Chemokine CCL19 and Its Receptors CCR7 and CCRL1 in Chronic Rhinosinusitis.

Background: CCL19 has been shown to predict disease severity in COVID-19 and treatment response in rheumatoid arthritis. CCL19 can exert both pro- and anti-inflammatory effects and is elevated in chronic rhinosinusitis (CRS). However, its role in CRS remains unknown. This study sought to determine the transcriptional changes in CCL19, its receptors, and associated cytokines and their association with disease severity in CRS. Methods: A clinical database of control subjects and patients with CRS was examined. Lund-Kennedy, Lund-Mackay, Sinonasal Outcomes Test 22 (SNOT-22), and rhinosinusitis disability index (RSDI) scores were collected at enrollment. mRNA was extracted from sinonasal tissues and subjected to multiplex gene expression analysis. Gene transcript differences between patients with CRS and controls were compared and correlated with disease severity metrics. Immunohistochemical analyses of CCL19, CCR7, and CCRL1 were conducted to compare differences in protein expression between cohorts. A subgroup analysis was performed to compare transcriptional and protein expression difference between patients with (CRSwNP) and without (CRSsNP) nasal polyps and controls. Results: Thirty-eight subjects (control group, n=7; CRS group, n=31) were included in this study. CCRL1 (p=0.0093) and CCR7 (p=0.017) levels were significantly elevated in CRS compared to those in controls. CCL19 (p=0.038) and CCR7 (p=0.0097) levels were elevated in CRSwNP and CCRL1 was elevated in CRSsNP (p=0.0004). CCR7 expression was significantly elevated in sinonasal epithelial cells in CRSwNP (p=0.04). CCL19 expression was positively correlated with TNFA expression (p<0.0002). CCL19 and CCR7 expression was positively correlated with SNOT-22 and RSDI scores (p<0.05). Conclusion: CCL19 and CCR7 may modulate TNF-α-driven pro-inflammatory signaling and contribute to increased disease severity in CRS. Mechanistic studies are required to further elucidate the role of CCRL1 in CRS.

Risk of Severe COVID-19-Related Outcomes among Patients with Cirrhosis: A Population-Based Cohort Study in Canada.

We assessed the association between cirrhosis and severe COVID-19-related outcomes among people with laboratory-diagnosed COVID-19 infection in British Columbia, Canada. We used data from the British Columbia (BC) COVID-19 Cohort, a population-based cohort that integrates data on all individuals tested for COVID-19, with data on hospitalizations, medical visits, emergency room visits, prescription drugs, chronic conditions, and deaths in the Canadian province of BC. We included all individuals aged ≥18 who tested positive for SARS-CoV-2 by real-time reverse transcription-polymerase chain reaction from 1 January 2021 to 31 December 2021. Multivariable logistic regression models were used to assess the associations of cirrhosis status with COVID-19-related hospitalization and with ICU admission. Of the 162,509 individuals who tested positive for SARS-CoV-2 and were included in the analysis, 768 (0.5%) had cirrhosis. In the multivariable models, cirrhosis was associated with increased odds of hospitalization (aOR = 1.97, 95% CI: 1.58-2.47) and ICU admission (aOR = 3.33, 95% CI: 2.56-4.35). In the analyses stratified by age, we found that the increased odds of ICU admission among people with cirrhosis were present in all the assessed age-groups. Cirrhosis is associated with increased odds of hospitalization and ICU admission among COVID-19 patients.

Postpartum care: Discussions and counseling for the peripartum period.

BACKGROUND: Traditionally, postpartum care is confined to inpatient care immediately post birth and one appointment approximately six weeks postpartum. Data supports a continuum of care model as best for the health of mother and baby. Despite most women having significant concerns about the postpartum period, these concerns are frequently incompletely addressed by providers. We surveyed prenatal and postpartum patients to understand their concerns and experiences discussing postpartum care with providers. METHODS: Cross sectional surveys were administered between June 2019 and May 2021. Principal component analysis was used to show higher than average (positive) or lower than average (negative) conversations with providers about postpartum care examined by race, education, and parity. Chi squared tests were conducted to examine the significance of specific postpartum concerns. RESULTS: 421/450 patient surveys were analyzed, based on completion. Most patients were White (193), had post graduate degrees (188), privately insured (236), married (248), first time pregnant (152), and used doctors as their primary provider (267). Patients with lower education, higher parity and Black patients without postgraduate degrees reported higher than average postpartum counseling. Additionally, most patients expressed significant concerns about postpartum exhaustion (65.8%), breastfeeding (62.3%), pain (61.2%), physical activity (54.9%) and the baby blues (50.4%). CONCLUSIONS: Postpartum concerns are incompletely and inconsistently addressed amongst patients based on race, parity, and education. A continuum of care approach, beginning in the third trimester, through the postpartum period, may provide better counseling to address all patients' concerns.

Emotion Recognition from Spatio-Temporal Representation of EEG Signals via 3D-CNN with Ensemble Learning Techniques.

The recognition of emotions is one of the most challenging issues in human-computer interaction (HCI). EEG signals are widely adopted as a method for recognizing emotions because of their ease of acquisition, mobility, and convenience. Deep neural networks (DNN) have provided excellent results in emotion recognition studies. Most studies, however, use other methods to extract handcrafted features, such as Pearson correlation coefficient (PCC), Principal Component Analysis, Higuchi Fractal Dimension (HFD), etc., even though DNN is capable of generating meaningful features. Furthermore, most earlier studies largely ignored spatial information between the different channels, focusing mainly on time domain and frequency domain representations. This study utilizes a pre-trained 3D-CNN MobileNet model with transfer learning on the spatio-temporal representation of EEG signals to extract features for emotion recognition. In addition to fully connected layers, hybrid models were explored using other decision layers such as multilayer perceptron (MLP), k-nearest neighbor (KNN), extreme learning machine (ELM), XGBoost (XGB), random forest (RF), and support vector machine (SVM). Additionally, this study investigates the effects of post-processing or filtering output labels. Extensive experiments were conducted on the SJTU Emotion EEG Dataset (SEED) (three classes) and SEED-IV (four classes) datasets, and the results obtained were comparable to the state-of-the-art. Based on the conventional 3D-CNN with ELM classifier, SEED and SEED-IV datasets showed a maximum accuracy of 89.18% and 81.60%, respectively. Post-filtering improved the emotional classification performance in the hybrid 3D-CNN with ELM model for SEED and SEED-IV datasets to 90.85% and 83.71%, respectively. Accordingly, spatial-temporal features extracted from the EEG, along with ensemble classifiers, were found to be the most effective in recognizing emotions compared to state-of-the-art methods.

Understanding the impact of mobility on COVID-19 spread: A hybrid gravity-metapopulation model of COVID-19.

The outbreak of the severe acute respiratory syndrome coronavirus 2 started in Wuhan, China, towards the end of 2019 and spread worldwide. The rapid spread of the disease can be attributed to many factors including its high infectiousness and the high rate of human mobility around the world. Although travel/movement restrictions and other non-pharmaceutical interventions aimed at controlling the disease spread were put in place during the early stages of the pandemic, these interventions did not stop COVID-19 spread. To better understand the impact of human mobility on the spread of COVID-19 between regions, we propose a hybrid gravity-metapopulation model of COVID-19. Our modeling framework has the flexibility of determining mobility between regions based on the distances between the regions or using data from mobile devices. In addition, our model explicitly incorporates time-dependent human mobility into the disease transmission rate, and has the potential to incorporate other factors that affect disease transmission such as facemasks, physical distancing, contact rates, etc. An important feature of this modeling framework is its ability to independently assess the contribution of each factor to disease transmission. Using a Bayesian hierarchical modeling framework, we calibrate our model to the weekly reported cases of COVID-19 in thirteen local health areas in Metro Vancouver, British Columbia (BC), Canada, from July 2020 to January 2021. We consider two main scenarios in our model calibration: using a fixed distance matrix and time-dependent weekly mobility matrices. We found that the distance matrix provides a better fit to the data, whilst the mobility matrices have the ability to explain the variance in transmission between regions. This result shows that the mobility data provides more information in terms of disease transmission than the distances between the regions.

Risk factors for COVID-19 hospitalization after COVID-19 vaccination: a population-based cohort study in Canada.

OBJECTIVES: With the uptake of COVID-19 vaccines, there is a need for population-based studies to assess risk factors for COVID-19-related hospitalization after vaccination and how they differ from unvaccinated individuals. METHODS: We used data from the British Columbia COVID-19 Cohort, a population-based cohort that includes all individuals (aged ≥18 years) who tested positive for SARS-CoV-2 by real-time reverse transcription-polymerase chain reaction from January 1, 2021 (after the start of vaccination program) to December 31, 2021. We used multivariable logistic regression models to assess COVID-19-related hospitalization risk by vaccination status and age group among confirmed COVID-19 cases. RESULTS: Of the 162,509 COVID-19 cases included in the analysis, 8,546 (5.3%) required hospitalization. Among vaccinated individuals, an increased odds of hospitalization with increasing age was observed for older age groups, namely those aged 50-59 years (odds ratio [OR] = 2.95, 95% confidence interval [CI]: 2.01-4.33), 60-69 years (OR = 4.82, 95% CI: 3.29, 7.07), 70-79 years (OR = 11.92, 95% CI: 8.02, 17.71), and ≥80 years (OR = 24.25, 95% CI: 16.02, 36.71). However, among unvaccinated individuals, there was a graded increase in odds of hospitalization with increasing age, starting at age group 30-39 years (OR = 2.14, 95% CI: 1.90, 2.41) to ≥80 years (OR = 41.95, 95% CI: 35.43, 49.67). Also, comparing all the age groups to the youngest, the observed magnitude of association was much higher among unvaccinated individuals than vaccinated ones. CONCLUSION: Alongside a number of comorbidities, our findings showed a strong association between age and COVID-19-related hospitalization, regardless of vaccination status. However, age-related hospitalization risk was reduced two-fold by vaccination, highlighting the need for vaccination in reducing the risk of severe disease and subsequent COVID-19-related hospitalization across all population groups.

Association between close interpersonal contact and vaccine hesitancy: Findings from a population-based survey in Canada.

Background: Vaccine hesitancy threatens efforts to bring the coronavirus disease 2019 (COVID-19) pandemic to an end. Given that social or interpersonal contact is an important driver for COVID-19 transmission, understanding the relationship between contact rates and vaccine hesitancy may help identify appropriate targets for strategic intervention. The purpose of this study was to assess the association between interpersonal contact and COVID-19 vaccine hesitancy among a sample of unvaccinated adults in the Canadian province of British Columbia (BC). Methods: Unvaccinated individuals participating in the BC COVID-19 Population Mixing Patterns Survey (BC-Mix) were asked to indicate their level of agreement to the statement, "I plan to get the COVID-19 vaccine." Multivariable multinomial logistic regression was used to assess the association between self-reported interpersonal contact and vaccine hesitancy, adjusting for age, sex, ethnicity, educational attainment, occupation, household size and region of residence. All analyses incorporated survey sampling weights based on age, sex, geography, and ethnicity. Results: Results were based on survey responses collected between March 8, 2021 and December 6, 2021, by a total of 4,515 adults aged 18 years and older. Overall, 56.7% of respondents reported that they were willing to get the COVID-19 vaccine, 27.0% were unwilling and 16.3% were undecided. We found a dose-response association between interpersonal contact and vaccine hesitancy. Compared to individuals in the lowest quartile (least contact), those in the fourth quartile (highest contact), third quartile and second quartile groups were more likely to be vaccine hesitant, with adjusted odd ratios (aORs) of 2.85 (95% CI: 2.02, 4.00), 1.91(95% CI: 1.38, 2.64), 1.78 (95% CI: 1.13, 2.82), respectively. Conclusion: Study findings show that among unvaccinated people in BC, vaccine hesitancy is greater among those who have high contact rates, and hence potentially at higher risk of acquiring and transmitting infection. This may also impact future uptake of booster doses.

Cohort profile: the British Columbia COVID-19 Population Mixing Patterns Survey (BC-Mix).

PURPOSE: Several non-pharmaceutical interventions, such as physical distancing, handwashing, self-isolation, and school and business closures, were implemented in British Columbia (BC) following the first laboratory-confirmed case of COVID-19 on 26 January 2020, to minimise in-person contacts that could spread infections. The BC COVID-19 Population Mixing Patterns Survey (BC-Mix) was established as a surveillance system to measure behaviour and contact patterns in BC over time to inform the timing of the easing/re-imposition of control measures. In this paper, we describe the BC-Mix survey design and the demographic characteristics of respondents. PARTICIPANTS: The ongoing repeated online survey was launched in September 2020. Participants are mainly recruited through social media platforms (including Instagram, Facebook, YouTube, WhatsApp). A follow-up survey is sent to participants 2-4 weeks after completing the baseline survey. Survey responses are weighted to BC's population by age, sex, geography and ethnicity to obtain generalisable estimates. Additional indices such as the Material and Social Deprivation Index, residential instability, economic dependency, and others are generated using census and location data. FINDINGS TO DATE: As of 26 July 2021, over 61 000 baseline survey responses were received of which 41 375 were eligible for analysis. Of the eligible participants, about 60% consented to follow-up and about 27% provided their personal health numbers for linkage with healthcare databases. Approximately 83.5% of respondents were female, 58.7% were 55 years or older, 87.5% identified as white and 45.9% had at least a university degree. After weighting, approximately 50% were female, 39% were 55 years or older, 65% identified as white and 50% had at least a university degree. FUTURE PLANS: Multiple papers describing contact patterns, physical distancing measures, regular handwashing and facemask wearing, modelling looking at impact of physical distancing measures and vaccine acceptance, hesitancy and uptake are either in progress or have been published.

Practices of sickle cell disease genetic screening and testing in the prenatal population.

BACKGROUND: Genetic screening and testing are technologies historically underutilized in Black populations despite predicting diseases like sickle cell disease (SCD), which is predominantly found in Blacks. We surveyed prenatal patients to understand choices, beliefs and experiences surrounding genetic screening and testing, specifically for SCD. METHODS: In this cross-sectional study, we surveyed 322 women during prenatal visits. Responses were analyzed to identify barriers to care and education about testing and screening for SCD. Patients rated whether they agreed or disagreed with statements regarding sickle cell health behaviors. We used χ2 tests to compare categorical variables by self-reported race. Binary logistic regression was used to determine the odds ratios and confidence intervals for each outcome. RESULTS: Women were a mean (SD) age of 33.3 (6.1). 42.9% of patients self-identified as White while 41.3% of patients self- identified as Black. Screening questions were adjusted for differences in race, insurance, and education levels to show significant differences in responses between Blacks and Whites for screening for SCD (p = 0.047, OR 95% CI = 0.455 [0.210-0.989]) and plans to meet with genetic counselors (p = 0.049, OR 95% CI = 0.299 [0.090-0.993]). The statements "if sickle cell is not in their family, then it is likely not in themselves or their children," was significantly different between Black and White populations (p = 0.011, OR 95% CI = 0.207 [0.081-0.526]). CONCLUSION: Our findings suggest gaps in screening, testing, education, and pregnancy management choices between Black and White patients. Research should focus on decreasing these healthcare gaps and improving education that address concerns about SCD for relevant populations.

The direct and indirect impact of COVID-19 pandemic on maternal and child health services in Africa: a scoping review.

INTRODUCTION: The novel coronavirus disease 2019 (COVID-19) continues to disrupt the availability and utilization of routine and emergency health care services, with differing impacts in jurisdictions across the world. In this scoping review, we set out to synthesize documentation of the direct and indirect effect of the pandemic, and national responses to it, on maternal, newborn and child health (MNCH) in Africa. METHODS: A scoping review was conducted to provide an overview of the most significant impacts identified up to March 15, 2022. We searched MEDLINE, Embase, HealthSTAR, Web of Science, PubMed, and Scopus electronic databases. We included peer reviewed literature that discussed maternal and child health in Africa during the COVID-19 pandemic, published from January 2020 to March 2022, and written in English. Papers that did not focus on the African region or an African country were excluded. A data-charting form was developed by the two reviewers to determine which themes to extract, and narrative descriptions were written about the extracted thematic areas. RESULTS: Four-hundred and seventy-eight articles were identified through our literature search and 27 were deemed appropriate for analysis. We identified three overarching themes: delayed or decreased care, disruption in service provision and utilization and mitigation strategies or recommendations. Our results show that minor consideration was given to preserving and promoting health service access and utilization for mothers and children, especially in historically underserved areas in Africa. CONCLUSIONS: Reviewed literature illuminates the need for continued prioritization of maternity services, immunization, and reproductive health services. This prioritization was not given the much-needed attention during the COVID-19 pandemic yet is necessary to shield the continent's most vulnerable population segments from the shocks of current and future global health emergencies.

COVID-19 vaccine hesitancy in Africa: a scoping review.

BACKGROUND: Vaccination against the novel coronavirus is one of the most effective strategies for combating the global Coronavirus disease (COVID-19) pandemic. However, vaccine hesitancy has emerged as a major obstacle in several regions of the world, including Africa. The objective of this rapid review was to summarize the literature on COVID-19 vaccine hesitancy in Africa. METHODS: We searched Scopus, Web of Science, African Index Medicus, and OVID Medline for studies published from January 1, 2020, to March 8, 2022, examining acceptance or hesitancy towards the COVID-19 vaccine in Africa. Study characteristics and reasons for COVID-19 vaccine acceptance were extracted from the included articles. RESULTS: A total of 71 articles met the eligibility criteria and were included in the review. Majority (n = 25, 35%) of the studies were conducted in Ethiopia. Studies conducted in Botswana, Cameroun, Cote D'Ivoire, DR Congo, Ghana, Kenya, Morocco, Mozambique, Nigeria, Somalia, South Africa, Sudan, Togo, Uganda, Zambia, Zimbabwe were also included in the review. The vaccine acceptance rate ranged from 6.9 to 97.9%. The major reasons for vaccine hesitancy were concerns with vaccine safety and side effects, lack of trust for pharmaceutical industries and misinformation or conflicting information from the media. Factors associated with positive attitudes towards the vaccine included being male, having a higher level of education, and fear of contracting the virus. CONCLUSIONS: Our review demonstrated the contextualized and multifaceted reasons inhibiting or encouraging vaccine uptake in African countries. This evidence is key to operationalizing interventions based on facts as opposed to assumptions. Our paper provided important considerations for addressing the challenge of COVID-19 vaccine hesitancy and blunting the impact of the pandemic in Africa.

Mathematical modeling of COVID-19 in British Columbia: An age-structured model with time-dependent contact rates.

Following the emergence of COVID-19 at the end of 2019, several mathematical models have been developed to study the transmission dynamics of this disease. Many of these models assume homogeneous mixing in the underlying population. However, contact rates and mixing patterns can vary dramatically among individuals depending on their age and activity level. Variation in contact rates among age groups and over time can significantly impact how well a model captures observed trends. To properly model the age-dependent dynamics of COVID-19 and understand the impacts of interventions, it is essential to consider heterogeneity arising from contact rates and mixing patterns. We developed an age-structured model that incorporates time-varying contact rates and population mixing computed from the ongoing BC Mix COVID-19 survey to study transmission dynamics of COVID-19 in British Columbia (BC), Canada. Using a Bayesian inference framework, we fit four versions of our model to weekly reported cases of COVID-19 in BC, with each version allowing different assumptions of contact rates. We show that in addition to incorporating age-specific contact rates and mixing patterns, time-dependent (weekly) contact rates are needed to adequately capture the observed transmission dynamics of COVID-19. Our approach provides a framework for explicitly including empirical contact rates in a transmission model, which removes the need to otherwise model the impact of many non-pharmaceutical interventions. Further, this approach allows projection of future cases based on clear assumptions of age-specific contact rates, as opposed to less tractable assumptions regarding transmission rates.

Amelioration of Experimental Hepatotoxicity in Rats by Portulaca oleracea Linn. from Kashmir Himalaya.

BACKGROUND: Traditionally, Portulaca oleracea Linn. is used for treating abscesses, dysentery and liver diseases. In addition, recent studies have reported its efficacy as an analgesic, as neuroprotective, anti-inflammatory, bronchodilatory, and anticancer agent, besides antioxidant, wound healing and other important pharmacological actions. AIMS AND OBJECTIVES: For curing liver diseases, Chinese use juice from the fresh leaves of Portulaca oleracea Linn. Hence, to prove this claim, an in-vivo hepatoprotective study of extracts from Portulaca oleracea Linn. against carbon tetrachloride hepatotoxic rats was carried out. METHODS: The in-vitro antioxidant activity by using 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assay and hepatoprotective activity of extracts of Portulaca oleracea Linn. was assessed against the carbon tetrachloride-induced toxicity rat model. RESULTS: The extracts of Portulaca oleracea Linn produced concentration-dependent percentage inhibition of 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical and most significantly, by methanol extract. Among the extracts, methanol extract showed a significant decrease in Serum glutamic oxaloacetic transaminase (SGOT), Serum glutamic pyruvic transaminase (SGPT), alkaline phosphatase (ALP) levels and a significant increase in total protein (TP) levels against carbon tetrachloride-induced liver toxicity. CONCLUSION: From the results obtained, it was concluded that methanol extract of Portulaca oleracea Linn. possesses significant DPPH free radical scavenging and hepatoprotective potential.

Sun-dried Azolla leaf meal at 10% dietary inclusion improved growth, meat quality, and increased skeletal muscle Ribosomal protein S6 kinase ß1 abundance in growing rabbit.

Rapidly growing human populations and the increased need for high nutritive value meat in terms of low fat, high protein, and low sodium content are the driving reasons for the increase in rabbit meat production. However, dietary protein alternatives to sustain rabbit meat production, without competing with humans for strategic crops are needed. Therefore, the current study was conducted to investigate the effect of Azolla leaf meal (ALM) as a dietary protein source on growth performance, meat quality, and abundance and activation of Ribosomal protein S6 kinase ß1 (p70S6K1), a downstream target of mammalian target of rapamycin signalling pathway and, thus, a key player in the regulation of protein synthesis and muscle mass. For this purpose, 60 weaned male V-Line rabbits were blocked for the initial BW and randomly allotted into four dietary treatments, with 15 replicate per treatment (n = 15/group) as follows: (1) CON group was fed on basal diet contains 0% of ALM, (2) AZ10 group fed on diet containing 10% ALM, (3) AZ20 group fed on diet containing 20% ALM, and (4) AZ30 group fed on diet containing 30% ALM. Rabbits were raised individually, and the experimental period was 42 days. At the end of the experiment, rabbits were euthanised and blood and skeletal muscle samples were collected. Body weight and BW gain were the highest in AZ10 group (P = 0.01), while feed intake was the highest in AZ30 (P = 0.01), feed conversion ratio was the lowest in AZ10 and highest in AZ30 (P = 0.01). Dressing % was the highest in AZ10 and lowest in AZ30 groups (P = 0.01). Muscle cross-sectional area was low in both AZ20 and AZ30 groups compared to CON (P = 0.01). The lysine concentration of Longissimus lumborum muscle increased (P = 0.03) while isoleucine tended to decrease in AZ10 vs CON (P = 0.09). The phosphorylation ratio of skeletal muscle p70S6K1 increased in AZ10 and AZ20 groups (P = 0.05). Therefore, ALM could be included in a growing rabbit diet, up to 10%, while higher doses negatively alter production performance, meat quality, and feed efficiency of growing rabbits.

Quantifying contact patterns: development and characteristics of the British Columbia COVID-19 population mixing patterns survey (BC-Mix)

IntroductionSeveral non-pharmaceutical interventions such as physical distancing, hand washing, self-isolation, and schools and business closures, were implemented in British Columbia (BC) following the first laboratory-confirmed case of coronavirus disease 2019 (COVID-19) on January 26, 2020, to minimize in-person contacts that could spread infections. The BC COVID-19 Population Mixing Patterns survey (BC-Mix) was established as a surveillance system to measure behaviour and contact patterns in BC over time to inform the timing of the easing/re-imposition of control measures. In this paper, we describe the BC-Mix survey design and the demographic characteristics of respondents. MethodsThe ongoing repeated online survey was launched in September 2020. Participants are mainly recruited through social media platforms (including Instagram, Facebook, YouTube, WhatsApp). A follow up survey is sent to participants two to four weeks after completing the baseline survey. Survey responses are weighted to BCs population by age, sex, geography, and ethnicity to obtain generalizable estimates. Additional indices such as the material and social deprivation index, residential instability, economic dependency, and others are generated using census and location data. ResultsAs of July 26, 2021, over 61,000 baseline survey responses were received of which 41,375 were eligible for analysis. Of the eligible participants, about 60% consented to follow up and about 27% provided their personal health numbers for linkage with healthcare databases. Approximately 50% of respondents were female, 39% were 55 years or older, 65% identified as white and 50% had at least a university degree. ConclusionThe pandemic response is best informed by surveillance systems capable of timely assessment of behaviour patterns. BC-Mix survey respondents represent a large cohort of British Columbians providing near real-time information on behavioural and contact patterns in BC. Data from the BC-Mix survey would inform provincial COVID-19-related control measures.

Impact of direct-acting antivirals for HCV on mortality in a large population-based cohort study.

BACKGROUND & AIMS: We evaluated the effect of direct-acting antiviral (DAA)-induced sustained virologic response (SVR) on all-cause, liver- and drug-related mortality in a population-based cohort in British Columbia, Canada. METHODS: We used data from the British Columbia Hepatitis Testers Cohort, which includes people tested for HCV since 1990, linked with data on medical visits, hospitalizations, prescription drugs and mortality. We followed people who received DAAs and people who did not receive any HCV treatment to death or December 31, 2019. We used inverse probability of treatment weighting to balance the baseline profile of treated and untreated individuals and performed multivariable proportional hazard modelling to assess the effect of DAAs on mortality. RESULTS: Our cohort comprised 10,851 people treated with DAAs (SVR 10,426 [96%], no-SVR: 425) and 10,851 matched untreated individuals. Median follow-up time was 2.2 years (IQR 1.3-3.6; maximum 6.2). The all-cause mortality rate was 19.5/1,000 person-years (PY) among the SVR group (deaths = 552), 86.5/1,000 PY among the no-SVR group (deaths = 96), and 99.2/1,000 PY among the untreated group (deaths = 2,133). In the multivariable model, SVR was associated with significant reduction in all-cause (adjusted hazard ratio [aHR] 0.19; 95% CI 0.17-0.21), liver- (adjusted subdistribution HR [asHR] 0.22, 95% CI 0.18-0.27) and drug-related mortality (asHR 0.26, 95% CI 0.21-0.32) compared to no-treatment. Older age and cirrhosis were associated with higher risk of liver-related mortality while younger age, injection drug use (IDU), problematic alcohol use and HIV/HBV co-infections were associated with a higher risk of drug-related mortality. CONCLUSIONS: DAA treatment is associated with a substantial reduction in all-cause, liver- and drug-related mortality. The association of IDU and related syndemic factors with a higher risk of drug-related mortality calls for an integrated social support, addiction, and HCV care approach among people who inject drugs. LAY SUMMARY: We assessed the effect of treatment of hepatitis C virus infection with direct-acting antiviral drugs on deaths from all causes, liver disease and drug use. We found that treatment with direct-acting antiviral drugs is associated with substantial lowering in risk of death from all causes, liver disease and drug use among people with hepatitis C virus infection.

Automated EEG pathology detection based on different convolutional neural network models: Deep learning approach.

The brain electrical activity, recorded and materialized as electroencephalogram (EEG) signals, is known to be very useful in the diagnosis of brain-related pathology. However, manual examination of these EEG signals has various limitations, including time-consuming inspections, the need for highly trained neurologists, and the subjectiveness of the evaluation. Thus, an automated EEG pathology detection system would be helpful to assist neurologists to enhance the treatment procedure by making a quicker diagnosis and reducing error due to the human element. This work proposes the application of a time-frequency spectrum to convert the EEG signals onto the image domain. The spectrum images are then applied to the Convolutional Neural Network (CNN) to learn robust features that can aid the automatic detection of pathology and normal EEG signals. Three popular CNN in the form of the DenseNet, Inception-ResNet v2, and SeizureNet were employed. The extracted deep-learned features from the spectrum images are then passed onto the support vector machine (SVM) classifier. The effectiveness of the proposed approach was assessed using the publicly available Temple University Hospital (TUH) abnormal EEG corpus dataset, which is demographically balanced. The proposed SeizureNet-SVM-based system achieved state-of-the-art performance: accuracy, sensitivity, and specificity of 96.65%, 90.48%, and 100%, respectively. The results show that the proposed framework may serve as a diagnostic tool to assist clinicians in the detection of EEG pathology for early treatment.

Towards TB elimination: how are macro-level factors perceived and addressed in policy initiatives in a high burden country?

BACKGROUND: Notwithstanding extensive general discussion of the effects of upstream forces on health, there has been limited empirical examination, let alone systematic evidence documenting policy responses to such pathways in the area of tuberculosis (TB) management and control. Our study aimed to gain insight into how macro level drivers of TB are perceived by key stakeholders involved in TB management and control in a high-endemic country, and to assess how such concerns are being addressed in policy initiatives in this setting. South Africa was chosen for this case study due to our team's long-standing collaborations there, its very high burden of TB, and its introduction of a strategic plan to combat this disease. METHOD: Semi-structured interviews were conducted with 20 key informants who were purposively selected for their knowledge and expertise of TB in South Africa. South Africa's National Strategic Plan for HIV, TB and STIs 2017-2022 was then reviewed to examine how identified themes from the interviews were reflected in this policy document. RESULTS: A history of colonization, the migrant labour system, economic inequality, poor shelter, health system challenges including TB governance, the HIV epidemic, and pertinent socio-cultural factors were all perceived to be major drivers of the epidemic. Although South Africa's current National Strategic Plan makes a firm discursive commitment to addressing the structural or macro-level drivers of TB, our analysis revealed that this commitment was not clearly reflected in projected budgetary allocations. CONCLUSION: As in many other high burden settings, macro-level drivers of TB are widely recognized. Nonetheless, while micro-level (biomedical and clinical) measures, such as improving diagnostic procedures and investment in more efficacious drugs, are being (and well should be) implemented, our findings showed that macro-level drivers of TB are underrepresented in budgeting allocations for initiatives to combat this disease. Although it could be argued that structural drivers that undermine health-promoting actions are beyond the purview of the health sector itself, we argue that strategic plans to combat TB in high burden settings need more attention to directly considering such drivers to prompt the necessary changes and reduce the burden of this and other such diseases.

HCV reinfection rates after cure or spontaneous clearance among HIV-infected and uninfected men who have sex with men.

BACKGROUND & AIMS: Hepatitis C virus (HCV) reinfection among high-risk groups threatens HCV elimination goals. We assessed HCV reinfection rates among men who have sex with men (MSM) in British Columbia (BC), Canada. METHODS: We used data from the BC Hepatitis Testers Cohort, which includes nearly 1.7 million individuals tested for HCV or HIV in BC. MSM who had either achieved sustained virologic response (SVR) after successful HCV treatment, or spontaneous clearance (SC) and had ≥1 subsequent HCV RNA measurement, were followed from the date of SVR or SC until the earliest of reinfection, death, or last HCV RNA measurement. Predictors of reinfection were identified by Cox proportional modelling. The earliest study start date was 6 November 1997 and latest end date was 13 April 2018. RESULTS: Of 1349 HCV-positive MSM who met the inclusion criteria, 493 had SC while 856 achieved SVR. 349 (25.65%) had HIV coinfection. We identified 98 reinfections during 5203 person-years (PYs) yielding a reinfection rate of 1.88/100PYs. The reinfection rate among SC (2.74/100PYs) was more than twice that of those with SVR (1.03/100 PYs). Problematic alcohol use (aHR 1.73, 95% CI 1.003-2.92), injection drug use (aHR 2.60, 95% CI 1.57-4.29) and HIV coinfection (aHR 2.04, 95% CI 1.29-3.23) were associated with increased risk of HCV reinfection. Mental health counselling history (aHR 0.24, 95% CI 0.13-0.46) was associated with reduced HCV reinfection risk. CONCLUSIONS: There is the need to engage MSM in harm reduction and prevention services following treatment to reduce reinfection risk.