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.
BackgroundLimited specimen collection and testing for influenza occurred in the English and Dutch‐speaking Caribbean countries prior to the 2009/2010 influenza pandemic. Caribbean Epidemiology Centre (CAREC) member countries rapidly mobilized to collect specimens during the pandemic and a vast majority of confirmed cases during the pandemic period were influenza A(H1N1)pdm09.ObjectivesTo describe the aetiology and distribution of acute respiratory illness (ARI) among laboratory confirmed cases during the first year after the 2009/2010 influenza pandemic in the English‐ and Dutch‐speaking Caribbean.ResultsIn total, 774 specimens were tested and 394 (52.7%) cases had positive laboratory confirmation. Respiratory syncytial virus (RSV) (28.4%) and influenza A(H3N2) (23.1%) were most frequently detected. RSV activity peaked in July 2011 while influenza A(H3N2) peaked in October 2010. Influenza was responsible for illness in greater numbers in persons 15–64 years while RSV was seen in primarily in children <5 years and adults >65 years. Other agents confirmed include rhinovirus (12.9%), influenza B (10.9%) and influenza A(H1N1)pdm09 (9.4%).ConclusionsRSV and influenza A(H3N2) were the most common viruses identified during the first year after the influenza A(H1N1)pdm09 pandemic. Influenza was detected every month with peak activity corresponding to that typically seen in North America (October to March). In order to determine the seasonality of influenza and RSV, laboratory data from subsequent years and increased specimen submission is needed.
The COVID-19 pandemic highlighted the importance of global genomic surveillance to monitor the emergence and spread of SARS-CoV-2 variants and inform public health decision-making. Until December 2020 there was minimal capacity for viral genomic surveillance in most Caribbean countries. To overcome this constraint, the COVID-19: Infectious disease Molecular epidemiology for PAthogen Control & Tracking (COVID-19 IMPACT) project was implemented to establish rapid SARS-CoV-2 whole genome nanopore sequencing at The University of the West Indies (UWI) in Trinidad and Tobago (T&T) and provide needed SARS-CoV-2 sequencing services for T&T and other Caribbean Public Health Agency Member States (CMS). Using the Oxford Nanopore Technologies MinION sequencing platform and ARTIC network sequencing protocols and bioinformatics pipeline, a total of 3610 SARS-CoV-2 positive RNA samples, received from 17 CMS, were sequenced in-situ during the period December 5th 2020 to December 31st 2021. Ninety-one Pango lineages, including those of five variants of concern (VOC), were identified. Genetic analysis revealed at least 260 introductions to the CMS from other global regions. For each of the 17 CMS, the percentage of reported COVID-19 cases sequenced by the COVID-19 IMPACT laboratory ranged from 0·02% to 3·80% (median = 1·12%). Sequences submitted to GISAID by our study represented 73·3% of all SARS-CoV-2 sequences from the 17 CMS available on the database up to December 31st 2021. Increased staffing, process and infrastructural improvement over the course of the project helped reduce turnaround times for reporting to originating institutions and sequence uploads to GISAID. Insights from our genomic surveillance network in the Caribbean region directly influenced non-pharmaceutical countermeasures in the CMS countries. However, limited availability of associated surveillance and clinical data made it challenging to contextualise the observed SARS-CoV-2 diversity and evolution, highlighting the need for development of infrastructure for collecting and integrating genomic sequencing data and sample-associated metadata.
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