class: center, middle, inverse, title-slide .title[ # Hotspots del Vector del Dengue en R ] .author[ ### Felipe Antonio Dzul Manzanilla ] .date[ ### 2022: Last compiled 2022-11-05 ] --- class: left, top <style>.xe__progress-bar__container { top:0; opacity: 1; position:absolute; right:0; left: 0; } .xe__progress-bar { height: 0.25em; background-color: #0051BA; width: calc(var(--slide-current) / var(--slide-total) * 100%); } .remark-visible .xe__progress-bar { animation: xe__progress-bar__wipe 200ms forwards; animation-timing-function: cubic-bezier(.86,0,.07,1); } @keyframes xe__progress-bar__wipe { 0% { width: calc(var(--slide-previous) / var(--slide-total) * 100%); } 100% { width: calc(var(--slide-current) / var(--slide-total) * 100%); } }</style> <div> <style type="text/css">.xaringan-extra-logo { width: 110px; height: 228px; z-index: 0; background-image: url(https://www.gob.mx/cms/uploads/action_program/main_image/26942/post_post_portadavectores.gif); background-size: contain; background-repeat: no-repeat; position: absolute; top:1em;right:1em; } </style> <script>(function () { let tries = 0 function addLogo () { if (typeof slideshow === 'undefined') { tries += 1 if (tries < 10) { setTimeout(addLogo, 100) } } else { document.querySelectorAll('.remark-slide-content:not(.title-slide):not(.inverse):not(.hide_logo)') .forEach(function (slide) { const logo = document.createElement('div') logo.classList = 'xaringan-extra-logo' logo.href = null slide.appendChild(logo) }) } } document.addEventListener('DOMContentLoaded', addLogo) })()</script> </div> # Conceptos `\(\color{#2ECC40}s_{\color{#2ECC40}i}\)`, `\(\color{#2ECC40}D\)`, & `\(\color{#2ECC40}u_{\color{#2ECC40}{si}}\)` <hr style="height:2px;border-width:0;color:#330019;background-color:#330019"> .pull-left[ <img src="index_files/figure-html/unnamed-chunk-1-1.png" width="100%" height="100%" style="display: block; margin: auto;" /> ] .pull-right[ `\(s{_i}\)` sitios de colecta con coordenadas geográficas (longitud. latitud). &nbsp; `\(D\)` area de estudio (zona metropolitana de Guadalajara). &nbsp; `\(Y{_i}\)` es la variable de respuesta (Número de Huevos por Ovitrampa o Manzana). &nbsp; `\(y{_i}\)` tiene una distribución (binomial negativa ó zibn). &nbsp; `\(U{_s{_i}}\)` el efecto espacial & el proceso ocurre en un campo gaussiano continuo (Gaussian Field). ] --- # Análisis Geoestadístico de Ovitrampas <hr style="height:2px;border-width:0;color:#330019;background-color:#330019"> .pull-left[ Modelo sin correlación espacial `\begin{align*} Huevos & = \beta{_0} + \beta x + \epsilon{_i} \\ \beta{_0} & = intercepto \\ \beta x & = pendiente \\ \epsilon{_i} & = error \\ \epsilon{_i} &\sim {\sf Norm}(0, \sigma^2) \\ \end{align*}` Modelo con efecto espacial `\begin{align*} Huevos & = \beta{_0} + \beta x + u{_i}+\epsilon{_i} \\ Huevos & = \beta{_0} + u{_i}+\epsilon{_i} \\ u{_i} & = efecto espacial \\ u{_i} &\sim {\sf GF}(0, \sum) \\ \end{align*}` ] .pull-rigth[ Cuando D es regular &nbsp; Se usa Gausian Makovian RF (GMRF) para aproximar la matriz de covarianzas &nbsp; Cuando D es irregular &nbsp; &nbsp; Se usa SPDE & Elemento Finito para aproximar la matriz de covarianzas ] --- # SPDE y elemento finito <hr style="height:2px;border-width:0;color:#330019;background-color:#330019"> .pull-left[ SPDE &nbsp; `$$(K^2-\Delta)^{a/2}U(s) = W(s)$$` Elemento Finito &nbsp; `$$u(s) = \sum_{i=1}^{G} \alpha{_k}(s{_i})W{_k}$$` ] .pull-right[ <!-- --> ``` ## [1] 31 ``` ] --- ## **Calculo de `\(\alpha{_k}\)`** <hr style="height:2px;border-width:0;color:#330019;background-color:#330019"> .pull-left[  ] .pull-right[ - Coordenadas en los vértices &nbsp; Sí `\(s{_i}\)` caé en el vértice 1, el resto 0. `\(u(s) = w{_k}\)` - Cordenadas dentro del Triángulo &nbsp; Sí `\(s{_i}\)` caé dentro del triángulo se ponderan los tres puntos `$$u(s) = \sum_{i=1}^{G} \alpha{_k}(s{_i})W{_k}$$` `$$0.17 * W{_1} + 0.54 * W{_3} + 0.29 * W{_3}$$` - Coordenadas sobre un borde &nbsp; Sí `\(s{_i}\)` caé en el borde se ponderan los dos valores `$$u(s) = \sum_{i=1}^{G} \alpha{_k}(s{_i})W{_k}$$` ] --- ## **Análisis Geoestadístico de Ovitrampas en R** .panelset.sideways[ .panel[.panel-name[Código] ```r x <- deneggs::eggs_hotspots(path_lect = "C:/Users/HOME/Dropbox/cenaprece_datasets/2022/14_jalisco", cve_ent = "14", locality = c("Guadalajara", "Zapopan", "Tlaquepaque", "Tonala"), path_coord = "C:/Users/HOME/Dropbox/cenaprece_datasets/2022/14_jalisco/DescargaOvitrampasMesFco.txt", longitude = "Pocision_X", latitude = "Pocision_Y", aproximation = "gaussian", integration = "eb", fam = "zeroinflatednbinomial1", k = 30, palette_vir = "magma", leg_title = "Huevos", plot = FALSE, hist_dataset = FALSE, sem = 41, var = "eggs", cell_size = 2000, alpha = .99) ggplot2::ggplot() + inlabru::gg(x$mesh) + ggplot2::geom_point(data = x$data, ggplot2::aes(x = x$data$Pocision_X, y = x$data$Pocision_Y), col = "red") ``` ] .panel[.panel-name[Mesh] <img src="index_files/figure-html/unnamed-chunk-4-1.png" width="100%" height="100%" /> ] .panel[.panel-name[Codigo] ```r x <- deneggs::eggs_hotspots(path_lect = "C:/Users/HOME/Dropbox/cenaprece_datasets/2022/14_jalisco", cve_ent = "14", locality = c("Guadalajara", "Zapopan", "Tlaquepaque", "Tonala"), path_coord = "C:/Users/HOME/Dropbox/cenaprece_datasets/2022/14_jalisco/DescargaOvitrampasMesFco.txt", longitude = "Pocision_X", latitude = "Pocision_Y", aproximation = "gaussian", integration = "eb", fam = "zeroinflatednbinomial1", k = 30, palette_vir = "magma", leg_title = "Huevos", plot = FALSE, hist_dataset = FALSE, sem = 41, var = "eggs", cell_size = 2000, alpha = .99) ggplot2::ggplot() + inlabru::gg(x$mesh) + ggplot2::geom_point(data = x$data, ggplot2::aes(x = x$data$Pocision_X, y = x$data$Pocision_Y), col = "red") + ggplot2::coord_sf(xlim = c(-103.30, -103.28), ylim = c(20.60, 20.61)) ``` ] .panel[.panel-name[Mesh zoom] <img src="index_files/figure-html/unnamed-chunk-5-1.png" width="100%" height="100%" /> ] ] --- ## **Análisis Geoestadístico de Ovitrampas en R** <hr style="height:2px;border-width:0;color:#330019;background-color:#330019"> ## 1. Instalar el paquete **INLA**. ## 2. Instalar el paquete **deneggs**. &nbsp; ## 3. Definir la ruta de los archivos de las lecturas y las coordenadas. &nbsp; ## 4. Definir la localidad de interes y la clave del estado. &nbsp; ## 5. Correr la función **deneggs::eggs_hotspots**. --- # Análisis Geoestadístico de Ovitrampas ## Definición de argumentos. <table class=" lightable-classic" style='font-family: "Arial Narrow", "Source Sans Pro", sans-serif; margin-left: auto; margin-right: auto;'> <thead> <tr> <th style="text-align:left;"> argumento </th> <th style="text-align:left;"> definicion </th> </tr> </thead> <tbody> <tr> <td style="text-align:left;"> path_lect </td> <td style="text-align:left;"> Ruta de ovitrampas </td> </tr> <tr> <td style="text-align:left;"> path_coord </td> <td style="text-align:left;"> Ruta de la coordenadas </td> </tr> <tr> <td style="text-align:left;"> year </td> <td style="text-align:left;"> Año a analizar </td> </tr> <tr> <td style="text-align:left;"> locality </td> <td style="text-align:left;"> localidad </td> </tr> <tr> <td style="text-align:left;"> cve_ent </td> <td style="text-align:left;"> Clave del Estado </td> </tr> <tr> <td style="text-align:left;"> leg_title </td> <td style="text-align:left;"> Título de la leyenda </td> </tr> <tr> <td style="text-align:left;"> fam </td> <td style="text-align:left;"> Nombre de la Distribución </td> </tr> <tr> <td style="text-align:left;"> alpha </td> <td style="text-align:left;"> Nivel de Significancia </td> </tr> <tr> <td style="text-align:left;"> plot </td> <td style="text-align:left;"> Valor lógico para visualizar el mesh </td> </tr> <tr> <td style="text-align:left;"> aproximation </td> <td style="text-align:left;"> Es el método de aproximación para calcular los hiperparametros y valores marginales. Las opciones son gaussian, simplified.laplace &amp; laplace </td> </tr> </tbody> </table> --- # Análisis Geoestadístico de Ovitrampas ## Definición de argumentos. <table class=" lightable-classic" style='font-family: "Arial Narrow", "Source Sans Pro", sans-serif; margin-left: auto; margin-right: auto;'> <thead> <tr> <th style="text-align:left;"> argumento </th> <th style="text-align:left;"> definicion </th> </tr> </thead> <tbody> <tr> <td style="text-align:left;"> integration </td> <td style="text-align:left;"> Es la estrategia de integración. Las opciones son grid, eb &amp; ccd) </td> </tr> <tr> <td style="text-align:left;"> longitude </td> <td style="text-align:left;"> Coordenada geográfica (longitud) </td> </tr> <tr> <td style="text-align:left;"> latitude </td> <td style="text-align:left;"> Coordenada geográfica (latitud) </td> </tr> <tr> <td style="text-align:left;"> k </td> <td style="text-align:left;"> es un parametro pera definir los triangules exteriores e interiores </td> </tr> <tr> <td style="text-align:left;"> sem </td> <td style="text-align:left;"> Es la semana epidemiológica </td> </tr> <tr> <td style="text-align:left;"> var </td> <td style="text-align:left;"> Es la variable de interes </td> </tr> <tr> <td style="text-align:left;"> cell_size </td> <td style="text-align:left;"> Es el tamaño de muestra para predecir </td> </tr> <tr> <td style="text-align:left;"> palette_vir </td> <td style="text-align:left;"> es la paleta de viridis. Las opciones son magma, inferno, plasma &amp; viridis </td> </tr> <tr> <td style="text-align:left;"> hist_dataset </td> <td style="text-align:left;"> Es un valor lógico para definir las bases históricas (FALSE) ó la actual base de ovitrampas(FALSE) </td> </tr> </tbody> </table> --- # Análisis Geoestadístico de Ovitrampas .panelset.sideways[ .panel[.panel-name[Código] ```r names(deneggs::eggs_hotspots(path_lect = "C:/Users/HOME/Dropbox/cenaprece_datasets/2022/14_jalisco", cve_ent = "14", locality = c("Guadalajara", "Zapopan", "Tlaquepaque", "Tonala"), path_coord = "C:/Users/HOME/Dropbox/cenaprece_datasets/2022/14_jalisco/DescargaOvitrampasMesFco.txt", longitude = "Pocision_X", latitude = "Pocision_Y", aproximation = "gaussian", integration = "eb", fam = "zeroinflatednbinomial1", k = 30, palette_vir = "magma", leg_title = "Huevos", plot = FALSE, hist_dataset = FALSE, sem = 41, var = "eggs", cell_size = 2000, alpha = .99)) ``` ] .panel[.panel-name[Elementos] ``` ## [1] "data" "map" "loc" "mod" "mesh" "dics" "hotspots" ``` ] .panel[.panel-name[Codigo] ```r deneggs::eggs_hotspots(path_lect = "C:/Users/HOME/Dropbox/cenaprece_datasets/2022/14_jalisco", cve_ent = "14", locality = c("Guadalajara", "Zapopan", "Tlaquepaque", "Tonala"), path_coord = "C:/Users/HOME/Dropbox/cenaprece_datasets/2022/14_jalisco/DescargaOvitrampasMesFco.txt", longitude = "Pocision_X", latitude = "Pocision_Y", aproximation = "gaussian", integration = "eb", fam = "zeroinflatednbinomial1", k = 30, palette_vir = "magma", leg_title = "Huevos", plot = FALSE, hist_dataset = FALSE, sem = 41, var = "eggs", cell_size = 2000, alpha = .99)$map ``` ] .panel[.panel-name[Mapa] <img src="index_files/figure-html/unnamed-chunk-10-1.png" width="100%" /> ] ] --- # Dios Botic! <hr style="height:2px;border-width:0;color:#330019;background-color:#330019"> &nbsp; - ***Bio*** : https://fdzul.github.io/web_site_fadm/ - ***email*** : [felipe.dzul.m@gmail.com]() - ***celular*** : [8139945623]() - ***slides***: https://animated-longma-729cee.netlify.app/talks/hotspots_eggs_R/#1 .footnote[La presentación fue creada via [**xaringan**](https://github.com/yihui/xaringan), [**revealjs**](https://revealjs.com/), [remark.js](https://remarkjs.com), [**knitr**](http://yihui.name/knitr), & [R Markdown](https://rmarkdown.rstudio.com) en [R]() & [RStudio](2.R_Scripts/libs/rstudio_leaflet/rstudio_leaflet.css).]