3 Data interpretation
Screening surveys and epidemiological studies usually require thousands of data points. For example, the first study on home-screening of antibodies to SARS-CoV2 done in the UK using lateral flow tests included 10,000 subjects. Such large studies give robust data but are clearly beyond the scope of this course. Nevertheless, the aim is to give you a flavour of how such studies can be analysed using the data you have obtained in the ELISA laboratory.
The aim of the next activity is to estimate the percentage of individuals who have IgG S-antibodies, from the samples in your data-set.
Activity 3 Prevalence of antibodies to SARS-CoV2
Take a cut-off point as a titre of 4 (dilution 1:4) and count the number of samples with a titre >4. Then estimate the percentage of individuals who are positive:
You may recall that at the time the samples were taken (August 2021) 60-70% of the adult population in the UK had been vaccinated against COVID-19 (Figure 3) and a much smaller percentage had had a natural infection. Individuals with antibodies have a level of immunity against virus infection and considerable protection against severe disease.
From your results, what percentage of individuals had some immunity to COVID-19 during this time?.
Answer
Due to the way in which the vaccination programme was rolled out (older people first), you might also expect to see that a higher proportion of older people would have antibodies than younger people. However, you probably do not have enough samples to confirm whether this is true or not.
Activity 4 Titres of antibodies to SARS-CoV2
Part 1
Using your data for Table 2, you can now estimate how the titre of antibodies varies across different groups within the population. Statistical analysis is beyond the scope of this course and would require larger data-sets. Nevertheless, you can carry out some simple comparisons. To do this first identify those individuals who are positive for IgG S-antibodies (titre >4). Then carry out two comparisons. In each case compare the median titre in one group with the median titre in the other.
The median is the individual who has the mid-point titre. For example, if the titres of a group of 11 individuals were: 8, 16, 64, 128, 128, 256, 512, 1024, 1024, 2048, 4096, then the median titre is 256, because this is the person in the mid-point of this group.
Part 2
Now compare the median in female and male individuals. Are they different? Generally titres in males and females are quite similar. It would be surprising if the results in your samples were greatly different, but it might be so if your samples do not represent the overall population well. The larger the number of samples you have taken, the more likely they will accurately reflect the S-antibody titres in the whole population.
Part 3
Next compare the median in older people (age >50) with those in younger people (age ≤50). Are they different? We expect that the titre in the older age group would be lower than the titre in the younger age group, but the interpretation of this is not quite so straightforward.
Can you think of two possible explanations of why the S-antibody titres could be lower in older people?
Answer
It may be that older people produce less antibodies. Alternatively, older people were mostly vaccinated early in 2021, and by this time their antibody titres will be declining. In comparison younger people were mostly vaccinated in Spring and early Summer, and antibody titres are usually highest 2−4 weeks after the second injection. Of course, it is possible that both explanations are true, but one cannot disentangle the two explanations from the data available so far.
This investigation has shown you how data on antibodies can be used for monitoring immunity in the population, but results have to be interpreted with caution. Next week you will start to look at how this type of data informs vaccination programmes.