Epidemiological drivers of transmissibility and severity of SARS-CoV-2 in England

Abstract

As the SARS-CoV-2 pandemic progressed, distinct variants emerged and dominated in England. These variants, Wildtype, Alpha, Delta, and Omicron were characterized by variations in transmissibility and severity. We used a robust mathematical model and Bayesian inference framework to analyse epidemiological surveillance data from England. We quantified the impact of non-pharmaceutical interventions (NPIs), therapeutics, and vaccination on virus transmission and severity. Each successive variant had a higher intrinsic transmissibility. Omicron (BA.1) had the highest basic reproduction number at 8.1 (95% credible interval (CrI) 6.8-9.3). Varying levels of NPIs were crucial in controlling virus transmission until population immunity accumulated. Immune escape properties of Omicron decreased effective levels of protection in the population by a third. Furthermore, in contrast to previous studies, we found Alpha had the highest basic infection fatality ratio (2.8%, 95% CrI 2.3-3.2), followed by Delta (2.0%, 95% CrI 1.5-2.4), Wildtype (1.2%, 95% CrI 1.0-1.3), and Omicron (0.6%, 95% CrI 0.4-0.8). Our findings highlight the importance of continued surveillance. Long-term strategies for monitoring and maintaining effective immunity against SARS-CoV-2 are critical to inform the role of NPIs to effectively manage future variants with potentially higher intrinsic transmissibility and severe outcomes.

Counterfactual analysis of the 2023 Omicron XBB wave in China

“…A similar intrinsic clinical severity of BA.1 variant (i.e., IHR = 3.5%, IFR = 0.6%) was reported by Perez-Guzman et al. ( Perez-Guzman et al., 2023 ). According to the World Health Organization, XBB variant does not show signs of change or increase in clinical severity ( World Health Organization ).…”

Pathways to altered virulence of SARS-CoV-2

“…Significantly, this suggests that virulence of SARS-CoV-2 variants is likely to be under drift and not natural selection, being free to increase or decrease randomly with ongoing viral evolution. Consistent with our model predictions, while some new SARS-CoV-2 variants have shown a reduction in intrinsic virulence (25,26), others have demonstrated increased virulence compared to the ancestral variant without a loss of transmissibility (27,28). This type of non-declining trajectory of virulence with SARS-CoV-2 viral evolution can lead to an unpredictable trajectory for the pandemic going forward (29)(30)(31).…”

“…Given that a substantial and increasing fraction of Omicron cases involve reinfection (63), the innate level of disease severity for each variant is difficult to compare. At least some of the reduction in severity for Omicron subvariants may arise from a decrease in innate virulence (25,26), but immunity generated by infections and vaccination also appears to decrease acute COVID-19 severity (64).…”

Redefining pandemic preparedness: Multidisciplinary insights from the CERP modelling workshop in infectious diseases, workshop report

“…While recognizing the continued significance of traditional surveillance data collection, the participants acknowledged the substantial benefits of integrating non-traditional approaches (mobility, pharmacy consumption, wastewater monitoring, social media). A holistic data approach is crucial in understanding and predicting disease spread, especially in the face of swift changes in behavior, interventions, the emergence of new variants, and evolving severity ( Perez-Guzman et al., 2023 ). Participants emphasized the importance of incorporating human behavioral data into Covid-19 modelling to improve the accuracy of transmission pattern predictions.…”