Comprehensive profiling of social mixing patterns in resource poor countries: A mixed methods research protocol.

BACKGROUND: Low-and-middle-income countries (LMICs) bear a disproportionate burden of communicable diseases. Social interaction data inform infectious disease models and disease prevention strategies. The variations in demographics and contact patterns across ages, cultures, and locations significantly impact infectious disease dynamics and pathogen transmission. LMICs lack sufficient social interaction data for infectious disease modeling. METHODS: To address this gap, we will collect qualitative and quantitative data from eight study sites (encompassing both rural and urban settings) across Guatemala, India, Pakistan, and Mozambique. We will conduct focus group discussions and cognitive interviews to assess the feasibility and acceptability of our data collection tools at each site. Thematic and rapid analyses will help to identify key themes and categories through coding, guiding the design of quantitative data collection tools (enrollment survey, contact diaries, exit survey, and wearable proximity sensors) and the implementation of study procedures. We will create three age-specific contact matrices (physical, nonphysical, and both) at each study site using data from standardized contact diaries to characterize the patterns of social mixing. Regression analysis will be conducted to identify key drivers of contacts. We will comprehensively profile the frequency, duration, and intensity of infants' interactions with household members using high resolution data from the proximity sensors and calculating infants' proximity score (fraction of time spent by each household member in proximity with the infant, over the total infant contact time) for each household member. DISCUSSION: Our qualitative data yielded insights into the perceptions and acceptability of contact diaries and wearable proximity sensors for collecting social mixing data in LMICs. The quantitative data will allow a more accurate representation of human interactions that lead to the transmission of pathogens through close contact in LMICs. Our findings will provide more appropriate social mixing data for parameterizing mathematical models of LMIC populations. Our study tools could be adapted for other studies.

Comprehensive profiling of social mixing patterns in resource poor countries: a mixed methods research protocol.

Background: Low-and-middle-income countries (LMICs) bear a disproportionate burden of communicable diseases. Social interaction data inform infectious disease models and disease prevention strategies. The variations in demographics and contact patterns across ages, cultures, and locations significantly impact infectious disease dynamics and pathogen transmission. LMICs lack sufficient social interaction data for infectious disease modeling. Methods: To address this gap, we will collect qualitative and quantitative data from eight study sites (encompassing both rural and urban settings) across Guatemala, India, Pakistan, and Mozambique. We will conduct focus group discussions and cognitive interviews to assess the feasibility and acceptability of our data collection tools at each site. Thematic and rapid analyses will help to identify key themes and categories through coding, guiding the design of quantitative data collection tools (enrollment survey, contact diaries, exit survey, and wearable proximity sensors) and the implementation of study procedures.We will create three age-specific contact matrices (physical, nonphysical, and both) at each study site using data from standardized contact diaries to characterize the patterns of social mixing. Regression analysis will be conducted to identify key drivers of contacts. We will comprehensively profile the frequency, duration, and intensity of infants' interactions with household members using high resolution data from the proximity sensors and calculating infants' proximity score (fraction of time spent by each household member in proximity with the infant, over the total infant contact time) for each household member. Discussion: Our qualitative data yielded insights into the perceptions and acceptability of contact diaries and wearable proximity sensors for collecting social mixing data in LMICs. The quantitative data will allow a more accurate representation of human interactions that lead to the transmission of pathogens through close contact in LMICs. Our findings will provide more appropriate social mixing data for parameterizing mathematical models of LMIC populations. Our study tools could be adapted for other studies.

Changing social contact patterns among US workers during the COVID-19 pandemic: April 2020 to December 2021.

Non-pharmaceutical interventions minimize social contacts, hence the spread of respiratory pathogens such as influenza and SARS-CoV-2. Globally, there is a paucity of social contact data from the workforce. In this study, we quantified two-day contact patterns among USA employees. Contacts were defined as face-to-face conversations, involving physical touch or proximity to another individual and were collected using electronic self-kept diaries. Data were collected over 4 rounds from 2020 to 2021 during the COVID-19 pandemic. Mean (standard deviation) contacts reported by 1456 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 then modeled SARS-CoV-2 transmission at home, work, and community settings. The model revealed reduced relative transmission in all settings in round 1. Subsequently, transmission increased at home and in the community but remained exceptionally low in work settings. To accurately parameterize models of infection transmission and control, we need empirical social contact data that capture human mixing behavior across time.

Social contact patterns among employees in U.S. long-term care facilities during the COVID-19 pandemic, December 2020 to June 2021.

OBJECTIVE: We measured contact patterns using social contact diaries for 157 U.S. long-term care facility employees from December 2020 - June 2021. These data are crucial for analyzing mathematical transmission models and for informing healthcare setting infection control policy. RESULTS: The median number of daily contacts was 10 (IQR 8-11). Household contacts were more likely partially masked than fully masked, more likely to involve physical contact, and longer in duration compared to facility contacts.

Use of surveillance data to elucidate household clustering of SARS-CoV-2 in Fulton County, Georgia a major metropolitan area.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. DISCUSSION: 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.

Factors influencing the decision to receive seasonal influenza vaccination among US corporate non-healthcare workers.

Influenza causes significant mortality and morbidity in the United States (US). Employees are exposed to influenza at work and can spread it to others. The influenza vaccine is safe, effective, and prevents severe outcomes; however, coverage among US adults (50.2%) is below Healthy People 2030 target of 70%. These highlights need for more effective vaccination promotion interventions. Understanding predictors of vaccination acceptance could inform vaccine promotion messages, improve coverage, and reduce illness-related work absences. We aimed to identify factors influencing influenza vaccination among US non-healthcare workers. Using mixed-methods approach, we evaluated factors influencing influenza vaccination among employees in three US companies during April-June 2020. Survey questions were adapted from the WHO seasonal influenza survey. Most respondents (n = 454) were women (272, 59.9%), 20-39 years old (n = 250, 55.1%); white (n = 254, 56.0%); had a college degree (n = 431, 95.0%); and reported receiving influenza vaccine in preceding influenza season (n = 297, 65.4%). Logistic regression model was statistically significant, X (16, N = 450) = 31.6, p = .01. Education [(OR) = 0.3, 95%CI = 0.1-0.6)] and race (OR = 0.4, 95%CI = 0.2-0.8) were significant predictors of influenza vaccine acceptance among participants. The majority had favorable attitudes toward influenza vaccination and reported that physician recommendation would influence their vaccination decisions. Seven themes were identified in qualitative analysis: "Protecting others" (109, 24.0%), "Protecting self" (105, 23.1%), "Vaccine accessibility" (94, 20.7%), "Education/messaging" (71, 15.6%), "Policies/requirements" (15, 3.3%), "Reminders" (9, 2.0%), and "Incentives" (3, 0.7%). Our findings could facilitate the development of effective influenza vaccination promotion messages and programs for employers, and workplace vaccination programs for other diseases such as COVID-19, by public health authorities.

Influenza causes significant mortality and morbidity in the United States (US).The US working-age group (18­64-year-old) bears a huge burden of influenza annually.Influenza vaccination coverage in the working-age group is low.Physicians and employers can influence vaccine acceptance of working adults.Employers can consider practical steps, e.g., incentivizing, or offering vaccine onsite.

Long-term effect of chronic hepatitis B on mortality in HIV-infected persons in a differential HBV transmission setting.

BACKGROUND: There remain gaps in quantifying mortality risk among individuals co-infected with chronic hepatitis B (HBV) and human immunodeficiency virus (HIV) in sub-Saharan African contexts. Among a cohort of HIV-positive individuals in Rwanda, we estimate the difference in time-to mortality between HBV-positive (HIV/HBV co-infected) and HBV-negative (HIV mono-infected) individuals. METHODS: Using a dataset of HIV-infected adults screened for hepatitis B surface antigen (HBsAg) from January to June 2016 in Rwanda, we performed time-to-event analysis from the date of HBsAg results until death or end of study (31 December 2019). We used the Kaplan-Meier method to estimate probability of survival over time and Cox proportional hazard models to adjust for other factors associated with mortality. RESULTS: Of 21,105 available entries, 18,459 (87.5%) met the inclusion criteria. Mean age was 42.3 years (SD = 11.4) and 394 (2.1%) died during follow-up (mortality rate = 45.7 per 100,000 person-months, 95% confidence interval (CI) 41.4-50.4) Mortality rate ratio for co-infection was 1.7, 95% CI 1.1-2.6, however, Cox regression analysis did not show any association with mortality between compared groups. The adjusted analysis of covariates stratified by co-infection status showed that males, residing outside of the capital Kigali, drinking alcohol, WHO-HIV-clinical stage 3 and 4 were associated with increased mortality in this HIV cohort. CONCLUSIONS: HBV infection does not significantly influence mortality among HIV-infected individuals in Rwanda. The current cohort is likely to have survived a period of high-risk exposure to HBV and HIV mortality and limited health care until their diagnosis.

Post-lockdown changes of age-specific susceptibility and its correlation with adherence to social distancing measures.

Social distancing measures are effective in reducing overall community transmission but much remains unknown about how they have impacted finer-scale dynamics. In particular, much is unknown about how changes of contact patterns and other behaviors including adherence to social distancing, induced by these measures, may have impacted finer-scale transmission dynamics among different age groups. In this paper, we build a stochastic age-specific transmission model to systematically characterize the degree and variation of age-specific transmission dynamics, before and after lifting the lockdown in Georgia, USA. We perform Bayesian (missing-)data-augmentation model inference, leveraging reported age-specific case, seroprevalence and mortality data. We estimate that overall population-level transmissibility was reduced to 41.2% with 95% CI [39%, 43.8%] of the pre-lockdown level in about a week of the announcement of the shelter-in-place order. Although it subsequently increased after the lockdown was lifted, it only bounced back to 62% [58%, 67.2%] of the pre-lockdown level after about a month. We also find that during the lockdown susceptibility to infection increases with age. Specifically, relative to the oldest age group (> 65+), susceptibility for the youngest age group (0-17 years) is 0.13 [0.09, 0.18], and it increases to 0.53 [0.49, 0.59] for 18-44 and 0.75 [0.68, 0.82] for 45-64. More importantly, our results reveal clear changes of age-specific susceptibility (defined as average risk of getting infected during an infectious contact incorporating age-dependent behavioral factors) after the lockdown was lifted, with a trend largely consistent with reported age-specific adherence levels to social distancing and preventive measures. Specifically, the older groups (> 45) (with the highest levels of adherence) appear to have the most significant reductions of susceptibility (e.g., post-lockdown susceptibility reduced to 31.6% [29.3%, 34%] of the estimate before lifting the lockdown for the 6+ group). Finally, we find heterogeneity in case reporting among different age groups, with the lowest rate occurring among the 0-17 group (9.7% [6.4%, 19%]). Our results provide a more fundamental understanding of the impacts of stringent lockdown measures, and finer evidence that other social distancing and preventive measures may be effective in reducing SARS-CoV-2 transmission. These results may be exploited to guide more effective implementations of these measures in many current settings (with low vaccination rate globally and emerging variants) and in future potential outbreaks of novel pathogens.

Changing social contact patterns among US workers during the COVID-19 pandemic: April 2020 to December 2021.

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. Teaser: Changes in social contact patterns shape disease dynamics at workplaces in the USA.

Rapid Review of Social Contact Patterns During the COVID-19 Pandemic.

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.

Social contact patterns among employees in 3 U.S. companies during early phases of the COVID-19 pandemic, April to June 2020.

We measured contact patterns using online diaries for 304 employees of 3 U.S. companies working remotely. The median number of daily contacts was 2 (IQR 1-4); majority were conversation (55 %), occurred at home (64 %) and lasted >4 h (38 %). These data are crucial for modeling outbreak control among the workforces.

A modeling study to inform screening and testing interventions for the control of SARS-CoV-2 on university campuses.

University administrators face decisions about how to safely return and maintain students, staff and faculty on campus throughout the 2020-21 school year. We developed a susceptible-exposed-infectious-recovered (SEIR) deterministic compartmental transmission model of SARS-CoV-2 among university students, staff, and faculty. Our goals were to inform planning at our own university, Emory University, a medium-sized university with around 15,000 students and 15,000 faculty and staff, and to provide a flexible modeling framework to inform the planning efforts at similar academic institutions. Control strategies of isolation and quarantine are initiated by screening (regardless of symptoms) or testing (of symptomatic individuals). We explored a range of screening and testing frequencies and performed a probabilistic sensitivity analysis. We found that among students, monthly and weekly screening can reduce cumulative incidence by 59% and 87%, respectively, while testing with a 2-, 4- and 7-day delay between onset of infectiousness and testing results in an 84%, 74% and 55% reduction in cumulative incidence. Smaller reductions were observed among staff and faculty. Community-introduction of SARS-CoV-2 onto campus may be controlled with testing, isolation, contract tracing and quarantine. Screening would need to be performed at least weekly to have substantial reductions beyond disease surveillance. This model can also inform resource requirements of diagnostic capacity and isolation/quarantine facilities associated with different strategies.

Effectiveness of Direct-acting Antivirals for the Treatment of Chronic Hepatitis C in Rwanda: A Retrospective Study.

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.

Multi-Organ Omics-Based Prediction for Adaptive Radiation Therapy Eligibility in Nasopharyngeal Carcinoma Patients Undergoing Concurrent Chemoradiotherapy.

PURPOSE: To investigate the role of different multi-organ omics-based prediction models for pre-treatment prediction of Adaptive Radiotherapy (ART) eligibility in patients with nasopharyngeal carcinoma (NPC). METHODS AND MATERIALS: Pre-treatment contrast-enhanced computed tomographic and magnetic resonance images, radiotherapy dose and contour data of 135 NPC patients treated at Hong Kong Queen Elizabeth Hospital were retrospectively analyzed for extraction of multi-omics features, namely Radiomics (R), Morphology (M), Dosiomics (D), and Contouromics (C), from a total of eight organ structures. During model development, patient cohort was divided into a training set and a hold-out test set in a ratio of 7 to 3 via 20 iterations. Four single-omics models (R, M, D, C) and four multi-omics models (RD, RC, RM, RMDC) were developed on the training data using Ridge and Multi-Kernel Learning (MKL) algorithm, respectively, under 10-fold cross validation, and evaluated on hold-out test data using average area under the receiver-operator-characteristics curve (AUC). The best-performing single-omics model was first determined by comparing the AUC distribution across the 20 iterations among the four single-omics models using two-sided student t-test, which was then retrained using MKL algorithm for a fair comparison with the four multi-omics models. RESULTS: The R model significantly outperformed all other three single-omics models (all p-value<0.0001), achieving an average AUC of 0.942 (95%CI: 0.938-0.946) and 0.918 (95%CI: 0.903-0.933) in training and hold-out test set, respectively. When trained with MKL, the R model (R_MKL) yielded an increased AUC of 0.984 (95%CI: 0.981-0.988) and 0.927 (95%CI: 0.905-0.948) in training and hold-out test set respectively, while demonstrating no significant difference as compared to all studied multi-omics models in the hold-out test sets. Intriguingly, Radiomic features accounted for the majority of the final selected features, ranging from 64% to 94%, in all the studied multi-omics models. CONCLUSIONS: Among all the studied models, the Radiomic model was found to play a dominant role for ART eligibility in NPC patients, and Radiomic features accounted for the largest proportion of features in all the multi-omics models.

Retrospective cohort study of COVID-19 among children in Fulton County, Georgia, March 2020-June 2021.

OBJECTIVE: To describe case rates, testing rates and percent positivity of COVID-19 among children aged 0-18 years by school-age grouping. DESIGN: We 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). SETTING: Fulton County, Georgia. MAIN OUTCOME MEASURES: COVID-19 case rates, testing rates and percent positivity. RESULTS: Over 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. CONCLUSIONS: Low 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.

Risk factors for viral hepatitis C infection in Rwanda: results from a nationwide screening program.

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.

Screening a nation for hepatitis C virus elimination: a cross-sectional study on prevalence of hepatitis C and associated risk factors in the Rwandan general population.

OBJECTIVES: We 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. DESIGN: We 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. SETTING: HCV 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. PARTICIPANTS: This 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 MEASURES: Two markers were examined: the presence of HCV antibodies and HCV RNA VL. RESULTS: Among 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 (<25 year olds) having a prevalence of 2.20% (95% CIs: 1.93% to 2.50%) (crude OR=8.78). After adjustment for covariates, an association remained between anti-HCV prevalence and age (p<0.001), province (p<0.001) and socioeconomic status (p<0.001). Of the 3771 anti-HCV-positive individuals who had an available HCV RNA VL result, 2099 (55.66%, 95% CI: 54.06% to 57.25%) had a detectable HCV RNA VL. Age was also associated with HCV viraemia (p<0.001). CONCLUSION: Results 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.

Vesicular Delivery of the Antifungal Antibiotics of Lysobacter enzymogenes C3.

Lysobacter enzymogenes C3 is a predatory strain of Gram-negative gliding bacteria that produces antifungal antibiotics by the polyketide synthetic pathway. Outer membrane vesicles (OMV) are formed as a stress response and can deliver virulence factors to host cells. The production of OMV by C3 and their role in antifungal activity are reported here. Vesicles in the range of 130 to 150 nm in diameter were discovered in the cell-free supernatants of C3 cultures. These OMV contain molecules characteristic of bacterial outer membranes, such as lipopolysaccharide and phospholipids. In addition, they contain chitinase activity and essentially all of the heat-stable antifungal activity in cell supernatants. We show here that C3 OMV can directly inhibit growth of the yeast Saccharomyces cerevisiae as well as that of the filamentous fungus Fusarium subglutinans The activity is dependent on physical contact between OMV and the cells. Furthermore, fluorescent lipid labeling of C3 OMV demonstrated transfer of the membrane-associated probe to yeast cells, suggesting the existence of a mechanism of delivery for membrane-associated molecules. Mass spectrometric analysis of C3 OMV extracts indicates the presence of molecules with molecular weights identical to some of the previously identified antifungal products of C3. These data together suggest that OMV act as an important remote mobile component of predation by LysobacterIMPORTANCE The data presented here suggest a newly discovered function of outer membrane vesicles (OMV) that are produced from the outer membrane of the bacterial species Lysobacter enzymogenes strain C3. We show that these OMV can be released from the surface of the cells to deliver antibiotics to target fungal organisms as a mechanism of killing or growth inhibition. Understanding the role of OMV in antibiotic delivery can generally lead to improved strategies for dealing with antibiotic-resistant organisms. These results also add to the evidence that some bacterially produced antibiotics can be discovered and purified using methods designed for isolation of nanoscale vesicles. Information on these systems can lead to better identification of active molecules or design of delivery vehicles for these molecules.

Chd8 mediates cortical neurogenesis via transcriptional regulation of cell cycle and Wnt signaling.

De novo mutations in CHD8 are strongly associated with autism spectrum disorder, but the basic biology of CHD8 remains poorly 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.