Risk maps for cities: Incorporating streets into geostatistical models

Spatial and Spatio-temporal Epidemiology - Tập 27 - Trang 47-59 - 2018
Erica Billig Rose1, Kwonsang Lee2, Jason A. Roy1, Dylan Small2, Michelle E. Ross1, Ricardo Castillo-Neyra1,3, Michael Z. Levy1
1University of Pennsylvania, Perelman School of Medicine, Department of Biostatistics, Epidemiology, and Informatics, Philadelphia, USA
2University of Pennsylvania, Wharton School, Department of Statistics, Philadelphia, USA
3Zoonotic Disease Research Laboratory, One Health Unit, School of Public Health, Universidad Peruana Cayetano Heredia, Lima, Peru

Tài liệu tham khảo

Adigun, 2015, Malaria risk in Nigeria: Bayesian geostatistical modelling of 2010 malaria indicator survey data, Malar J, 14, 1, 10.1186/s12936-015-0683-6 Anders, 2003, Spatial covariance modelling in a complex coastal domain by multidimensional scaling, Environmetrics, 14, 307, 10.1002/env.588 Barbu, 2014, Residual infestation and recolonization during urban Triatoma infestans bug control campaign, Peru, Emerg Infect Dis, 20, 2055, 10.3201/eid2012.131820 Barbu, 2013, The effects of city streets on an urban disease vector, PLoS Comput Biol, 9, e1002801, 10.1371/journal.pcbi.1002801 Bern, 2015, Chagas’ disease, N. Engl. J Med, 373, 456, 10.1056/NEJMra1410150 Besag, 1975, Statistical analysis of non-lattice data, Stat, 24, 179 Blangiardo, 2013, Spatial and spatio-temporal models with r-inla, Spat Spat-Temp Epidemiol, 7, 39, 10.1016/j.sste.2013.07.003 Bowman, 2008, Chagas disease transmission in periurban communities of Arequipa, Peru, Clin Infect Dis, 46, 1822, 10.1086/588299 Brooker, 2007, Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control, Trans Royal Soc Trop Med Hyg, 101, 1, 10.1016/j.trstmh.2006.08.004 Curriero, 2006, On the use of non-euclidean distance measures in geostatistics, Math Geol, 38, 907, 10.1007/s11004-006-9055-7 Delgado, 2013, A country bug in the city: urban infestation by the chagas disease vector triatoma infestans in arequipa, peru, Int J Health Geogr, 12, 1, 10.1186/1476-072X-12-48 Dias, 2002, The impact of chagas diseasecontrol in latin america: a review, Memórias do Instituto Oswaldo Cruz, 97, 603, 10.1590/S0074-02762002000500002 Diggle, 2003, An introduction to model-based geostatistics, 43 Gutfraind A., Peterson J.K., Rose E.B., Arevalo-Nieto C., Sheen J., Condori-Luna G.F., Tankasala N., Castillo-Neyra R., Condori C., Anand P., Naquira-Velarde C., Levy M.Z.. Integrating evidence, models and maps to enhance chagas disease vector surveillance. PLOS Negl Trop DisIn Press. Haley, 2012, Controlling urban epidemics of west nile virus infection, JAMA, 308, 1325, 10.1001/2012.jama.11930 Hong, 2013 Jaya, 2016, Bayesian spatial modeling and mapping of Dengue fever: a case study of Dengue fever in the city of Bandung, Indonesia, Int J Appl Math Stat™, 54, 94 Knudsen, 1992, Vector-borne disease problems in rapid urbanization: new approaches to vector control., Bull World Health Organ, 70, 1 Krainski E., Lindgren F.. The R-INLA tutorial: SPDE models. 2013. https://folk.ntnu.no/fuglstad/Lund2016/Session6/spde-tutorial.pdf. Krivoruchko, 2004, Geostatistical interpolation and simulation in the presence of barriers, 331 LaDeau, 2015, The ecological foundations of transmission potential and vector-borne disease in urban landscapes, Functional Ecol, 29, 889, 10.1111/1365-2435.12487 Levy, 2006, Periurban Trypanosoma cruzi–infected Triatoma infestans, Arequipa, Peru, Emerg Infect Dis, 12, 1345, 10.3201/eid1209.051662 Lindgren, 2011, An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach, J Royal Stat Soc: Ser B (Stat Methodol), 73, 423, 10.1111/j.1467-9868.2011.00777.x López-Quílez, 2009, Geostatistical computing of acoustic maps in the presence of barriers, Math Comput Model, 50, 929, 10.1016/j.mcm.2009.05.021 Oluwole, 2015, Bayesian geostatistical model-based estimates of soil-transmitted helminth infection in nigeria, including annual deworming requirements, PLoS Negl Trop Dis, 9, e0003740, 10.1371/journal.pntd.0003740 Rossi, 1992, Geostatistical tools for modeling and interpreting ecological spatial dependence, Ecol Monogr, 62, 277, 10.2307/2937096 Rue, 2005 Rue, 2009, Approximate Bayesian inference for latent gaussian models by using integrated nested laplace approximations, J Royal Stat Soc: Ser B (Stat Methodol), 71, 319, 10.1111/j.1467-9868.2008.00700.x Rue, 2014, INLA: functions which allow to perform full Bayesian analysis of latent Gaussian models using integrated nested Laplace approximaxion, R Package Vienna: R Foundation for Statistical Computing, 2014. Version 00–1389624686 Sampson, 1992, Nonparametric estimation of nonstationary spatial covariance structure, J Am Stat Assoc, 87, 108, 10.1080/01621459.1992.10475181 Sikka, 2016, The emergence of Zika virus as a global health security threat: a review and a consensus statement of the Indusem joint working group (JWG), J Glob Infect Dis, 8, 3, 10.4103/0974-777X.176140 Weaver, 2013, Urbanization and geographic expansion of zoonotic arboviral diseases: mechanisms and potential strategies for prevention, Trends Microbiol, 21, 360, 10.1016/j.tim.2013.03.003 Whittle, 1954, On stationary processes in the plane, Biometrika, 41, 434, 10.1093/biomet/41.3-4.434 Whittle, 1963, Stochastic-processes in several dimensions, Bull Int Stat Inst, 40, 974