Asymptomatic Spread Is So Rare It Only Happens 0.7% of the Time Even in Households

But enjoy your mask anyway

The Covid RougeThe Great Hysteria Pandemic

Dr. Zachary J. Madewell 16 Dec 20 1878 4

Just 1 out of 150 asymptomatics will infect another household member,. Even 82% of symptomatics fail to infect any other household member.

Key Points

Question

What is the household secondary attack rate for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)?

Findings

In this meta-analysis of 54 studies with 77 758 participants, the estimated overall household secondary attack rate was 16.6%, higher than observed secondary attack rates for SARS-CoV and Middle East respiratory syndrome coronavirus. Controlling for differences across studies, secondary attack rates were higher in households from symptomatic index cases than asymptomatic index cases, to adult contacts than to child contacts, to spouses than to other family contacts, and in households with 1 contact than households with 3 or more contacts.

Meaning

These findings suggest that households are and will continue to be important venues for transmission, even in areas where community transmission is reduced.

New JAMA meta-analysis of 54 studies with 77,758 participants finds household secondary attack rate (chance an infected person will infect one or more people at home) is 18% if the index case is symptomatic and 0.7% if asymptomatic.https://t.co/K09cAeCaEr pic.twitter.com/YX4tYI2dcL

— Phil Kerpen (@kerpen) December 14, 2020

Abstract

Importance

Crowded indoor environments, such as households, are high-risk settings for the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Objectives

To examine evidence for household transmission of SARS-CoV-2, disaggregated by several covariates, and to compare it with other coronaviruses.

Data Source

PubMed, searched through October 19, 2020. Search terms included SARS-CoV-2 or COVID-19 with secondary attack rate, household, close contacts, contact transmission, contact attack rate, or family transmission.

Study Selection

All articles with original data for estimating household secondary attack rate were included. Case reports focusing on individual households and studies of close contacts that did not report secondary attack rates for household members were excluded.

Data Extraction and Synthesis

Meta-analyses were done using a restricted maximum-likelihood estimator model to yield a point estimate and 95% CI for secondary attack rate for each subgroup analyzed, with a random effect for each study. To make comparisons across exposure types, study was treated as a random effect, and exposure type was a fixed moderator. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline was followed.

Main Outcomes and Measures

Secondary attack rate for SARS-CoV-2, disaggregated by covariates (ie, household or family contact, index case symptom status, adult or child contacts, contact sex, relationship to index case, adult or child index cases, index case sex, number of contacts in household) and for other coronaviruses.

Results

A total of 54 relevant studies with 77 758 participants reporting household secondary transmission were identified. Estimated household secondary attack rate was 16.6% (95% CI, 14.0%-19.3%), higher than secondary attack rates for SARS-CoV (7.5%; 95% CI, 4.8%-10.7%) and MERS-CoV (4.7%; 95% CI, 0.9%-10.7%). Household secondary attack rates were increased from symptomatic index cases (18.0%; 95% CI, 14.2%-22.1%) than from asymptomatic index cases (0.7%; 95% CI, 0%-4.9%), to adult contacts (28.3%; 95% CI, 20.2%-37.1%) than to child contacts (16.8%; 95% CI, 12.3%-21.7%), to spouses (37.8%; 95% CI, 25.8%-50.5%) than to other family contacts (17.8%; 95% CI, 11.7%-24.8%), and in households with 1 contact (41.5%; 95% CI, 31.7%-51.7%) than in households with 3 or more contacts (22.8%; 95% CI, 13.6%-33.5%).

Conclusions and Relevance

The findings of this study suggest that given that individuals with suspected or confirmed infections are being referred to isolate at home, households will continue to be a significant venue for transmission of SARS-CoV-2.

Introduction

The coronavirus disease 2019 (COVID-19) pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is spread via direct or indirect contact with infected people via infected respiratory droplets or saliva, fomites, or aerosols.¹^,2 Crowded indoor environments with sustained close contact and conversations, such as households, are a particularly high-risk setting.³

The World Health Organization China Joint Mission reported human-to-human transmission in China largely occurred within families, accounting for 78% to 85% of clusters in Guangdong and Sichuan provinces.⁴ Stay-at-home orders reduced human mobility by 35% to 63% in the United States,⁵ 63% in the United Kingdom,⁶ and 54% in Wuhan,⁷ relative to normal conditions, which concomitantly increased time at home. Modeling studies demonstrated that household transmission had a greater relative contribution to the basic reproductive number after social distancing (30%-55%) than before social distancing (5%-35%).⁸ While current US Centers for Disease Control and Prevention recommendations are to maintain 6 feet of distance from a sick household member, this may be difficult to achieve in practice and not be fully effective.⁹

The household secondary attack rate characterizes virus transmissibility. Studies can collect detailed data on type, timing, and duration of contacts and identify risk factors associated with infectiousness of index cases and susceptibility of contacts. Our objective was to estimate the secondary attack rate of SARS-CoV-2 in households and determine factors that modify this parameter. We also estimated the proportion of households with index cases that had any secondary transmission. Furthermore, we compared the SARS-CoV-2 household secondary attack rate with that of other severe viruses and with that to close contacts for studies that reported the secondary attack rate for both close and household contacts.

Methods

Definitions

We estimated the transmissibility of SARS-CoV-2 within the household or family by the empirical secondary attack rate by dividing the number of new infections among contacts by the total number of contacts. Household contacts include anyone living in the same residence as the index case. Family contacts include the family members of index cases, including individuals who live outside the index case’s household. Close contact definitions varied by study and included physical proximity to an index case, exceeding a minimum contact time, and/or not wearing effective protection around index cases before the index case was tested.

Search Strategy

Following Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline, we searched PubMed using terms including SARS-CoV-2 or COVID-19 with secondary attack rate, household, close contacts, contact transmission, contact attack rate, or family transmission (eTable 1 in the Supplement) with no restrictions on language, study design, time, or place of publication. The last search was conducted October 19, 2020.

Eligibility Criteria

Eligibility criteria are described in eAppendix 1 in the Supplement. All articles with original data for estimating household secondary attack rate were included. Case reports focusing on individual households and studies of close contacts that did not report secondary attack rates for household members were excluded.

Data Extraction

One of us (Z.J.M.) extracted data from each study. Details appear in eAppendix 2 in the Supplement.

Evaluation of Study Quality and Risk of Bias

To assess the methodological quality and risk of bias of included studies of SARS-CoV-2, we used the same modified version of the Newcastle-Ottawa quality assessment scale for observational studies used by Fung et al.¹⁰^,11 Studies received as many as 9 points based on participant selection (4 points), study comparability (1 point), and outcome of interest (4 points). Studies were classified as having high (≤3 points), moderate (4-6 points), and low (≥7 points) risk of bias. One of us (Z.J.M.) evaluated the study quality and assigned the quality grades.

Statistical Analysis

Meta-analyses were done using a restricted maximum-likelihood estimator model to yield Freeman-Tukey double arcsine–transformed point estimates and 95% CI for secondary attack rate for each subgroup analyzed, with a random effect for each study.¹² For comparisons across covariates (ie, household or family, index case symptom status, adult or child contacts, contact sex, relationship to index case, adult or child index cases, index case sex, number of household contacts, study location, universal or symptomatic testing, dates of study) and comparisons with close contacts and other viruses, study was treated as a random effect, and the covariate was a fixed moderator. Variables had to have been collected in at least 3 studies to be included in meta-analyses. The Cochran Q test and I² statistic are reported as measures of heterogeneity. I² values of 25%, 50%, and 75% indicated low, moderate, and high heterogeneity, respectively.¹³ Stastistical significance was set at a 2-tailed α = .05. All analyses were done in R version 4.0.2 using the package metafor (R Project for Statistical Computing).¹⁴^,15

When at least 10 studies were available, we used funnel plots, Begg correlation, and Egger test to evaluate publication bias, with significance set at P < .10.¹⁶^,17 If we detected publication bias, we used the Duval and Tweedie trim-and-fill approach for adjustment.¹⁸

Results

We identified 54 relevant published studies that reported household secondary transmission, with 77 758 participants (eTable 1 in the Supplement).¹⁹^–72 A total of 16 of 54 studies (29.6%) were at high risk of bias, 27 (50.0%) were moderate, and 11 (20.4%) were low (eTable 2 in the Supplement). Lower quality was attributed to studies with 1 or fewer test per contact (35 studies [64.8%]), small sample sizes (31 [57.4%]), and secondary attack rate not disaggregated by covariates (28 [51.9%]).

A description of index case identification period and methods and symptom status is provided in eTable 3 in the Supplement. Most studies did not describe how co–primary index cases were handled or whether secondary infections could have been acquired from outside the household, both of which can inflate the empirical secondary attack rate. Testing and monitoring strategies varied between studies, often reflecting variations in local testing guidelines implemented as part of contact tracing (eTable 4 and eAppendix 3 in the Supplement).

Figure 1 summarizes secondary attack rates for 44 studies¹⁹^–26,28^–30,32^–36,38^–45,47^–57,59^,61^–63,65^–67,69^,70 of household contacts and 10 of family contacts.²⁶^,31^,37^,45^,58^,60^,65^,68^,71^,72 Estimated mean secondary attack rate for household contacts was 16.4% (95% CI, 13.4%-19.6%) and family contacts was 17.4% (95% CI, 12.7%-22.5%). One study⁴⁰ restricted index cases to children (age <18 years), resulting in a substantially lower secondary attack rate of 0.5%. Excluding this outlier, the combined secondary attack rate for household and family contacts was 17.1% (95%, 14.6%-19.7%). Secondary attack rates for household and family contacts were more than 3 times higher than for close contacts (4.8%; 95% CI, 3.4%-6.5%; P < .001) (eFigure 2 in the Supplement). Significant heterogeneity was found among studies of household (I² = 96.9%; P < .001), family (I² = 93.0%; P < .001), and close (I² = 97.0%; P < .001) contacts. No significant publication bias was observed for studies of household, family, or close contacts (eFigure 3 in the Supplement). Secondary attack rates were not significantly different when restricting to 38 studies¹⁹^,20,22^,23,26^–31,34^–40,42^,44^–51,54^–57,60^,62^,63,65^,67^–69,72 with low or moderate risk of bias (15.6%; 95%, 12.8%-18.5%) (eFigure 4 in the Supplement). There were no significant differences in secondary attack rates between 21 studies in China²²^,27^,31^,36^,37,39^,45^,46,48^,58^,61^–68,70^–72 and 33 studies from other countries¹⁹^–21,23^–26,28^–30,32^–35,38^,40^–44,47^,49^–57,59^,60,69 (eFigure 5 in the Supplement), 18 studies that tested symptomatic contacts¹⁹^–21,24^,25,28^,29,33^,34,41^,47^,50^,53^,56^,58^,59,61^,64 and 33 studies that reported testing all contacts²²^,23,26^,27,30^,31,35^–40,42^–46,48^,49,51^,52,54^,55,57^,60^,63^,65^–67,69^–72 (eFigure 6 in the Supplement), and 16 early studies²²^,23,25^,31^,37^,39^,45^,58^,61^,63^–66,68^,71^,72 (January-February) and 20 later studies¹⁹^,24^,26^,29^,30,32^–35,38^,42^,44^,50^,53^–56,59^,60,69 (March-July) (eFigure 7 in the Supplement).

To study the transmissibility of asymptomatic SARS-CoV-2 index cases, eFigure 8 in the Supplement summarizes 27 studies¹⁹^–21,23^–26,30^,32^–34,44^,45,47^,50^,52^–54,56^,59^–61,63^,64,68^,69,72 reporting household secondary attack rates from symptomatic index cases and 4 studies²⁶^,43^,44,52 from asymptomatic or presymptomatic index cases. Estimated mean household secondary attack rate from symptomatic index cases (18.0%; 95% CI, 14.2%-22.1%) was significantly higher than from asymptomatic or presymptomatic index cases (0.7%; 95% CI, 0%-4.9%; P < .001), although there were few studies in the latter group.

These findings are consistent with other household studies²⁸^,70 reporting asymptomatic index cases as having limited role in household transmission.

There is evidence for clustering of SARS-CoV-2 infections within households, with some households having many secondary infections while many others have none.⁷³^–75 For example, 1 study⁵⁵ reported that 26 of 103 (25.2%) households had all members test positive. This is consistent with observation of overdispersion in the number of secondary cases per index case across a range of settings.³ While most studies reported only the average number of secondary infections per index case, some also reported transmission by household.⁴⁴^,55^,56,63^,65^,69 Figure 2 summarizes the proportion of households with any secondary transmission. Using an empirical analysis based on secondary attack rates and mean number of contacts per household, we found the proportion of households with any secondary transmission was lower than expected in a setting with no clustering (eg, most transmission is not characterized by a minority of infected individuals) (eTable 5 in the Supplement). Ideally, future studies will assess this formally by fitting a β binomial to quantify overdispersion in the full data.

A number of studies examined factors associated with susceptibility of household contacts to infection (eTable 6 in the Supplement). Age was the most examined covariate, with most studies²⁰^,29^,36^–39,45^,46,48^,49,55^,63^,65^,68 reporting lower secondary transmission of SARS-CoV-2 to child contacts than adult contacts. In 5 studies,²⁰^,36^,39^,48^,49 individuals older than 60 years were most susceptible to SARS-CoV-2 infection. Contact age was not associated with susceptibility in 9 studies,²⁶^,28^,32^,44^,47^,58^,66^,67,70 although these were typically less powered to detect a difference. Figure 3 summarizes 15 studies²²^,26^,29^,37^,39^,42^,44^,45,47^,49^,55^,59^,60,63^,65 reporting separate secondary attack rates to children and adult contacts. The estimated mean household secondary attack rate was significantly higher to adult contacts (28.3%; 95% CI, 20.2%-37.1%) than to child contacts (16.8%; 95% CI, 12.3%-21.7%; P < .001). Significant heterogeneity was found among studies of adult (I² = 96.8%; P < .001) and child contacts (I² = 78.9%; P < .001). Begg (P = .03) and Egger (P = .03) tests were statistically significant for studies of adult but not child contacts (eFigure 9 in the Supplement). One study of adults⁶³ had a high secondary attack rate in the forest plot. Excluding this study improved the funnel plot symmetry and resulted in a secondary attack rate to adult contacts of 26.3% (95% CI, 19.3%-33.2%).

The second most examined factor was sex of exposed contacts, which was not associated with susceptibility for most studies²⁰^,22^,26^,32^,36^,39^,44^,45,47^–49,58^,65^–67,70 except 3.³⁸^,46^,68 eFigure 10 in the Supplement summarizes results from 11 studies²⁰^,39^,42^,44^,45,47^,49^,58^,65^,67^,69 reporting household secondary attack rates by contact sex. Estimated mean household secondary attack rate to female contacts (20.7%; 95% CI, 15.0%-26.9%) was not significantly different than to male contacts (17.7%; 95% CI, 12.4%-23.8%). Significant heterogeneity was found among studies of female contacts (I² = 87.4%; P < .001) and male contacts (I² = 87.7%; P < .001). Moderate asymmetry was observed in the funnel plots, which was significant for studies of female contacts from Egger test (P = .07) but not male contacts (eFigure 11 in the Supplement). However, imputation of an adjusted effect size using the trim-and-fill method did not significantly change the secondary attack rate to female contacts (19.7%; 95% CI, 13.9%-25.6%).

Spouse relationship to index case was associated with secondary infection in 4 studies²⁶^,45^,46,58 of 6 in which this was examined.⁶⁵^,67 Infection risk was highest for spouses, followed by nonspouse family members and other relatives, which were all higher than other contacts.⁴⁶ Figure 4 summarizes results from 7 studies²⁶^,44^–46,58^,65^,67 reporting household secondary attack rates by relationship. Estimated mean household secondary attack rate to spouses (37.8%; 95% CI, 25.8%-50.5%) was significantly higher than to other contacts (17.8%; 95% CI, 11.7%-24.8%). Significant heterogeneity was found among studies of spouses (I² = 78.6%; P < .001) and other relationships (I² = 83.5%; P < .001).

Several studies examined factors associated with infectiousness of index cases. Older index case age was associated with increased secondary infections in 3 studies²⁰^,47^,67 of 9 in which this was examined.²²^,36^,39^,44^,63^,65 eFigure 12 in the Supplement summarizes results from 3 studies⁴²^,44^,51 reporting household secondary attack rates by index case age. Estimated mean household secondary attack rate from adults (15.2%; 95% CI, 6.2%-27.4%) was not significantly different than that from children (7.9%; 95% CI, 1.7%-16.8%). Index case sex was associated with transmission in 3 studies⁴²^,44^,67 of 9 in which this was examined.²⁰^,36^,45^,47^,63^,65 eFigure 13 in the Supplement summarizes results from 7 studies²⁰^,42^,44^,45,65^,67^,69 reporting household secondary attack rates by index case sex. Estimated mean household secondary attack rate from female contacts (16.6%; 95% CI, 11.2%-22.8%) was not significantly different than from male contacts (16.4%; 95% CI, 9.0%-25.5%).

Critically severe index case symptoms was associated with higher infectiousness in 6 studies²⁰^,38^,46^–48,67 of 9 in which this was examined.⁴⁴^,63^,70 Index case cough was associated with infectivity in 2 studies ²⁰^,65 of 8 in which this was examined⁴⁵^–48,63^,67 (eAppendix 4 in the Supplement).

Contact frequency with the index case was associated with higher odds of infection, specifically at least 5 contacts during 2 days before the index case was confirmed,⁷⁰ at least 4 contacts and 1 to 3 contacts,⁶³ or frequent contact within 1 meter.²²^,67^,68 Smaller households were associated with transmission in 4 studies²⁰^,39^,47^,49 of 7 in which this was examined.⁵⁵^,63^,65 Figure 5 summarizes results from 6 studies²⁰^,47^,49^,55^,61^,65 reporting household secondary attack rates by number of contacts in the household. Estimated mean household secondary attack rate for households with 1 contact (41.5%; 95% CI, 31.7%-51.7%) was significantly higher than households with at least 3 contacts (22.8%; 95% CI, 13.6%-33.5%; P < .001) but not different than households with 2 contacts (38.6%; 95% CI, 17.9%-61.6%). There was significant heterogeneity in secondary attack rates between studies with 1 contact (I² = 52.9%; P = .049), 2 contacts (I² = 93.6%; P < .001), or 3 or more contacts (I² = 91.6%; P < .001). Information was not available on household crowding (eg, number of people per room).

eFigure 14 in the Supplement summarizes 7 studies⁷⁶^–82 reporting household secondary attack rates for SARS-CoV, and 7 studies⁸³^–89 for Middle East respiratory syndrome coronavirus (MERS-CoV). Estimated mean household secondary attack rate was 7.5% (95% CI, 4.8%-10.7%) for SARS-CoV and 4.7% (95% CI, 0.9%-10.7%) for MERS-CoV (eTable 7 in the Supplement), both lower than the household secondary attack rate of 16.6% for SARS-CoV-2 in this study (P < .001). The SARS-CoV-2 secondary attack rate was also higher than secondary attack rates reported for HCoV-NL63 (0-12.6%), HCoV-OC43 (10.6-13.2%), HCoV-229E (7.2-14.9%), and HCoV-HKU1 (8.6%).⁹⁰^–92 Household secondary attack rates for SARS-CoV-2 were within the mid-range of household secondary attack rates reported for influenza, which ranged from 1% to 38% based on polymerase chain reaction–confirmed infection.⁹³

Discussion

We synthesized the available evidence on household studies of SARS-CoV-2. The combined household and family secondary attack rate was 16.6% (95% CI, 14.0%-19.3%), although with significant heterogeneity between studies. This point estimate is higher than previously observed secondary attack rates for SARS-CoV and MERS-CoV. Households are favorable environments for transmission. They are what are known as 3Cs environments, as they are closed spaces, where family members may crowd and be in close contact with conversation.⁹⁴ There may be reduced use of personal protective equipment relative to other settings.

That secondary attack rates were not significantly different between household and family contacts may indicate that most family contacts are in the same household as index cases. Household and family contacts are at higher risk than other types of close contacts, and risks are not equal within households. Spouses were at higher risk than other family contacts, which may explain why the secondary attack rate was higher in households with 1 vs 3 or greater contacts. Spouse relationship to the index case was also a significant risk factor observed in studies of SARS-CoV and H1N1.⁸²^,95 This may reflect intimacy, sleeping in the same room, or longer or more direct exposure to index cases. Further investigation is required to determine whether sexual contact is a transmission route. Although not directly assessed, household crowding (eg, number of people per room) may be more important for SARS-CoV-2 transmission than the total number of people per household, as has been demonstrated for influenza.⁹⁶^–98

The finding that secondary attack rates were higher to adult contacts than to child contacts is consistent with empirical and modeling studies.⁹⁹^,100 Lower infection rates in children may be attributed to asymptomatic or mild disease, reduced susceptibility from cross-immunity from other coronaviruses,¹⁰¹ and low case ascertainment,¹⁰² but the difference persisted in studies in which all contacts were tested regardless of symptoms. Higher transmission rates to adults may be influenced by spousal transmission. Given the increased risk to spousal contacts, future studies might compare child contacts and nonspouse adult contacts to ascertain whether this difference persists. Limited data suggest children have not played a substantive role in household transmission of SARS-CoV-2.⁴⁰^,103^–105 However, a study in South Korea of 10 592 household contacts noted relatively high transmission from index cases who were aged 10 to 19 years.⁵¹ Although children seem to be at reduced risk for symptomatic disease, it is still unclear whether they shed virus similarly to adults.¹⁰⁶

We did not find associations between household contact or index case sex and secondary transmission. The World Health Organization reports roughly even distribution of SARS-CoV-2 infections between women and men worldwide, with higher mortality in men.¹⁰⁷

We found significantly higher secondary attack rates from symptomatic index cases than asymptomatic or presymptomatic index cases, although less data were available on the latter. The lack of substantial transmission from observed asymptomatic index cases is notable. However, presymptomatic transmission does occur, with some studies reporting the timing of peak infectiousness at approximately the period of symptom onset.¹⁰⁸^,109 In countries where infected individuals were isolated outside the home, this could further alter the timing of secondary infections by limiting contacts after illness onset.¹¹⁰

Household secondary attack rates were higher for SARS-CoV-2 than SARS-CoV and MERS-CoV, which may be attributed to structural differences in spike proteins,¹¹¹ higher basic reproductive rates,¹¹² and higher viral loads in the nose and throat at the time of symptom onset.¹¹³ Symptoms associated with MERS-CoV and SARS-CoV often require hospitalization, which increases nosocomial transmission, whereas less severe symptoms of SARS-CoV-2 facilitate community transmission.¹¹³ Similarly, presymptomatic transmission was not observed for MERS-CoV or SARS-CoV.¹¹⁴^,115

Limitations

Our study had several limitations. The most notable is the large amount of unexplained heterogeneity across studies. This is likely attributable to variability in study definitions of index cases and household contacts, frequency and type of testing, sociodemographic factors, household characteristics (eg, density, air ventilation), and local policies (eg, centralized isolation). Rates of community transmission also varied across locations. Given that studies cannot always rule out infections from outside of the home (eg, nonhousehold contacts), household transmission may be overestimated. For this reason, we excluded studies that used antibody tests to diagnose household contacts. Furthermore, many analyses ignored tertiary transmission within the household, classifying all subsequent cases as secondary to the index case. Eighteen studies¹⁹^–21,24^,25,28^,29,33^,34,41^,47^,50^,53^,56^,58^,59,61^,64 involved testing only symptomatic household contacts, which would miss asymptomatic or subclinical infections, although secondary attack rate estimates were similar across studies testing all vs only symptomatic contacts.

Important questions remain regarding household spread of SARS-CoV-2. Chief among them is the infectiousness of children to their household contacts and the infectiousness of asymptomatic, mildly ill, and severely ill index cases. This study did not provide additional elucidation of factors influencing intergenerational spread. People unable to work at home may have greater risk of SARS-CoV-2 exposure, which may increase transmission risk to other household members. There may be overdispersion in the number of secondary infections per index case, which could be caused by variations in viral shedding, household ventilation, or other factors.

Conclusions

The findings of this study suggest that households are and will continue to be important venues for transmission, even where community transmission is reduced. Prevention strategies, such as increased mask-wearing at home, improved ventilation, voluntary isolation at external facilities, and targeted antiviral prophylaxis, should be further explored.

Article Information

Accepted for Publication: November 6, 2020.

Published: December 14, 2020. doi:10.1001/jamanetworkopen.2020.31756

Corresponding Author: Zachary J. Madewell, Department of Biostatistics, University of Florida, PO Box 117450, Gainesville, FL 32611 (zmadewell@ufl.edu).

Author Contributions: Drs Madewell and Dean had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Madewell, Longini, Dean.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Madewell, Longini, Dean.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: All authors.

Obtained funding: Dean.

Administrative, technical, or material support: Dean.

Supervision: Dean.

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported by grant R01-AI139761 from the National Institutes of Health.

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

References

World Health Organization. Transmission of SARS-CoV-2: implications for infection prevention precautions. Published July 9, 2020. Accessed November 11, 2020. https://www.who.int/news-room/commentaries/detail/transmission-of-sars-cov-2-implications-for-infection-prevention-precautions

Oran DP, Topol EJ. Prevalence of asymptomatic SARS-CoV-2 infection : a narrative review. Ann Intern Med. 2020;173(5):362-367. doi:10.7326/M20-3012 PubMed Google Scholar Crossref

Nishiura H, Oshitani H, Kobayashi T, et al. Closed environments facilitate secondary transmission of coronavirus disease 2019 (COVID-19). medRxiv. Preprint published online April 16, 2020. doi:10.1101/2020.02.28.20029272 Google Scholar

World Health Organization. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). February 16-24, 2020. Accessed November 11, 2020. https://www.who.int/docs/default-source/coronaviruse/who-china-joint-mission-on-covid-19-final-report.pdf

Badr HS, Du H, Marshall M, Dong E, Squire MM, Gardner LM. Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study. Lancet Infect Dis. 2020;20(11):1247-1254. doi:10.1016/S1473-3099(20)30553-3 PubMed Google Scholar Crossref

Drake TM, Docherty AB, Weiser TG, Yule S, Sheikh A, Harrison EM. The effects of physical distancing on population mobility during the COVID-19 pandemic in the UK. Lancet Digit Health. 2020;2(8):e385-e387. doi:10.1016/S2589-7500(20)30134-5 PubMed Google Scholar Crossref

Fang H, Wang L, Yang Y. Human mobility restrictions and the spread of the novel coronavirus (2019-nCoV) in China. National Bureau of Economic Research. Published March 2020. Accessed November 11, 2020. https://www.nber.org/papers/w26906

Curmei M, Ilyas A, Evans O, Steinhardt J. Estimating household transmission of SARS-CoV-2. medRxiv. Preprint published online June 27, 2020. doi:10.1101/2020.05.23.20111559 Google Scholar

US Centers for Disease Control and Prevention. Coronavirus disease 2019 (COVID-19): how to protect yourself and others. Updated November 4, 2020. Accessed November 11, 2020. https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/prevention.html

10.

Wells G. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analysis. Accessed November 11, 2020. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp

11.

Fung HF, Martinez L, Alarid-Escudero F, et al; SC-COSMO Modeling Group. The household secondary attack rate of SARS-CoV-2: a rapid review. Clin Infect Dis. Published online October 12, 2020:ciaa1558. doi:10.1093/cid/ciaa1558 PubMed Google Scholar

12.

Freeman MF, Tukey JW. Transformations related to the angular and the square root. Annals Math Stat. 1950;21(4):607-611. doi:10.1214/aoms/1177729756 Google Scholar Crossref

13.

Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557-560. doi:10.1136/bmj.327.7414.557 PubMed Google Scholar Crossref

14.

Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Software. 2010;36(3):1-48. doi:10.18637/jss.v036.i03 Google Scholar Crossref

15.

R Core Team. R: a language and environment for statistical computing. Accessed November 13, 2020. https://www.gbif.org/tool/81287/r-a-language-and-environment-for-statistical-computing

16.

Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994;50(4):1088-1101. doi:10.2307/2533446 PubMed Google Scholar Crossref

17.

Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629-634. doi:10.1136/bmj.315.7109.629 PubMed Google Scholar Crossref

18.

Duval S, Tweedie R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics. 2000;56(2):455-463. doi:10.1111/j.0006-341X.2000.00455.x PubMed Google Scholar Crossref

19.

Adamik B, Bawiec M, Bezborodov V, et al. Bounds on the total number of SARS-CoV-2 infections: the link between severeness rate, household attack rate and the number of undetected cases. Published August 15, 2020. Accessed November 11, 2020. https://docisolation.prod.fire.glass/?guid=8579b2af-bdb0-4d1f-f538-bc52f86d984e

20.

Arnedo-Pena A, Sabater-Vidal S, Meseguer-Ferrer N, et al. COVID-19 secondary attack rate and risk factors in household contacts in Castellon (Spain): preliminary report. Enfermedades Emergentes. 2020;19(2):64-70. Accessed November 11, 2020. https://docisolation.prod.fire.glass/?guid=45f61a53-bdcc-40ab-ded8-dd9646aa077c Google Scholar

21.

Bae S, Kim H, Jung T-Y, et al. Epidemiological characteristics of COVID-19 outbreak at fitness centers in Cheonan, Korea. J Korean Med Sci. 2020;35(31):e288. doi:10.3346/jkms.2020.35.e288 PubMed Google Scholar

22.

Bi Q, Wu Y, Mei S, et al. Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study. Lancet Infect Dis. 2020;20(8):911-919. doi:10.1016/S1473-3099(20)30287-5 PubMed Google Scholar Crossref

23.

Böhmer MM, Buchholz U, Corman VM, et al. Investigation of a COVID-19 outbreak in Germany resulting from a single travel-associated primary case: a case series. Lancet Infect Dis. 2020;20(8):920-928. doi:10.1016/S1473-3099(20)30314-5 PubMed Google Scholar Crossref

24.

Boscolo-Rizzo P, Borsetto D, Spinato G, et al. New onset of loss of smell or taste in household contacts of home-isolated SARS-CoV-2-positive subjects. Eur Arch Otorhinolaryngol. 2020;277(9):2637-2640. doi:10.1007/s00405-020-06066-9 PubMed Google Scholar Crossref

25.

Burke RM. Active monitoring of persons exposed to patients with confirmed COVID-19—United States, January-February 2020. MMWR Morb Mortal Wkly Rep. 2020;69:245-246. doi:10.15585/mmwr.mm6909e1 Google Scholar Crossref

26.

Chaw L, Koh WC, Jamaludin SA, Naing L, Alikhan MF, Wong J. SARS-CoV-2 transmission in different settings: analysis of cases and close contacts from the Tablighi cluster in Brunei Darussalam. Emerg Infect Dis. 2020;26(11):2598-2606. doi:10.3201/eid2611.202263 Google Scholar Crossref

27.

Chen Y, Wang AH, Yi B, et al. [Epidemiological characteristics of infection in COVID-19 close contacts in Ningbo city]. Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(5):667-671. doi:10.3760/cma.j.cn112338-20200304-00251 PubMed Google Scholar

28.

Cheng HY, Jian SW, Liu DP, Ng TC, Huang WT, Lin HH; Taiwan COVID-19 Outbreak Investigation Team. Contact tracing assessment of COVID-19 transmission dynamics in Taiwan and risk at different exposure periods before and after symptom onset. JAMA Intern Med. 2020;180(9):1156-1163. doi:10.1001/jamainternmed.2020.2020
Article PubMed Google Scholar Crossref

29.

Dattner I, Goldberg Y, Katriel G, et al. The role of children in the spread of COVID-19: Using household data from Bnei Brak, Israel, to estimate the relative susceptibility and infectivity of children. medRxiv. Preprint published online October 11, 2020. doi:10.1101/2020.06.03.20121145 Google Scholar

30.

Dawson P, Rabold EM, Laws RL, et al. Loss of taste and smell as distinguishing symptoms of COVID-19. Clin Infect Dis. 2020;ciaa799. doi:10.1093/cid/ciaa799 PubMed Google Scholar

31.

Dong XC, Li JM, Bai JY, et al. [Epidemiological characteristics of confirmed COVID-19 cases in Tianjin]. Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(5):638-641. doi:10.3760/cma.j.cn112338-20200221-00146 PubMed Google Scholar

32.

Doung-ngern P, Suphanchaimat R, Panjagampatthana A, et al. Case-control study of use of personal protective measures and risk for SARS-CoV 2 infection, Thailand. Emerg Infect Dis. 2020;26(11):2607-2616. doi:10.3201/eid2611.203003 PubMed Google Scholar Crossref

33.

Draper AD, Dempsey KE, Boyd RH, et al. The first 2 months of COVID-19 contact tracing in the Northern Territory of Australia, March-April 2020. Commun Dis Intell (2018). 2020;44:44.PubMed Google Scholar

34.

Fateh-Moghadam P, Battisti L, Molinaro S, et al. Contact tracing during phase I of the COVID-19 pandemic in the Province of Trento, Italy: key findings and recommendations. medRxiv. Preprint published online July 29, 2020. doi:10.1101/2020.07.16.20127357 Google Scholar

35.

Han T. Outbreak investigation: transmission of COVID-19 started from a spa facility in a local community in Korea. Epidemiol Health. 2020;42(0):e2020056-e2020050. doi:10.4178/epih.e2020056 PubMed Google Scholar Crossref

36.

Hu S, Wang W, Wang Y, et al. Infectivity, susceptibility, and risk factors associated with SARS-CoV-2 transmission under intensive contact tracing in Hunan, China. medRxiv. Preprint published online November 3, 2020. doi:10.1101/2020.07.23.20160317 Google Scholar

37.

Hua CZ, Miao ZP, Zheng JS, et al. Epidemiological features and viral shedding in children with SARS-CoV-2 infection. J Med Virol. Published online June 15, 2020. doi:10.1002/jmv.26180 PubMed Google Scholar

38.

Islam SS, Noman ASM. Transmission dynamics and contact tracing assessment of COVID-19 in Chattogram, Bangladesh and potential risk of close contacts at different exposure settings. Published October 12, 2020. Accessed November 11, 2020. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3677863

39.

Jing Q-L, Liu M-J, Zhang ZB, et al. Household secondary attack rate of COVID-19 and associated determinants in Guangzhou, China: a retrospective cohort study. Lancet Infect Dis. 2020;20(10):1141-1150. doi:10.1016/S1473-3099(20)30471-0 PubMed Google Scholar Crossref

40.

Kim J, Choe YJ, Lee J, et al. Role of children in household transmission of COVID-19. Arch Dis Child. 2020;archdischild-2020-319910. doi:10.1136/archdischild-2020-319910 PubMed Google Scholar

41.

COVID-19 National Emergency Response Center, Epidemiology and Case Management Team, Korea Centers for Disease Control and Prevention. Coronavirus disease-19: summary of 2,370 contact investigations of the first 30 cases in the Republic of Korea. Osong Public Health Res Perspect. 2020;11(2):81-84. doi:10.24171/j.phrp.2020.11.2.04 PubMed Google Scholar Crossref

42.

Laxminarayan R, Wahl B, Dudala SR, et al. Epidemiology and transmission dynamics of COVID-19 in two Indian states. Science. 2020;370(6517):691-697. doi:10.1126/science.abd7672 PubMed Google Scholar Crossref

43.

Lee M, Eun Y, Park K, Heo J, Son H. Follow-up investigation of asymptomatic COVID-19 cases at diagnosis in Busan, Korea. Epidemiol Health. 2020;42:e2020046. doi:10.4178/epih.e2020046 PubMed Google Scholar

44.

Lewis NM, Chu VT, Ye D, et al. Household transmission of SARS-CoV-2 in the United States. Clin Infect Dis. Published online August 16, 2020. doi:10.1093/cid/ciaa1166 Google Scholar

45.

Li W, Zhang B, Lu J, et al. Characteristics of household transmission of COVID-19. Clin Infect Dis. 2020;71(8):1943-1946. doi:10.1093/cid/ciaa450 PubMed Google Scholar Crossref

46.

Liu T, Liang W, Zhong H, et al. Risk factors associated with COVID-19 infection: a retrospective cohort study based on contacts tracing. Emerg Microbes Infect. 2020;9(1):1546-1553. doi:10.1080/22221751.2020.1787799 PubMed Google Scholar Crossref

47.

Lopez Bernal J, Panagiotopoulos N, Byers C, et al. Transmission dynamics of COVID-19 in household and community settings in the United Kingdom. medRxiv. Preprint published online August 22, 2020. doi:10.1101/2020.08.19.20177188 Google Scholar

48.

Luo L, Liu D, Liao X, et al. Contact settings and risk for transmission in 3410 close contacts of patients with COVID-19 in Guangzhou, China: a prospective cohort study. Ann Intern Med. Published August 13, 2020. doi:10.7326/M20-2671 PubMed Google Scholar

49.

Lyngse FP, Kirkeby CT, Halasa T, et al. COVID-19 transmission within Danish households: a nationwide study from lockdown to reopening. medRxiv. Preprint published online September 9, 2020. doi:10.1101/2020.09.09.20191239 Google Scholar

50.

Malheiro R, Figueiredo AL, Magalhães JP, et al. Effectiveness of contact tracing and quarantine on reducing COVID-19 transmission: a retrospective cohort study. Public Health. 2020;189:54-59. doi:10.1016/j.puhe.2020.09.012 PubMed Google Scholar Crossref

51.

Park YJ, Choe YJ, Park O, et al; COVID-19 National Emergency Response Center, Epidemiology and Case Management Team. Contact tracing during coronavirus disease outbreak, South Korea, 2020. Emerg Infect Dis. 2020;26(10):2465-2468. doi:10.3201/eid2610.201315 PubMed Google Scholar Crossref

52.

Park SY, Kim Y-M, Yi S, et al. Coronavirus disease outbreak in call center, South Korea. Emerg Infect Dis. 2020;26(8):1666-1670. doi:10.3201/eid2608.201274 PubMed Google Scholar Crossref

53.

Patel A, Charani E, Ariyanayagam D, et al. New-onset anosmia and ageusia in adult patients diagnosed with SARS-CoV-2 infection. Clin Microbiol Infect. Published online June 2 2020.PubMed Google Scholar

54.

Phiriyasart F, Chantutanon S, Salaeh F, et al. Outbreak investigation of coronavirus disease (COVID-19) among Islamic missionaries in southern Thailand, April 2020. Outbreak, Surveillance, Investigation, and Response (OSIR) Journal. 2020;13(2). Accessed November 11, 2020. http://www.osirjournal.net/index.php/osir/article/view/195

55.

Rosenberg ES, Dufort EM, Blog DS, et al; New York State Coronavirus 2019 Response Team. COVID-19 testing, epidemic features, hospital outcomes, and household prevalence, New York State—March 2020. Clin Infect Dis. 2020;71(8):1953-1959. doi:10.1093/cid/ciaa549 PubMed Google Scholar Crossref

56.

Shah K, Desai N, Saxena D, Mavalankar D, Mishra U, Patel GC. Household secondary attack rate in Gandhinagar district of Gujarat state from Western India. medRxiv. Preprint published online September 5, 2020. doi:10.1101/2020.09.03.20187336 Google Scholar

57.

Son H, Lee H, Lee M, et al. Epidemiological characteristics of and containment measures for COVID-19 in Busan, South Korea. Epidemiology and Health. 2020;42:e2020035. doi:10.4178/epih.e2020035 PubMed Google Scholar

58.

Sun WW, Ling F, Pan JR, et al. [Epidemiological characteristics of COVID-19 family clustering in Zhejiang Province]. Zhonghua Yu Fang Yi Xue Za Zhi. 2020;54(6):625-629. doi:10.3760/cma.j.cn112150-20200227-00199 PubMed Google Scholar

59.

Teherani MF, Kao CM, Camacho-Gonzalez A, et al. Burden of illness in households with SARS-CoV-2 infected children. J Pediatric Infect Dis Soc. 2020;9(5):613-616. doi:10.1093/jpids/piaa097 PubMed Google Scholar Crossref

60.

van der Hoek W, Backer JA, Bodewes R, et al. [The role of children in the transmission of SARS-CoV-2]. Ned Tijdschr Geneeskd. 2020;164:D5140.PubMed Google Scholar

61.

Wang Z, Ma W, Zheng X, Wu G, Zhang R. Household transmission of SARS-CoV-2. J Infect. 2020;81(1):179-182. doi:10.1016/j.jinf.2020.03.040 PubMed Google Scholar Crossref

62.

Wang X, Pan Y, Zhang D, et al. Basic epidemiological parameter values from data of real-world in mega-cities: the characteristics of COVID-19 in Beijing, China. BMC Infect Dis. 2020;20(1):526. doi:10.1186/s12879-020-05251-9 PubMed Google Scholar Crossref

63.

Wang Y, Tian H, Zhang L, et al. Reduction of secondary transmission of SARS-CoV-2 in households by face mask use, disinfection and social distancing: a cohort study in Beijing, China. BMJ Glob Health. 2020;5(5):e002794. doi:10.1136/bmjgh-2020-002794 PubMed Google Scholar

64.

Wang X, Zhou Q, He Y, et al. Nosocomial outbreak of COVID-19 pneumonia in Wuhan, China. Eur Respir J. 2020;55(6):2000544. doi:10.1183/13993003.00544-2020 PubMed Google Scholar

65.

Wu J, Huang Y, Tu C, et al. Household transmission of SARS-CoV-2, Zhuhai, China, 2020. Clin Infect Dis. Published online May 11, 2020;ciaa557. doi:10.1093/cid/ciaa557 PubMed Google Scholar

66.

Wu Y, Song S, Kao Q, Kong Q, Sun Z, Wang B. Risk of SARS-CoV-2 infection among contacts of individuals with COVID-19 in Hangzhou, China. Public Health. 2020;185:57-59. doi:10.1016/j.puhe.2020.05.016 PubMed Google Scholar Crossref

67.

Xin H, Jiang F, Xue A, et al. Risk factors associated with occurrence of COVID-19 among household persons exposed to patients with confirmed COVID-19 in Qingdao Municipal, China. Transbound Emerg Dis. 2020. doi:10.1111/tbed.13743 PubMed Google Scholar

68.

Yu HJ, Hu YF, Liu XX, et al. Household infection: the predominant risk factor for close contacts of patients with COVID-19. Travel Med Infect Dis. 2020;36:101809. doi:10.1016/j.tmaid.2020.101809 PubMed Google Scholar

69.

Yung CF, Kam KQ, Chong CY, et al. Household transmission of SARS-CoV-2 from adults to children. J Ped. 2020;225:249-251. doi:10.1016/j.jpeds.2020.07.009 Google Scholar Crossref

70.

Zhang W, Cheng W, Luo L, et al. Secondary transmission of coronavirus disease from presymptomatic persons, China. Emerg Infect Dis. 2020;26(8):1924-1926. doi:10.3201/eid2608.201142 PubMed Google Scholar Crossref

71.

Zhang JZ, Zhou P, Han DB, et al. [Investigation on a cluster epidemic of COVID-19 in a supermarket in Liaocheng, Shandong province]. Zhonghua Liu Xing Bing Xue Za Zhi. Published April 27, 2020.PubMed Google Scholar

72.

Zhuang YL, Zhang YT, Li M, et al. [Analysis on the cluster epidemic of coronavirus disease 2019 in Guangdong Province]. Zhonghua Yu Fang Yi Xue Za Zhi. 2020;54(7):720-725.PubMed Google Scholar

73.

Stringhini S, Wisniak A, Piumatti G, et al. Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): a population-based study. Lancet. 2020;396(10247):313-319. doi:10.1016/S0140-6736(20)31304-0 PubMed Google Scholar Crossref

74.

Yang K, Wang L, Li F, et al. Analysis of epidemiological characteristics of coronavirus 2019 infection and preventive measures in Shenzhen China: a heavy population city. medRxiv. Preprint published online March 3, 2020. doi:10.1101/2020.02.28.20028555 Google Scholar

75.

Fontanet A, Grant R, Tondeur L, et al. SARS-CoV-2 infection in primary schools in northern France: A retrospective cohort study in an area of high transmission. medRxiv. Preprint published online June 29, 2020. doi:10.1101/2020.06.25.20140178 Google Scholar

76.

Chan LY, Wong JT, Li PK, Lui SF, Fung H, Sung J. Risk of transmission of severe acute respiratory syndrome to household contacts by infected health care workers and patients. Am J Med. 2004;116(8):559-560. doi:10.1016/j.amjmed.2003.11.011 PubMed Google Scholar Crossref

77.

Goh DL, Lee BW, Chia KS, et al. Secondary household transmission of SARS, Singapore. Emerg Infect Dis. 2004;10(2):232-234. doi:10.3201/eid1002.030676 PubMed Google Scholar Crossref

78.

Lau JT, Lau M, Kim JH, Tsui HY, Tsang T, Wong TW. Probable secondary infections in households of SARS patients in Hong Kong. Emerg Infect Dis. 2004;10(2):235-243. doi:10.3201/eid1002.030626 PubMed Google Scholar

79.

Wilson-Clark SD, Deeks SL, Gournis E, et al. Household transmission of SARS, 2003. CMAJ. 2006;175(10):1219-1223. doi:10.1503/cmaj.050876 PubMed Google Scholar Crossref

80.

Ou J, Li Q, Zeng G, Dun Z; Centers for Disease Control and Prevention (CDC). Efficiency of quarantine during an epidemic of severe acute respiratory syndrome—Beijing, China, 2003. MMWR Morb Mortal Wkly Rep. 2003;52(43):1037-1040.PubMed Google Scholar

81.

Tuan PA, Horby P, Dinh PN, et al; WHO SARS Investigation Team in Vietnam. SARS transmission in Vietnam outside of the health-care setting. Epidemiol Infect. 2007;135(3):392-401. doi:10.1017/S0950268806006996 PubMed Google Scholar Crossref

82.

Pang X, Zhu Z, Xu F, et al. Evaluation of control measures implemented in the severe acute respiratory syndrome outbreak in Beijing, 2003. JAMA. 2003;290(24):3215-3221. doi:10.1001/jama.290.24.3215
Article PubMed Google Scholar Crossref

83.

Al Hosani FI, Kim L, Khudhair A, et al. Serologic follow-up of Middle East respiratory syndrome coronavirus cases and contacts—Abu Dhabi, United Arab Emirates. Clin Infect Dis. 2019;68(3):409-418. doi:10.1093/cid/ciy503 PubMed Google Scholar Crossref

84.

Arwady MA, Alraddadi B, Basler C, et al. Middle East respiratory syndrome coronavirus transmission in extended family, Saudi Arabia, 2014. Emerg Infect Dis. 2016;22(8):1395-1402. doi:10.3201/eid2208.152015 PubMed Google Scholar Crossref

85.

Assiri A, McGeer A, Perl TM, et al; KSA MERS-CoV Investigation Team. Hospital outbreak of Middle East respiratory syndrome coronavirus. N Engl J Med. 2013;369(5):407-416. doi:10.1056/NEJMoa1306742 PubMed Google Scholar Crossref

86.

Drosten C, Meyer B, Müller MA, et al. Transmission of MERS-coronavirus in household contacts. N Engl J Med. 2014;371(9):828-835. doi:10.1056/NEJMoa1405858 PubMed Google Scholar Crossref

87.

Memish ZA, Al-Tawfiq JA, Alhakeem RF, et al. Middle East respiratory syndrome coronavirus (MERS-CoV): a cluster analysis with implications for global management of suspected cases. Travel Med Infect Dis. 2015;13(4):311-314. doi:10.1016/j.tmaid.2015.06.012 PubMed Google Scholar Crossref

88.

Payne DC, Biggs HM, Al-Abdallat MM, et al. Multihospital outbreak of a Middle East respiratory syndrome coronavirus deletion variant, Jordan: a molecular, serologic, and epidemiologic investigation. Open Forum Infect Dis. 2018;5(5):ofy095. doi:10.1093/ofid/ofy095 PubMed Google Scholar

89.

Van Kerkhove MD, Alaswad S, Assiri A, et al. Transmissibility of MERS-CoV infection in closed setting, Riyadh, Saudi Arabia, 2015. Emerg Infect Dis. 2019;25(10):1802-1809. doi:10.3201/eid2510.190130 PubMed Google Scholar Crossref

90.

Esposito S, Bosis S, Niesters HG, et al. Impact of human coronavirus infections in otherwise healthy children who attended an emergency department. J Med Virol. 2006;78(12):1609-1615. doi:10.1002/jmv.20745 PubMed Google Scholar Crossref

91.

Monto AS, DeJonge PM, Callear AP, et al. Coronavirus occurrence and transmission over 8 years in the HIVE cohort of households in Michigan. J Infect Dis. 2020;222(1):9-16. doi:10.1093/infdis/jiaa161 PubMed Google Scholar Crossref

92.

Beale S, Lewer D, Aldridge RW, et al. Household transmission of seasonal coronavirus infections: results from the Flu Watch cohort study. Wellcome Open Research. 2020;5(145):145. doi:10.12688/wellcomeopenres.16055.1 Google Scholar Crossref

93.

Tsang TK, Lau LLH, Cauchemez S, Cowling BJ. Household transmission of influenza virus. Trends Microbiol. 2016;24(2):123-133. doi:10.1016/j.tim.2015.10.012 PubMed Google Scholar Crossref

94.

Ministry of Health, Labour, and Welfare. Avoid the “Three Cs”! Accessed August 5, 2020. https://www.mhlw.go.jp/content/10900000/000619576.pdf

95.

Pang X, Yang P, Li S, et al. Pandemic (H1N1) 2009 among quarantined close contacts, Beijing, People’s Republic of China. Emerg Infect Dis. 2011;17(10):1824-1830. doi:10.3201/eid1710.101344 PubMed Google Scholar Crossref

96.

Tam K, Yousey-Hindes K, Hadler JL. Influenza-related hospitalization of adults associated with low census tract socioeconomic status and female sex in New Haven County, Connecticut, 2007-2011. Influenza Other Respir Viruses. 2014;8(3):274-281. doi:10.1111/irv.12231 PubMed Google Scholar Crossref

97.

Chandrasekhar R, Sloan C, Mitchel E, et al. Social determinants of influenza hospitalization in the United States. Influenza Other Respir Viruses. 2017;11(6):479-488. doi:10.1111/irv.12483 PubMed Google Scholar Crossref

98.

Sloan C, Chandrasekhar R, Mitchel E, Schaffner W, Lindegren ML. Socioeconomic disparities and influenza hospitalizations, Tennessee, USA. Emerg Infect Dis. 2015;21(9):1602-1610. doi:10.3201/eid2109.141861 PubMed Google Scholar Crossref

99.

Viner RM, Mytton OT, Bonell C, et al. Susceptibility to SARS-CoV-2 infection among children and adolescents compared with adults: a systematic review and meta-analysis. JAMA Pediatr. Published September 25, 2020. doi:10.1001/jamapediatrics.2020.4573
Article PubMed Google Scholar

100.

Davies NG, Klepac P, Liu Y, Prem K, Jit M, Eggo RM; CMMID COVID-19 working group. Age-dependent effects in the transmission and control of COVID-19 epidemics. Nat Med. 2020;26(8):1205-1211. doi:10.1038/s41591-020-0962-9 PubMed Google Scholar Crossref

101.

Huang AT, Garcia-Carreras B, Hitchings MDT, et al. A systematic review of antibody mediated immunity to coronaviruses: kinetics, correlates of protection, and association with severity. Nat Commun. 2020;11(1):4704. doi:10.1038/s41467-020-18450-4 PubMed Google Scholar Crossref

102.

Mehta NS, Mytton OT, Mullins EWS, et al. SARS-CoV-2 (COVID-19): what do we know about children? a systematic review. Clin Infect Dis. Published May 11, 2020;ciaa556. doi:10.1093/cid/ciaa556 PubMed Google Scholar

103.

Posfay-Barbe KM, Wagner N, Gauthey M, et al. COVID-19 in children and the dynamics of infection in families. Pediatrics. 2020;146(2):e20201576. doi:10.1542/peds.2020-1576 PubMed Google Scholar

104.

Lee B, Raszka WV Jr. COVID-19 transmission and children: the child is not to blame. Pediatrics. 2020;146(2):e2020004879. doi:10.1542/peds.2020-004879 PubMed Google Scholar

105.

Zhu Y, Bloxham CJ, Hulme KD, et al. Children are unlikely to have been the primary source of household SARS-CoV-2 infections. medRxiv. Preprint published online March 30, 2020. doi:10.1101/2020.03.26.20044826 Google Scholar

106.

L’Huillier AG, Torriani G, Pigny F, Kaiser L, Eckerle I. Culture-competent SARS-CoV-2 in nasopharynx of symptomatic neonates, children, and adolescents. Emerg Infect Dis. 2020;26(10):2494-2497. doi:10.3201/eid2610.202403 Google Scholar Crossref

107.

World Health Organization. Gender and COVID-19. Published May 14, 2020. Accessed November 11, 2020. https://www.who.int/publications/i/item/gender-and-covid-19

108.

Walsh KA, Jordan K, Clyne B, et al. SARS-CoV-2 detection, viral load and infectivity over the course of an infection. J Infect. 2020;81(3):357-371. doi:10.1016/j.jinf.2020.06.067 PubMed Google Scholar Crossref

109.

He X, Lau EHY, Wu P, et al. Temporal dynamics in viral shedding and transmissibility of COVID-19. Nat Med. 2020;26(5):672-675. doi:10.1038/s41591-020-0869-5 PubMed Google Scholar Crossref

110.

Ali ST, Wang L, Lau EHY, et al. Serial interval of SARS-CoV-2 was shortened over time by nonpharmaceutical interventions. Science. 2020;369(6507):1106-1109. doi:10.1126/science.abc9004 PubMed Google Scholar Crossref

111.

Rabaan AA, Al-Ahmed SH, Haque S, et al. SARS-CoV-2, SARS-CoV, and MERS-COV: a comparative overview. Infez Med. 2020;28(2):174-184.PubMed Google Scholar

112.

Petersen E, Koopmans M, Go U, et al. Comparing SARS-CoV-2 with SARS-CoV and influenza pandemics. Lancet Infect Dis. 2020;20(9):e238-e244. doi:10.1016/S1473-3099(20)30484-9 PubMed Google Scholar Crossref

113.

Petrosillo N, Viceconte G, Ergonul O, Ippolito G, Petersen E. COVID-19, SARS and MERS: are they closely related? Clin Microbiol Infect. 2020;26(6):729-734. doi:10.1016/j.cmi.2020.03.026 PubMed Google Scholar Crossref

114.

Fraser C, Riley S, Anderson RM, Ferguson NM. Factors that make an infectious disease outbreak controllable. Proc Natl Acad Sci U S A. 2004;101(16):6146-6151. doi:10.1073/pnas.0307506101 PubMed Google Scholar Crossref

115.

Cowling BJ, Park M, Fang VJ, Wu P, Leung GM, Wu JT. Preliminary epidemiological assessment of MERS-CoV outbreak in South Korea, May to June 2015. Euro Surveill. 2015;20(25):7-13. doi:10.2807/1560-7917.ES2015.20.25.21163 PubMed Google Scholar Crossref

The Covid Rouge The Great Hysteria Pandemic

4 Comments

ke4ram says 4 years ago

No such thing as asymptomatic. You may not notice it but you have symptoms if you are infected. Even Typhoid Mary had symptoms,,, she ignored them.

fresnoman4man says 4 years ago

What a load of nonsense. COVID is a total myth. Recently, a consortium of life scientists debunked the bogus PCR “test” on which this article is based. Also, COVID has never been scientifically identified despite al the lurid nonsense about its manufacture in a bio tech lab in Wuhan. The fear mongering propaganda has been honed for decades so it is quite effective in herding the gullible thru the mazes of misdirects to create the Great Reset as the global elites are calling their new feudalism.

1. hranfred says 4 years ago
  
  Asymptomatic transmission” of SARS-Cov-2 refuted – Conclusively
  
  https://doi.org/10.1038/s41467-020-19802-w
  
  Nature Communications volume 11, Article number: 5917 (2020)
  
  From the abstract:
  
  “No new symptomatic cases and 300 asymptomatic cases (detection rate 0.303/10,000, 95% CI 0.270–0.339/10,000) were identified. There were no positive tests amongst 1,174 close contacts of asymptomatic cases.”
  
  The 300 “asymptomatic Covid-19 positives” and the identified 1,174 close contacts were put in isolation/quarantine for at least two weeks, tested and retested. Viral load testing was done as well.
  
  So there was not a single case of asymptomatic transmission
  
Charles Homer says 4 years ago

As shown in this article, recent information from the FDA clearly shows that we are all unofficial lab rats for the latest approved vaccine:

https://viableopposition.blogspot.com/2020/12/the-pfizer-biontech-covid-19-vaccine.html

The useless eaters have all just become lab rats in what is perhaps the world’s largest medical experiment simply because of the unprecedented haste in which this unprecedented vaccine has been brought to market.