Reimagining Predictive Analytics for Pandemics and Rare Disease
What is proposed is a way to avoid Infodemics by means of informing the public the basic of medical statistics. This can assist people in differentiating misleading medical information from much more accurate medical data.
Along with this is the explanation of rare disease statistics for minority communities.
Winston Grace
- Respond (Decrease transmission & spread), such as: Optimal preventive interventions & uptake maximization, Cutting through “infodemic” & enabling better response, Data-driven learnings for increased efficacy of interventions
The public can become confused by what is accurate versus what is inaccurate information. Another issue is how to inform communities that may feel left out of the mainstream.
Awareness of the rare infectious diseases and increasing the ability to identify outbreaks early on is a method of teaching medical statistics to these communities. If data from small communities is important, this implies minority communities are also important.
In terms of rare disease and data analytics, anomalies in terms of patterns on charts can be rare diseases. With finding a pattern, the standard procedure is to eliminate anomalies in order to establish a predictive pattern. The reason this solution is called "reimagine predictive analytics" is because the anomalies can be teaching tools for cases of rare diseases. Presenting the essential dichotomy of the following can aid in the learning process of predictive analytics:
1. Removing anomalies aids the predictive nature of the remaining data.
2. Analyzing anomalies may help to determine rare diseases in the community.
The reasoning is that uniform, in the "pipeline", procedures for data processing can lose the student in terms of attention to detail. Showing the possible importance of #2 presents rare disease as a topic.
Communities vulnerable to Infodemics as well as minority communities.
The presentation incorporates how to predict the possibility of outbreaks.
This is approached by means of predictive analytics education.
They are being engaged by means of the online education course. As they learn the material, their learning is the development of the solution.
- Pilot: A project, initiative, venture, or organisation deploying its research, product, service, or business/policy model in at least one context or community
- Artificial Intelligence / Machine Learning
- Behavioral Technology
- Big Data
-Awareness of the medical statistics as well as that of predictive analysis
-Awareness of the predictive analytics in terms of rare disease. This in turn can protect communities in the even a rare disease developments into an epidemic.
With the above, this can increase the ability for the public to understand the medical literature in terms of medical statistics as well as data analytics. This can empower the public to differentiate accurate versus inaccurate information on epidemic and pandemic research. This can help communities avoid Infodemics.
I impact should especially benefit the medical community as well as the public in general.
By means of the online course, the project will be scaled to grow over the next year to 3 years.
Success against the impact goals is measured by the success of the students in the course.
- United States
- Costa Rica
The main barrier would be finding educators for the creation of new content, as well as funding for significant increases in enrollment.
- Individual
I am not presently affiliated nor working with any organizations at this moment.
I am applying because, with the proper resources, the public can become more prepared for the possible infodemic of an epidemic or pandemic by means of an online course that allows learning how to differentiate information based upon medical statistics and predictive analytics in an easy to understand presentation.
I would like to partner with the World Health Organization (WHO) because this could assist their mission as well provide this educational material on a global scale.