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IKTPLUSS-IKT og digital innovasjon

COVID-19 in Norway: A real-time analytical pipeline for preparedness, planning and response during the COVID-19 pandemic in Norway

Alternative title: COVID-19 i Norge

Awarded: NOK 5.0 mill.

The coronavirus pandemic is a threat to human health worldwide. It has already caused significant damage to many societies, and politicians need high-quality data on the spread of this infection to choose good measures. We use both mathematical models and collect data on symptoms from the population to provide a detailed picture of the epidemic in Norway. An important way to limit the spread is to reduce person-to-person contact. We collect data about people's movements in society using mobile phones. This, together with data on disease symptoms in the general population, enables us to estimate the infectivity of the coronavirus and provide good short-term forecasts on the spread and number of hospital admissions. The models give the politicians important information by showing how various measures, such as prioritizing vaccines and isolation, can reduce the spread of infection. We run long-term scenarios to provide insight into the possible development of the epidemic that is used in risk assessments. The methods we use are at the forefront of research regarding statistical science and will be important in strengthening preparedness against other infectious diseases in the years to come. We collect data in existing population surveys, such as the Norwegian Mother, Father and Child Survey (MoBa) and the Norwegian Influenza Study (NorFlu). We link the data to register information about COVID-19 incidence to understand why some people have a higher risk of infection and severe illness than others. These studies include essential information based on previous genetic and immunological analyzes. Such information, together with data on education, occupation and previous illness, provides an understanding of how SARS-CoV-2 will affect the population's health. We also analyze the entire Norwegian population based on the central personal register. To this register, we link information from the patient register, the primary health register, the reporting system for infectious diseases and the cause of death register to be able to describe and understand the consequences of the epidemic in Norway.

The rapidly expanding COVID-19 pandemic poses an imminent threat to the human population and the world economy. There is a need for novel data and high quality analyses of the evolving epidemic in order to guide policies. The overarching purpose of our project is to deliver real-time relevant output to guide policies on the actions to combat the ongoing Covid-19 epidemic in Norway. Our vehicle for these outputs is an advanced mathematical model that incorporates population movements from telephone surveillance as well as a series of epidemiological observations, including data from large cohorts and nation-wide registries. The model can simulate and assess the effects of actions that decrease person-to-person contact in the whole population, as well as in subgroups. Mathematical modelling will make projections of scenarios with different mitigation measures. We will combine dedicated analytical capacities with real time data harvesting, and we will interpret trends, the future course of the pandemic, and explore the possibilities for action to guide decision makers despite remaining uncertainty. We will use repeated data on symptoms from more than 200 000 participants in The Norwegian Influenza Cohort (NorFlu) and the Norwegian Mother, Father and Child Cohort Study (MoBa) with extensive information on previous diseases, exposures and life styles, and whole-genome genotyping. We will examine if underlying genetic predisposition to various diseases influence the susceptibility for COVID-19, or the progression of the disease. Using registry data on the whole Norwegian populations, we will include sociodemographic variables from Statistics Norway and data from health registries that include the newly odes for Covid-19 infection in primary and secondary health care. This will enable us to describe the burden of disease caused by this epidemic and analyse long-term consequences.

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IKTPLUSS-IKT og digital innovasjon