Project description:Coronavirus disease 2019 (COVID-19) vaccines are highly efficacious at preventing symptomatic infection, severe disease, and death. Most of the evidence that COVID-19 vaccines also reduce transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is based on retrospective, observational studies. Specifically, an increasing number of studies are evaluating vaccine effectiveness against the secondary attack rate of SARS-CoV-2 using data available in existing health-care databases or contact-tracing databases. Since these types of databases were designed for clinical diagnosis or management of COVID-19, they are limited in their ability to provide accurate information on infection, infection timing, and transmission events. We highlight challenges with using existing databases to identify transmission units and confirm potential SARS-CoV-2 transmission events. We discuss the impact of common diagnostic testing strategies, including event-prompted and infrequent testing, and illustrate their potential biases in estimating vaccine effectiveness against the secondary attack rate of SARS-CoV-2. We articulate the need for prospective observational studies of vaccine effectiveness against the SARS-CoV-2 secondary attack rate, and we provide design and reporting considerations for studies using retrospective databases.
Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spread by direct, indirect, or close contact with infected people via infected respiratory droplets or saliva. Crowded indoor environments with sustained close contact and conversations are a particularly high-risk setting. We performed a meta-analysis through July 29, 2020 of SARS-CoV-2 household secondary attack rate (SAR), disaggregating by several covariates (contact type, symptom status, adult/child contacts, contact sex, relationship to index case, index case sex, number of contacts in household, coronavirus). We identified 40 relevant published studies that report household secondary transmission. The estimated overall household SAR was 18.8% (95% confidence interval [CI]: 15.4%-22.2%), which is higher than previously observed SARs for SARS-CoV and MERS-CoV. We observed that household SARs were significantly higher from symptomatic index cases than asymptomatic index cases, to adult contacts than children contacts, to spouses than other family contacts, and in households with one contact than households with three or more contacts. To prevent the spread of SARS-CoV-2, people are being asked to stay at home worldwide. With suspected or confirmed infections referred to isolate at home, household transmission will continue to be a significant source of transmission.
Project description:Contact tracing data of SARS-CoV-2 Omicron variant cases during December 2021 in Cantabria, Spain, showed increased transmission (secondary attack rate 39%) compared with Delta cases (secondary attack rate 26%), uninfluenced by vaccination status. Incubation and serial interval periods were also reduced. Half of Omicron transmissions happened before symptom onset in the index case-patient.
Project description:Analysis of 772 complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from early in the Boston-area epidemic revealed numerous introductions of the virus, a small number of which led to most cases. The data revealed two superspreading events. One, in a skilled nursing facility, led to rapid transmission and significant mortality in this vulnerable population but little broader spread, whereas other introductions into the facility had little effect. The second, at an international business conference, produced sustained community transmission and was exported, resulting in extensive regional, national, and international spread. The two events also differed substantially in the genetic variation they generated, suggesting varying transmission dynamics in superspreading events. Our results show how genomic epidemiology can help to understand the link between individual clusters and wider community spread.
Project description:BackgroundWe estimated the secondary attack rate of SARS-CoV-2 among household contacts of PCR-confirmed cases of COVID-19 in rural Kenya and analysed risk factors for transmission.MethodsWe enrolled incident PCR-confirmed cases and their household members. At baseline, a questionnaire, a blood sample, and naso-oropharyngeal swabs were collected. Household members were followed 4, 7, 10, 14, 21 and 28 days after the date of the first PCR-positive in the household; naso-oropharyngeal swabs were collected at each visit and used to define secondary cases. Blood samples were collected every 1-2 weeks. Symptoms were collected in a daily symptom diary. We used binomial regression to estimate secondary attack rates and survival analysis to analyse risk factors for transmission.ResultsA total of 119 households with at least one positive household member were enrolled between October 2020 and September 2022, comprising 503 household members; 226 remained in follow-up at day 14 (45%). A total of 43 secondary cases arose within 14 days of identification of the primary case, and 81 household members remained negative. The 7-day secondary attack rate was 4% (95% CI 1%-10%), the 14-day secondary attack rate was 28% (95% CI 17%-40%). Of 38 secondary cases with data, eight reported symptoms (21%, 95% CI 8%-34%). Antibody to SARS-CoV-2 spike protein at enrolment was not associated with risk of becoming a secondary case.ConclusionHouseholds in our setting experienced a lower 7-day attack rate than a recent meta-analysis indicated as the global average (23%-43% depending on variant), and infection is mostly asymptomatic in our setting.
Project description:BackgroundAlthough much of the public health effort to combat coronavirus disease 2019 (COVID-19) has focused on disease control strategies in public settings, transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within households remains an important problem. The nature and determinants of household transmission are poorly understood.MethodsTo address this gap, we gathered and analyzed data from 22 published and prepublished studies from 10 countries (20 291 household contacts) that were available through 2 September 2020. Our goal was to combine estimates of the SARS-CoV-2 household secondary attack rate (SAR) and to explore variation in estimates of the household SAR.ResultsThe overall pooled random-effects estimate of the household SAR was 17.1% (95% confidence interval [CI], 13.7-21.2%). In study-level, random-effects meta-regressions stratified by testing frequency (1 test, 2 tests, >2 tests), SAR estimates were 9.2% (95% CI, 6.7-12.3%), 17.5% (95% CI, 13.9-21.8%), and 21.3% (95% CI, 13.8-31.3%), respectively. Household SARs tended to be higher among older adult contacts and among contacts of symptomatic cases.ConclusionsThese findings suggest that SARs reported using a single follow-up test may be underestimated, and that testing household contacts of COVID-19 cases on multiple occasions may increase the yield for identifying secondary cases.
Project description:It is imperative to advance our understanding of heterogeneities in the transmission of SARS-CoV-2 such as age-specific infectiousness and superspreading. To this end, it is important to exploit multiple data streams that are becoming abundantly available during the pandemic. In this paper, we formulate an individual-level spatiotemporal mechanistic framework to integrate individual surveillance data with geolocation data and aggregate mobility data, enabling a more granular understanding of the transmission dynamics of SARS-CoV-2. We analyze reported cases, between March and early May 2020, in five (urban and rural) counties in the state of Georgia. First, our results show that the reproductive number reduced to below one in about 2 wk after the shelter-in-place order. Superspreading appears to be widespread across space and time, and it may have a particularly important role in driving the outbreak in rural areas and an increasing importance toward later stages of outbreaks in both urban and rural settings. Overall, about 2% of cases were directly responsible for 20% of all infections. We estimate that the infected nonelderly cases (<60 y) may be 2.78 [2.10, 4.22] times more infectious than the elderly, and the former tend to be the main driver of superspreading. Our results improve our understanding of the natural history and transmission dynamics of SARS-CoV-2. More importantly, we reveal the roles of age-specific infectiousness and characterize systematic variations and associated risk factors of superspreading. These have important implications for the planning of relaxing social distancing and, more generally, designing optimal control measures.
Project description:Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiological agent of the Coronavirus Disease 2019 (COVID-19) disease, has moved rapidly around the globe, infecting millions and killing hundreds of thousands. The basic reproduction number, which has been widely used-appropriately and less appropriately-to characterize the transmissibility of the virus, hides the fact that transmission is stochastic, often dominated by a small number of individuals, and heavily influenced by superspreading events (SSEs). The distinct transmission features of SARS-CoV-2, e.g., high stochasticity under low prevalence (as compared to other pathogens, such as influenza), and the central role played by SSEs on transmission dynamics cannot be overlooked. Many explosive SSEs have occurred in indoor settings, stoking the pandemic and shaping its spread, such as long-term care facilities, prisons, meat-packing plants, produce processing facilities, fish factories, cruise ships, family gatherings, parties, and nightclubs. These SSEs demonstrate the urgent need to understand routes of transmission, while posing an opportunity to effectively contain outbreaks with targeted interventions to eliminate SSEs. Here, we describe the different types of SSEs, how they influence transmission, empirical evidence for their role in the COVID-19 pandemic, and give recommendations for control of SARS-CoV-2.
Project description:BackgroundHousehold transmission studies offer the opportunity to assess both secondary attack rate (SAR) and persistence of SARS-CoV-2 antibodies over time.MethodsIn Spring 2020, we invited confirmed COVID-19 cases and their household members to four visits, where we collected nasopharyngeal and serum samples over 28 days after index case onset. We calculated SAR based on the presence of SARS-CoV-2 neutralizing antibodies (NAb) and assessed the persistence of NAb and IgG antibodies (Ab) against SARS-CoV-2 spike glycoprotein and nucleoprotein.ResultsSAR was 45% (39/87), including 35 symptomatic secondary cases. During the initial 28-day follow-up, 62% (80/129) of participants developed NAb. Of those that seroconverted, 90% (63/70), 85% (63/74), and 78% (45/58) still had NAb to early B-lineage SARS-CoV-2 3, 6, and 12 months after the onset of the index case. Anti-spike IgG Ab persisted in 100% (69/69), 97% (72/74), and 93% (55/59) of seroconverted participants after 3, 6, and 12 months, while anti-nucleoprotein IgG Ab levels waned faster, persisting in 99% (68/69), 78% (58/74), and 55% (39/71) of participants, respectively.ConclusionFollowing detection of a COVID-19 case in a household, other members had a high risk of becoming infected. NAb to early B-lineage SARS-CoV-2 persisted for at least a year in most cases.
Project description:BackgroundAccurate estimation of household secondary attack rate (SAR) is crucial to understand the transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The impact of population-level factors, such as transmission intensity in the community, on SAR estimates is rarely explored.MethodsIn this study, we included articles with original data to compute the household SAR. To determine the impact of transmission intensity in the community on household SAR estimates, we explored the association between SAR estimates and the incidence rate of cases by country during the study period.ResultsWe identified 163 studies to extract data on SARs from 326 031 cases and 2 009 859 household contacts. The correlation between the incidence rate of cases during the study period and SAR estimates was 0.37 (95% CI, 0.24-0.49). We found that doubling the incidence rate of cases during the study period was associated with a 1.2% (95% CI, 0.5%-1.8%) higher household SAR.ConclusionsOur findings suggest that the incidence rate of cases during the study period is associated with higher SAR. Ignoring this factor may overestimate SARs, especially for regions with high incidences, which further impacts control policies and epidemiological characterization of emerging variants.