Predictive Models For Decision Support In The Covid 19 Crisis - Springerbriefs

The Covid-19 pandemic has presented a significant challenge to governments and organizations worldwide. The rapid spread of the virus and the uncertainties surrounding its impact have made decision-making extremely difficult. In such circumstances, predictive models have emerged as valuable tools for decision support. One of the most comprehensive resources on this topic is the book "Predictive Models For Decision Support In The Covid 19 Crisis", part of the SpringerBriefs series.

The Importance of Predictive Models

During the Covid-19 crisis, governments and organizations have had to make critical decisions regarding public health, social distancing measures, economic support, and resource allocation. Predictive models offer a way to simulate potential scenarios and estimate the impact of different actions. By utilizing these models, decision-makers can better understand the consequences of their choices and make informed decisions.

Predictive Models for Decision Support in the COVID-19 Crisis (SpringerBriefs in Applied Sciences and Technology)

by Turgon Annárë (1st ed. 2021 Edition, Kindle Edition)

4.2 out of 5

Language	:	English
File size	:	27169 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Word Wise	:	Enabled
Print length	:	147 pages

FREE

Predictive Models For Decision Support In The Covid 19 Crisis - A Comprehensive Guide

The book "Predictive Models For Decision Support In The Covid 19 Crisis" is an essential resource for anyone seeking to understand and utilize predictive models during this global pandemic. Written by experts in the field, this book provides a comprehensive overview of various predictive modeling techniques and their application in decision-making processes.

With over 3000 words of content, the book covers topics such as:

• to predictive modeling
• Data collection and analysis
• Model selection and evaluation
• Forecasting the spread of the virus
• Optimizing resource allocation
• Evaluating the impact of social distancing measures
• Economic impact analysis
• Risk assessment and mitigation

Each chapter presents practical examples and case studies, allowing readers to grasp the concepts and apply them to real-world scenarios. The book also provides insights into the challenges and limitations of predictive modeling tools, helping decision-makers navigate potential pitfalls and make more accurate predictions.

Long Descriptive Keyword for Alt Attribute: Predictive Models For Decision Support In The Covid 19 Crisis SpringerBriefs

Long Tail Clickbait Title: "Unveiling the Secrets of Predictive Models: Your Ultimate Weapon Against the Covid-19 Crisis"

Predictive models have proven to be invaluable tools in the fight against the Covid-19 pandemic. As decision-makers continue to navigate through challenges and uncertainties, understanding the concepts and applications of predictive modeling becomes increasingly crucial. With "Predictive Models For Decision Support In The Covid 19 Crisis", readers gain access to a comprehensive guide that empowers them to make informed decisions based on accurate predictions. This book is a must-have resource for researchers, policymakers, and professionals seeking effective decision support during these challenging times.

Predictive Models for Decision Support in the COVID-19 Crisis (SpringerBriefs in Applied Sciences and Technology)

by Turgon Annárë (1st ed. 2021 Edition, Kindle Edition)

4.2 out of 5

Language	:	English
File size	:	27169 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Word Wise	:	Enabled
Print length	:	147 pages

FREE

COVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations.

Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future.