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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.
The measurements are from SLAC which shut down on March 17th, 2020, so the traffic on its links may have dramatically decreased after that.
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.
- 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-least-300-000-covid-19-deaths
- Another possibility is South and Central America and the Carribean (AKA Latin America).
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.

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Social distancing encouraged
Case-based measures
School and college closures
Public events banned
Lockdown
Interventions removed

Also, see See COVID 19 Internet Usage timeline for how companies have reduced their Internet traffic. Also see Akami sees 30 per cent surge in Internet traffic.

Statistics:

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< R<1, each case transmit transmits 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
Proections Projections on: all beds needed, ICU beds needed, invasive ventilators needed.
20% daily growth = cases or deaths double in < 4 days

Monitoring

The PingER monitor at SLAC, Stanford University in California currently monitors about 100 hosts in China. Using the pingtable.pl web page we selected daily aggregated data from SLAC to China for the last 365 days and looked at various metrics derived from the RTTs. Since many of the targets are Universities that may have taken lockdown measures and sent many students and staff home, we decided to look at the overall impact on SLAC to China pings. To do this we scroll down the pingtable.pl page to summary tables as shown below.

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Using Motion Charts to look at PingER data by metric versus Covid cases

One attempt to explore and correlate the impact of the Covid-19 virus on Internet 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 raw daily	Covid-19 Confirmed (Selected)	Covid-19 Deaths (Selected)	Covid-19 Confirmed (Europe)	Covid-19 Confirmed (Africa)
ipdv or jitter (msec)	M otion	Motion	Motion	Motion
Throughput (kbps)
Average RTT (msec)				Motion
Unpredictability (%)

We repeated the above except:

To smooth out the PingER data we used a running average of the data over the last 7 days,
Also rather than displaying the bubble size as proportional to the population, we made the bubble size proportional to Population in thousands / country's area.