Difference between revisions of "COVID-19"
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− | ==SARS-CoV-2 | + | ==The Virus: SARS-CoV-2== |
− | [https://www.nytimes.com/interactive/2020/04/ | + | {{Post-summary |
− | + | | summary-category = | |
+ | | summary-title = [https://www.nytimes.com/interactive/2020/04/30/science/coronavirus-mutations.html How Coronavirus Mutates and Spreads] | ||
+ | | summary-author = ''J. Corum'' and ''C. Zimmer'' | ||
+ | | summary-institution = NY Times | ||
+ | | summary-date = April 30, 2020 | ||
+ | | summary-text = The coronavirus is an oily membrane packed with genetic instructions to make millions of copies of itself. The instructions are encoded in 30,000 ''letters'' of RNA — '''a''', '''c''', '''g''' and '''u''' — which the infected cell reads and translates into many kinds of virus proteins. | ||
+ | }} | ||
− | [https://www. | + | {{Post-summary |
− | + | | summary-category = https://static01.nyt.com/newsgraphics/2020/03/10/coronavirus-pathogen/0ee8f1a44b1932072653a0a75ff96486feb6f36d/covid-vaccine.png | |
+ | | summary-title = [https://www.nytimes.com/interactive/2020/04/03/science/coronavirus-genome-bad-news-wrapped-in-protein.html Bad News Wrapped in Protein: Inside the Coronavirus Genome] | ||
+ | | summary-author = ''J. Corum'' and ''C. Zimmer'' | ||
+ | | summary-institution = NY Times | ||
+ | | summary-date = April 3, 2020 | ||
+ | | summary-text = The genome of the new coronavirus is less than 30,000 ''letters'' long, while the human genome is over 3 billion. Scientists have identified genes for as many as 29 proteins, which carry out a range of jobs from making copies of the coronavirus to suppressing the body’s immune responses. | ||
+ | }} | ||
+ | |||
+ | {{Post-summary | ||
+ | | summary-category = https://static01.nyt.com/newsgraphics/2020/03/10/coronavirus-pathogen/0ee8f1a44b1932072653a0a75ff96486feb6f36d/covid-soap.png | ||
+ | | summary-title = [https://www.nytimes.com/interactive/2020/03/11/science/how-coronavirus-hijacks-your-cells.html How Coronavirus Hijacks Your Cells] | ||
+ | | summary-author = ''J. Corum'' and ''C. Zimmer'' | ||
+ | | summary-institution = NY Times | ||
+ | | summary-date = March 13, 2020 | ||
+ | | summary-text = The virus that causes Covid-19 is currently spreading around the world. At least six other types of coronavirus are known to infect humans, with some causing the common cold and two causing outbreaks: SARS and MERS. | ||
+ | }} | ||
<hr class="stylish2"> | <hr class="stylish2"> | ||
− | ==Data Sources== | + | ==Treatment, Vaccine, Prevention== |
+ | |||
+ | {{Post-summary | ||
+ | | summary-category = https://static01.nyt.com/newsgraphics/2020/04/08/opinion-covid-timeline/b006abb8ec5ece8b419f2ad57b88ceee5b576856/vaccine-success-Artboard_1.png | ||
+ | | summary-title = [https://www.nytimes.com/interactive/2020/04/30/opinion/coronavirus-covid-vaccine.html How Long Will a Vaccine Really Take?] | ||
+ | | summary-author = ''S. A. Thompson'' | ||
+ | | summary-institution = NY Times | ||
+ | | summary-date = April 30, 2020 | ||
+ | | summary-text = A vaccine would be the ultimate weapon against the coronavirus and the best route back to normal life. Officials like Dr. Anthony S. Fauci, the top infectious disease expert on the US administration’s coronavirus task force, estimate a vaccine could arrive in at least 12 to 18 months. | ||
+ | }} | ||
+ | |||
+ | <hr class="stylish2"> | ||
+ | |||
+ | ==Data Sources (pandemic)== | ||
+ | |||
+ | [https://ourworldindata.org/covid-sources-comparison How do sources compare?] by ''H. Ritchie et al.'', March 19, 2020 — <span class="is-all-small-caps">Our World in Data</span> | ||
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— There are three key sources providing regular updates of COVID-19 cases and deaths globally and by country. | — There are three key sources providing regular updates of COVID-19 cases and deaths globally and by country. | ||
− | + | # [https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/ World Health Organization] | |
− | + | # [https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases European Center for Disease Control and Prevention (ECDC)] | |
− | + | # [https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6 Johns Hopkins University] | |
+ | |||
+ | '''Addendum''' | ||
+ | |||
+ | * [https://ourworldindata.org/coronavirus Our World in Data] — <span class="is-all-small-caps">Global Change Data Lab</span> | ||
* [https://wolfr.am/COVID19Dashboard Wolfram] | * [https://wolfr.am/COVID19Dashboard Wolfram] | ||
* [https://www.worldometers.info/coronavirus/ Worldometers] | * [https://www.worldometers.info/coronavirus/ Worldometers] | ||
− | * [https://www. | + | * [https://www.wolframcloud.com/obj/examples/COVID19Gene Genetic Data for SARS-CoV-2] — <span class="is-all-small-caps il-sans-serif">Wolfram</span> |
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− | == | + | '''NOTE:''' [https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide Script] for downloading the CSV file into '''R''' |
+ | <syntaxhighlight lang="R" line='line'> | ||
+ | #these libraries need to be loaded | ||
+ | library(utils) | ||
− | + | #read the Dataset sheet into “R”. The dataset will be called "data". | |
− | + | data <- read.csv("https://opendata.ecdc.europa.eu/covid19/casedistribution/csv", na.strings = "", fileEncoding = "UTF-8-BOM") | |
− | + | </syntaxhighlight> | |
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<hr class="stylish2"> | <hr class="stylish2"> | ||
− | == | + | ==Data Sources (other)== |
− | * [https:// | + | |
− | + | * [https://www.apple.com/covid19/mobility Mobility Trends Reports] — <span class="is-all-small-caps il-sans-serif">Apple</span><br> | |
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<hr class="stylish2"> | <hr class="stylish2"> | ||
− | == | + | ==Datasets== |
− | * [https:// | + | * [https://pages.semanticscholar.org/coronavirus-research COVID-19 Open Research Dataset (CORD-19)] — <span class="is-all-small-caps">Semantic Scholar</span> |
− | * [https:// | + | * [https://datasetsearch.research.google.com/search?query=coronavirus&docid=BrjdJJ2D8wVenNxVAAAAAA%3D%3D Coronavirus Database Search] — <span class="is-all-small-caps">Google</span> |
− | + | * [https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge CORD-19 Research Challenge] — <span class="is-all-small-caps">Kaggle</span> | |
− | * [https:// | ||
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<hr class="stylish2"> | <hr class="stylish2"> | ||
− | === | + | ==Updates== |
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+ | * [https://www.canada.ca/en/public-health/services/diseases/2019-novel-coronavirus-infection.html Outbreak Updates (Government of Canada)] | ||
+ | * [https://www.canada.ca/en/public-health/services/diseases/2019-novel-coronavirus-infection/awareness-resources.html Coronavirus disease (COVID-19): Awareness resources (Government of Canada)] | ||
+ | * [https://www.cdc.gov/coronavirus/2019-ncov/about/index.html The Centers for Disease Control and Prevention (CDC)] | ||
+ | * [https://github.com/HopkinsIDD/ncov_incubation Real-time estimation of the novel coronavirus incubation time] | ||
+ | * [https://www.rcsb.org/structure/6LU7 The crystal structure of COVID-19] | ||
+ | * [https://nyti.ms/31jGhk2 The Coronavirus Outbreak] — <span class="is-all-small-caps">NY Times</span> | ||
+ | * [https://flatten.ca/ Flatten] | ||
+ | * [https://www.repidemicsconsortium.org/projects/ R Epidemics Consortium] | ||
+ | * [https://www.endcoronavirus.org EndCoronavirus (ECV)] — <span class="is-all-small-caps">NECSI </span> | ||
+ | * [https://github.com/soroushchehresa/awesome-coronavirus Awesome Coronavirus] | ||
* [https://nextstrain.org/ncov Genomic epidemiology of novel coronavirus (hCoV-19)] | * [https://nextstrain.org/ncov Genomic epidemiology of novel coronavirus (hCoV-19)] | ||
* [https://ncov.dxy.cn/ncovh5/view/en_pneumonia?from=dxy&source=&link=&share= DXY] | * [https://ncov.dxy.cn/ncovh5/view/en_pneumonia?from=dxy&source=&link=&share= DXY] | ||
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* [https://covid19obs.fbk.eu/ Infodemics Observatory] | * [https://covid19obs.fbk.eu/ Infodemics Observatory] | ||
* [http://covid19.science.unimelb.edu.au/ 10 Day Forecast] — <span class="is-all-small-caps">University of Melbourne</span> | * [http://covid19.science.unimelb.edu.au/ 10 Day Forecast] — <span class="is-all-small-caps">University of Melbourne</span> | ||
+ | * [https://graphics.reuters.com/world-coronavirus-tracker-and-maps/index.html Global Tracker] — <span class="is-all-small-caps">REUTERS</span> | ||
+ | <hr class="stylish2"> | ||
+ | |||
+ | ==Dashboards== | ||
+ | |||
+ | * [https://gabgoh.github.io/COVID/index.html Epidemic Calculator] by ''G. Goh'' | ||
+ | * [https://observablehq.com/collection/@observablehq/coronavirus Observable Collection] | ||
+ | ** [https://observablehq.com/@yy/covid-19-fatality-rate Fatality Rate and Spreading Trends] by ''Y. Ahn'' | ||
+ | ** [https://observablehq.com/@nirajd/sars2-cov-epi-curve EPi Curve] by ''Niraj D'' | ||
+ | * Shiny | ||
+ | ** [https://andrecalerovaldez.shinyapps.io/CovidTimeSeries/ CoronaTacker] by ''A. C. Valdez'' | ||
+ | ** [https://chschoenenberger.shinyapps.io/covid19_dashboard/ A Dashboard] by ''C. Schoenenberger'' | ||
+ | ** [https://alhill.shinyapps.io/COVID19seir/ Modeling Spread and Capacity] by ''A. Hill et al.'' | ||
+ | ** [https://tinu.shinyapps.io/Flatten_the_Curve/ Flatten the Curve] by ''M. Höhle'' | ||
+ | ** [https://jgassen.shinyapps.io/tidycovid19/ Explore the Spread] by ''J. Gassen'' | ||
+ | ** [https://worldhealthorg.shinyapps.io/covid/ WHO Covid-19 Explorer] | ||
+ | * Tableau | ||
+ | ** [https://www.tableau.com/covid-19-coronavirus-data-resources Data Hub] | ||
+ | ** [https://public.tableau.com/profile/jonas.nart#!/vizhome/COVID19_15844962693420/COVID19-TrendTracker Trend Tracker] | ||
+ | ** [https://public.tableau.com/profile/marc.psaila#!/vizhome/Coronavirusfortableaupublic/Coronaviruscasesbycountry Progression] | ||
+ | ** [https://public.tableau.com/profile/daminda.de.silva#!/vizhome/corona-virusspreadingacrosstheworld/Dashboard33 Daily Updates] | ||
<hr class="stylish2"> | <hr class="stylish2"> | ||
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* [https://meltingasphalt.com/interactive/outbreak/ Outbreak] by ''K. Simler'' | * [https://meltingasphalt.com/interactive/outbreak/ Outbreak] by ''K. Simler'' | ||
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* [https://blog.ephorie.de/contagiousness-of-covid-19-part-i-improvements-of-mathematical-fitting-guest-post Contagiousness of COVID-19 Part I: Improvements of Mathematical Fitting] by ''M. Weterings'' | * [https://blog.ephorie.de/contagiousness-of-covid-19-part-i-improvements-of-mathematical-fitting-guest-post Contagiousness of COVID-19 Part I: Improvements of Mathematical Fitting] by ''M. Weterings'' | ||
+ | * [https://www.ncbi.nlm.nih.gov/research/coronavirus/ LitCovid] — <span class="is-all-small-caps">NCBI</span> | ||
+ | * [https://asone.ai/polymath/index.php?title=COVID-19_dataset_clearinghouse COVID-19 dataset clearinghouse] — <span class="is-all-small-caps">Polymath</span> | ||
+ | * [https://rviews.rstudio.com/2020/04/07/some-select-covid-19-modeling-resources/ Modeling resources] by ''J. Rickert'' — <span class="is-all-small-caps">R Views</span> | ||
+ | * [https://blog.ephorie.de/contagiousness-of-covid-19-part-i-improvements-of-mathematical-fitting-guest-post Contagiousness of COVID-19 Part I: Improvements of Mathematical Fitting] — <span class="is-all-small-caps">Learning Machines</span> | ||
+ | * [https://blog.ephorie.de/epidemiology-how-contagious-is-novel-coronavirus-2019-ncov Epidemiology: How contagious is Novel Coronavirus (2019-nCoV)?] — <span class="is-all-small-caps">Learning Machines</span> | ||
+ | * [https://blog.ephorie.de/covid-19-analyze-mobility-trends-with-r COVID-19: Analyze Mobility Trends with R] — <span class="is-all-small-caps">Learning Machines</span> | ||
+ | |||
+ | ==Self-check== | ||
+ | |||
+ | * [[Covid-19 Progress in Turkey]] | ||
− | + | {{Top}} | |
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▪
|
NY Times - April 30, 2020 |
The coronavirus is an oily membrane packed with genetic instructions to make millions of copies of itself. The instructions are encoded in 30,000 letters of RNA — a, c, g and u — which the infected cell reads and translates into many kinds of virus proteins. |
▪
|
NY Times - April 3, 2020 |
The genome of the new coronavirus is less than 30,000 letters long, while the human genome is over 3 billion. Scientists have identified genes for as many as 29 proteins, which carry out a range of jobs from making copies of the coronavirus to suppressing the body’s immune responses. |
![]() |
▪
|
NY Times - March 13, 2020 |
The virus that causes Covid-19 is currently spreading around the world. At least six other types of coronavirus are known to infect humans, with some causing the common cold and two causing outbreaks: SARS and MERS. |
![]() |
▪
|
NY Times - April 30, 2020 |
A vaccine would be the ultimate weapon against the coronavirus and the best route back to normal life. Officials like Dr. Anthony S. Fauci, the top infectious disease expert on the US administration’s coronavirus task force, estimate a vaccine could arrive in at least 12 to 18 months. |
![]() |
How do sources compare? by H. Ritchie et al., March 19, 2020 — Our World in Data
— There are three key sources providing regular updates of COVID-19 cases and deaths globally and by country.
Addendum
NOTE: Script for downloading the CSV file into R
1 #these libraries need to be loaded
2 library(utils)
3
4 #read the Dataset sheet into “R”. The dataset will be called "data".
5 data <- read.csv("https://opendata.ecdc.europa.eu/covid19/casedistribution/csv", na.strings = "", fileEncoding = "UTF-8-BOM")
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