class: center, middle, inverse, title-slide # 探索COIVD-19資料 ## R 語言於流行病學資料之視覺化運用 ### 蘇睿寧 ### 2021-12-26 --- ## The Diagram of nCov2019 architecture <img src="nCov2019.png" width="68%" style="display: block; margin: auto;" /> --- ## Overviews ###- Data collection 數據收集 ###- Data query 資料查詢 ###- Data operation with Geographic maps 資料操作 ###- Interactive dashboard 互動式儀表板 --- ## {nCov2019}安裝package ###有時候資料下載會比較慢 ```r #remotes::install_github("yulab-smu/nCov2019", dependencies = TRUE) library("nCov2019") ``` ## Data collection ###-WorldoMeters 實時統計數據的網站 ###-Center for Systems Science and Engineering(CSSE) ###-website of raps.org 疫苗研發資料 --- <style type="text/css"> /* custom.css */ .left-code { color: #777; width: 30%; height: 150%; float: left; } .pull-left { float: left; width: 47%; } .pull-right { float: right; width: 47%; } </style> .pull-left[ ```r res <- query() ``` ``` ## Querying the latest data... ``` ``` ## last update: 2021-12-26 ``` ``` ## Querying the global data... ``` ``` ## Gloabl total 279848485 cases; and 5413544 deaths ## Gloabl total affect country or areas: 224 ## Gloabl total recovered cases: 59214 ## last update: 2021-12-26 ``` ``` ## Querying the historical data... ``` ``` ## Querying the vaccine data... ``` ``` ## Total Candidates Programs : 51 ``` ``` ## Querying the therapeutics data... ``` ``` ## Total Candidates Programs : 84 ``` ``` ## Query finish, each time you can launch query() to reflash the data ``` ] .pull-right[ ## Data query 啟動資料分類 ###- **the latest data** ###- **global data** ###- **historical data** ###- **vaccine/therapeutics data** ] ```r names(res) ``` ``` ## [1] "latest" "global" "historical" "vaccine" "therapeutics" ``` --- ## Data operation: Global data ```r x<- res$latest DT::datatable(x["Global"], rownames=FALSE, options=list(scrollY = 300, pageLength=10), fillContainer =TRUE) ``` <div id="htmlwidget-cbed5869b06e296eb3b9" style="width:100%;height:auto;" class="datatables html-widget"></div> <script type="application/json" data-for="htmlwidget-cbed5869b06e296eb3b9">{"x":{"filter":"none","vertical":false,"fillContainer":true,"data":[["France","Italy","USA","Russia","Turkey","Germany","Vietnam","South Africa","Ireland","Netherlands","Poland","Portugal","Australia","Denmark","Belgium","Argentina","India","Greece","Peru","S. 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class=\"display fill-container\">\n <thead>\n <tr>\n <th>country<\/th>\n <th>cases<\/th>\n <th>deaths<\/th>\n <th>recovered<\/th>\n <th>active<\/th>\n <th>todayCases<\/th>\n <th>todayDeaths<\/th>\n <th>todayRecovered<\/th>\n <th>population<\/th>\n <th>tests<\/th>\n <th>updated<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"scrollY":300,"pageLength":10,"columnDefs":[{"className":"dt-right","targets":[1,2,3,4,5,6,7,8,9]}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script> ```r #return all global countries ``` --- ## Data query: Taiwan as example ```r DT::datatable(x[c("Taiwan")], options=list(scrollY = 80, pageLength=10), fillContainer =FALSE) ``` <div id="htmlwidget-13bfdfdd97f6226c6c60" style="width:100%;height:auto;" class="datatables html-widget"></div> <script type="application/json" data-for="htmlwidget-13bfdfdd97f6226c6c60">{"x":{"filter":"none","vertical":false,"fillContainer":false,"data":[["130"],["Taiwan"],[16891],[850],[15802],[239],[18],[0],[4],[23880616],[9099571],["2021-12-26"]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th> <\/th>\n <th>country<\/th>\n <th>cases<\/th>\n <th>deaths<\/th>\n <th>recovered<\/th>\n <th>active<\/th>\n <th>todayCases<\/th>\n <th>todayDeaths<\/th>\n <th>todayRecovered<\/th>\n <th>population<\/th>\n <th>tests<\/th>\n <th>updated<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"scrollY":80,"pageLength":10,"columnDefs":[{"className":"dt-right","targets":[2,3,4,5,6,7,8,9,10]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script> ```r # return only for Taiwan ``` <img src="nCov2019TTW.png" width="859" style="display: block; margin: auto;" /> ### 資料一致性高 --- ## Data query: Historical data of Taiwan .pull-left[ ```r Z<- res$historical print(Z) ``` ``` ## last update: 2021-12-25 ``` ```r tail(Z[c("Taiwan")]) ``` ``` ## country date cases deaths recovered ## 136981 Taiwan 2021-12-20 16816 850 0 ## 137177 Taiwan 2021-12-21 16826 850 0 ## 137373 Taiwan 2021-12-22 16840 850 0 ## 137569 Taiwan 2021-12-23 16853 850 0 ## 137765 Taiwan 2021-12-24 16873 850 0 ## 137961 Taiwan 2021-12-25 16891 850 0 ``` ] .pull-right[ <img src="historical.png" width="599" /> ] ### **雖有一點時間差，準確性仍高** --- ## Data query: Vaccine data ```r X <-res$ vaccine summary(X) ``` ``` ## phase candidates ## 1 Phase 3 10 ## 2 Phase 2/3 3 ## 3 Phase 2 2 ## 4 Phase 1/2 9 ## 5 Phase 1 13 ## 6 Pre-clinical 14 ``` --- ## Data query: Vaccine data(但找不到高端) ```r DT::datatable(X["all"], rownames=FALSE, options=list(scrollY = 300, pageLength=10), fillContainer =TRUE) ``` <div id="htmlwidget-d0d5c089937d99eef764" style="width:100%;height:auto;" class="datatables html-widget"></div> <script type="application/json" data-for="htmlwidget-d0d5c089937d99eef764">{"x":{"filter":"none","vertical":false,"fillContainer":true,"data":[["id1","id2","id3","id4","id5","id6","id7","id8","id9","id10","id11","id12","id13","id14","id15","id16","id17","id18","id19","id20","id21","id22","id23","id24","id25","id26","id27","id28","id29","id30","id31","id32","id33","id34","id35","id36","id37","id38","id39","id40","id41","id42","id43","id44","id45","id46","id47","id48","id49","id50","id51"],["BNT162","mRNA-1273","Ad5-nCoV","AZD1222","CoronaVac","Covaxin","JNJ-78436735 (formerly Ad26.COV2.S)","No name announced","NVX-CoV2373","Sputnik V","Bacillus Calmette-Guerin (BCG) vaccine","INO-4800","VIR-7831","No name announced","ZyCoV-D","No name announced","AG0301-COVID19","BBIBP-CorV","EpiVacCorona","GX-19","LNP-nCoVsaRNA","ARCT-021 (LUNAR-COV19)","No name announced","No name announced","AdimrSC-2f","bacTRL-Spike","COVAX-19","CVnCoV","DelNS1-2019-nCoV-RBD-OPT1","GRAd-COV2","UQ-CSL V451","No name announced","SCB-2019","UB-612","V590","V591","VXA-CoV2-1","AAVCOVID","AdCOVID","ChAd-SARS-CoV-2-S","HaloVax","HDT-301","LineaDNA","MRT5500","No name announced","No name announced","No name announced","No name announced","No name announced","PittCoVacc","T-COVIDTM"],["mRNA-based vaccine","mRNA-based vaccine","Recombinant vaccine (adenovirus type 5 vector)","Replication-deficient viral vector vaccine (adenovirus from chimpanzees)","Inactivated vaccine (formalin with alum adjuvant)","Inactivated vaccine","Non-replicating viral vector","Inactivated vaccine","Nanoparticle vaccine","Non-replicating viral vector","Live-attenuated vaccine","DNA vaccine (plasmid)","Plant-based adjuvant vaccine","Recombinant vaccine","DNA vaccine (plasmid)","Adjuvanted protein subunit vaccine","DNA vaccine","Inactivated vaccine","Peptide vaccine","DNA vaccine","Self-amplifying RNA vaccine","Self-replicating RNA vaccine","Protein subunit vaccine","Inactivated vaccine","Protein subunit vaccine","Monovalent oral vaccine (bifidobacteria)","Monovalent recombinant protein vaccine","mRNA-based vaccine","Replicating viral vector","Adenovirus-based vaccine","Protein subunit vaccine","Adenovirus-based vaccine","Protein subunit vaccine","Multitope peptide-based vaccine","Recombinant vaccine (vesicular stomatitis virus)","Measles vector vaccine","Recombinant vaccine (adenovirus type 5 vector)","Gene-based vaccine","Intranasal vaccine","Adenovirus-based vaccine","Self-assembling vaccine","RNA vaccine","DNA vaccine","Recombinant vaccine","Ii-Key peptide COVID-19 vaccine","Protein subunit vaccine","mRNA-based vaccine","gp96-based vaccine","Inactivated vaccine","Recombinant protein subunit vaccine (delivered through microneedle array)","Intranasal vaccine"],["Pfizer, BioNTech","Moderna","CanSino Biologics","The University of Oxford","Sinovac","Bharat Biotech","Johnson & Johnson","Wuhan Institute of Biological Products","Novavax","Gamaleya Research Institute, Acellena Contract Drug Research and Development","University of Melbourne and Murdoch Children&rsquo","Inovio Pharmaceuticals","Medicago","Anhui Zhifei Longcom Biopharmaceutical, Institute of Microbiology of the Chinese Academy of Sciences","Zydus Cadila","","AnGes, Inc.","Beijing Institute of Biological Products","Federal Budgetary Research Institution State Research Center of Virology and Biotechnology","Genexine","Imperial College London","Arcturus Therapeutics&nbsp","Sanofi","Chinese Academy of Medical Sciences, Institute of Medical Biology","Adimmune","Symvivo","Vaxine Pty Ltd.","CureVac","Xiamen University, Beijing Wantai Biological Pharmacy","ReiThera","CSL","ImmunityBio","GlaxoSmithKline,&nbsp","COVAXX","Merck","University of Pittsburgh’s Center for Vaccine Research","Vaxart","Massachusetts Eye and Ear","Altimmune","Washington University School of Medicine in St. Louis","Voltron Therapeutics, Inc.","University of Washington","Takis Biotech","Sanofi, Translate Bio","Generex Biotechnology","University of Saskatchewan Vaccine and Infectious Disease Organization-International Vaccine Centre","Chulalongkorn University’s Center of Excellence in Vaccine Research and Development","Heat Biologics","Shenzhen Kangtai Biological Products","UPMC/University of Pittsburgh School of Medicine","Altimmune"],["Phase 3","Phase 3","Phase 3","Phase 3","Phase 3","Phase 3","Phase 3","Phase 3","Phase 3","Phase 3","Phase 2/3","Phase 2/3","Phase 2/3","Phase 2","Phase 2","Phase 1/2","Phase 1/2","Phase 1/2","Phase 1/2","Phase 1/2","Phase 1/2","Phase 1/2","Phase 1/2","Phase 1/2","Phase 1","Phase 1","Phase 1","Phase 1","Phase 1","Phase 1","Phase 1","Phase 1","Phase 1","Phase 1","Phase 1","Phase 1","Phase 1","Pre-clinical","Pre-clinical","Pre-clinical","Pre-clinical","Pre-clinical","Pre-clinical","Pre-clinical","Pre-clinical","Pre-clinical","Pre-clinical","Pre-clinical","Pre-clinical","Pre-clinical","Pre-clinical"],["Multiple study sites in Europe, North America and China","Kaiser Permanente Washington Health Research Institute","Tongji Hospital","The University of Oxford,&nbsp","Sinovac Research and Development Co., Ltd.","","Johnson & Johnson","Henan Provincial Center for Disease Control and Prevention","Novavax","Various","University of Melbourne and Murdoch Children&rsquo","Center for Pharmaceutical Research, Kansas City. Mo.","Medicago","Various","Zydus Cadila","","AnGes, Inc.","Henan Provincial Center for Disease Control and Prevention","Federal Budgetary Research Institution State Research Center of Virology and Biotechnology","","Imperial College London","Duke-NUS Medical School, Singapore","Various","West China Second University Hospital, Yunnan Center for Disease Control and Prevention","Adimmune","Symvivo Corporation","Royal Adelaide Hospital","CureVac","Jiangsu Provincial Centre For Disease Control and Prevention","Lazzaro Spallanzani National Institute for Infectious Diseases","","","Linear Clinical Research (Australia)","United Biomedical Inc. (UBI)","","University of Pittsburgh","Vaxart","","University of Alabama at Birmingham","Washington University School of Medicine in St. Louis","MGH Vaccine and Immunotherapy Center","","Takis Biotech","","Generex","University of Saskatchewan Vaccine and Infectious Disease Organization-International Vaccine Centre","","University of Miami Miller School of Medicine","","University of Pittsburgh",""]],"container":"<table class=\"display fill-container\">\n <thead>\n <tr>\n <th>id<\/th>\n <th>candidate<\/th>\n <th>mechanism<\/th>\n <th>sponsors<\/th>\n <th>trialPhase<\/th>\n <th>institutions<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"scrollY":300,"pageLength":10,"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script> --- ## Data query: Vaccine data試驗細節 ```r X[ID="id1"] ``` <img src="vaccine.png" width="1081" style="display: block; margin: auto;" /> --- ## Data operation: Visualization (Confirmed Cases) .pull-left[ ```r plot( x, region="Global", continuous_scale = F, palette = "Reds", date = NULL, from = NULL, to = NULL, title = "COVID-19", type = "cases") ``` ] .pull-right[ <img src="global map.png" width="839" /> ] --- ## Data operation: Visualization (Recovered Cases) .pull-left[ ```r plot( x, region="Global", continuous_scale = F, palette = "Green", date = NULL, from = NULL, to = NULL, title = "COVID-19", type = "recovered" ) ``` ] .pull-left[ <img src="global map recov.png" width="839" /> ] --- ## Data operation: ggplot ###折線圖比較資料的趨勢 .pull-left[ ```r library(ggplot2) library(dplyr) X <- res$historical tmp <- X["global"] %>% group_by(country) %>% arrange(country,date) %>% mutate(diff = cases - lag(cases, default = first(cases))) %>% filter(country %in% c("Taiwan","Japan")) ggplot(tmp,aes(date, log(diff+1), color=country)) + geom_line() + labs(y="Log2(daily increase cases)") + theme(axis.text = element_text(angle = 15, hjust = 1)) + scale_x_date(date_labels = "%Y-%m-%d") + theme_minimal() ``` ] .pull-left[ <img src="confirmed TW.png" width="1041" /> ] --- ## Data operation: Animations plot (動畫圖示) ### 以顏色動態呈現個案確診個數在各地區的變化 .pull-left[ ```r library(nCov2019) res = query() from = "2021-11-01" to = "2021-11-30" y = res$historical plot(y, from = from, to=to) ``` ] .pull-right[ <img src="nCov2019.gif" width="200%" /> ] --- ## Data operation: Other plots(視覺累積圖) .pull-left[ ```r library(ggplot2) x <- res$historical d = x['Taiwan'] d = d[order(d$cases), ] ggplot(d, aes(date, cases)) + geom_col(fill = 'firebrick') + theme_minimal(base_size = 14) + xlab(NULL) + ylab(NULL) + scale_x_date(date_labels = "%Y/%m/%d") + labs(caption = paste("accessed date:", max(d$date))) ``` ] .pull-right[ <img src="confirmed TW2.png" width="1051" /> * **可看出來5-6月間台灣一波疫情大爆發** ] --- ## Data operation: Other plots(個案增加趨勢圖) .pull-left[ ```r library("dplyr") library("ggrepel") x <- res$latest y <- res$historical country_list = x["global"]$country[1:3] y[country_list] %>% subset( date > as.Date("2021-07-01") ) %>% group_by(country) %>% arrange(country,date) %>% mutate(increase = cases - lag(cases, default = first(cases))) -> df ggplot(df, aes(x=date, y=increase, color=country ))+ geom_smooth() + geom_label_repel(aes(label = paste(country,increase)), data = df[df$date == max(df$date), ], hjust = 1) + labs(x=NULL,y=NULL, title=paste("visualize the cumulative summary data of Taiwan"))+ theme_bw() + theme(legend.position = 'none') ``` ] .pull-right[ <img src="casestrajectory.png" width="840" /> * **Omicron自11月最早在南非被發現和確定後，個案數有增加的趨勢** ] --- ##Data operation: Taiwan 確診、復原及死亡數 .pull-left[ ```r library('tidyr') library('ggrepel') library('ggplot2') y <- res$historical country = "Taiwan" y[country] -> d d <- gather(d, curve, count, -date, -country) ggplot(d, aes(date, count, color = curve)) + geom_point() + geom_line() + labs(x=NULL,y=NULL,title=paste("Trend of cases, recovered and deaths in", country)) + scale_color_manual(values=c("#f39c12", "#dd4b39", "#00a65a")) + theme_bw() + geom_label_repel(aes(label = paste(curve,count)), data = d[d$date == max(d$date), ], hjust = 1) + theme(legend.position = "none",axis.text = element_text(angle = 15, hjust = 1)) + scale_x_date(date_labels = "%Y-%m-%d") ``` ] .pull-right[ <img src="trend TW.png" width="839" /> ] ```r require(dplyr) ``` ``` ## 載入需要的套件：dplyr ``` ``` ## ## 載入套件：'dplyr' ``` ``` ## 下列物件被遮斷自 'package:stats': ## ## filter, lag ``` ``` ## 下列物件被遮斷自 'package:base': ## ## intersect, setdiff, setequal, union ``` ```r require(ggplot2) ``` ``` ## 載入需要的套件：ggplot2 ``` ```r require(shadowtext) ``` ``` ## 載入需要的套件：shadowtext ``` --- ## Interactive dashboard(shiny APP) ```r dashboard() ``` <img src="dashboard.png" width="1249" /> --- ## Conclusion of R .pull-left[ ###- 資料串接可增加運用性 ###- 視覺性的圖像有助於理解流性病學的趨勢 ###- 疾管局亦有類似資料呈現方式 ] .pull-right[ <img src="cdc.png" width="571" /> ] --- ## Conclusion of myself .pull-left[ ###- R可以辦到的事很神奇 ###- R可以辦到的事情我大多辦不到 ###- RRRRRRRRRR... ] .pull-right[ <img src="happyNY.png" width="685" /> ]