The Asymptomatic Proportion of SARS-CoV-2 Omicron Variant Infections in Households: A Systematic Review.
Nancy D J ShiAdrian J MarcatoVioleta SpirkoskaNiamh MeagherJuan Pablo Villanueva-CabezasDavid J PricePublished in: Influenza and other respiratory viruses (2024)
Understanding the clinical spectrum of SARS-CoV-2 infection, including the asymptomatic fraction, is important as asymptomatic individuals are still able to infect other individuals and contribute to ongoing transmission. The WHO Unity Household transmission investigation (HHTI) protocol provides a platform for the prospective and systematic collection of high-quality clinical, epidemiological, serological and virological data from SARS-CoV-2 confirmed cases and their household contacts. These data can be used to understand key severity and transmissibility parameters-including the asymptomatic proportion-in relation to local epidemic context and help inform public health response. We aimed to estimate the asymptomatic proportion of SARS-CoV-2 Omicron variant infections in Unity-aligned HHTIs. We conducted a systematic review and meta-analysis in alignment with the PRISMA 2020 guidelines and registered our systematic review on PROSPERO (CRD42022378648). We searched EMBASE, Web of Science, MEDLINE and bioRxiv and medRxiv from 1 November 2021 to 22 August 2023. We identified 8368 records, of which 98 underwent full text review. We identified only three studies for data extraction, with substantial variation in study design and corresponding estimates of the asymptomatic proportion. As a result, we did not generate a pooled estimate or I 2 metric. The limited number of quality studies that we identified highlights the need for improved preparedness and response capabilities to facilitate robust HHTI implementation, analysis and reporting, to better inform national, regional and global risk assessments and policymaking.
Keyphrases
- sars cov
- public health
- systematic review
- respiratory syndrome coronavirus
- electronic health record
- big data
- quality improvement
- healthcare
- primary care
- meta analyses
- emergency department
- clinical trial
- smoking cessation
- adverse drug
- artificial intelligence
- antiretroviral therapy
- case control
- study protocol
- coronavirus disease
- deep learning
- placebo controlled