Genomic sequencing is essential to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments, vaccines, and guide public health responses. To investigate the global SARS-CoV-2 genomic surveillance, we used sequences shared via GISAID to estimate the impact of sequencing intensity and turnaround times on variant detection in 189 countries. In the first two years of the pandemic, 78% of high-income countries sequenced >0.5% of their COVID-19 cases, while 42% of low- and middle-income countries reached that mark. Around 25% of the genomes from high income countries were submitted within 21 days, a pattern observed in 5% of the genomes from low- and middle-income countries. We found that sequencing around 0.5% of the cases, with a turnaround time <21 days, could provide a benchmark for SARS-CoV-2 genomic surveillance. Socioeconomic inequalities undermine the global pandemic preparedness, and efforts must be made to support low- and middle-income countries improve their local sequencing capacity.

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.

PfEMP1 is a family of cytoadhesive surface antigens expressed on erythrocytes infected with Plasmodium falciparum, the parasite that causes the most severe form of malaria. These surface antigens play a role in immune evasion and are thought to contribute to the pathogenesis of the malaria parasite. Previous studies have suggested a role for a specific subset of PfEMP1 called “group A” in severe malaria. To explore the role of group A PfEMP1 in disease, we measured the expression of the var genes that encode them in parasites from clinical isolates collected from children suffering from malaria. We also looked at the ability of these clinical isolates to induce rosetting of erythrocytes, which indicates a cytoadhesion phenotype that is thought to be important in pathogenesis. These two sets of data were correlated with the presence of two life-threatening manifestations of severe malaria in the children: impaired consciousness and respiratory distress. Using regression analysis, we show that marked rosetting was associated with respiratory distress, whereas elevated expression of group A–like var genes without elevated rosetting was associated with impaired consciousness. The results suggest that manifestations of malarial disease may reflect the distribution of cytoadhesion phenotypes expressed by the infecting parasite population.

The COVID-19 pandemic has revealed the importance of virus genome sequencing to guide public health interventions to control virus transmission and understand SARS-CoV-2 evolution. As of July 20th, 2021, >2 million SARS-CoV-2 genomes have been submitted to GISAID, 94% from high income and 6% from low and middle income countries. Here, we analyse the spatial and temporal heterogeneity in SARS-CoV-2 global genomic surveillance efforts. We report a comprehensive analysis of virus lineage diversity and genomic surveillance strategies adopted globally, and investigate their impact on the detection of known SARS-CoV-2 virus lineages and variants of concern. Our study provides a perspective on the global disparities surrounding SARS-CoV-2 genomic surveillance, their causes and consequences, and possible solutions to maximize the impact of pathogen genome sequencing for efforts on public health. One-Sentence Summary The causes, consequences and possible solutions for disparities in genomic surveillance observed in the COVID-19 pandemic.

Genomic surveillance of SARS-CoV-2 is important for understanding both the evolution and the patterns of local and global transmission. Here, we generated 311 SARS-CoV-2 genomes from samples collected in coastal Kenya between 17^th March and 31^st July 2020. We estimated multiple independent SARS-CoV-2 introductions into the region were primarily of European origin, although introductions could have come through neighbouring countries. Lineage B.1 accounted for 74% of sequenced cases. Lineages A, B and B.4 were detected in screened individuals at the Kenya-Tanzania border or returning travellers. Though multiple lineages were introduced into coastal Kenya following the initial confirmed case, none showed extensive local expansion other than lineage B.1. International points of entry were important conduits of SARS-CoV-2 importations into coastal Kenya and early public health responses prevented established transmission of some lineages. Undetected introductions through points of entry including imports from elsewhere in the country gave rise to the local epidemic at the Kenyan coast.

Detailed information on the source, spread and evolution of respiratory syncytial virus (RSV) during seasonal community outbreaks remains sparse. Molecular analyses of attachment (G) gene sequences from hospitalized cases suggest that multiple genotypes and variants co-circulate during epidemics and that RSV persistence over successive seasons is characterized by replacement and multiple new introductions of variants. No studies have defined the patterns of introduction, spread and evolution of RSV at the local community and household level. We present a whole genome sequence analysis of 131 RSV group A viruses collected during 6-month household-based RSV infection surveillance in Coastal Kenya, 2010 within an area of 12 km². RSV infections were identified by regular symptom-independent screening of all household members twice weekly. Phylogenetic analysis revealed that the RSV A viruses in nine households were closely related to genotype GA2 and fell within a single branch of the global phylogeny. Genomic analysis allowed the detection of household-specific variation in seven households. For comparison, using only G gene analysis, household-specific variation was found only in one of the nine households. Nucleotide changes were observed both intra-host (viruses identified from same individual in follow-up sampling) and inter-host (viruses identified from different household members) and these coupled with sampling dates enabled a partial reconstruction of the within household transmission chains. The genomic evolutionary rate for the household dataset was estimated as 2.307 × 10 ^{− 3} (95% highest posterior density: 0.935–4.165× 10 ^{− 3}) substitutions/site/year. We conclude that (i) at the household level, most RSV infections arise from the introduction of a single virus variant followed by accumulation of household specific variation and (ii) analysis of complete virus genomes is crucial to better understand viral transmission in the community. A key question arising is whether prevention of RSV introduction or spread within the household by vaccinating key transmitting household members would lead to a reduced onward community-wide transmission.