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Non-pharmaceutical interventions minimize social contacts, hence the spread of SARS-CoV-2. We quantified two-day contact patterns among USA employees from 2020–2021 during the COVID-19 pandemic. Contacts were defined as face-to-face conversations, involving physical touch or proximity to another individual and were collected using electronic diaries. Mean (standard deviation) contacts reported by 1,456 participants were 2.5 (2.5), 8.2 (7.1), 9.2 (7.1) and 10.1 (9.5) across round 1 (April–June 2020), 2 (November 2020–January 2021), 3 (June–August 2021), and 4 (November–December 2021), respectively. Between round 1 and 2, we report a 3-fold increase in the mean number of contacts reported per participant with no major increases from round 2–4. We modeled SARS-CoV-2 transmission at home, work, and community. The model revealed reduced relative transmission in all settings in round 1. Subsequently, transmission increased at home and in the community but remained very low in work settings. Contact data are important to parameterize models of infection transmission and control.TeaserChanges in social contact patterns shape disease dynamics at workplaces in the USA.

Households are important for SARS-CoV-2 transmission due to high intensity exposure in enclosed spaces over prolonged durations. We quantified and characterized household clustering of COVID-19 cases in Fulton County, Georgia.We used surveillance data to identify all confirmed COVID-19 cases in Fulton County. Household clustered cases were defined as cases with matching residential address. We described the proportion of COVID-19 cases that were clustered, stratified by age over time and explore trends in age of first diagnosed case within households and subsequent household cases.Between June 1, 2020 and October 31, 2021, 31,449(37%) of 106,233 cases were clustered in households. Children were the most likely to be in household clusters than any other age group. Initially, children were rarely (∼ 10%) the first cases diagnosed in the household but increased to almost 1 of 3 in later periods.One-third of COVID-19 cases in Fulton County were part of a household cluster. Increasingly children were the first diagnosed case, coinciding with temporal trends in vaccine roll-out among the elderly and the return to in-person schooling in Fall 2021. Limitations include restrictions to cases with a valid address and unit number and that the first diagnosed case may not be the infection source for the household.

BackgroundHouseholds are important for SARS-CoV-2 transmission due to high intensity exposure in enclosed living spaces over prolonged durations. Using contact tracing, the secondary attack rate in households is estimated at 18-20%, yet no studies have examined COVID-19 clustering within households to inform testing and prevention strategies. We sought to quantify and characterize household clustering of COVID-19 cases in Fulton County, Georgia and further explore age-specific patterns in household clusters.MethodsWe used state surveillance data to identify all PCR- or antigen-confirmed cases of COVID-19 in Fulton County, Georgia. Household clustered cases were defined as cases with matching residential address with positive sample collection dates within 28 days of one another. We described proportion of COVID-19 cases that were clustered, stratified by age and over time and explored trends in age of first diagnosed case within clusters and age patterns between first diagnosed case and subsequent household cases.ResultsBetween 6/1/20–10/31/21, there were 106,233 COVID-19 cases with available address reported in Fulton County. Of these, 31,449 (37%) were from 12,955 household clusters. Children were more likely to be in household clusters than any other age group and children increasingly accounted for the first diagnosed household case, rising from 11% in February 2021 to a high of 31% in August 2021. Bubble plot density of age of first diagnosed case and subsequent household cases mirror age-specific patterns in household social mixing.DiscussionOne-third of COVID-19 cases in Fulton County were part of a household cluster. High proportion of children in household clusters reflects higher probability of living in larger homes with caregivers or other children. Increasing probability of children as the first diagnosed case coincide with temporal trends in vaccine roll-out among the elderly in March 2021 and the return to in-person schooling for the Fall 2021 semester. While vaccination remains the most effective intervention at reducing household clustering, other household-level interventions should also be emphasized such as timely testing for household members to prevent ongoing transmission.

ObjectiveTo describe case rates, testing rates, and percent positivity of coronavirus disease 2019 (COVID-19) among children aged 0-18 years by school-age grouping.DesignWe abstracted data from Georgia’s State Electronic Notifiable Disease Surveillance System on all 10,437 laboratory-confirmed COVID-19 cases among children aged 0-18 years during March 30, 2020 to June 6, 2021. We examined case rates, testing rates, and percent positivity by school-aged groupings, namely: preschool (0-4 years), elementary school (5-10 years), middle school (11-13 years), and high school (14-18 years) and compared these data among school aged children to those in the adult population (19 years and older).SettingFulton County, Georgia.Main outcome measuresCOVID-19 case rates, testing rates, and percent positivity.ResultsOver time, the proportion of pediatric cases rose substantially from 1.1% (April 2020) to 21.6% (April 2021) of all cases in the county. Age-specific case rates and test rates were consistently highest among high-school aged children. Test positivity was similar across school-age groups, with periods of higher positivity among high-school aged children.ConclusionsLow COVID-19 testing rates among children, especially early in the pandemic, likely underestimate the true burden of disease in this age group. Despite children having lower measured incidence of COVID-19, we found when broader community incidence increased, incidence also increased among all pediatric age groups. As the COVID-19 pandemic continues to evolve, it remains critical to continue learning about the incidence and transmissibility of COVID-19 in children.

Supplemental Digital Content is available in the text., Background: Physical distancing measures aim to reduce person-to-person contact, a key driver of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. In response to unprecedented restrictions on human contact during the coronavirus disease 2019 (COVID-19) pandemic, studies measured social contact patterns under the implementation of physical distancing measures. This rapid review synthesizes empirical data on the changing social contact patterns during the COVID-19 pandemic. Method: We conducted a systematic review using PubMed, Medline, Embase, and Google Scholar following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We descriptively compared the distribution of contacts observed during the pandemic to pre-COVID data across countries to explore changes in contact patterns during physical distancing measures. Results: We identified 12 studies reporting social contact patterns during the COVID-19 pandemic. Eight studies were conducted in European countries and eleven collected data during the initial mitigation period in the spring of 2020 marked by government-declared lockdowns. Some studies collected additional data after relaxation of initial mitigation. Most study settings reported a mean of between 2 and 5 contacts per person per day, a substantial reduction compared to pre-COVID rates, which ranged from 7 to 26 contacts per day. This reduction was pronounced for contacts outside of the home. Consequently, levels of assortative mixing by age substantially declined. After relaxation of initial mitigation, mean contact rates increased but did not return to pre-COVID levels. Increases in contacts post-relaxation were driven by working-age adults. Conclusion: Information on changes in contact patterns during physical distancing measures can guide more realistic representations of contact patterns in mathematical models for SARS-CoV-2 transmission.

ObjectiveTo describe case rates, testing rates and percent positivity of COVID-19 among children aged 0–18 years by school-age grouping.DesignWe abstracted data from Georgia’s State Electronic Notifiable Disease Surveillance System on all 10 437 laboratory-confirmed COVID-19 cases among children aged 0–18 years during 30 March 2020 to 6 June 2021. We examined case rates, testing rates and percent positivity by school-aged groupings, namely: preschool (0–4 years), elementary school (5–10 years), middle school (11–13 years), and high school (14–18 years) and compared these data among school-aged children with those in the adult population (19 years and older).SettingFulton County, Georgia.Main outcome measuresCOVID-19 case rates, testing rates and percent positivity.ResultsOver time, the proportion of paediatric cases rose substantially from 1.1% (April 2020) to 21.6% (April 2021) of all cases in the county. Age-specific case rates and test rates were consistently highest among high-school aged children. Test positivity was similar across school-age groups, with periods of higher positivity among high-school aged children.ConclusionsLow COVID-19 testing rates among children, especially early in the pandemic, likely underestimated the true burden of disease in this age group. Despite children having lower measured incidence of COVID-19, we found when broader community incidence increased, incidence also increased among all paediatric age groups. As the COVID-19 pandemic continues to evolve, it remains critical to continue learning about the incidence and transmissibility of COVID-19 in children.

2.AbstractImportanceDevising control strategies against diseases such as COVID-19 require understanding of contextual social mixing and contact patterns. There has been no standardized multi-site social contact study conducted in workplace settings in the United States that can be used to broadly inform pandemic preparedness policy in these settings.ObjectiveThe study aimed to characterize the patterns of social contacts and mixing across workplace environments, including on-site or when teleworking.DesignThis was a cross-sectional non-probability survey that used standardized social contact diaries to collect data. Employees were requested to record their physical and non-physical contacts in a diary over two consecutive days, documented at the end of each day. Employees from each company were enrolled through email and electronic diaries sent as individual links. Data were collected from April to June 2020.SettingTwo multinational consulting companies and one university administrative department, all located in Georgia, USA.ParticipantsEmployees opted into the study by accepting the invitation on a link sent via email.Main OutcomeThe outcome was median number of contacts per person per day. This was stratified by day of data collection, age, sex, race and ethnicity.ResultsOf 3,835 employees approached, 357 (9.3%) completed the first day of contact diary of which 304 completed both days of contact diary. There was a median of 2 contacts (IQR: 1-4, range: 0-21) per respondent on both day one and two. The majority (55%) of contacts involved conversation only, occurred at home (64%), and cumulatively lasted more than 4 hours (38%). Most contacts were repeated, and within same age groups, though participants aged 30-59 years reported substantial inter-generational mixing with children.ConclusionParticipating employees in 3 surveyed workplaces reported few contacts, similar to studies from the UK and China when shelter-in-place orders were in effect during the pandemic. Many contacts were repeated which may limit the spread of infection. Future rounds are planned to assess changes in contact patterns when employees resume work in the office after the lockdown due to COVID-19 pandemic.

In response to the COVID-19 pandemic, institutions of higher education in almost every nation closed in the first half of 2020. University administrators are now facing decisions about how to safely return students, staff and faculty to campus. To provide a framework to evaluate various strategies, we developed a susceptible-exposed-infectious-recovered (SEIR) type of deterministic compartmental transmission model of SARS-CoV-2 among students, staff and faculty. Our goals were to support the immediate pandemic planning at our own university, and to provide a flexible modeling framework to inform the planning efforts at similar academic institutions. We parameterized the model for our institution, Emory University, a medium-size private university in Atlanta, Georgia. Control strategies of isolation and quarantine are initiated by screening (regardless of symptoms) or testing (of symptomatic individuals). We explore a range of screening and testing frequencies and perform a probabilistic sensitivity analysis of input parameters. We find that monthly and weekly screening can reduce cumulative incidence by 42% and 80% in students, respectively, while testing with a 2-, 4- and 7-day delay results in an 88%, 79% and 67% reduction in cumulative incidence in students over the semester, respectively. Similar reductions are observed among staff and faculty. A testing strategy requires far fewer diagnostic assays to be implemented than a screening assay. Our intervention model is conservative in that we assume a fairly high reproductive number that is not reduced through social distancing measures. We find that community-introduction of SARS-CoV-2 infection onto campus can be controlled with effective testing, isolation, contract tracing and quarantine, but that cases, hospitalization, and (in some scenarios) deaths may still occur. In addition to estimating health impacts, this model can help to predict the resource requirements in terms of diagnostic capacity and isolation/quarantine facilities associated with different strategies.

Background Direct-acting antivirals (DAAs) are becoming accessible in sub-Saharan Africa. This study examined the effectiveness of DAAs in patients treated through the Rwandan national health system and identified factors associated with treatment outcomes. Methods This retrospective study used data from the national hepatitis C virus (HCV) program for patients who initiated DAAs between November 2015 and March 2017. Sustained virological response at 12 weeks after treatment (SVR12) was the primary outcome. Logistic regression models were fit to estimate the relationship between patients’ clinical and demographic characteristics and treatment outcome. Results 894 patients started treatment during the study period; 590 completed treatment and had SVR12 results. Among the 304 patients without SVR12 results, 48 were lost to follow-up and 256 had no SVR12 results but clinical data indicated they likely completed treatment; these patients were classified as nonvirological failure because viral clearance could not be determined. In a per-protocol analysis of 590 patients with SVR12 results, SVR12 was achieved in 540 (92%), and virological failure occurred in 50 (8%). Pretreatment HCV RNA above the median split was associated with virological failure. Intention-to-treat analyses including all patients showed that SVR12 was achieved in 540 (60%), with nonvirological failure in 304 (34%) and virological failure in 50 (6%). Patients in Western Province were more likely to experience nonvirological failure than patients in Kigali, likely owing to the 5–7-hour travel required to access testing and treatment. Conclusions DAAs were effective when implemented through the Rwandan national health system. Decentralization and enhanced financing are underway in Rwanda, which could improve access to treatment and follow-up as the country prepares for HCV elimination.

Background: The epidemiology and risk factors for hepatitis C virus (HCV) infection in Rwanda are not well known; however, this information is crucial to shaping the country’s public health approach to hepatitis C control. Methods: A HCV screening campaign was conducted in the general population in 24 districts previously identified to have a high HCV disease burden. At the time of sample collection, sociodemographic information and self-reported risk factors were collected. Bivariate and multivariate logistic regressions were conducted to assess risk factors independently associated with hepatitis C antibodies (HCVAb) seroprevalence. Results: Out of a total of 326,263 individuals screened for HCVAb, 22,183 (6.8%) were positive. In multivariate analysis, risk factors identified as statistically associated with HCVAb Seroprevalence include history of traditional operation or scarification (OR=1.09, 95% CI: 1.05-1.14), presence of viral hepatitis in the family (OR=1.27, 95% CI: 1.15-1.40), widowed or separated/divorced (OR=1.36, 95% CI: 1.26-1.47), Southern province (OR=1.98, 95% CI: 1.88-2.08) and aged 65 years and older (OR=4.86, 95% CI: 4.62-5.11). Ubudehe category 3 (OR=0.97, 95% CI: 0.93-1.01) and participants using RAMA (Health insurances for employees of public and private sectors) insurance (OR=0.76, 95% CI: 0.70-0.85) had lower odds of HCV seroprevalence. Conclusions: Our findings provide important information for Rwanda’s strategy on prevention and case-finding. Future prevention interventions should aim to reduce transmission through targeted messaging around traditional healing practices and case-finding targeting individuals with a history of exposure or advanced age.

De novo mutations in CHD8 are strongly associated with autism spectrum disorder (ASD), however the basic biology of CHD8 remains poor understood. Here we report that Chd8 knockdown during cortical development results in defective neural progenitor proliferation and differentiation that ultimately manifests in abnormal neuronal morphology and behaviors in adult mice. Transcriptome analysis revealed that while Chd8 stimulates the transcription of cell cycle genes, it also precludes the induction of neural specific genes by regulating the expression of PRC2 complex components. Furthermore, knockdown of Chd8 disrupts the expression of key transducers of Wnt signaling, and enhancing Wnt signaling rescues the transcriptional and behavioral deficits caused by Chd8 knockdown. We propose that these roles of Chd8 and the dynamics of Chd8 expression during development help negotiate the fine balance between neural progenitor proliferation and differentiation. Together, these observations provide new insights into the neurodevelopmental role of Chd8.

ObjectivesWe analysed data collected during programmatic screening activities conducted in 2017 to describe hepatitis C virus (HCV) seroprevalence in the general population and identify associated factors.DesignWe analysed data collected between June and September 2017. For both seroprevalence and viraemia, variations across demographic and geographic factors were assessed and multivariate regression models were fit to identify factors independently associated with each marker. Geospatial data were examined for visualisation.SettingHCV screening was organised within each of the 30 districts in Rwanda. One designated location in each district was selected as the screening site and screening took place for 1 week at each site.ParticipantsThis study included 124 223 male and female volunteers. Anti-HCV-positive individuals were followed up with HCV RNA viral load (VL) testing for infection confirmation.Main outcome measuresTwo markers were examined: the presence of HCV antibodies and HCV RNA VL.ResultsAmong 124 223 individuals screened, 11 003 (8.86%, 95% CIs: 8.70% to 9.02%) were positive for anti-HCV. Anti-HCV prevalence varied by age with the oldest age group (>55 year olds) having a prevalence of 16.46% (95% CIs: 16.14% to 16.80%) and the youngest age group (ConclusionResults suggest that over 55% of individuals who screened positive for HCV-antibodies were chronically infected. Targeted screening for HCV among older individuals is recommended, given the association between age and infection. Further geographical hotspots of HCV infection can also inform targeted screening as Rwanda moves towards HCV elimination.