Predictive Modeling for COVID-19

Insights and Recommendations for Public Health

Introduction

Problems

Public health organizations have faced immense challenges in predicting the spread of COVID-19

Health Guard Analytics aims to use predictive modeling for decision-making in public health.

Objectives

Build predictive models to forecast trends.

Analyze factors influencing transmission.

Provide actionable insights for policy and resource allocation.

Data Collection and Sources

Dataset

COVID-19 Dataset (CORD-19) from Kaggle

Data Preprocessing

• Addressed missing values

• standardized date formats

• normalized numerical features

• encoded categorical features.

Feature Engineering

Created additional variables:

• daily growth rates

• mortality ratios

• cases per population.

Global Metrics

5,679,750

Confirmed Cases

253,474

Deaths

3,732,368

Recovered Cases

1,693,908

Active Cases

Global Trend

• Rapid increases in confirmed and recovered cases.

• Mortality ratio and daily growth rate fluctuate but show a steady rise

Continent Metrics

Continent

Cases Per Million

Mortality Ratio (%)

Daily Growth Rate (%)

Africa

869.4736

0.0013

1.9551

Asia

4898.3340

0.0044

1.1862

Oceanic

86.1566

0.0001

12.0188

Europe

2788.6630

0.0148

-5.9808

North America

1263.9043

0.0034

-14.6743

South America

4907.7841

0.0173

2.9007

Asia and South America: High cases per million.

Africa: Low cases per million but large total cases.

Australia/Oceania: Lowest cases per million, effective containment.

Europe and South America: Higher mortality rates and fluctuations in daily growth

Continental Trend

Most affected continent: Europe | Least affected continent: Oceania

Top 15 countries with the highest confirmed cases

Spread across continents, showing the global nature of the pandemic.

Factors Influencing Covid-19 Impact:.

Population Density

Healthcare System

Government Response Measures

Predicted COVID-19 Cases by Continent for the Next 60 Days

Continent

Predicted Cases

Key Countries Affected

Asia

Over 120 million

Saudi Arabia, Iran, Turkey, Iraq, Kazakhstan

Europe

Approximately 110 million

Spain (17.5 million), Italy, France, Germany, Sweden

South America

About 108 million

Peru (3.5 million), Chile, Columbia, Argentina

Africa

60 million

South Africa (highest increase)

North America

30 million

Canada (highest count)

Australia/Oceania

1.4 million

Australia (dominant cases)

Top 10 Predicted Countries with High COVID-19 Counts

South Africa (Africa), Peru (South America), Chile(South America), Colombia(South America), Saudi Arabia (Asia), Iran(Asia), Argentina (South America), Spain (Europe), Turkey(Asia) and Italy(Europe)

Recommendations and Insights

Global Level

• Continuously monitor the spread of the virus and identify new variants.

• Encourage vaccination to protect everyone.

• Work together with other countries to share information and resources.

Continental Level

• Focus on high-risk countries to control the spread.

• Strengthen healthcare systems in vulnerable areas.

Country-Level

• Strengthen contact tracing and isolation measures.

• Invest in healthcare infrastructure.

Conclusion

Predictive modeling offers invaluable insights into COVID-19 trends, improving decision-making and optimizing resource allocation. Continued research and collaboration are important to reduce the spread of virus.