COVID-19 Seasonality: The effect of environmental variation on the spatio-temporal dynamics at national, regional and global scales
- Funded by The Research Council of Norway (RCN)
- Total publications:0 publications
Grant number: unknown
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Key facts
Disease
COVID-19Start & end year
20202022Known Financial Commitments (USD)
$550,000Funder
The Research Council of Norway (RCN)Principal Investigator
Nils Christian StensethResearch Location
Norway, China…Lead Research Institution
UNIVERSITETET I OSLOResearch Priority Alignment
N/A
Research Category
Animal and environmental research and research on diseases vectorsResearch Subcategory
Animal source and routes of transmissionSpecial Interest Tags
N/AStudy Type
ClinicalClinical Trial Details
Not applicableBroad Policy Alignment
PendingAge Group
UnspecifiedVulnerable Population
UnspecifiedOccupations of Interest
Unspecified
Abstract
COVID-19 Seasonality is a Norwegian based project with strong collaborations with leading research and response organisations in China, Iran, UK, USA, and the African Union to develop fundamental information and inform the response to the ongoing COVID-19 pandemic. The objectives are organized into three Work Packages (WP) to (I) Extract the functional response of SARS-CoV-2 to environmental factors (including weather/seasonal variation) from variations in the growth rate of the COVID-19 pandemic; to (II) Predict the near term and long term seasonality and age-specific burden of infection of COVID-19 in Norway and other countries; and to (III) Prepare Norway (and other countries) for future pandemics by assessing the potential speed and intensity with which new emerging infectious diseases (EIDs) will arrive from geographic high-risk regions. Early in the project, we will produce quantitative models to forecast the seasonal conditions in Norway and other countries that favour and hinder the transmission of SARS-CoV-2, improving predictions of epidemic trends. We will continue to improve and iterate on these models throughout the project. In addition to the quantitative models, we will produce three high-quality novel datasets: (1) a dataset of the timing and spatial extent of various control measures, testing regimes and hospital patient overflows, (2) a dataset of global hotspots of human-wildlife interactions sourced from grey and published literature, and (3) a spatial database with a probabilistic assessment of the speed and intensity with which future viral spillovers are expected to arrive. We will through COVID-19 Seasonality carry out basic research and apply the obtained insights to one of the biggest challenges of our time. We expect that improved understanding of the spatio-temporal dynamics of COVID-19 pandemic will contribute profoundly to improve the preparedness against future diseases in Norway as well as globally.