In a recent study posted to the medRxiv* pre-print server, a team of researchers evaluated the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant on the prevalence of SARS-CoV-2 infections among unvaccinated and vaccinated populations of South Africa and 50 other countries.
The University of Maryland Global COVID-19 Trends and Impact Surveys (UMD Global CTIS) had collected more than 100,000 responses from across the world, related to coronavirus disease 2019 (COVID-19) symptoms, habits, testing, and vaccination status.
About the study
For the present study, the researchers accessed the UMD Global CTIS data and data of SARS-CoV-2 genome sequencing from the global initiative on sharing all influenza data (GISAID).
They removed abnormal responses of the participants who declared to have all the COVID-19 symptoms or reported unusual values (greater than 100) in the quantitative questions of the survey.
To closely track the evolution of active COVID-19 cases, they derived a proxy for active COVID-19 cases using a Random Forest classifier. The corresponding results or proxy estimates were labeled Random Forest, UMD COVID-like illness (CLI), Stringent CLI, Classic CLI, and Broad CLI. They compared each proxy estimate with the estimate of active COVID-19 cases, as described by Alvarez et al., where each new case was assumed to remain active for 10 days. These last estimates were called Confirmed, and both Confirmed and the estimates using the various proxies led to time series with one estimated value of vaccine efficacy (VE) per day.
Random Forest classifier was versatile and adaptive, hence researchers were able to create several models per country with this model, allowing capturing and adapting to aspects that varied over time, like the level of vaccination and the surge of new SARS-CoV-2 variants.
To obtain the official test positivity rates (TPR) using our world in data (OWID TPR) dataset from June 18, 2021, to December 31, 2021, the researchers selected 20 countries that had the largest number of available responses in the UMD Global CTIS dataset along with South Africa.
In South Africa, the decrease in VE was evaluated from mid-June 2021 until the end of 2021, more specifically, in three time periods of one month each i) June 18 to July 18, 2021; ii) August 9 to September 6, 2021; and December 1 to 31, 2021 (dominated by Omicron). The researchers studied the Gauteng province in South Africa separately, as it was among the most severely affected by Omicron.
In all, the researchers studied 50 countries for which the UMD Global CTIS had the largest amount of data and computed the VE for two months – October and December 2021. During this time, the VE estimates were compared using the Random Forest identifier among all three vaccination groups using correlation analysis.
Only non-negative VE values in a sample size of a minimum of 1000 samples, which showed prevalences PV and PU of at least 0.01, were considered.
The results confirmed the presence of a measurable drop in vaccine efficacy from 0.62 in the Delta period to 0.24 in the Omicron period in South Africa. In addition, these results confirmed that having two vaccine doses conferred better protection than one dose, across both periods, dominated by Delta (0.81 versus 0.51) and Omicron (0.30 versus 0.09). However, the results did not indicate the status of respondents in relation to a booster dose.
By January 7, 2022, a limited number of countries exhibited a high Omicron prevalence with a high level of sequencing data supporting it. Nevertheless, upon extending the study analysis to other countries where Omicron was detected, comparing the situation in October (before Omicron’s emergence) with that of December 2021 showed an average drop in vaccine efficacy from 0.53 to 0.45 among those vaccinated with two doses. In addition, a significant negative (Pearson) correlation ~0.6 between the measured prevalence of Omicron and the VE was observed.
Of all the five proxies, the Random Forest proxy was the most promising, as it exhibited the highest correlation values for most countries. Of the 21 countries for which TPR values were estimated, 17 countries exhibited low TPR values of ≤ 0.1 in either official or survey-based TPR, and 11 exhibited low values for both, with 7 having values under 0.053. These findings suggested that these countries kept COVID-19 case counts relatively under control and reported data correctly.
To summarize, the present study remarkably tracked the prevalence of COVID-19 infections using daily participatory symptom surveillance data, particularly those with stronger surveillance systems and consistent TPRs.
The authors cautioned that the observed reduction of VE in the Omicron period is towards COVID-19 infection and impacts Omicron transmission but does not imply a VE reduction in relation to COVID-19 severity, hospitalization, and death. Further studies should confirm these results once Omicron becomes dominant in other countries.
medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
- Jesus Rufino, et al. (2022). Using Survey Data to Estimate the Impact of the Omicron Variant on Vaccine Efficacy against COVID-19 Infection. medRxiv. doi: https://doi.org/10.1101/2022.01.21.22269636 https://www.medrxiv.org/content/10.1101/2022.01.21.22269636v1
Posted in: Medical Science News | Medical Research News | Disease/Infection News
Tags: Coronavirus, Coronavirus Disease COVID-19, covid-19, Efficacy, Evolution, Genome, Influenza, Omicron, Respiratory, SARS, SARS-CoV-2, Severe Acute Respiratory, Severe Acute Respiratory Syndrome, Syndrome, Vaccine
Neha Mathur has a Master’s degree in Biotechnology and extensive experience in digital marketing. She is passionate about reading and music. When she is not working, Neha likes to cook and travel.
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