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Outbreak curves are one of the most recognizable tools in epidemiology. They appear to show whether an epidemic is rising, peaking, or falling in real time. But what if the curve is reflecting reporting behavior as much as disease transmission?
In this episode, we break down why outbreak curves often mislead, how reporting delays and revisions distort the shape people think they are seeing, and why epidemiologic interpretation has to go deeper than the visual alone.
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If you found the content helpful, consider leaving a rating or review—it helps support the podcast.
For business and sponsorship inquiries, email us at:
📧 [email protected]
Youtube: https://www.youtube.com/@BJANALYTICS
Instagram: https://www.instagram.com/bjanalyticsconsulting/
Twitter/X: https://x.com/BJANALYTICS
Threads: https://www.threads.com/@bjanalyticsconsulting
By BJANALYTICSOutbreak curves are one of the most recognizable tools in epidemiology. They appear to show whether an epidemic is rising, peaking, or falling in real time. But what if the curve is reflecting reporting behavior as much as disease transmission?
In this episode, we break down why outbreak curves often mislead, how reporting delays and revisions distort the shape people think they are seeing, and why epidemiologic interpretation has to go deeper than the visual alone.
👉 Enjoyed the episode? Follow the show to get new episodes automatically.
If you found the content helpful, consider leaving a rating or review—it helps support the podcast.
For business and sponsorship inquiries, email us at:
📧 [email protected]
Youtube: https://www.youtube.com/@BJANALYTICS
Instagram: https://www.instagram.com/bjanalyticsconsulting/
Twitter/X: https://x.com/BJANALYTICS
Threads: https://www.threads.com/@bjanalyticsconsulting