The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

Detailed description of Senegalia massiliensis strain SIT17(T), a bacterium isolated from the human gut

Strain SIT17(T) was isolated from the stool of a healthy 13-month-old Senegalese boy. It is a Gram-positive, anaerobic, rod-shaped, non-spore-forming and mobile bacterium. It exhibited 92.74% 16S rRNA gene sequence similarity with the Brassicibacter thermophilus strain Cel2f, the phylogenetically most closely related species. Its genome is about 2.87 Mb long with 27.39 mol% G + C content. We provide more details of Senegalia massiliensis strain SIT17(T) (= CSURP2130 = DSM 103071), the creation of which was previously announced

Taxonogenomics description of Bacillus dakarensis sp. nov., Bacillus sinesaloumensis sp. nov. and Bacillus massiliogabonensis sp. nov., three new species isolated from human stools

Using microbial culturomics, three Bacillus strains were isolated, identified and characterized following the taxonogenomics strategy. Bacillus dakarensis strain Marseille-P3515(T) (=CSURP3515), Bacillus sinesaloumensis strain Marseille-P3516(T) (=CSURP3516), and Bacillus massiliogabonensis strain Marseille-P2639(T) (=CSURP2639) were isolated from human stool samples. The phylogenetic analysis, phenotypic characteristics and genotypic data presented here prove that these three bacteria are different from previously known bacterial species with standing in nomenclature and represent new Bacillus species

Vaginisenegalia massiliensis gen. nov., sp. nov., a new bacterium isolated from the vagina flora and its taxono-genomic description

Strain Marseille-P5643(T) was isolated from a vaginal sample of a healthy Senegalese woman. It is an anaerobic Gram-negative, rod-shaped bacterium. Strain Marseille-P5643(T) exhibits 93.7% similarity levels with the Facklamia hominis strain ATCC 700628(T), the phylogenetically closest related species with standing in nomenclature. The draft genome size of strain Marseille-P5643(T) is 1.79 Mb with 39.0 mol% of G+C content. We propose here the creation of Vaginisenegalia massiliensis gen. nov., sp. nov., as a new bacterial genus from the phylum Firmicutes

MALDI-TOF Mass Spectrometry: A Powerful Tool for Clinical Microbiology at Hopital Principal de Dakar, Senegal (West Africa)

Our team in Europe has developed the routine clinical laboratory identification of microorganisms by matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). To evaluate the utility of MALDI-TOF MS in tropical Africa in collaboration with local teams, we installed an apparatus in the Hopital Principal de Dakar (Senegal), performed routine identification of isolates, and confirmed or completed their identification in France. In the case of discordance or a lack of identification, molecular biology was performed. Overall, 153/191(80.1%) and 174/191(91.1%) isolates yielded an accurate and concordant identification for the species and genus, respectively, with the 2 different MALDI-TOF MSs in Dakar and Marseille. The 10 most common bacteria, representing 94.2% of all bacteria routinely identified in the laboratory in Dakar (Escherichia coli, Klebsiella pneumoniae, Streptococcus agalactiae, Acinetobacter baumannii, Pseudomonas aeruginosa, Staphylococcus aureus, Staphylococcus haemolyticus, Enterobacter cloacae, Enterococcus faecalis, and Staphylococcus epidermidis) were accurately identified with the MALDI-TOF MS in Dakar. The most frequent misidentification in Dakar was at the species level for Achromobacter xylosoxidans, which was inaccurately identified as Achromobacter denitrificans, and the bacteria absent from the database, such as Exiguobacterium aurientacum or Kytococcus schroeteri, could not be identified. A few difficulties were observed with MALDI-TOF MS for Bacillus sp. or oral streptococci. 16S rRNA sequencing identified a novel bacterium, "Necropsobacter massiliensis." The robust identification of microorganisms by MALDI-TOF MS in Dakar and Marseille demonstrates that MALDI-TOF MS can be used as a first-line tool in clinical microbiology laboratories in tropical countries

Sixteen clinical isolates not identified in Dakar (Senegal).

<p>Sixteen clinical isolates not identified in Dakar (Senegal).</p

The ongoing revolution of MALDI-TOF mass spectrometry for microbiology reaches tropical Africa

Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) represents a revolution in routine pathogen identification in clinical microbiology laboratories. A MALDI-TOF MS was introduced to tropical Africa in the clinical microbiology laboratory of the Hopital Principal de Dakar (Senegal) and used for routine pathogen identification. Using MS, 2,429 bacteria and fungi isolated from patients were directly assayed, leading to the identification of 2,082 bacteria (85.7%) and 206 fungi (8.5%) at the species level, 109 bacteria (4.5%) at the genus level, and 16 bacteria (0.75%) at the family level. Sixteen isolates remained unidentified (0.75%). Escherichia coli was the most prevalent species (25.8%) followed by Klebsiella pneumoniae (14.8%), Streptococcus agalactiae (6.2%), Acinetobacter baumannii (6.1%), Pseudomonas aeruginosa (5.9%), and Staphylococcus aureus (5.9%). MALDI-TOF MS has also enabled the detection of rare bacteria and fungi. MALDI-TOF MS is a powerful tool for the identification of bacterial and fungal species involved in infectious diseases in tropical Africa