People who have COVID-19 but aren’t showing any symptoms are much less likely to transmit the virus that causes the disease, researchers have found.
Health officials around the world have warned throughout the pandemic that people who don’t have symptoms could transmit SARS-CoV-2, which causes COVID-19 and is also known as the CCP (Chinese Communist Party) virus.
The warnings prompted the imposition of a slew of measures, such as mass testing of people, regardless of whether they had manifestations of the illness.
But the new research, published in PLOS One following peer review, concluded that the secondary attack rate—the primary measure of the risk of transmission of SARS-CoV-2—was about two-thirds lower from asymptomatic people than those who were experiencing symptoms.
People with asymptomatic infection are “less infectious than those with symptomatic infection,” Nicola Low, an epidemiologist with the Institute of Social and Preventative Medicine at the University of Bern, said in a statement.
The researchers included scientists from France, Spain, Switzerland, Sweden, Colombia, Argentina, the United States, and the United Kingdom. They updated a study they initially released that was only based on studies published in April 2020.
The updated research was based on 130 studies published between then and July 2021. The studies analyzed 28,246 people who tested positive for COVID-19, of whom nearly 12,000 experienced an infection but no symptoms.
Symptoms of COVID-19 include fever, cough, fatigue, loss of taste or smell, sore threat, headache, diarrhea, and aches and pains.
Researchers also estimated that a higher proportion of infections trigger symptoms, with asymptomatic infections consisting a share as low as 14 percent of infections in the studies reviewed.
However, while it is clear that asymptomatic infections don’t cause as much transmission as symptomatic ones, it is difficult to ascertain the true number of asymptomatic infections, the researchers said.
They said that future studies examining asymptomatic COVID-19 infections should focus on whether there are differences across variants of the CCP virus, and whether vaccination or prior infection affects transmission.
“Future studies should determine the asymptomatic proportion of SARS-CoV-2 infections caused by variants of concern and in people with immunity following vaccination or previous infection,” the researchers wrote. “Without prospective longitudinal studies with methods that minimize selection and measurement biases, further updates with the study types included in this living systematic review are unlikely to be able to provide a reliable summary estimate of the proportion of asymptomatic infections caused by SARS-CoV-2.”
The CDC admitted in November 2021 that there is no record of the naturally immune transmitting the virus.
For the Scientifically Inclined who want to read the details of the study, here it is:
https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003987
TITLE:
Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: Update of a living systematic review and meta-analysis
ABSTRACT:
BACKGROUND
Debate about the level of asymptomatic Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection continues. The amount of evidence is increasing and study designs have changed over time. We updated a living systematic review to address 3 questions: (1) Among people who become infected with SARS-CoV-2, what proportion does not experience symptoms at all during their infection? (2) What is the infectiousness of asymptomatic and presymptomatic, compared with symptomatic, SARS-CoV-2 infection? (3) What proportion of SARS-CoV-2 transmission in a population is accounted for by people who are asymptomatic or presymptomatic?
METHODS AND FINDINGS
The protocol was first published on 1 April 2020 and last updated on 18 June 2021. We searched PubMed, Embase, bioRxiv, and medRxiv, aggregated in a database of SARS-CoV-2 literature, most recently on 6 July 2021. Studies of people with PCR-diagnosed SARS-CoV-2, which documented symptom status at the beginning and end of follow-up, or mathematical modelling studies were included. Studies restricted to people already diagnosed, of single individuals or families, or without sufficient follow-up were excluded. One reviewer extracted data and a second verified the extraction, with disagreement resolved by discussion or a third reviewer. Risk of bias in empirical studies was assessed with a bespoke checklist and modelling studies with a published checklist. All data syntheses were done using random effects models. Review question (1): We included 130 studies.
Heterogeneity was high so we did not estimate a mean proportion of asymptomatic infections overall (interquartile range (IQR) 14% to 50%, prediction interval 2% to 90%), or in 84 studies based on screening of defined populations (IQR 20% to 65%, prediction interval 4% to 94%).
In 46 studies based on contact or outbreak investigations, the summary proportion asymptomatic was 19% (95% confidence interval (CI) 15% to 25%, prediction interval 2% to 70%). (2) The secondary attack rate in contacts of people with asymptomatic infection compared with symptomatic infection was 0.32 (95% CI 0.16 to 0.64, prediction interval 0.11 to 0.95, 8 studies). (3) In 13 modelling studies fit to data, the proportion of all SARS-CoV-2 transmission from presymptomatic individuals was higher than from asymptomatic individuals.
Limitations of the evidence include high heterogeneity and high risks of selection and information bias in studies that were not designed to measure persistently asymptomatic infection, and limited information about variants of concern or in people who have been vaccinated.
CONCLUSIONS
Based on studies published up to July 2021, most SARS-CoV-2 infections were not persistently asymptomatic, and asymptomatic infections were less infectious than symptomatic infections. Summary estimates from meta-analysis may be misleading when variability between studies is extreme and prediction intervals should be presented.
Future studies should determine the asymptomatic proportion of SARS-CoV-2 infections caused by variants of concern and in people with immunity following vaccination or previous infection. Without prospective longitudinal studies with methods that minimise selection and measurement biases, further updates with the study types included in this living systematic review are unlikely to be able to provide a reliable summary estimate of the proportion of asymptomatic infections caused by SARS-CoV-2.
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About the Authors
Diana Buitrago-Garcia
Contributed equally to this work with: Diana Buitrago-Garcia, Aziz Mert Ipekci, Leonie Heron
ROLES Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Validation, Writing – original draft, Writing – review & editing
AFFILIATIONS Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland, Graduate School of Health Sciences, University of Bern, Bern, Switzerland
ORCID logohttps://orcid.org/0000-0001-9761-206X
Aziz Mert Ipekci
Contributed equally to this work with: Diana Buitrago-Garcia, Aziz Mert Ipekci, Leonie Heron
ROLES Conceptualization, Data curation, Investigation, Methodology, Project administration, Validation, Writing – original draft, Writing – review & editing
AFFILIATION Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
ORCID logohttps://orcid.org/0000-0002-0260-9691
Leonie Heron
Contributed equally to this work with: Diana Buitrago-Garcia, Aziz Mert Ipekci, Leonie Heron
ROLES Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing – original draft, Writing – review & editing
AFFILIATION Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
ORCID logohttps://orcid.org/0000-0002-3820-3343
Hira Imeri
ROLES Data curation, Project administration, Software, Validation, Writing – review & editing
AFFILIATION Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
ORCID logohttps://orcid.org/0000-0002-0412-1649
Lucia Araujo-Chaveron
ROLES Data curation, Validation, Writing – review & editing
AFFILIATIONS EHESP French School of Public Health, Paris and Rennes, France, Institut Pasteur, Paris, France
ORCID logohttps://orcid.org/0000-0002-2110-6088
Ingrid Arevalo-Rodriguez
ROLES Data curation, Investigation, Validation, Writing – review & editing
AFFILIATION Clinical Biostatistics Unit, Hospital Universitario Ramon y Cajal, IRYCIS, CIBER of Epidemiology and Public Health, Madrid, Spain
ORCID logohttps://orcid.org/0000-0002-7326-4504
Agustín Ciapponi
ROLES Data curation, Investigation, Validation, Writing – review & editing
AFFILIATION Instituto de Efectividad Clínica y Sanitaria (IECS-CONICET), Buenos Aires, Argentina
ORCID logohttps://orcid.org/0000-0001-5142-6122
Muge Cevik
ROLES Data curation, Validation, Writing – review & editing
AFFILIATION Division of Infection and Global Health Research, School of Medicine, University of St. Andrews, Fife, Scotland, United Kingdom
ORCID logohttps://orcid.org/0000-0003-1133-3874
Anthony Hauser
ROLES Investigation, Methodology, Validation, Writing – review & editing
AFFILIATION Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
ORCID logohttps://orcid.org/0000-0002-7221-1929
Muhammad Irfanul Alam
ROLES Data curation, Validation, Writing – review & editing
AFFILIATION EHESP French School of Public Health, Paris and Rennes, France
ORCID logohttps://orcid.org/0000-0002-8759-6585
Kaspar Meili
ROLES Data curation, Validation, Writing – review & editing
AFFILIATION Department of Epidemiology and Global Health, Umeå University, Umeå, Sweden
ORCID logohttps://orcid.org/0000-0002-9889-4406
Eric A. Meyerowitz
ROLES Data curation, Investigation, Validation, Writing – review & editing
AFFILIATION Division of Infectious Diseases, Montefiore Medical Center, Bronx, New York, New York, United States of America
ORCID logohttps://orcid.org/0000-0001-7954-6548
Nirmala Prajapati
ROLES Data curation, Investigation, Validation, Writing – review & editing
AFFILIATION Université Paris-Saclay, Paris, France
ORCID logohttps://orcid.org/0000-0001-7518-5968
Xueting Qiu
ROLES Data curation, Validation, Writing – review & editing
AFFILIATION Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
ORCID logohttps://orcid.org/0000-0001-6810-7304
Aaron Richterman
ROLES Data curation, Investigation, Validation, Writing – review & editing
AFFILIATION Division of Infectious Diseases, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
ORCID logohttps://orcid.org/0000-0001-7920-7191
William Gildardo Robles-Rodriguez
ROLES Data curation, Investigation, Validation, Writing – review & editing
AFFILIATION Fundación Universitaria de Ciencias de la Salud, Bogotá, Colombia
ORCID logohttps://orcid.org/0000-0002-8383-6844
Shabnam Thapa
ROLES Data curation, Validation, Writing – review & editing
AFFILIATION Manchester Centre for Health Economics, University of Manchester, Manchester, United Kingdom
Ivan Zhelyazkov
ROLES Data curation, Validation, Writing – review & editing
AFFILIATION University of Sheffield, Sheffield, United Kingdom
ORCID logohttps://orcid.org/0000-0001-6320-7517
Georgia Salanti
ROLES Formal analysis, Methodology, Supervision, Validation, Visualization, Writing – review & editing
AFFILIATION Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
ORCID logohttps://orcid.org/0000-0002-3830-8508
Nicola Low
ROLES Conceptualization, Funding acquisition, Investigation, Methodology, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing
* E-mail: nicola.low@ispm.unibe.ch
AFFILIATION Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
ORCID logohttps://orcid.org/0000-0003-4817-8986
