Understanding Public Health Trends Through Data Visualization

About the Data

Data plays a pivotal role in uncovering patterns, enabling informed decision-making, and improving public health outcomes. Leveraging a robust dataset, I created interactive Tableau dashboards to analyze critical metrics such as disease rates, gender-based disparities, fiscal year trends, and population insights across various provinces. Here's a walkthrough of my analysis, methodology, and key findings.

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Data Dictionary

Geography- The location to which the data pertains Example – Canada (Only country names)

Sex- Gender of the individual, Males, Females, Both

Age group- the age range Example 40+ ? (numeric ranges)

Fiscal Year- the year of data collection Example 2000-2001 (Format YYYY-YYYY)

Rate (Per 100,000)- Incidence rate per 100,000 people Example - 8,15,701 (Positive Decimal values)

Dashboard Analysis

1. Bar Chart: Regional Disease Rates

Visualization: A bar chart showing disease rates across provinces.

• Highest: Nunavut, with a rate of 53,263 per 100,000.
• Lowest: Newfoundland and Labrador, with a rate of 23,872 per 100,000.

Interpretation: The disparity in disease rates highlights the unique public health challenges faced by different provinces. Factors like healthcare access, environmental conditions, and population density

2. Pie Chart: Gender-Based Analysis

Visualization: A pie chart comparing disease rates by gender.

• Male: 219,850 per 100,000.
• Female: 163,570 per 100,000.
• Both: 189,042 per 100,000.

Interpretation: Males exhibit significantly higher disease rates compared to females, suggesting potential behavioral, occupational, or biological risk factors that warrant targeted interventions.

3. Line Graph: Trends Over Fiscal Years

Visualization: A line graph showing disease rates over time.

• Peak Year: 2010-2011, with a rate of 27,353 per 100,000.
• Lowest Year: 2022-2023, with a rate of 19,911 per 100,000.

Interpretation: The downward trend reflects improved public health measures, advancements in medical interventions, and increased awareness over time. Continued efforts are essential to sustain this positive momentum.

?4. Bar Chart: Population and Statistical Indicators

Visualization: A bar chart comparing provincial populations with statistical measures.

• Highest Population: Canada, at 79,699,905.
• Lowest Population: Newfoundland and Labrador, at 775,580.

Interpretation: Population size correlates with resource allocation and healthcare infrastructure needs. Smaller provinces like Newfoundland and Labrador may face unique challenges requiring tailored public health strategies.

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Data Interpretation

1)? Regional disparities in disease rates necessitate location-specific public health policies.

2)? Gender-based differences highlight the importance of customized interventions for males and females.

3)? A consistent decline in disease rates over fiscal years showcases the effectiveness of healthcare advancements.

4)? Population-based analysis aids in better resource allocation for improved healthcare delivery.

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Conclusion

The data reveals significant public health insights across various provinces. Nunavut's notably high disease rate (53,263 per 100,000) and Newfoundland and Labrador's low rate (23,872 per 100,000) highlight regional disparities that may stem from healthcare access, environmental factors, or socio-economic conditions. Gender-based analysis shows males have a higher disease rate (219,850 per 100,000) compared to females (163,570 per 100,000), emphasizing the importance of gender-specific health strategies. Over time, a steady decline in disease rates, from a peak in 2010-2011 (27,353 per 100,000) to the lowest in 2022-2023 (19,911 per 100,000), suggests effective public health measures and interventions. The population analysis underscores how larger provinces like Canada face greater healthcare demands, while smaller provinces face challenges in resource allocation.

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Tableau Public Dashboard Link:

https://public.tableau.com/app/profile/sayali.daphale/viz/TableauBVA/Dashboard1?publish=yes

?I’m immensely grateful to Harish Rijhwani Sir for the guidance and support he has provided me. His expertise and commitment have played a crucial role in helping me learn and master various tools with deep understanding and clarity. The insights I've gained under his mentorship have significantly enriched my learning. You’ve been a great mentor, and I’m thankful for everything!