Estimation of fatality rate in Africa through the behavior of COVID-19 in Italy relevance to age profiles

Abstract

The emergence and pandemic of COVID-19 has rapidly become a global concern. In Italy, on 27 March 2020, there were 8165 deaths and 80539 confirmed cases of COVID-19. Demographic situations, like age profiles is reported to be the cause of high case fatality rate (CFR) in Italy. In Africa, the COVID-19 pandemic has not yet grasped epic proportion, but the estimation of CFR is still needed. We compared the CFR observed in Italy with the age profiles in 46 Africa countries and 2 territories which are already confirmed COVID-19 case. The estimation of the CFR in Africa ranges between (1.0%-5.4%) while in Italy is 10.1%. The five highest CFR countries and territories in Africa are Reunion (5.4%), Mauritius (5.1 %), Tunisia (3.9%), Seychelles (3.8%) and Morocco (3.3%). The last three countries with low CFR are Uganda (1.0%), Zambia (1.1%) and Angola (1.1%). The observed difference is related to the age profiles.

Genomic diversity analysis of SARS-CoV-2 genomes in Rwanda

“…In total, we downloaded 75 genomes sequences of SARS-CoV-2 from the global initiative on sharing all influenza data (GISAID) (https://www.gisaid.org/) database, such as 10 genomes isolated in Rwanda, 3 parameters (17). All targeted genomes of SARS-CoV-2 samples were aligned to the reference strains using the Maximum Parsimony method by the Subtree-Pruning-Regrafting algorithm (18).…”

“…Coronavirus-2) a divergent RNA (ribonucleic acid) virus for the present devasting the world, with over 60 million cases and more than 1.4 million deaths until November 25, 2020 (1). The SARS-CoV-2 genome replication and how COVID-19 disease spread rapidly in the early phase across the globe contributed to the genetic diversity inside the genome sequence of SARS-CoV-2 including clades (2,3). Scientists isolated the virus and named SARS-CoV-2, they found a high nucleotide sequence homology with Betacorona viruses isolated from bats such as bat-SL-CoVZXC21 and bat-SL-CoVZXC21 (88%) and Malayan pangolins Pangolin-CoV (85.5% to 92.4%) (4) .…”