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How to prevent sequencing and sampling bias

In this video a specialists discusses the potential sampling biases and how to prevent them

In this video, Dr Catherine Ludden talks about sampling strategies that can prevent biases which can impact public health actions.

When deciding which samples to sequence, there are many options depending on the capacity of your network, the stage of the pandemic in your country and the most pressing public health questions requiring answers. Figure 1 shows some different categories of samples and one way of thinking about prioritisation.

Whilst these priorities will be different in each setting, it is almost universally accepted that the most important and primary activity in genomic surveillance is the tracking of different lineages and variants. This is best achieved by taking a random, unbiased and geographically representative sample of cases. This approach will be informative as to the lineages circulating, potentially at low levels depending on the size of the sample.

Sampling in hospitals, intensive care units, suspected imported cases, and care homes can answer very important targeted public health questions but, without being accompanied by general surveillance, risks a bias in the data.

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Figure 1 – An example of some potential categories of public health options and the types of samples you might decide to sequence.

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A Practical Guide for SARS-CoV-2 Whole Genome Sequencing

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