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

Are patients with pulmonary tuberculosis who are identified through active case finding in the community different than those identified in healthcare facilities?

The lack of healthcare access contributes to large numbers of tuberculosis (TB) cases being missed and has led to renewed interest in outreach approaches to increase detection. It is however unclear whether outreach activities increase case detection or merely identify patients before they attend health facilities. We compared adults with cough of >2 weeks' duration recruited in health facilities (1202 participants) or in urban slums (2828 participants) in Nigeria. Participants provided demographic and clinical information and were screened using smear microscopy. The characteristics of smear-positive and smear-negative individuals were compared stratified by place of enrolment. Two hundred nine health facility participants (17.4%) and 485 community-based participants (16.9%) were smear positive for pulmonary TB. Community-based smear-positive cases were older (mean age, 36.3 vs. 31.8 years), had longer cough duration (10.3 vs. 6.8 weeks) and longer duration of weight loss (4.6 vs. 3.6 weeks) than facility-based cases; and they complained more of fever (87.4% vs. 74.6%), chest pain (89.0% vs. 67.0%) and anorexia (79.5% vs. 55.5%). Community smear-negative participants were older (mean, 39.4 vs. 34.0 years), were more likely to have symptoms and were more likely to have symptoms of longer duration than smear-negative facility-based participants. Patients with pulmonary TB identified in the community had more symptoms and longer duration of illness than facility-based patients, which appeared to be due to factors differentially affecting access to healthcare. Community-based activities targeted at urban slum populations may identify a different TB case population than that accessing stationary services

Patient characteristics.

<p>NA: Not available (for cultures this includes contamination).</p><p>a Excludes 1 withdrawn patient see Methods.</p><p>b Reported result for both RIF resistant cases.</p><p>c Number of samples positive by either or both Culture/GeneXpert.</p><p>d The patient with NA culture was Smear positive and was included in the Culture/GeneXpert positive group in the analyses.</p><p>Patient characteristics.</p

Serum IP-10 concentrations at day 0 and 7 of therapy.

<p>Each set of 2 connected points represent data from a single patient from Nigeria (blue) or Nepal (red). Panel A: IP-10 concentrations of HIV-positive, Smear (Sm) positive, and culture/Xpert (Cult) positive patients. The MDR-TB patient is shown with a dashed line. One smear-positive patient had missing culture (Open symbols). Panel B-D: IP-10 concentrations of HIV- Sm+ (B), HIV+ Sm- (C), and HIV- Sm- (D) culture/GeneXpert positive patients. E: Concentrations from Sm-Cult- patients, of which 4 had missing HIV result (open square symbols) and all others were HIV- (round symbols). IP-10 levels in culture/GeneXpert positives were significantly different between day 0 and day 7 (p<0.0001). For culture/GeneXpert negatives p>0.05 between day 0 and day 7.</p

Distribution of samples with serum IP-10 decreasing >300 pg/ml between day 0 and day 7.

<p>* the not responding patient was confirmed MDR.</p><p>Distribution of samples with serum IP-10 decreasing >300 pg/ml between day 0 and day 7.</p

Serum TNFα levels of TB patients at day 0 and day 7 of therapy.

<p>See legend <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129552#pone.0129552.g002" target="_blank">Fig 2</a> for details on the panels and labels. P<0.001 between day 0 and day 7; No significant differences between day 0 and day 7 for culture/GeneXpert negative patients.</p