What is it about?
Assessing how many people are infected with a new disease outbreak can be difficult, especially at the beginning of an epidemic or pandemic. This was a big problem during the COVID-19 pandemic's first year. We have developed a simple statistical method that uses data on confirmed cases to estimate the minimum number of infected people (including those with no symptoms), also referred to as the "Iceberg" of the disease. Our method helps policy makers better understand how widespread the disease is and how deadly it might be. It is easy to use and is designed for the early days of an outbreak before vaccines are available.
Featured Image
Photo by Alexander Hafemann on Unsplash
Why is it important?
Estimating disease prevalence in the presence of infectious asymptomatic carriers is crucial, but challenging, especially in developing countries. Our method, which utilizes simple PCR-RT tests, provides policy makers with a valuable tool in the early stages of a pandemic, allowing for greater control and reduced uncertainty.
Perspectives
As someone who works with data, I was new to working with health and mortality data. I was struck by how policy decisions had a significant impact on people's lives, particularly among the most vulnerable age groups in different countries. The data provided a clear narrative of these effects.
Osnat Mokryn
University of Haifa
Read the Original
This page is a summary of: A statistical model for early estimation of the prevalence and severity of an epidemic or pandemic from simple tests for infection confirmation, PLoS ONE, January 2023, PLOS,
DOI: 10.1371/journal.pone.0280874.
You can read the full text:
Contributors
The following have contributed to this page
