Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study

Abstract

Background: The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility.

Methods: We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, R_t, for the two incidence estimates.

Findings: From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6-0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56-0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38-0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the R_t of B.1.1.7 by a factor of 1·35 (95% CI 1·02-1·69) relative to pre-existing variants. However, R_t fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant.

Interpretation: The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant.

Funding: Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society.

Figure 1

Presence of the B.1.1.7 variant by region in the UK from Sept 27 to Dec 31, 2020, measured using COG-UK genomic surveillance data and SGTF data Grey bars indicate the daily number of samples of positive cases available in the COG-UK data. SGTF data were not available for Scotland or Wales. COG-UK=COVID-19 Genomics UK Consortium. SGTF=spike-gene target failure.

Figure 2

Regional plots of the frequency of reporting of each symptom in users reporting positive test results over time from Sept 28 to Dec 27, 2020 Symptom occurrence per 1-week window is shown smoothed over three timepoints as a function of time. The drop in reporting of fever in early November was caused by a change in the wording of the question; this wording was subsequently reverted a week later.

Figure 3

Number of reports of possible reinfection by region from Sept 28 to Dec 27, 2020 Bars indicate the number of reports of possible reinfection each week, plotted by the date of the second infection. Lines show the total number of positive tests reported through the COVID Symptom Study app and the proportion of infections with the B.1.1.7 variant for the same period.

Figure 4

Total case numbers and R_t for pre-existing variants and B.1.1.7, and ratio between these R_t values, from Sept 28 to Dec 27, 2020 Data are shown for the three regions in England with the highest proportion of infections with the B.1.1.7 variant. R_t=effective reproduction number.

Figure 5

Total case numbers and R_t from Oct 15, 2020, to Jan 16, 2021, capturing the third national lockdown beginning Jan 5, 2021 Data are shown for the three regions in England with the highest proportion of infections with the B.1.1.7 variant in December, 2020. R_t=effective reproduction number.