"Since mortality rates are generally higher in older people, it could be assumed that a younger African population distribution will lessen the death rate of COVID-19 on the continent. However, it is too early to predict the death rate as Africa is at the ascending phase of the epidemic curve. Furthermore, the high prevalence of HIV, tuberculosis, hypertension, and diabetes, coupled with weak health-care systems in Africa, might lead to high mortality rates among comorbid populations. Indeed, Egypt (3659 cases with 276 deaths; Casualty Fatality Rates (CFR) 7·5%) and Democratic Republic of the Congo (359 cases with 25 deaths; CFR 6·9%) have reported much higher CFRs than South Africa and Senegal."
Some of the interventions applicable in N. America, Europe and Asia may not be applicable in Africa. "First, the benefits of physical distancing could be substantially smaller in low-income countries due to the smaller proportions of older people and because, although physical distancing and lockdowns flatten the epidemic curve and reduce pressure on health systems, this effect is less apparent in countries with already overwhelmed and weak health-care systems. Second, the economic value in terms of lives saved by physical distancing policies is likely to be much higher in high-income countries than countries in which these policies have more detrimental effects on incomes. Although physical distancing slows the transmission of the virus, it exacts a heavy toll on the informal economic and casual labour sector. In search of income for the day-to-day livelihood of extended families, many Africans could be forced to ignore concerns about contracting COVID-19 and fend for their survival."
The above quotes are from Limiting the spread of COVID-19 in Africa: one size mitigation strategies do not fit all countries, the Lancet, April 28.
Limiting the spread of COVID-19 in Africa: one size mitigation strategies do not fit all countries
South Africa
"South Africa detected its first novel coronavirus infection on 5 March. For the next few weeks, the epidemic followed an exponential curve similar to those in the United Kingdom, the United States, and many other countries. On 15 March, the country’s president, Cyril Ramaphosa, declared a national state of emergency banning visitors from high-risk countries, stopping large gatherings, closing more than half of its land borders, and shutting schools. On 27 March the country started a 21-day lockdown, closing all borders and confining everyone except those performing essential services to their homes except to buy groceries and medicine or to collect welfare payments." Science Magazine.
PingER
We investigated various PingER metrics derived from the ping measurements made from SLAC, including average Round Trip Time (RTT), Conditional Loss Probability (CLP). Inter Packet Delay Variability IPDV), Inter Quartile Range (IQR) of the round trip times, and derived throughput (see Tutorial on Internet Monitoring and Pinger at SLAC). The most sensitive to this type of disruption appeared to be IPDV.
We used the PingER IPDV daily data for the last 365 days. It includes measurements from the SLAC host pinger.slac.stanford.edu in Northern California (Lat, Long =37.4177, -122.2035) to 7 hosts in South Africa.
| www.nmmu.ac.za, Port Elizabeth | bontany.uwc.ac.za, Cape Town | www.dut.ac.za, Durban | http://www.museumsnc.co.za./, Kimberley | www.ru.ac.za, Grahamstown | sagrid.ac.za,? | brunsvigia.tenet.ac.za, Cape Town |
Since there are large differences between weekday and weekend performance responses, we selected just the weekday (determined by UDT) measurements and smoothed the data using a sliding average over the last 5 days. The chart below shows the result (the 25 percentile, median and 75 percentiles for the 7 hosts) together with South Africa's Covid-19 confirmed cases from Johns Hopkins University's GitHub site: https://github.com/CSSEGISandData/COVID-19, plus the dates of notable interventions taken by South Africa.
It is seen that the 75 percentile shows a notable increase at the time of the interventions
We then looked in more detail at the IPDVs for the individual hosts. See below.
It is seen that the major contributor to the rise in IPDV is www.museumsnc.co.za, followed by www.dut.ac.za. The bontany.uwc.ac.za is no longer accessible. The other hosts are connected to the South African Tertiary Education Network (TENET). That, in turn, connects directly to ESnet that connects SLAC to the Internet thus avoiding any commodity networks. ESnet supports the Energy Sciences in the US and is well provisioned. TENET supports tertiary academic and research establishments in South Africa. It is a well provisioned network that is probably lightly loaded on average, thus changes in traffic volumes (e.g. due to lockdown) have little effect.
Both www.museumsnc.co.za and www.dut.ac.za traverse commodity networks after leaving ESnet and are thus less likely to be over-provisioned and more sensitive to unplanned or increases in traffic load. For example, a traceroute for www.museumsnc.co.za leaves the ESnet network at Sunnyvale near SLAC to join the Equinix network, followed by the PCCW Inc. network, followed by Afrihost in South Africa.
| Traceroute from SLAC to www.museumsnc.co.za from SLACs |
|---|
Wed May 6 12:29:15 2020: executing exec(traceroute -m 30 -q 1 -w 1 -A 154.0.166.162 140)=traceroute 16 gm-colo3-core2-lq.aserv.co.za (169.1.21.187) [AS37611] 317.722 ms |