Unlock the Black Box within Population Health Domain for Smarter Decision Making

Often in various disease domains a black box occurs once referring to overall population health and disease risks. Most of the data used for assessing necessary prevention measures come from hospitals and other clinical institutions with acute cases distorting the overall picture. Thus, the decisions made and research conducted on assumptions drawn from this data continue to complement the incomplete picture we have about the situation in both specific disease domains and overall population health.

Driving population towards assessment of their own health risks plainly for the greater good has not only proved to be rather ineffective, but it also leaves hanging an important factor that is at the core of any research initiative – promotion of healthier society. With the help of Longenesis.Engage the population engagement in health assessment initiatives can be brought to the next level. The tool is designed to be user-friendly for everyone involved and among many other important features, it also includes the possibility to deliver educational recommendations tied to each individual's preconditions – answers, symptoms, etc. Thus, while on an individual level participants gain useful insights about their health along with recommendations for disease prevention, the results can also be used for greater good such as participant pre-screening programs, epidemiological studies on public health, public policy planning, etc.

Case study of COVID-19 meta-data curation and real-time identification

Partners: Under National Research Programme in Nordics Longenesis in collaboration with the Latvian Biomedical Research and Study Centre (BMC), University of Latvia, Riga Stradins University and Riga Technical University launched an initiative aimed towards COVID-19 research acceleration and enabling of the Federated Learning pipeline.

Goals: The main goal of the project was to involve Latvian population in a research initiative that could provide an ability to provide real-time, borderless biomedical data and patient identification for COVID-19 research with an ability to provide collected results or access to specific subsets of data without compromising data security and participant privacy.

Use case: A dataset of 700+ participants has been collected under two subsequent surveys targeted at the population at large. Both surveys were deployed on a landing page specifically designed for the initiative collecting data about participants' overall health while assessing their potential risk to be among severe COVID-19 cases. The other survey tried to determine their readiness to get vaccinated. Results of this study are published in MDPI Vaccines Journal: https://www.mdpi.com/2076-393X/9/12/1384

Other use case scenarios: The data collected could have been studied for decision making purposes, such as communication planning for state-wide vaccination or the necessary state-wide restriction planning, taking into account the number of potential high risk cases and participant attitudes. The platform also performed the function of a supplementary and trust-worthy communication channel to educate the population about the necessary preventive measures and risks associated with COVID-19 pandemics.
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