Home Immunity What is the impact of the SARS-CoV-2 omicron wave in South Africa?

What is the impact of the SARS-CoV-2 omicron wave in South Africa?

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A study published in the journal Science Translational Medicine described severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmissibility, population-level immunity and the impact of the omicron wave in South Africa.

Study: SARS-CoV-2 transmission, persistence of immunity and estimates of the impact of Omicron in South African population cohorts. Image Credit: PHOTOCREO Michal Bednarek/Shutterstock

Background

The omicron variant of SARS-CoV-2 was first detected in South Africa in November 2021. Prior to its emergence, South Africa experienced three distinct waves dominated by wild-type SARS-CoV-2 with D614G mutation, beta variant and delta variant, respectively.

Compared to previously circulating viral variants, omicron exhibits a highly mutated genome, which makes the variant immunologically superior at evading pre-existing population-level immunity (herd immunity) induced by previous infections and vaccinations.

In the present study, scientists determined the long-term dynamics of SARS-CoV-2 in two groups of households from a rural and urban area in South Africa. Both groups were followed for 13 months.

Specifically, the scientists estimated the robustness of cross-reactive immunity induced by consecutive waves of SARS-CoV-2 variants. They recreated the landscape of herd immunity in South Africa before the emergence of the omicron variant, as well as determined the impact of the omicron wave in the same population.

SARS-CoV-2 epidemiology in South Africa

The study was conducted in a rural area and an urban area located in two South African provinces. The study population included 1200 people living in 222 households. Only 10% of the study population were fully vaccinated during the study period.

At baseline, the seroprevalence of nucleocapsid anti-SARS-CoV-2 antibodies was 1.1% in the rural area, which increased to 7%, 25% and 39% after the first (D614G), the second (beta), and third (delta) waves, respectively. The infection rate was almost 60% in this region.

In the urban area, seroprevalence was 14% at enrollment, which increased to 27%, 40% and 55% after the first, second and third waves, respectively. The infection rate was almost 70% in this region.

Dynamics of viral RNA shedding

Household exposure to the virus depends primarily on levels of viral RNA excreting among family members.

Analysis of viral RNA dynamics revealed that the three variants have similar characteristics, represented by a short proliferation phase and a longer clearance phase.

The prevalence of symptomatic infection among household members was 13%, 16, and 18% for SARS-CoV-2 D614G, beta, and delta variants, respectively. The time of peak viral shedding coincided with the time of symptom onset, indicating that significant viral shedding occurs before symptom onset.

Further analysis revealed that symptomatic infections are characterized by a high viral load. The highest viral load was seen in delta infections, followed by beta and SARS-CoV-2 D614G infections. Notably, household members with prior infections had significantly reduced viral shedding levels and duration upon re-infection.

Risk of primary infection and reinfection with SARS-CoV-2

A positive correlation was observed between the intensity of household exposure and the risk of SARS-CoV-2 infection. This association was stronger at the proliferation stage than at the clearance stage. The delta variant showed the highest infectivity, followed by the beta and D614G variants.

Regarding the protective efficacy of pre-existing immunity, the results revealed that prior infection provides 92% protection against reinfection during the first three months, which decreases to 87% after nine months.

The lowest risk of infection was observed in people over the age of 65 during the D614G wave. During the delta wave, the risk was highest in children and adolescents 6 to 18 years old. In addition, an increased risk of infection has been observed in obese people and those residing in urban areas.

Impact of the omicron wave in the urban region

Scientists developed mathematical models to assess the trajectory of omicron waves as well as viral dynamics in the urban region.

Model projections revealed that omicron has a growth advantage of 0.338 per day over delta. The basic reproduction number was also higher for omicron. As expected, a higher infection rate was observed during the omicron wave than during previous waves. Over 40% of omicron infections were expected to be reinfections and breakthrough infections.

Using a baseline scenario for the immune evasion characteristics of Omicron, the impact of the omicron wave was estimated. The results revealed that the ratio of the basic omicron to delta reproduction number is 2.4, the infection rate is 69%, the duration of the wave is 32 days, and the proportion of reinfections and breakthroughs vaccination is 68%.

To understand the robustness of omicron-induced immunity against existing and future variants, mathematical models were developed to project the degree of protection under different exposure conditions (contact rate).

Given the contact rate of the delta wave, models predicted that the degree of herd immunity would not be sufficient to prevent a recurrent omicron outbreak unless previous omicron infections induce protection. robust and durable.

Considering a 100% higher contact rate, models predicted that if it reappeared, omicron could cause outbreaks, regardless of the protection induced by previous omicron infections. Taken together, these predictions indicate that an induction of contact rates can lead to the emergence of new waves caused by pre-existing or new viral variants.