ABSTRACT
Background. Effective vaccines deployable globally are needed to control the COVID-19 pandemic. INO-4800, a plasmid DNA vaccine encoding the ancestral SARS-CoV-2 spike (S) protein, has demonstrated safety and immunogenicity. We report the stability of multiple INO-4800 lots used in Phase 3 clinical trials. Methods. Lots of INO-4800 stored at the test temperatures (storage temperature [2-8degreeC] and accelerated temperature [25 +/- 2degreeC]) were sampled every 3 months. Sample stability at each timepoint was assessed in terms of 2 parameters: i) purity as measured by DNA isoform homogeneity by capillary gel electrophoresis (CGE) to quantify relative proportions of different plasmid topologies (supercoiled, open circular, and linear), and ii) potency as measured by a cell-based assay for flow cytometric detection of fluorescently labeled S protein. Results. At 2-8degreeC, all tested lots of INO-4800 retained structural homogeneity for >=12 months (Fig. 1A). Proportions of circular and supercoiled plasmid isoforms were >=96% and >=89%, respectively, remaining above minimum regulatory authority-approved specifications (>=85% for circular and >=80% for supercoiled isoforms). At 25 +/- 2degreeC, all tested lots retained structural homogeneity within specifications for >=6 months (Fig. 1B), with proportions of circular and supercoiled plasmid isoforms being >=96% and >=81%, respectively. Moreover, structural homogeneity of 1/ 2 (50%) lots was within specification at 9 months at 25 +/- 2degreeC. Potency of all tested lots was >=84% for >=6 months at both 2-8degreeC and 25 +/- 2degreeC, remaining above the regulatory authority-approved minimum of 77% (Figs. 1C and 1D). Moreover, 3/3 (100%) of tested lots were within potency specification at 12 months at 2-8degreeC and 2 lots and 1 lot, respectively, were within specification at 9 and 12 months at 25 +/- 2degreeC. Data from additional timepoints are accruing and will be presented. Conclusion. INO-4800 is stable across temperatures ranging from 2degreeC to 25 +/- 2degree C and does not require ultra-cold storage. This demonstrated stability confers upon INO-4800 the potential to be deployed globally even in resource-constrained settings lacking cold chain infrastructure, thereby contributing to pandemic preparedness and control. (Figure Presented).
ABSTRACT
The temporary decrease of fine particulate matter (PM2.5) concentrations in many parts of the world due to the COVID-19 lockdown spurred discussions on urban air pollution and health. However there has been little focus on sub-Saharan Africa, as few African cities have air quality monitors and if they do, these data are often not publicly available. Spatial differentials of changes in PM2.5 concentrations as a result of COVID also remain largely unstudied. To address this gap, we use a serendipitous mobile air quality monitoring deployment of eight Sensirion SPS 30 sensors on motorbikes in the city of Nairobi starting on 16 March 2020, before a COVID-19 curfew was imposed on 25 March and continuing until 5 May 2020. We developed a random-forest model to estimate PM2.5 surfaces for the entire city of Nairobi before and during the COVID-19 curfew. The highest PM2.5 concentrations during both periods were observed in the poor neighborhoods of Kariobangi, Mathare, Umoja, and Dandora, located to the east of the city center. Changes in PM2.5 were heterogeneous over space. PM2.5 concentrations increased during the curfew in rapidly urbanizing, the lower-middle-class neighborhoods of Kahawa, Kasarani, and Ruaraka, likely because residents switched from LPG to biomass fuels due to loss of income. Our results indicate that COVID-19 and policies to address it may have exacerbated existing air pollution inequalities in the city of Nairobi. The quantitative results are preliminary, due to sampling limitations and measurement uncertainties, as the available data came exclusively from low-cost sensors. This research serves to highlight that spatial data that is essential for understanding structural inequalities reflected in uneven air pollution burdens and differential impacts of events like the COVID pandemic. With the help of carefully deployed low-cost sensors with improved spatial sampling and at least one reference-quality monitor for calibration, we can collect data that is critical for developing targeted interventions that address environmental injustice in the African context.