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Covid-19 severity statistics slide
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Coronavirus Protection Actions Graphics (PPT Template)
Covid-19 Severity Statistics
Slide Content
The slide presents information about the varying severity of Covid-19 cases. It states that most cases are mild, which means they present with flu-like symptoms and can recover at home without hospitalization. It breaks down the statistics as follows: '80.9% Mild Infections' describing cases with flu-like symptoms that can convalesce at home, '13.8% Severe' indicating cases involving pneumonia and shortness of breath that typically require more serious medical attention, and '4.7% Critical' referring to cases that suffer from respiratory failure, septic shock, or multi-organ failure, often necessitating intensive care.
Graphical Look
- The title is in a large, bold font, highlighted by a decorative underline that extends to the right.
- A ribbon banner below the title emphasizes that most cases of Covid-19 are mild.
- A circular diagram is the focal point, with a stylized icon of a person's face in the center.
- Colored segments extend from the circle, visualizing the proportion of mild, severe, and critical cases.
- Lines connect the circle to text boxes that label each segment with specific percentages and descriptions.
- The source of the information is cited at the bottom in a smaller font.
The overall look of the slide is modern, with a clean and structured design. The color palette is composed of teal, purple, and orange, which are used to distinguish between the different severity levels of Covid-19 cases.
Use Cases
- To explain the breakdown of Covid-19 cases by severity during a health seminar or public health briefing.
- Within a medical presentation, to educate patients or healthcare professionals about the likelihood of different outcomes after infection.
- During a business meeting to discuss pandemic preparedness and the impact of illness severity on workforce management.
- In an educational context for students studying public health, epidemiology, or related fields to visualize the distribution of disease severity.