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"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

"The Republic. of 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.

...

Traceroute from SLAC to www.museumsnc.co.za from SLACsSLAC
Wed May  6 12:29:15 2020: executing exec(traceroute -m 30 -q 1 -w 1 -A 154.0.166.162 140)=traceroute 
from 134.79.197.214(www.slac.stanford.edu) to 154.0.166.162(www.museumsnc.co.za) for 134.79.138.4 traceroute to 154.0.166.162 (154.0.166.162), 30 hops max, 140 byte packets 1 rtr-serv01-02-serv01-dmz-webserv.slac.stanford.edu (134.79.197.131) [AS3671] 0.644 ms 2 rtr-core1-p2p-serv01-01.slac.stanford.edu (134.79.253.249) [AS3671] 0.568 ms 3 rtr-fwcore2-trust-p2p-core2.slac.stanford.edu (134.79.254.146) [AS3671] 1.114 ms 4 rtr-core1-p2p-fwcore1-untrust.slac.stanford.edu (134.79.254.137) [AS3671] 1.346 ms 5 rtr-border1-7k-p2p-core2.slac.stanford.edu (134.79.252.177) [AS3671] 1.523 ms 6 rtr-border2-7k-p2p-border1-7k.slac.stanford.edu (192.68.191.214) [AS3671] 1.690 ms 7 sunn-cr5-ip-p2p-border2-7k.slac.stanford.edu (192.68.191.233) [AS3671] 1.961 ms 8 sacrcr5-ip-b-sunncr5.es.net (134.55.40.145) [AS293] 4.510 ms #AS = Equinix 9 pnwgcr5-ip-a-sacrcr5.es.net (134.55.43.21) [AS293] 18.646 ms 10 ge3-0.cr02.sea01.pccwbtn.net (206.81.80.13) [*] 18.886 ms 11 HundredGE0-3-0-0.br02.frf06.pccwbtn.net (63.218.232.33) [AS3491] 162.286 ms #AS=PCCW Global, Inc. 12 telkom.te0-1-0-15.br02.frf06.pccwbtn.net (63.218.233.102) [AS3491] 157.321 ms 13 * 14 * 15 169-1-21-100.ip.afrihost.co.za (169.1.21.100) [AS37611] 338.447 ms #AS=Afrihost (PTY) Ltd
16  gm-colo3-core2-lq.aserv.co.za (169.1.21.187) [AS37611]  317.722 ms

Countries bordering South  Africa

A possibility explored was just selecting hosts in the 6 countries bordering and including South Africa (TLDs BW, LS, SZ, ZA, ZW) and then just using hosts with TLDs .co, .com, .go, .gov or including banc or bank in the name. The ideas was that such hosts are probably on commodity networks. However as of May 5th, 2020 these countries have few Covid-19 cases (BW:23, LS: 0, NA 101, SZ (Eswatine): 145, ZA: 218,329, ZW:34). As expected we could not identify a significant impact of Covid-19 on IPDV.

Useful other documents

Coronavirus-free Lesotho relaxes lockdown restrictions, 5/6/2020

Covid-19 9n Africa, from The Center For Disease Dynamics, Economics & Policy