A FRACTION OF INFECTIONS DETECTED
Without an infection prevalence survey, it is necessary to fall back on less accurate measures of infection estimates.
For example, the fraction of people admitted to hospitals who test positive for COVID-19 is an unreliable estimate of infection prevalence because it is biased by a large number of factors that are difficult to control for.
Namely, people rarely turn up at a hospital for random reasons. Many of the same factors that might drive hospital admissions, even for reasons not directly linked to COVID-19, are nonetheless related to COVID-19 infection risks.
As an example of infection prevalence data in action, in early January, the UK recorded an average of around 200,000 daily confirmed cases. The ONS survey estimated just under 4 million people were infected at the time.
Details around the length of the survey period during which people might test positive can affect the exact value of the CAR. But the UK figures paint a picture of only a small fraction of infections being detected, even with ARTs being provided frequently and free to every household.
With access to testing in Aotearoa being more limited than in the UK, we might expect our CAR to be even lower, and hence the number of reported cases is likely to significantly undercount true infections.
But without an infection prevalence survey, it’s difficult to tell exactly how much we are undercounting by.
Dr Dion O’Neale is a Senior Lecturer in the Department of Physics at the University of Auckland. He is also the Project Lead of COVID Modelling Aotearoa. Kylie Stewart from Project Te Matatini o te Horapa contributed to this article. This commentary first appeared in The Conversation.