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- A timeline for COVID-19 can be found here. Also looking at a map of how the COVID-19 traveled the world or the HealthMap one can see how and when various regions were impacted. Also see the Unacast interactive Social Distancing Scoreboard, updated daily, to empower organizations to measure and understand the efficacy of social distancing initiatives at the local level.
- Unacast is only for the US. It is broken down into States and counties. It uses cell phone location data to track locations. From this it derives for example distance traveled. An example of the information aggregated for the US is below (in the chart the bars are the new cases, the red dots are events, the state map colors are green for low mobility and dark orange for high mobility). Similar information is available state by state.
- Unacast is only for the US. It is broken down into States and counties. It uses cell phone location data to track locations. From this it derives for example distance traveled. An example of the information aggregated for the US is below (in the chart the bars are the new cases, the red dots are events, the state map colors are green for low mobility and dark orange for high mobility). Similar information is available state by state.
- For detailed statistics see:
- For the raw data:
- You can get up-to-date raw data on the coronavirus from Johns Hopkins from their GitHub site: https://github.com/CSSEGISandData/COVID-19. They have daily summaries and time-series data, both available as CSV files. You just have to browse around a bit to find what you want.
- To get down to the level of US states and counties see https://github.com/nytimes/covid-19-data
- For scientific modeling of the COVAD-19's impacts see:
- The Imperial College London reports on the Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand and Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries.
- Projections for US hospital resources and deaths.
- For Interventions see
- For Intevention Intervention stringency vs cases see https://www.bsg.ox.ac.uk/sites/default/files/2020-04/BSG-WP-2020-031-v4.0_0.pdf
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- For Europe, US and Canada the Christmas/New Year season (end November thru 2nd week in January) may also be expected to change behaviors, so comparing with data before the first cases (Nov-Jan) may be tricky.
- Also the The measurements are from SLAC which shutdown shut down on March 17th, 2020, so the traffic on its links may have dramatically decreased after that.
- The links from SLAC use the well-provisioned ESnet network and beyond that academic networks such as Internet2 in the US, GEANT in Europe, APAN in Asia so the measurements from SLAC may not be fully representative.
- Utilization across networks and services has changed dramatically in terms of volumes, number of connections, utilization of links, interfaces, service endpoints. Most services are scaling up to handle the load. There are also many outages due to misconfiguration as people are trying to configure with configurations in production.
- The links from SLAC use the well-provisioned ESnet network and beyond that academic networks such as Internet2 in the US, GEANT in Europe, APAN in Asia, thus the measurements from SLAC may not be fully representative. Many of the targets are academic establishments that may have been closed, thus the target itself may be lightly loaded and so respond more quickly than in the past.
- Africa might be interesting since its networks tend to be less over-provisioned
- than those elsewhere. Also, see https://www.npr.org/sections/coronavirus-live-updates/2020/04/17/836896562/u-n-agency-fears-vulnerable-africa-may-suffer-at-
- Many of the targets are academic establishments that may have been closed, thus the target itself may be lightly loaded and so respond more quickly than in the past.
Milestones and Statistics
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- Number of days to double cases
- Basic reproduction number R0 the average number of secondary infections produced by an infectious case where everyone is susceptible.
- For R >1 each individual infected by a transmissible disease is expected to infect a number of individuals that increase exponentially. For R< each case transmit the disease to less than one individual and the disease dies out.
- Control reproductive number RC, the value of R in the presence of control measures.
- Incubation period
- Risk of importation
- Prpections Proections on: all beds needed, ICU beds needed, invasive ventilators needed.
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One attempt to explore and correlate the impact of the Covid-19 virus on Internet responsiveness responsiveness is to use a Motion Charts tool from https://www.charte.ca/ to look for correlations between say Covid-19 cases (cases, hospital admissions, deaths etc.) and PingER metrics as a function of time, by country, continent, plus population or density of population. The idea is that as Covid-19 cases pass say 100, the country will impose interventions such as school closing, social distancing etc. which will change the usage patterns of the Internet which may have noticeable impacts on the PingER measurements. We use the PingER 'Last120days' data measured from SLAC as provided and updated daily in https://www-iepm.slac.stanford.edu/pinger/prmout/. The data is available by metric, country Monitoring Agent (in this case pinger.slac.stanford.edu)' as Excel csv files, e.g. ipdv-EDU.SLAC.STANFORD.PINGER-country-last120days.csv. By means of a script covid.pl we create Excel csv files available at https://www-iepm.slac.stanford.edu/pinger/covid/ by PingER Metric and Covid-19 Confirmation cases or deaths, e.g. ipdv-confirmed.txt for the last 120 days. These covid/ files are suitable for copying into www.charte.ca to create motion charts for a selected Pinger metric's data vs Covid-19 cases by country by day. N.b. both the PingER 'last120days' data and the tables of the Covid-19 versus the PingER metric are availble publicly via the web, so you can make your own motion charts .(see
See Using Chart.ca for how to make your own motion charts, and an example. Note since the Covid-19 data for the USA and Austrailia are only available by state and for China are only available by province we currently have not included those countries. Some examples are below
| PingER Metric | Covid-19 Confirmed (All) | Covid-19 Deaths(All) | Covid-19 Confirmed (Europe) | Covid-19 Confirmed (Africa) | |
|---|---|---|---|---|---|
| ipdv or jitter (msec) | Here | Here | Here | https://charteca.blob.core.windows.net/pubs/3Z3qcBXqCT9B3WHz | Here |
| Throughput (kbps) | Here | ||||
Examining using PingER metrics from pingtable.pl
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