the United States, overall and by population subgroup. American Journal of Epidemiology, 179:216-25, 2014.
Souris M, Selenic D, Khaklang S, Ninphanomchai S, Minet G, Gonzalez JP, Kittayapong P Poultry farm vulnerability and risk of avian influenza re-emergence in Thailand. International Journal of Environmental Research and Public Health, 11:934-951, 2014. [view]
Zhang Y, Shen Z, Ma C, Jiang C, Feng C, Shankar N, Yang P, Sun W, Wang Q. Cluster of Human Infections with Avian Influenza A (H7N9) Cases: A Temporal and Spatial Analysis. International Journal of Environmental Research and Public Health, 12:816-828, 2015. [view]
Pinchoff J, Chipeta J, Banda GC, Miti S, Shields T, Curriero F, Moss W J. Spatial clustering of measles cases during endemic (1998-2002) and epidemic (2010) periods in Lusaka, Zambia. BMC infectious diseases, 15:121, 2015. [view]
Food and Water Borne Diseases
Cruz Payão Pellegrini D. Análise espaço-temporal da leptospirose no município do Rio de Janeiro (1995-1999). Rio de Janeiro: Fundação Oswaldo Cruz, 2002. [view]
Enemark HL, Ahrens P, Juel CD, Petersen E, Petersen RF, Andersen JS, Lind P, Thamsborg SM. Molecular characterization of Danish Cryptosporidium parvum isolates. Parasitology, 125:331-341, 2002.
Sauders BD, Fortes ED, Morse DL, Dumas N, Kiehlbauch JA, Schukken Y, Hibbs JR, Wiedmann M. Molecular subtyping to detect human listeriosis clusters. Emerging Infectious Diseases, 9:672-680, 2003. [view]
Odoi A, Martin SW, Michel P, Middleton D, Holt J, Wilson J. Investigation of clusters of giardiasis using GIS and a spatial scan statistic. International Journal of Health Geographics, 3:11, 2004. [view]
Yih K, Abrams A, Kleinman K, Kulldorff M, Nordin J, Platt R. Ambulatory-care diagnoses as potential indicators of outbreaks of gastrointestinal illness --- Minnesota. Morbidity and Mortality Weekly Report, 54 Suppl:157-62, 2005. [view]
Jones RC, Liberatore M, Fernandez JR Gerber SI. Use of a prospective space-time scan statistic to prioritize shigellosis case investigations in an urban jurisdiction. Public Health Reports, 121:133-9, 2006.
Pearl DL, Louie M, Chui L, Dore K, Grimsrud KM, Leedell D, Martin SW, Michel P, Svenson LW, McEwen SA. The use of outbreak information in the interpretation of clustering of reported cases of Escherichia coli O157 in space and time in Alberta, Canada, 2000-2002. Epidemiology and Infection, pud ahead of print, 2006.
de Souza EA, da Silva-Nunes M, Malafronte Rdos S, Muniz PT, Cardoso MA, Ferreira MU. Prevalence and spatial distribution of intestinal parasitic infections in a rural Amazonian settlement, Acre State, Brazil. Cadernos de Saude Publica, 23:427-34, 2007. [view]
Osei FB, Duker AA. Spatial dependency of V. cholera prevalence on open space refuse dumps in Kumasi, Ghana: a spatial statistical modeling. International Journal of Health Geographics, 7:62, 2008. [view]
Sowmyanarayanan TV, Mukhopadhya A, Gladstone BP, Sarkar R, Kang G. Investigation of a hepatitis A outbreak in children in an urban slum in Vellore, Tamil Nadu, using geographic information systems. Indian Journal of Medical Research, 128:32-37, 2008.
Oviedo M, Munoz P, Dominguez A, Carmona G, Batalla J, Borras E, Jansá JM. Evaluation of Mass Vaccination Programmes: The experience of hepatitis A in Catalonia (in Spanish). Revista Española de Salud Pública, 83:697-709, 2009. [view]
Luquero FJ, Banga CN, Remartínez D, Palma PP, Baron E, Grais RF. Cholera epidemic in Guinea-Bissau (2008): the importance of "place". PLoS One, 6:e19005, 2011. [view]
Bompangue Nkoko D, Giraudoux P, Plisnier PD, Tinda AM, Piarroux M, Sudre B, Horion S, Tamfum JJ, Ilunga BK, Piarroux R. Dynamics of cholera outbreaks in Great Lakes region of Africa, 1978-2008. Emerging Infectious Diseases, 17:2026-2034, 2011. [view]
Tang F, Cheng Y, Bao C, Hu J, Liu W, Liang W, Wu Y, Norris J, Peng Z, Yu R, Shen H, Chen F. Spatio-temporal trends and risk factors for Shigella from 2001 to 2011 in Jiangsu province, People's Republic of China. PLoS ONE, 9:e83487, 2014. [view]
Chan TC, Hwang JS, Chen RH, King CC, Chiang PH. Spatio-temporal analysis on enterovirus cases through integrated surveillance in Taiwan. BMC Public Health, 14:11, 2014. [view]
Briggs ADM, Boxall NS, van Santen D, Chalmers RM, McCarthy ND. Approaches to the detection of very small, common, and easily missed outbreaks that together contribute substantially to human Cryptosporidium infection. Epidemiology and Infection, epub, 2014.
Wang J, Cao Z, Zeng DD, Wang Q, Wang X, Qian H. Epidemiological Analysis, Detection, and Comparison of Space-Time Patterns of Beijing Hand-Foot-Mouth Disease (2008-2012). PLoS One, 9:e2745, 2014. [view]
Viñas M, Tuduri E, Galar A, Yih WK, Pichel M, Stelling J, Brengi S, Della Gaspera A, van der Ploeg C, Bruno S, Rogé A, Caffer M,, Kulldorff M, Galas M. Laboratory-based prospective surveillance for community outbreaks of Shigella spp. in Argentina. PLoS Neglected Tropical Diseases, 2013, 7:e2521, 2013.
Sexually Transmitted Diseases
Jennings JM, Curriero FC, Celentano D, Ellen JM. Geographic identification of high gonorrhea transmission areas in Baltimore, Maryland. American Journal of Epidemiology, 161: 73-80, 2005.
Wylie JL, Cabral T, Jolly AM. Identification of networks of sexually transmitted infection: a molecular, geographic, and social network analysis. J Infect Diseases, 191:899-906, 2005.
Wand H, Ramjee G. Targeting the hotspots: Investigating spatial and demographic variations in HIV infection in small communities in South Africa. Journal of the International AIDS Society, 13:41, 2010. [view]
Egger JR, Konty KJ, Borrelli JM, Cummiskey J, Blank S. Monitoring temporal changes in the specificity of an oral HIV test: a novel application for use in postmarketing surveillance.PLoS One, 25:e12231, 2010. [view]
Gesink DC, Sullivan AB, Miller WC, Bernstein KT. Sexually transmitted disease core theory: roles of person, place, and time. American Journal of Epidemiology. 174:81-9, 2011.
Hixon BA, Omer SA, del Rio C, Frew PM. Spatial clustering of HIV prevalence in Atlanta, Georgia and population characteristics associated with case concentrations. Journal of Urban Health, 88:129-141, 2011.
Cuadros DF, Awad SF, Abu-Raddad LJ. Mapping HIV clustering: a strategy for identifying populations at high risk of HIV infection in sub-Saharan Africa. International Journal of Health Geographics, 12:28, 2013. [view]
Cuadros DF, Abu-Raddad LJ. Spatial variability in HIV prevalence declines in several countries in sub-Saharan Africa. Health and Place, 28:45-49, 2014.
González R, Augusto OJ, Munguambe K, Pierrat C, Pedro EN, Sacoor C, de Lazzari E, Aponte JJ. Macete E, Alonso PL, Menendez C, Naniche D. HIV incidence and spatial clustering in a rural area of southern Mozambique. PloS One, 10:e0132053, 2015. [view]
Vector Borne Diseases
Fevre EM, Coleman PG, Odiit M, Magona JW, Welburn SC, Woolhouse MEJ. The origins of a new Trypanosoma brucei rhodesiense sleeping sickness outbreak in eastern Uganda. The Lancet, 358:625-628, 2001.
Chaput EK, Meek JI, Heimer R. Spatial analysis of human granulocytic ehrlichiosis near Lyme, Connecticut. Emerging Infectious Diseases, 8:943-948, 2002. [view]
Mostashari F, Kulldorff M, Hartman JJ, Miller JR, Kulasekera V. Dead bird clustering: A potential early warning system for West Nile virus activity. Emerging Infectious Diseases, 9:641-646, 2003. [view]
Ghebreyesus TA, Byass P, Witten KH, Getachew A, Haile M, Yohannes M, Lindsay SW. Appropriate Tools and Methods for Tropical Microepidemiology: a Case-study of Malaria Clustering in Ethiopia. Ethiopian Journal of Health Development. 17:1-8, 2003.
Brooker S, Clarke S, Njagi JK, Polack S, Mugo B, Estambale B, Muchiri E, Magnussen P, Cox J. Spatial clustering of malaria and associated risk factors during an epidemic in a highland area of western Kenya. Tropical Medicine and International Health, 9: 757-766, 2004.
Washington CH, Radday J, Streit TG, Boyd HA, Beach MJ, Addiss DG, Lovince R, Lovegrove MC, Lafontant JG, Lammie PJ, Hightower AW. Spatial clustering of filarial transmission before and after a Mass Drug Administration in a setting of low infection prevalence. Filaria Journal, 3:3, 2004. [view]
Gosselin PL, Lebel G, Rivest S, Fradet MD. The Integrated System for Public Health Monitoring of West Nile Virus (ISPHM-WNV): a real-time GIS for surveillance and decision-making. International Journal of Health Geographics, 4:21, 2005. [view]
Gaudart J, Poudiougou B, Ranque S, Doumbo O. Oblique decision trees for spatial pattern detection: optimal algorithm and application to malaria risk. BMC Medical Research Methodology, 5:22, 2005. [view]
Nisha V, Gad SS, Selvapandian D, Suganya V, Rajagopal V, Suganti P, Balraj V, Devasundaram J. Geographical information system (GIS) in investigation of an outbreak [of dengue fever]. Journal of Communicable Diseases, 37:39-43, 2005.
Reperant LA, Deplazes P. Cluster of Capillaria hepatica infections in non-commensal rodents from the canton of Geneva, Switzerland. Parasitology Research, 96:340-342, 2005.
Fang L, Yan L, Liang S, de Vlas SJ, Feng D, Han X, Zhao W, Xu B, Bian L, Yang H, Gong P, Richardus JH, Cao W. Spatial analysis of hemorrhagic fever with renal syndrome in China. BMC Infectious Diseases, 6:77, 2006. [view]
Bonilla RE. Distribución Espacio-Temporal de la Fiebre Dengue en Costa Rica. Población y Salud en Mesoamérica, 3:2:2. [view]
Gaudart J, Poudiougou B, Dicko A, Ranque S, Toure O, Sagara I, Diallo M, Diawara S, Ouattara A, Diakite M, Doumbo OK. Space-time clustering of childhood malaria at the household level: a dynamic cohort in a Mali village. BMC Public Health, 6:286, 2006. [view]
Lian M, Warner RD, Alexander JL, Dixon KR. Using geographic information systems and spatial and space-time scan statistics for a population-based risk analysis of the 2002 equine West Nile epidemic in six contiguous regions of Texas. International Journal of Health Geographics, 6:42, 2007. [view]
Coleman M, Coleman M, Mabuza AM, Kok G, Coetzee M, Durrheim DN. Using the SaTScan method to detect local malaria clusters for guiding malaria control programmes. Malaria Journal, 8:68, 2009. [view]
Mirghani SE, Nour BY, Bushra SM, Elhassan IM, Snow RW, Noor AM. The spatial-temporal clustering of Plasmodium falciparum infection over eleven years in Gezira State, The Sudan. Malaria Journal, 9:172, 2010. [view]
Haque U, Sunahara T, Hashizume M, Shields T, Yamamoto T, Haque R, Glass GE. Malaria prevalence, risk factors and spatial distribution in a hilly forest area of Bangladesh. PLoS ONE 6(4): e18908, 2011. [view]
Schmidt W-P, Suzuki M, Dinh Thiem V, White RG, Tsuzuki A, Yoshida LM, Yanai H, Haque U, Huu Tho L, Duc Anh D,Ariyoshi K. Population Density, Water Supply, and the Risk of Dengue Fever in Vietnam: Cohort Study and Spatial Analysis. PLoS Medicine, 8:8, e1001082, 2011. [view]
Winskill P, Rowland M, Mtove G, Malima RC, Kirby MJ. Malaria risk factors in north-east Tanzania. Malaria Journal 10:98, 2011. [view]
Washington CH, Radday J, Streit TG, Boyd HA, Beach MJ, Addiss DG, Lovince R, Lovegrove MC, Lafontant JG, Lammie PJ, Hightower AW. Spatial clustering of filarial transmission before and after a mass drug administration in a setting of low infection prevalence. Filaria Journal, 3: 3, 2004. [view]
Bhattarai NR, Van der Auwera G, Rijal S, Picado A, Speybroeck N, Khanal B, De Doncker S, Lal Das M, Ostyn B, Davies C, Coosemans M, Berkvens D, Boelaert M, Dujardin JC. Domestic animals and epidemiology of visceral leishmaniasis, Nepal. Emerging Infectious Diseases, 16:231-237, 2010. [view]
Cook J, Kleinschmidt I, Schwabe C, Nseng G, Bousema T, Corran PH, Riley EM, Drakeley CJ. Serological markers suggest heterogeneity of effectiveness of malaria control interventions on Bioko Island, Equatorial Guinea. PLoS One, 6:e25137, 2011. [view]
Nourein AB, Abass MA, Nugud AH, El Hassan I, Snow RW, Noor AM. Identifying residual foci of Plasmodium falciparum infections for malaria elimination: the urban context of Khartoum, Sudan. PLoS One, 6:e16948, 2011. [view]
Rochlin I, Turbow D, Gomez F, Ninivaggi DV, Campbell SR. Predictive mapping of human risk for West Nile virus (WNV) based on environmental and socioeconomic factors. PLoS One. 6:e23280, 2011. [view]
Impoinvil DE, Solomon T, Schluter WW, Rayamajhi A, Bichha RP, Shakya G, Caminade C, Baylis M. The spatial heterogeneity between Japanese encephalitis incidence distribution and environmental variables in Nepal. PLoS One, 6:e22192, 2011. [view]
Bejon P, Turner L, Lavstsen T, Cham G, Olotu A, Drakeley CJ, Lievens M, Vekemans J, Savarese B, Lusingu J, von Seidlein L, Bull PC, Marsh K, Theander TG. Serological evidence of discrete spatial clusters of Plasmodium falciparum parasites. PLoS One, 6:e21711, 2011. [view]
Jones SG, Conner W, Song B, Gordon D, Jayakaran A. Comparing spatio-temporal clusters of arthropod-borne infections using administrative medical claims and state reported surveillance data. Spatial and Spatio-Temporal Epidemiology, 2012.
Sindato C, Karimuribo ED, Pfeiffer DU, Mboera LE, Kivaria F, Dautu G, Bernadrd B, Paweska JT. Spatial and temporal pattern of Rift Valley fever outbreaks in Tanzania; 1930 to 2007. PloS One, 9(2), e88897, 2014. [view]
Bejon P, Williams TN, Nyundo C, Hay SI, Benz D. Gething PW, Otiende M, Peshu J, Bashraheil M, Greenhouse B, Bousema T, Bauni E, Marsh K, Smith DL, Borrmann S. A micro-epidemiological analysis of febrile malaria in Coastal Kenya showing hotspots within hotspots. eLife, 3:e02130, 2014. [view]
Mosha JF, Sturrock HJ, Greenwood B, Sutherland CJ, Gadalla NB, Atwal S, Hemelaar S, Brown JM, Drakeley C, Kibiki G, Bousema T, Chandramohan D, Gosling RD. Hot spot or not: a comparison of spatial statistical methods to predict prospective malaria infections. Malaria Journal, 13:53, 2014. [view]
Carson C, Lavender CJ, Handasyde KA, O'Brien CR, Hewitt N, Johnson PD, Fyfe JA. Potential wildlife sentinels for monitoring the endemic spread of human buruli ulcer in South-East Australia. PLoS Neglected Tropical Diseases, 8:e2668, 2014. [view]
Delgado-Ratto C, Soto-Calle VE, Van den Eede P, Gamboa D, Rosas A, Abatih EN, Rodriguez Ferrucci H, Llanos-Cuentas A, Van Geertruyden JP, Erhart A, D'Alessandro U. Population structure and spatio-temporal transmission dynamics of Plasmodium vivax after radical cure treatment in a rural village of the Peruvian Amazon. Malaria Journal, 13:8, 2014. [view]
Kracalik I, Malania L, Tsertsvadze N, Manvelyan J, Bakanidze L, Imnadze P, Tsanava S, Blackburn JK. Human cutaneous anthrax, Georgia 2010-2012. Emerging Infectious Diseases, 20:261-264, 2014. [view]
Liu C, Liu Q, Lin H, Xin B, Nie J. Spatial analysis of dengue fever in Guangdong Province, China, 2001-2006. Asia Pacific Journal of Public Health, 26:58-66, 2014.
Mulatti P, Mazzucato M, Montarsi F, Ciocchetta S, Capelli G, Bonfanti L, Marangon S. Retrospective space-time analysis methods to support West Nile virus surveillance activities. Epidemiology and Infection, 143:202-213, 2015.
Mollalo A, Alimohammadi A, Shirzadi MR, Malek MR. Geographic Information System-Based Analysis of the Spatial and Spatio-Temporal Distribution of Zoonotic Cutaneous Leishmaniasis in Golestan Province, North-East of Iran. Zoonoses and Public Health., 62:18-28, 2015.
Lal A, Hales S. Heterogeneity in hotspots: spatio-temporal patterns in neglected parasitic diseases. Epidemiology and Infection, 143:631-639, 2015.
Nsoesie EO, Ricketts RP, Brown HE, Fish D, Durham DP, Mbah MLN, Christian T, Ahmed S, Marcellin C, Shelly E, Owers K, Wenzel N, Galvani AP, Brownstein JS. Spatial and temporal clustering of chikungunya virus transmission in Dominica. PLoS Neglected Tropical Diseases, 9:e0003977, 2015. [view]
Wahnich A, Lall R, Weiss D. Monitoring for Local Transmission of Zika Virus using Emergency Department Data. Online Journal of Public Health Informatics, 9:e115, 2017. [view]
Hospital Associated Infections
Huang SS, Yokoe DS, Stelling J, Placzek H, Kulldorff M, Kleinman K, O'Brien TF, Calderwood MS, Vostok J, Platt R. Automated detection of infectious disease outbreaks in hospitals: A Retrospective Cohort Study. PLoS Medicine, 7:e1000238, 2010. [view]
Vlek AL, Cooper BS, Kypraios T, Cox A, Edgeworth JD, Auguet OT. Clustering of antimicrobial resistance outbreaks across bacterial species in the intensive care unit. Clinical Infectious Diseases, 57:65-76,2013. [view]
Faires MC. The Epidemiology of Methicillin-Resistant Staphylococcus aureus and Clostridium difficile in Community Hospitals. PhD Thesis, University of Guelph, 2013. [view]
Abboud CS, Monteiro J, França JI, Pignatari AC, Souza EE, Camargo EC, Monteiro AM, Santos RG, Kiffer CR. A space-time model for carbapenemase-producing Klebsiella pneumoniae (KPC) cluster quantification in a high-complexity hospital. Epidemiology and Infection, 2015. [view]
Lefebvre A, Bertrand X, Vanhems P, Lucet JC, Chavanet P, Astruc K, Thouverez M, Quantin C, Aho-Glélé, L S. Detection of Temporal Clusters of Healthcare-Associated Infections or Colonizations with Pseudomonas aeruginosa in Two Hospitals: Comparison of SaTScan and WHONET Software Packages. PLoSOne, 10, e0139920, 2015. [view]
Other Infectious Diseases
Cousens S, Smith PG, Ward H, Everington D, Knight RSG, Zeidler M, Stewart G, Smith-Bathgate EAB, Macleod MA, Mackenzie J, Will RG. Geographical distribution of variant Creutzfeldt-Jakob disease in Great Britain, 1994-2000. The Lancet, 357:1002-1007, 2001.
Huillard d'Aignaux J, Cousens SN, Delasnerie-Laupretre N, Brandel JP, Salomon D, Laplanche JL, Hauw JJ, Alperovitch A. Analysis of the geographical distribution of sporadic Creutzfeldt-Jakob disease in France between 1992 and 1998. International Journal of Epidemiology, 31: 490-495, 2002. [view]
Dreesman J, Scharlach H. Spatial-statistical analysis of infectious disease notification data in Lower Saxony. Gesundheitswesen, 66: 783-789, 2004.
Polack SR, Solomon AW, Alexander NDE, Massae PA, Safari S, Shao JF, Foster A, Mabey DC. The household distribution of trachoma in a Tanzanian village: an application of GIS to the study of trachoma. Transactions of the Royal Society of Tropical Medicine and Hygiene, 99: 218-225, 2005.
Ghosh AN, Bhatta DR, Ansari MT, Tiwari HK, Mathuria JP, Gaur A, Supram HS, Gokhale S. Application of WHONET in the Antimicrobial Resistance Surveillance of Uropathogens: A First User Experience from Nepal. Journal of Clinical and Diagnostic Research, 7:845-848,2013. [view]
Prospective Real-Time Disease Outbreak Detection
Mostashari F, Kulldorff M, Hartman JJ, Miller JR, Kulasekera V. Dead bird clustering as an early warning system for West Nile virus activity. Emerging Infectious Diseases, 9:641-646, 2003. [view]
Heffernan R, Mostashari F, Das D, Karpati A, Kulldorff M, Weiss D. Syndromic surveillance in public health practice: The New York City emergency department system. Emerging Infectious Diseases, 10:858-864, 2004. [view]
Reinhardt M, Elias J, Albert J, Frosch M, Harmsen D, Vogel U. EpiScanGIS: an online geographic surveillance system for meningococcal disease. International Journal of Health Geographics, 7:33, 2008. [view]
Yih WK, Deshpande S, Fuller C, Heisey-Grove D, Hsu J, Kruskal BA, Kulldorff M, Leach M, Nordin J, Patton-Levine J, Puga E, Sherwood E, Shui I, Platt R. Evaluating real-time syndromic surveillance signals from ambulatory care data in four states. Public Health Reports, 2010, 125:111-120.
Viñas M, Tuduri E, Galar A, Yih WK, Pichel M, Stelling J, Brengi S, Della Gaspera A, van der Ploeg C, Bruno S, Rogé A, Caffer M,, Kulldorff M, Galas M. Laboratory-based prospective surveillance for community outbreaks of Shigella spp. in Argentina. PLoS Neglected Tropical Diseases, 7:e2521, 2013. [view]
Yih WK, Cocoros NM, Crockett M, Klompas M, Kruskal BA, Kulldorff M, Lazarus R, Madoff LC, Morrison MJ, Smole S, Platt R. Automated influenza-like illness reporting, an efficient adjunct to traditional sentinel surveillance. Public Health Reports, 129:66-63, 2014.
Greene S, Peterson ER, Kapell D, Fine AD, Kulldorff M. Daily reportable disease spatiotemporal cluster detection, New York City, New York, 2014-2015. Emerging Infectious Diseases, 22:1808-1812, 2016. [view]
Natale A, Stelling J, Meledandri M, Messenger LA, D'Ancona F. Use of WHONET-SaTScan system for simulated real-time detection of antimicrobial resistance clusters in a hospital in Italy, 2012 to 2014. Eurosurveillance. 22:30484, 2017. [view]
Minnesota Department of Health. Syndromic Surveillance: A New Tool to Detect Disease Outbreaks. Disease Control Newsletter, 32:16-17, 2004.
Kleinman K, Abrams A, Kulldorff M, Platt R. A model-adjusted space-time scan statistic with an application to syndromic surveillance. Epidemiology and Infection, 2005, 133:409-419.
Nordin JD, Goodman MJ, Kulldorff M, Ritzwoller DP, Abrams AM, Kleinman K, Levitt MJ, Donahue J, Platt R. Simulated anthrax attacks and syndromic surveillance. Emerging Infectious Diseases, 2005, 11:1394-98. [view]
Besculides M, Heffernan R, Mostashari F, Weiss D. Evaluation of school absenteeism for early outbreak detection, New York City. BMC Public Health, 5:105, 2006. [[view]]
Horst MA, Coco AS. Observing the spread of common illnesses through a community: Using geographic information systems (GIS) for surveillance. Journal of the American Board of Family Medicine, 23:32-41, 2010. [view]
van den Wijngaard CC, van Asten L, van Pelt W, Doornbos G, Nagelkerke NJ, Donker GA, van der Hoek W, Koopmans MP. Syndromic surveillance for local outbreaks of lower-respiratory infections: would it work? PLoS One, 29;e10406, 2010. [view]
Cancer: Incidence, Prevalence and Mortality
Hjalmars U, Kulldorff M, Gustafsson G, Nagarwalla N. Childhood leukemia in Sweden: Using GIS and a spatial scan statistic for cluster detection. Statistics in Medicine, 15:707-715, 1996.
Kulldorff M, Feuer EJ, Miller BA, Freedman LS. Breast cancer in northeastern United States: A geographic analysis. American Journal of Epidemiology, 146:161-170, 1997. [view]
Imai J. Spatial disease clustering in Kochi prefecture in Japan. National Institute of Public Health Epidemiology and Biostatistics Research, 57-96, 1998 (in Japanese).
VanEenwyk J, Bensley L, McBride D, Hoskins R, Solet D, McKeeman Brown A, Topiwala H, Richter A, Clark R. Addressing community health concerns around SeaTac Airport: Second Report. Washington State Department of Health, 1999. [view]
Hjalmars U, Kulldorff M, Wahlquist Y, Lannering B. Increased incidence rates but no space-time clustering of childhood malignant brain tumors in Sweden. Cancer, 85:2077-2090, 1999.
Viel JF, Arveux P, Baverel J, Cahn JY. Soft-tissue sarcoma and non-Hodgkin’s lymphoma clusters around a municipal solid waste incinerator with high dioxin emission levels. American Journal of Epidemiology, 152:13-19, 2000.
New York State Department of Health. Cancer Surveillance Improvement Initiative, 2001. [view]
Jemal A, Kulldorff M, Devesa SS, Hayes RB, Fraumeni JF. A geographic analysis of prostate cancer mortality in the United States. International Journal of Cancer, 101:168-174, 2002.
Michelozzi P, Capon A, Kirchmayer U, Forastiere F, Biggeri A, Barca A, Perucci CA. Adult and childhood leukemia near a high-power radio station in Rome, Italy. American Journal of Epidemiology, 155:1096-1103, 2002.
Zhan FB, Lin H. Geographic patterns of cancer mortality clusters in Texas, 1990 to 1997. Texas Medicine, 99:58-64, 2003.
Buntinx F, Geys H, Lousbergh D, Broeders G, Cloes E, Dhollander D, Op De Beeck L, Vanden Brande J, Van Waes A, Molenberghs G. Geographical differences in cancer incidence in the Belgian province of Limburg. European Journal of Cancer, 39:2058-72, 2003.
Santamaria Ulloa C. Evaluación de alarmas por cáncer utilizando análisis espacial: una aplicación para Costa Rica. Reivista Costarricense de Salud Pública, 12:18-22, 2003. [view]
Sheehan TJ, DeChello LM, Kulldorff M, Gregorio DI, Gershman S, Mroszczyk M. The geographic distribution of breast cancer incidence in Massachusetts 1988-1997, adjusted for covariates. International Journal of Health Geographics, 2004, 3:17. [view]
Fang Z, Kulldorff M, Gregorio DI. Brain cancer in the United States, 1986-95: A geographic analysis. Neuro-Oncology, 2004, 6:179-187.
Hsu CE, Jacobson HE, Soto Mas F. Evaluating the disparity of female breast cancer mortality among racial groups - a spatiotemporal analysis. International Journal of Health Geographics 3:4, 2004. [view]
Han DW, Rogerson PA, Nie J, Bonner MR, Vena JE, Vito D, Muti P, Trevisan M, Edge SB, Freudenheim JL. Geographic clustering of residence in early life and subsequent risk of breast cancer ( United States). Cancer Causes and Control, 15:921-929, 2004.
Campo J, Comber H, Gavin A T. All-Ireland Cancer Statistics 1998-2000. Northern Ireland Cancer Registry / National Cancer Registry, 2004. [view]
Hayran M. Analyzing factors associated with cancer occurrence: A geographical systems approach. Turkish Journal of Cancer, 34:67-70, 2004. [view]
Fukuda Y, Umezaki M, Nakamura K, Takano T. Variations in societal characteristics of spatial disease clusters: examples of colon, lung and breast cancer in Japan. International Journal of Health Geographics, 4:16, 2005. [view]
Ozonoff A, Webster T, Vieira V, Weinberg J, Ozonoff D, Aschengrau A. Cluster detection methods applied to the Upper Cape Cod cancer data. Environmental Health: A Global Access Science Source, 4:19, 2005. [view]
DeChello LM, Sheehan TJ. The geographic distribution of melanoma incidence in Massachusetts, adjusted for covariates. Int J Health Geogr. 2006;5:31. [view]
Gregorio DI, Samociuk H, DeChello L, Swede H. Effects of study area size on geographic characterizations of health events: prostate cancer incidence in Southern New England, USA, 1994-1998. Int J Health Geogr. 2006;5:8. [view]
Chen Y, Yi Q, Mao Y. Cluster of liver cancer and immigration: a geographic analysis of incidence data for Ontario 1998-2002. Int J Health Geogr. 2008;7:28. [view]
Lorenzo-Luaces Alvarez P, Guerra-Yi ME, Faes C, Galán Alvarez Y, Molenberghs G. Spatial analysis of breast and cervical cancer incidence in small geographical areas in Cuba, 1999-2003. European Journal of Cancer Prevention, 18:395-403, 2009.
Amin R, Bohnert A, Holmes L, Rajasekaran A, Assanasen C. Epidemiologic mapping of Florida childhood cancer clusters. Pediatric Blood Cancer, 54:511-518, 2010.
Liu-Mares W, MacKinnon JA, ShermanR, Fleming LE, Rocha-Lima C, Hu, JJ, Lee DJ. Pancreatic cancer clusters and arsenic-contaminated drinking water wells in Florida. BMC Cancer, 13, 111, 2013. [view]
Baastrup Nordsborg R, Meliker JR, Kjær Ersbøll A, Jacquez GM, Raaschou-Nielsen O. Space-Time Clustering of Non-Hodgkin Lymphoma Using Residential Histories in a Danish Case-Control Study. PLoS One, 8, e60800, 2013. [view]
Amin R, Hendryx M, Shull M, Bohnert A. A cluster analysis of pediatric cancer incidence rates in Florida: 2000-2010. Statistics in Public Policy, 1:69-77, 2014. [view]
Chawińska E, Tukiendorf A, Miszczyk L. Lower risk of cancer in the areas inhabited by the German minority in the region of Opole, Poland. Oncology Research and Treatment, 38:523-527, 2015.
Cancer: Early versus Late Detection, Stage and Grade
Roche LM, Skinner R, Weinstein RB. Use of a geographic information system to identify and characterize areas with high proportions of distant stage breast cancer. Journal of Public Health Management and Practice, 8:26-32, 2002.
Thomas AJ, Carlin BP. Late detection of breast and colorectal cancer in Minnesota counties: an application of spatial smoothing and clustering. Statistics in Medicine, 22:113-127, 2003.
Sheehan TJ, DeChello LM. A space-time analysis of the proportion of late stage breast cancer in Massachusetts, 1988 to 1997. International Journal of Health Geographics, 4:15, 2005. [view]
Klassen A, Curriero F, Kulldorff M, Alberg AJ, Platz EA, Neloms ST. Missing stage and grade in Maryland prostate cancer surveillance data, 1992-1997. American Journal of Preventive Medicine, 30:S77-87, 2006. [view]
Pollack LA, Gotway CA, Bates JH, Parikh-Patel A, Richards TB, Seeff LC, Hodges H, Kassim S. Use of the spatial scan statistic to identify geographic variations in late stage colorectal cancer in California ( United States). Cancer Causes and Control, 17:449–457, 2006.
DeChello LM, Sheehan TJ. Spatial analysis of colorectal cancer incidence and proportion of late-stage in Massachusetts residents: 1995-1998. Int J Health Geogr. 2007;6:20. [view]
Cancer: Screening, Treatment and Survival
Sheehan TJ, Gershman ST, MacDougal L, Danley R, Mrosszczyk M, Sorensen AM, Kulldorff M. Geographical surveillance of breast cancer screening by tracts, towns and zip codes. Journal of Public Health Management and Practice, 6: 48-57, 2001.
Gregorio DI, Kulldorff M, Barry L, Samociuk H, Zarfos K. Geographic differences in primary therapy for early stage breast cancer. Annals of Surgical Oncology, 2001; 8:844-849, 2001. [view]
Henry KA, Niu X, Boscoe FP. Geographic disparities in colorectal cancer survival. International Journal of Health Geographics 2009, 8:48. [view]
Kuehl KS, Loffredo CA. A cluster of hypoplastic left heart malformation in Baltimore, Maryland Pediatric Cardiology, 27:25-31, 2006.
Li XY, Chen K. Scan statistic theory and its application in spatial epidemiology (in Chinese). Zhonghua Liu Xing Bing Xue Za Zhi., 29:828-31, 2008.
Park JO, Yoon S, Na MH, Song HC. The Effects of Air Pollution on Mortality in South Korea. Procedia Environmental Sciences, 26:62-65, 2015. [view]
Rheumatology and Auto-Immune Diseases
Walsh SJ, Fenster JR. Geographical clustering of mortality from systemic sclerosis in the Southeastern United States, 1981-90. Journal of Rheumatology, 24:2348-2352, 1997.
Walsh SJ, DeChello LM. Geographical variation in mortality from systemic lupus erythematosus in the United States. Lupus, 10:637-646, 2001.
López-Abente G, Morales-Piga A, Bachiller-Corral FJ, Illera-Martín O, Martín-Domenech R, Abraira V. Identification of possible areas of high prevalence of Paget’s disease of bone in Spain. Clinical and Experimental Rheumatology, 21:635-368, 2003.
Donnan PT, Parratt JDE, Wilson SV, Forbes RB, O'Riordan JI, Swingler RJ. Multiple sclerosis in Tayside, Scotland: detection of clusters using a spatial scan statistic. Multiple Sclerosis, 11:403-408, 2005.
Ala A, Stanca CM, Bu-Ghanim M, Ahmado I, Branch AD, Schiano TD, Odin JA, Bach N. Increased prevalence of primary biliary cirrhosis near superfund toxic waste sites. Hepatology, 43:525-531, 2006.
Stanca CM, Babar J, Singal V, Ozdenerol E, Odin JA. Pathogenic role of environmental toxins in immune-mediated liver diseases. Journal of Immunotoxicology, 5:59-68, 2008.
McNally RJQ, Ducker S, James OFW. Are Transient Environmental Agents Involved in the Cause of Primary Biliary Cirrhosis? Evidence from Space-Time Clustering Analysis. Hepatology, 50:1169-1174, 2009.
Green C, Hoppa RD, Young TK, Blanchard JF. Geographic analysis of diabetes prevalence in an urban area. Social Science and Medicine, 57:551-560, 2003.
Aamodt G, Stene LC, Njølstad PR, Søvik O, Joner G, for the Norwegian Childhood Diabetes Study Group. Spatiotemporal trends and age-period-cohort modelling of the incidence of type 1 diabetes among children ages <15 years in Norway 1973-1982 and 1989-2003. Diabetes Care, 30:884-889, 2007.
Allergy and Asthma
Yiannakoulias N, Schopflocher DP, Svenson LW. Using administrative data to understand the geography of case ascertainment. Chronic Diseases in Canada, 30:20-28, 2009. [view]
Lee H, Kim GS. Geographical and sociodemographic risk factors for allergic diseases in Korean children. Asian Nursing Research, 5:1-10, 2011.
Torabi M. Spatial disease cluster detection: An application to childhood asthma in Manitoba, Canada. Journal of Biometrics and Biostatistics, S7:010, 2012. [view]
Sabel CE, Boyle PJ, Löytönen M, Gatrell AC, Jokelainen M, Flowerdew R, Maasilta P. Spatial clustering of amyotrophic lateral sclerosis in Finland at place of birth and place of death. American Journal of Epidemiology, 157: 898-905, 2003.
Banta JE, Addison A, Beeson WL. Spatial patterns of epilepsy-related emergency department visits in California. Journal of Public Health Research, 4:441, 2015. [view]
Rooney J, Vajda A, Heverin M, Elamin M, Crampsie A, McLaughlin R, Staines A, Hardiman O. Spatial cluster analysis of population amyotrophic lateral sclerosis risk in Ireland. Neurology, 84:1537-1544, 2015. [view]
Ekele BA, Bello SO, Adamu AN. Clusters of eclampsia in a Nigerian teaching hospital. International Journal of Gynecology & Obstetrics, 62-66, 2007.
Graham W, Bell J, Fitzmaurice A, Neal S, Qomariyah SN, Matthews Z. The geography of maternal death. In Maternal and infant deaths: Chasing millennium development goals 4 and 5; Kehoe, Neilson, Norman (eds), London: RCOG Press, 2010.
Bahtiar H. Analysis distribusi spasial kematian ibu di Kabupaten Lombok Timur provinsi nusa tenggara barat tahun 2007-2009. Thesis, Gadjah Mada University, Indonesia, 2011.
Eastwood JG, Jalaludin BB, Kemp LA, Phung HN, Adusumilli SK. Clusters of maternal depressive symptoms in South Western Sydney, Australia. Spatial and spatio-temporal epidemiology, 31;4:25-31, 2013.
Chong S, Nelson M, Byun R, Harris L, Eastwood J, Jalaludin B. Geospatial analyses to identify clusters of adverse antenatal factors for targeted interventions. International journal of health geographics, 12:1, 2013. [view]
Birth Defects and Other Congenital Outcomes
Kharrazi M, et al. Pregnancy outcomes around the B.K.K. landfill, West Covina, California: An analysis by address. California Department of Health Services, 1998.
Bell S.Spatial Analysis of Disease - Applications. In Beam C (ed). Biostatistical Applications in Cancer Research. Boston: Kluwer p151-182, 2002.
Forand SP, Talbot TO, Druschel C, Cross PK. Data quality and the spatial analysis of disease rates: congenital malformations in New York State. Health and Place, 8:191-199, 2002.
Colorado Department of Public Health and Environment. Analysis of birth defect data in the vicinity of the Redfield plume area in southeastern Denver county: 1989-1999. Colorado Department of Public Health and the Environment, 2002. [view]
Boyle E, Johnson H, Kelly A, McDonnell R. Congenital anomalies and proximity to landfill sites. Irish Medical Journal, 97:16-18, 2004.
Ozdenerol E, Williams BL, Kang SY, Magsumbol MS. Comparison of spatial scan statistic and spatial filtering in estimating low birth weight clusters. International Journal of Health Geographics, 4:19, 2005. [view]
Viel JF, Floret N, Mauny F. Spatial and space-time scan statistics to detect low clusters of sex ratio. Environmental and Ecological Statistics, 12:289-299, 2005.
Grady SC, Enander H. Geographic analysis of low birthweight and infant mortality in Michigan using automated zoning methodology International Journal of Health Geographics 2009, 8:10. [view]
Kihal-Talantikite W, Padilla CM, Lalloué B, Gelormini M, Zmirou-Navier D, Deguen S. Green space, social inequalities and neonatal mortality in France. BMC pregnancy and childbirth, 13:191, 2013. [view]
George M, Wiklund L, Aastrup M, Pousette J, Thunholm B, Saldeen T, Wernroth L, Zaren B, Holmberg L. Incidence and geographical distribution of sudden infant death syndrome in relation to content of nitrate in drinking water and groundwater levels. European Journal of Clinical Investigation, 31: 1083-1094, 2001.
Sankoh OA, Ye Y, Sauerborn R, Muller O, Becher H. Clustering of childhood mortality in rural Burkina Faso. International Journal of Epidemiology, 30:485-492, 2001. [view]
Ali M, Asefaw T, Byass P, Beyene H, Karup Pedersen F. Helping northern Ethiopian communities reduce childhood mortality: population-based intervention trial. Bulletin of the World Health Organization. 83:27-33, 2005. [view]
Awini E, Mattah P, Sankoh O, Gyapong M. Spatial variations in childhood mortalities at the Dodowa Health and Demographic Surveillance System site of the INDEPTH Network in Ghana. Tropical Medicine and International Health, 2010.
Yiannakoulias N, Rowe BH, Svenson LW, Schopflocher DP, Kelly K, Voaklander DC. Zones of prevention: the geography of fall injuries in the elderly. Social Science and Medicine, 57:2065-73, 2003.
Vaneckova P, Beggs PJ, Jacobson CR. Spatial analysis of heat-related mortality among the elderly between 1993 and 2004 in Sydney, Australia. Social Science and Medicine, 70:293-304, 2010.
Margai F, Henry N. A community-based assessment of learning disabilities using environmental and contextual risk factors. Social Science and Medicine, 56: 1073-1085, 2003.
Wood ND. Location, Location, Location: Applying Spatial Statistics to the Relationship Landscape. Family Process, 53:596-607, 2014.
Yoshida M, Naya Y, Miyashita Y. Anatomical organization of forward fiber projections from area TE to perirhinal neurons representing visual long-term memory in monkeys. Proceedings of the National Academy of Sciences of the United States of America, 100:4257-4262, 2003. [view]
Yoshida M, Naya Y, Miyashita Y. Anatomical organization of forward fiber projections from area TE to perirhinal neurons representing visual long-term memory in monkeys. Proceedings of the National Academy of Sciences of the United States of America, 100:4257-4262, 2003. [view]
Pharmaceutical Drugs and Vaccines
Copeland KR, Allen AE, Basic Models for Mapping Prescription Drug Data. Proceedings of the ASA Section on Survey Research Methods, 2904-2909, 2005. [view]
Moore GE, Ward MP, Kulldorff M, Caldanaro RJ, Guptill LF, Lewis HB, Glickman LT. A space-time cluster of adverse events associated with a canine rabies vaccine. Vaccine, 23:5557-62, 2005.
Omer SB, Enger S, Moulton LH, Halsey NA, Stokley S, Salmon DA. Geographic clustering of nonmedical exemptions to school immunization requirements and associations with geographic clustering of pertussis. American Journal of Epidemiology, 168:1389-1396, 2008. [view]
Penfold RB, Wang W, Pajer K, Strange B, Kelleher KJ. Spatio-temporal clusters of new psychotropic medications among Michigan children insured by Medicaid. Pharmacoepidemiology and Drug Safety, 18: 531-539, 2009.
Brownstein JS, Green TC, Cassidy TA, Butler SF. Geographic information systems and pharmacoepidemiology: using spatial cluster detection to monitor local patterns of prescription opioid abuse. Pharmacoepidemiology and Drug Safety, 19:627-637, 2010.
King M, Essic C. The geography of antidepressant, antipsychotic, and stimulant utilization in the United States, Health and Place, 20:32-38, 2013.
Atwell JE, Van Otterloo J, Zipprich J, Winter K, Harriman K, Salmon DA, Halsey NA, Omer SB. Nonmedical vaccine exemptions and pertussis in California 2010. Pediatrics, 132:624-630, 2013. [view]
Lieu TA, Ray GT, Klein NP, Chung C, Kulldorff M. Geographic clusters in under immunization and vaccine refusal, Pediatrics, 135:280-289, 2015.
Alcohol, Tobacco and Recreational Drugs
Hanson CE, Wieczorek WF. Alcohol mortality: a comparison of spatial clustering methods. Social Science and Medicine, 55:791-802, 2002.
Sudakin D, Power LE. Regional and temporal variation in methamphetamine-related incidents: applications of spatial and temporal scan statistics. Clinical Toxicology, 47:243-247, 2009.
Chong S, Nelson M, Byun R, Harris L, Eastwood J, Jalaludin B. Geospatial analyses to identify clusters of adverse antenatal factors for targeted interventions. International Journal of Health Geographics, 2013, 12:46. [view]
Dahly D. Obesity clustering in Cebu, Philippines: an application of satscan and the spatial scan statistic Journal of Epidemiology and Community Health, 65, A71, 2011. [view]
Chalkias C, Papadopoulos AG, Mpenekos G, Tambalis K, Psarra G, Sidossis L. Spatial variability of childhood obesity in response to socioeconomic heterogeneity. The case of Athens metropolitan area, Greece. Proceedings of the 17th European Colloquium on Quantitative and Theoretical Geography, 605-611, 2011. [view]
Health Care Quality of Life Outcomes
Bell N, Kruse S, Simons RK, Brussoni M. A spatial analysis of functional outcomes and quality of life outcomes after pediatric injury. Injury Epidemiology, 1:16, 2014. [view]
Sports and Recreation
López FA, Martínez JA, Ruiz M. Análisis espacial de lanzamientos en baloncesto; el caso de L.A. Lakers / Spatial pattern analysis of shot attempts in basketball; The case of LA Lakers. Revista Internacional de Medicina y Ciencias de la Actividad Física y el Deporte, 13: 585-613, 2013. [view]
Schmicker RH. An application of SaTScan to evaluate the spatial distribution of corner kick goals in major league soccer. International Journal of Computer Science in Sport, 12:70-79, 2013.
Nkhoma ET, Hsu CE, Hunt VI, Harris AM. Detecting spatiotemporal clusters of accidental poisoning mortality among Texas counties, U.S., 1980 - 2001. International Journal of Health Geographics, 3:25, 2004. [view]
Warden CR. Comparison of Poisson and Bernoulli spatial cluster analyses of pediatric injuries in a fire district. International Journal of Health Geographics, 7:51, 2008. [view]
Dey AN, Hicks P, Benoit S, Tokars JI. Automated monitoring of clusters of falls associated with severe winter weather using the BioSense system. Injury Prevention, 16:403-407, 2010.
Saman DM, Cole HP, Odoi A, Myers ML, Carey DI, Westneat SC. A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002.PLoS One, 7:e30532, 2012. [view]
Amin R, Ritter EK, Cossette L. A Geospatial Analysis of Shark Attack Rates for the Coast of California: 1994-2010. Journal of Environment and Ecology, 3:246-255, 2012.
Fuchs S, Ornetsmüller C, Totschnig R. Spatial scan statistics in vulnerability assessment - an application to mountain hazards. Natural Hazards 64:2129-2151, 2012.
Campo J. Firearm deaths in Washington State. Washington State Health Services Research Brief No. 71, 2013. [view]
Exeter DJ, Boyle PJ. Does young adult suicide cluster geographically in Scotland? Journal of Epidemiology and Community Health, 61:731-736, 2007.
Mesoudi A. The cultural dynamics of copycat suicide. PLoS One, 4:e7252, 2009. [view]
Jones P, Gunnell D, Platt S, Scourfield J, Lloyd K, Huxley P, John A, Kamran B, Wells C, Dennis M. Identifying Probable Suicide Clusters in Wales Using National Mortality Data, PLoS One, 8:e71713, 2013. [view]
Collado Chaves A. Fecundidad adolescente en el gran área metropolitana de Costa Rica. Población y Salud en Mesoamérica, 1:4, 2003. [view]
Veterinary Medicine, Domestic Animals
Norström M, Pfeiffer DU, Jarp J. A space-time cluster investigation of an outbreak of acute respiratory disease in Norwegian cattle herds. Preventive Veterinary Medicine, 47: 107-119, 2000.
Ward MP. Blowfly strike in sheep flocks as an example of the use of a time-space scan statistic to control confounding. Preventive Veterinary Medicine, 49: 61-69, 2001.
United States Department of Agriculture. West Nile virus in. USDA, APHIS, Veterinary Services, 2001.
Doherr MG, Hett AR, Rufenacht J, Zurbriggen A, Heim D. Geographical clustering of cases of bovine spongiform encephalopathy (BSE) born in Switzerland after the feed ban. Veterinary Record, 151: 467-472, 2002.
Perez AM, Ward MP, Torres P, Ritacco V. Use of spatial statistics and monitoring data to identify clustering of bovine tuberculosis in Argentina. Preventive Veterinary Medicine, 56: 63-74, 2002.
Schwermer H, Rufenacht J, Doherr MG, Heim D. Geographic distribution of BSE in Switzerland. Schweizer Archiv fur Tierheilkunde, 144:701-708, 2002.
Ward MP. Clustering of reported cases of leptospirosis among dogs in the United States and Canada. Preventive Veterinary Medicine, 56:215-226, 2002.
Falconi F, Ochs H, Deplazes P. Serological cross-sectional survey of psoroptic sheep scab in Switzerland. Veterinary Parasitology, 109:119-127, 2002.
Knuesel R, Segner H, Wahli T. A survey of viral diseases in farmed and feral salmonids in Switzerland. Journal of Fish Diseases, 26:167-182, 2003.
Berke O, Grosse Beilage E. Spatial relative risk mapping of pseudorabies-seropositive pig herds in an animal-dense region. Journal of Veterinary Medicine, B50: 322–325, 2003.
Abrial D, Calavas D, Lauvergne N, Morignat E, Ducrot C. Descriptive spatial analysis of BSE in western France. Veterinary Research, 34:749-60, 2003.
Sheridan HA, McGrath G, White P, Fallon R, Shoukri MM, Martin SW. A temporal-spatial analysis of bovine spongiform encephalopathy in Irish cattle herds, from 1996 to 2000. Canadian Journal of Veterinary Research, 69:19-25, 2005. [view]
Guerin MT, Martin SW, Darlington GA, Rajic A. A temporal study of Salmonella serovars in animals in Alberta between 1990 and 2001. Canadian Journal of Veterinary Research, 69:88-89, 2005. [view]
López-Quílez A, Forte A, Fernández G, Casal J. Spatial analysis of bovine spongiform encephalopathy in Galicia, Spain (2000-2005). Preventive Veterinary Medicine, 79:174-85, 2007. [view]
Heres L, Brus DJ, Hagenaars TJ. Spatial analysis of BSE cases in the Netherlands. BMC Veterinary Research, 4:21, 2008. [view]
Frossling J, Nodtvedt A, Lindberg A, Björkman C. Spatial analysis of Neospora caninum distribution in dairy cattle from Sweden. Geospatial Health, 3:39-45, 2008.
Beaudeau F, Björkman C, Alenius S, Frössling J. Spatial patterns of bovine corona virus and bovine respiratory syncytial virus in the Swedish beef cattle population. Acta Veterinaria Scandinavica, 52:33, 2010. [view]
Veterinary Medicine, Wildlife
Smith KL, DeVos V, Bryden H, Price LB, Hugh-Jones ME, Keim P. Bacillus anthracis diversity in Kruger National Park. Journal of Clinical Microbiology, 38:3780-3784, 2000. [view]
Berke O, von Keyserlingk M, Broll S, Kreienbrock L. On the distribution of Echinococcus multilocularis in red foxes in Lower Saxony: identification of a high risk area by spatial epidemiological cluster analysis. Berliner und Munchener Tierarztliche Wochenschrift. 115:428-434, 2002.
Miller MA, Gardner IA, Kreuder C, Paradies DM, Worcester KR, Jessup DA, Dodd E, Harris MD, Ames JA, Packham AE, Conrad PA. Coastal freshwater runoff is a risk factor for Toxoplasma gondii infection of southern sea otters (Enhydra lutris nereis). International Journal for Parasitology, 32:997-1006, 2002.
Hoar BR, Chomel BB, Rolfe DL, Chang CC, Fritz CL, Sacks BN, Carpenter TE. Spatial analysis of Yersinia pestis and Bartonella vinsonii subsp berkhoffii seroprevalence in California coyotes (Canis latrans). Preventive Veterinary Medicine, 56:299-311, 2003.
Olea-Popelka FJ, Griffin JM, Collins JD, McGrath G, Martin SW. Bovine tuberculosis in badgers in four areas in Ireland: does tuberculosis cluster? Preventive Veterinary Medicine, 59:103-111, 2003.
Joly DO, Ribic CA, Langenberg JA, Beheler K, Batha CA, Dhuey BJ, Rolley RE, Bartelt G, Van Deelen TR, Samual MD. Chronic wasting disease in free-ranging Wisconsin white-tailed deer. Emerging Infectious Disease, 9: 599-601, 2003. [view]
Miller MA, Grigg ME, Kreuder C, James ER, Melli AC, Crosbie PR, Jessup DA, Boothroyd JC, Brownstein D, Conrad PA. An unusual genotype of Toxoplasma gondii is common in California sea otters (Enhydra lutris nereis) and is a cause of mortality. International Journal for Parasitology, 34:275-284, 2004.
Olea-Popelka FJ, Flynn O, Costello E, McGrath G, Collins JD, O’Keeffe JO, Kelton DF, Berke O, Martin SW. Spatial relationship between Mycobacterium bovis strains in cattle and badgers in four areas in Ireland. Preventive Veterinary Medicine, 71:57-70, 2005.
Carricondo-Sanchez D, Odden M, Linnell JDC, Odden J. The range of the mange: Spatiotemporal patterns of sarcoptic mange in red foxes (Vulpes vulpes) as revealed by camera trapping. Serrano Ferron E, ed. PLoS ONE, 12:e0176200, 2017. [view]
Webb NF, Hebblewhite M, Merrill EH. Statistical methods for identifying wolf kill sites using global positioning system locations. Journal of Wildlife Management, 2008, 72, 798-807.
McPhee HM, Webb NF, Merrill EH. Hierarchical predation: Wolf (Canis lupus) selection along hunt paths and at kill sites. Canadian Journal of Zoology, 2012, 90:555-563.
Ouko EO. Where, when and why are there elephant poaching hotspots in Kenya? MSc Thesis, University of Twente, Netherlands, 2013. [view]
Seidel DP, Boyce MS. Patch-use dynamics by a large herbivore. Movement Ecology, 3:7, 2015. [view]
Seidel DP, Boyce MS. Varied tastes: home range implications of foraging-patch selection. Oikos, 2015. [view]
Porcasi X, Catalá SS, Hrellac H, Scavuzzo MC, Gorla DE. Infestation of Rural Houses by Triatoma Infestans (Hemiptera: Reduviidae) in Southern Area of Gran Chaco in Argentina. Journal of Medical Entomology, 43:1060-1067, 2006.
Bayles BR, Thomas SM, Simmons GS, Grafton-Cardwell EE, Daugherty MP. Spatiotemporal dynamics of the Southern California Asian citrus psyllid (Diaphorina citri) invasion. PLoS ONE 12(3): e0173226, 2017. [view]
Spindler BD, Chipps SR, Klumb RA, Wimberly MC. Spatial analysis of pallid sturgeon Scaphirhynchus albus distribution in the Missouri River, South Dakota. Journal of Applied Ichthyology, 25:8-13, 2009.
Bayon C, Pei MH, Ruiz C, Hunter T. Genetic structure and spatial distribution of the mycoparasite Sphaerellopsis filum on Melampsora larici-epitea in a short-rotation coppice willow planting. Plant Pathology, 56:616-623, 2007.
Cuadros DF, Hernandez A, Torres MF, Torres DM, Branscum AJ, Rincon DF. Vector Transmission Alone Fails to Explain the Potato Yellow Vein Virus Epidemic among Potato Crops in Colombia. Frontiers in Plant Science. 8:1654, 2017. [view]
Coulston JW, Riitters KH. Geographic Analysis of Forest Health Indicators Using Spatial Scan Statistics. Environmental Management, 31: 764-773, 2003.
Riitters KH, Coulston JW. Hot spots of perforated forest in the eastern United States. Environmental Management, 35:483-492, 2005.
Tuia D, Ratle F, Lasaponara R, Telesca L, Kanevski M. Scan statistics analysis of forest fire clusters. Communications in Nonlinear Sciences and Numerical Simulations, 13:1689-94, 2008.
Tonini M, Tuia D, Ratle F. Detection of clusters using space-time scan statistics. International Journal of Wildland Fire, 18 830-836, 2009.
Fei S. Applying hotspot detection methods in forestry: A case study of Chestnut Oak regeneration. International Journal of Forestry Research., 815292, 2010. [view]
Vega Orozco C, Tonini M, Conedera M, Kanveski M. Cluster recognition in spatial-temporal sequences: the case of forest fires. Geoinformatica, 16: 653-673, 2012. [view]
Vadrevu KP. Analysis of fire events and controlling factors in eastern India using spatial scan and multivariate statistics. Geografiska Annaler, 90A: 315-328, 2008.
Sudakin DL, Horowitz Z, Giffin S. Regional variation in the incidence of symptomatic pesticide exposures: Applications of geographic information systems. Journal of Toxicology - Clinical Toxicology, 40:767-773, 2002.
Gao J, Zhang ZJ, Wang ZL, Bian JC, Wang JB, Jiang W, Wang XM, Jiang QW. Spatial distribution characteristics of iodine in drinking water in Shandong province between year 2008 and 2010. Chinese Journal of Preventive Medicine, 47:18-22, 2013.
Krolik J, Maier A, Evans G, Belanger P, Hall G, Joyce A, Majury A. A spatial analysis of private well water Escherichia coli contamination in southern Ontario. Geospatial Health 8:65-75, 2013.
Krolik J, Evans G, Belanger P, Maier A, Hall G, Joyce A, Guimont S, Pelot A, Majury A. Microbial source tracking and spatial analysis of E. coli contaminated private well waters in southeastern Ontario. Journal of Water and Health, 12:348-357, 2014.
Gao J, Zhang Z, Hu Y, Bian J, Jiang W, Wang X. Geographical distribution patterns of iodine in drinking-water and its associations with geological factors in Shandong Province, China. [view]
Witham CS, Oppenheimer C. Mortality in England during the 1783-4 Laki Craters eruption. Bulletin of Volcanology, 67:15-25, 2004.
Stevenson JR Emrich CT Mitchell JT, Cutter SL. Using building permits to monitor disaster recovery: A spatio-temporal case study of coastal Mississippi following hurricane Katrina, Cartography and Geographic Information Science, 37:S57-68, 2010.
Ziemke J. From battles to massacres. 3rd Annual Harvard-Yale-MIT Graduate Student Conference on Order, Conflict and Violence, 2008.
O'Loughlin J, Witmer F, Linke A. The Afghanistan-Pakistan Wars 2008-2009: Micro-geographies, Conflict Diffusion, and Clusters of Violence. Eurasian Geography and Economics, 2010, 51, 437-71. [view]
O'Loughlin J, Witmer FDW, Linke AM, Thorwardson N. Peering into the Fog of War: The Geography of the WikiLeaks Afghanistan War Logs, 2004-2009. Eurasian Geography and Economics, 51:472-495, 2010. [view]
O'Loughlin J, Witmer FDW, The Localized Geographies of Violence in the North Caucasus of Russia, 1999-2007', Annals of the Association of American Geographers, 101: 178-201, 2011. [view]
Jefferis ES. A multi-method exploration of crime hot spots: SaTScan results. National Institute of Justice, Crime Mapping Research Center, 1998.
Kaminski RJ, Jefferis ES, Chanhatasilpa C. A spatial analysis of American police killed in the line of duty. In Turnbull et al. (eds.), Atlas of crime: Mapping the criminal landscape. Phoenix , AZ : Oryx Press, 2000.
LeBeau JL. Demonstrating the analytical utility of GIS for police operations: A final report. National Criminal Justice Reference Service, 2000. [view]
Beato Filho CC, Assunção RM, Silva BF, Marinho FC, Reis IA, Almeida MC. Homicide clusters and drug traffic in Belo Horizonte, Minas Gerais, Brazil from 1995 to 1999. Cadernos de Saúde Pública, 17:1163-1171, 2001. [view]
Ceccato V, Haining R. Crime in border regions: The Scandinavian case of Öresund, 1998-2001. Annals of the Association of American Geographers, 94:807-826, 2004.
Ceccato V. Homicide in Sao Paulo, Brazil: Assessing the spatial-temporal and weather variations. Journal of Environmental Psychology, 25:307-321, 2005.
Minamisava R, Nouer SS, de Morais Neto OL, Melo LK, Andrade ALS. Spatial clusters of violent deaths in a newly urbanized region of Brazil: Highlighting the social disparities. International Journal of Health Geographics, 8:66, 2009. [view]
Nakaya T, Yano K. Visualizing crime clusters in a space-time cube: An exploratory data-analysis approach using space-time kernel density estimation and scan statistics. Transactions in GIS, 14:223-239, 2010.
Leitner M, Helbich M. The Impact of Hurricanes on Crime: A Spatio-temporal Analysis in the City of Houston, TX. Cartography and Geographic Information Science, 37:214-222, 2011.
Zeoli AM, Pizarro JM, Grady SC, Melde C. Homicide as infectious disease: Using public health methods to investigate the diffusion of homicide. Justice Quarterly, 31:609-632, 2014.
Urban and Rural Planning
Huang L, Stinchcomb DG, Pickle LW, Dill J, Berrigan D. Identifying clusters of active transportation using spatial scan statistics. American Journal of Preventive Medicine, 37:157-166, 2009.
Montrone S, Perchinunno P, Di Giuro A, Rotondo F, Torre CM. Identification of "hot spots" of social and housing difficulty in urban areas: scan statistics for housing market and urban planning policies. In Geocomputation and Urban Planning, pp. 57-78, Berlin: Springer, 2009.
Helbich M. Beyond potsuburbia? Multifunctional service agglomeration in Vienna's urban fringe. Journal of Economic and Social Geography, 2011.
Chadillon-Farinacci V, Apparicio P, Morselli C. Cannabis cultivation in Quebec: Between space-time hotspots and coldspots. International Journal of Drug Policy, 26:311-322, 2015.
Kaza N, Lester TW, Rodriguez DA. The spatio-temporal clustering of green buildings in the United States, Urban Studies, 50:3262-3282, 2013. [view]
History and Archeology
Usher BM, Allen KL. Identifying kinship clusters: SaTScan for genetic spatial analysis. American Journal of Physical Anthropology, Supplement, 126:S40:210, 2005.
Wang F, Hartmann J, Luo W, Huang P. GIS-based spatial analysis of Tai place names in southern China: An exploratory study of methodology. Annals of GIS, 12:1-9, 2006. [view]
Munoz SE, Gajewski K. Distinguishing prehistoric human influence on late-Holocene forests in southern Ontario, Canada. The Holocene, 20:967-981, 2010.
Wilczek J, Monna F, Gabillot M, Navarro N, Rusch L, Chateau C. Unsupervised model-based clustering for typological classification of Middle Bronze Age flanged axes. Journal of Archaeological Science: Reports, 3:381-391, 2015. [view]
Marcos RDLF, Marcos CDLF. From star complexes to the field: Open cluster families, 672:342-351, 2008.
Bidin CM, Marcos RD, Marcos CD, Carraro, G. Not an open cluster after all: the NGC 6863 asterism in Aquila. Astronomy and Astrphysics, 510:A44, 2010. [view]