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BackgroundRacialized populations in the United States, Canada, and the United Kingdom have been disproportionately affected by COVID-19. Higher vaccine hesitancy has been reported among racial and ethnic minorities in some of these countries. In the United Kingdom, for example, higher vaccine hesitancy has been observed among the South Asian population and Black compared with the White population, and this has been attributed to lack of trust in government due to historical and ongoing racism and discrimination. ObjectiveThis study aimed to assess vaccine receipt by ethnicity and its relationship with mistrust among ethnic groups in British Columbia (BC), Canada. MethodsWe included adults ≥18 years of age who participated in the BC COVID-19 Population Mixing Patterns Survey (BC-Mix) from March 8, 2021, to August 8, 2022. The survey included questions about vaccine receipt and beliefs based on a behavioral framework. Multivariable logistic regression was used to assess the association between mistrust in vaccines and vaccine receipt among ethnic groups. ResultsThe analysis included 25,640 adults. Overall, 76.7% (22,010/28,696) of respondents reported having received at least 1 dose of COVID-19 vaccines (Chinese=86.1%, South Asian=79.6%, White=75.5%, and other ethnicity=73.2%). Overall, 13.7% (3513/25,640) of respondents reported mistrust of COVID-19 vaccines (Chinese=7.1%, South Asian=8.2%, White=15.4%, and other ethnicity=15.2%). In the multivariable model (adjusting for age, sex, ethnicity, educational attainment, and household size), mistrust was associated with a 93% reduced odds of vaccine receipt (adjusted odds ratio 0.07, 95% CI 0.06-0.08). In the models stratified by ethnicity, mistrust was associated with 81%, 92%, 94%, and 95% reduced odds of vaccine receipt among South Asian, Chinese, White, and other ethnicities, respectively. Indecision, whether to trust the vaccine or not, was significantly associated with a 70% and 78% reduced odds of vaccine receipt among those who identified as White and of other ethnic groups, respectively. ConclusionsVaccine receipt among those who identified as South Asian and Chinese in BC was higher than that among the White population. Vaccine mistrust was associated with a lower odds of vaccine receipt in all ethnicities, but it had a lower effect on vaccine receipt among the South Asian and Chinese populations. Future research needs to focus on sources of mistrust to better understand its potential influence on vaccine receipt among visible minorities in Canada.

Abstract Background Women living with hepatitis C virus (HCV) are rarely addressed in research and may be overrepresented within key populations requiring additional support to access HCV care and treatment. We constructed the HCV care cascade among people diagnosed with HCV in British Columbia, Canada, as of 2019 to compare progress in care and treatment and to assess sex/gender gaps in HCV treatment access. Methods The BC Hepatitis Testers Cohort includes 1.7 million people who tested for HCV, HIV, reported cases of hepatitis B, and active tuberculosis in BC from 2000 to 2019. Test results were linked to medical visits, hospitalizations, cancers, prescription drugs, and mortality data. Six HCV care cascade stages were identified: (1) antibody diagnosed; (2) RNA tested; (3) RNA positive; (4) genotyped; (5) initiated treatment; and (6) achieved sustained virologic response (SVR). HCV care cascade results were assessed for women, and an ‘inverse’ cascade was created to assess gaps, including not being RNA tested, genotyped, or treatment initiated, stratified by sex. Results In 2019, 52,638 people with known sex were anti-HCV positive in BC; 37% (19,522) were women. Confirmatory RNA tests were received by 86% (16,797/19,522) of anti-HCV positive women and 83% (27,353/33,116) of men. Among people who had been genotyped, 68% (6756/10,008) of women and 67% (12,640/18,828) of men initiated treatment, with 94% (5023/5364) of women and 92% (9147/9897) of men achieving SVR. Among the 3252 women and 6188 men not yet treated, higher proportions of women compared to men were born after 1975 (30% vs. 21%), had a mental health diagnosis (42% vs. 34%) and had used injection drugs (50% vs. 45%). Among 1619 women and 2780 men who had used injection drugs and were not yet treated, higher proportions of women than men used stimulants (64% vs. 57%), and opiates (67% vs. 60%). Conclusions Women and men appear to be equally engaged into the HCV care cascade; however, women with concurrent social and health conditions are being left behind. Treatment access may be improved with approaches that meet the needs of younger women, those with mental health diagnoses, and women who use drugs.

BackgroundWhile the evidence for the clinical effectiveness of most noncommunicable disease (NCD) prevention and treatment interventions is well established, care delivery models and means of scaling these up in a variety of resource-constrained health systems are not. The objective of this review was to synthesize evidence on the current state of implementation research on priority NCD prevention and control interventions provided by health systems in low- and middle-income countries (LMICs).Methods and findingsOn January 20, 2021, we searched MEDLINE and EMBASE databases from 1990 through 2020 to identify implementation research studies that focused on the World Health Organization (WHO) priority NCD prevention and control interventions targeting cardiovascular disease, cancer, diabetes, and chronic respiratory disease and provided within health systems in LMICs. Any empirical and peer-reviewed studies that focused on these interventions and reported implementation outcomes were eligible for inclusion. Given the focus on this review and the heterogeneity in aims and methodologies of included studies, risk of bias assessment to understand how effect size may have been compromised by bias is not applicable. We instead commented on the distribution of research designs and discussed about stronger/weaker designs. We synthesized extracted data using descriptive statistics and following the review protocol registered in PROSPERO (CRD42021252969). Of 9,683 potential studies and 7,419 unique records screened for inclusion, 222 eligible studies evaluated 265 priority NCD prevention and control interventions implemented in 62 countries (6% in low-income countries and 90% in middle-income countries). The number of studies published has been increasing over time. Nearly 40% of all the studies were on cervical cancer. With regards to intervention type, screening accounted for 49%, treatment for 39%, while prevention for 12% (with 80% of the latter focusing on prevention of the NCD behavior risk factors). Feasibility (38%) was the most studied implementation outcome followed by adoption (23%); few studies addressed sustainability. The implementation strategies were not specified well enough. Most studies used quantitative methods (86%). The weakest study design, preexperimental, and the strongest study design, experimental, were respectively employed in 25% and 24% of included studies. Approximately 72% of studies reported funding, with international funding being the predominant source. The majority of studies were proof of concept or pilot (88%) and targeted the micro level of health system (79%). Less than 5% of studies report using implementation research framework.ConclusionsDespite growth in implementation research on NCDs in LMICs, we found major gaps in the science. Future studies should prioritize implementation at scale, target higher levels health systems (meso and macro levels), and test sustainability of NCD programs. They should employ designs with stronger internal validity, be more conceptually driven, and use mixed methods to understand mechanisms. To maximize impact of the research under limited resources, adding implementation science outcomes to effectiveness research and regional collaborations are promising.

Background: Hepatitis C (HCV) affects diverse populations such as people who inject drugs (PWID), 'baby boomers,’ gay/bisexual men who have sex with men (gbMSM), and people from HCV endemic regions. Assessing HCV syndemics (i.e.relationships with mental health/chronic diseases) among subpopulations using Latent Class Analysis (LCA) may facilitate targeted program planning. Methods: The BC Hepatitis Testers Cohort(BC-HTC) includes all HCV cases identified in BC between 1990 and 2015, integrated with medical administrative data. LCA grouped all BC-HTC HCV diagnosed people(n = 73,665) by socio-demographic/clinical indicators previously determined to be relevant for HCV outcomes. The final model was chosen based on fit statistics, epidemiological meaningfulness, and posterior probability. Classes were named by most defining characteristics. Results: The six-class model was the best fit and had the following names and characteristics:‘Younger PWID’ (n =11,563): recent IDU (67%), people born >1974 (48%), mental illness (62%), material deprivation (59%).‘Older PWID’ (n =15,266): past IDU (78%), HIV (17%), HBV (17%) coinfections, alcohol misuse(68%).‘Other Middle-Aged People’ (n = 9019): gbMSM (26%), material privilege (31%), people born between 1965−1974 (47%).‘People of Asian backgrounds’ (n = 4718): East/South Asians (92%), no alcohol misuse (97%) or mental illness (93%), people born

BackgroundClose-contact rates are thought to be a driving force behind the transmission of many infectious respiratory diseases. Yet, contact rates and their relation to transmission and the impact of control measures, are seldom quantified. We quantify the response of contact rates, reported cases and transmission of COVID-19, to public health contact-restriction orders, and examine the associations among these three variables in the province of British Columbia, Canada.MethodsWe derived time series data for contact rates, daily cases and transmission of COVID-19 from a social contacts survey, reported case counts and by fitting a transmission model to reported cases, respectively. We used segmented regression to investigate impacts of public health orders; Pearson correlation to determine associations between contact rates and transmission; and vector autoregressive modeling to quantify lagged associations between contacts rates, daily cases, and transmission.ResultsDeclines in contact rates and transmission occurred concurrently with the announcement of public health orders, whereas declines in cases showed a reporting delay of about 2 weeks. Contact rates were a significant driver of COVID-19 and explained roughly 19 and 20% of the variation in new cases and transmission, respectively. Interestingly, increases in COVID-19 transmission and cases were followed by reduced contact rates: overall, daily cases explained about 10% of the variation in subsequent contact rates.ConclusionWe showed that close-contact rates were a significant time-series driver of transmission and ultimately of reported cases of COVID-19 in British Columbia, Canada and that they varied in response to public health orders. Our results also suggest possible behavioral feedback, by which increased reported cases lead to reduced subsequent contact rates. Our findings help to explain and validate the commonly assumed, but rarely measured, response of close contact rates to public health guidelines and their impact on the dynamics of infectious diseases.

BackgroundThe development and approval of COVID-19 vaccines have generated optimism for the end of the COVID-19 pandemic and a return to normalcy. However, vaccine hesitancy, often fueled by misinformation, poses a major barrier to achieving herd immunity. ObjectiveWe aim to investigate Twitter users’ attitudes toward COVID-19 vaccination in Canada after vaccine rollout. MethodsWe applied a weakly supervised aspect-based sentiment analysis (ABSA) technique, which involves the human-in-the-loop system, on COVID-19 vaccination–related tweets in Canada. Automatically generated aspect and opinion terms were manually corrected by public health experts to ensure the accuracy of the terms and make them more domain-specific. Then, based on these manually corrected terms, the system inferred sentiments toward the aspects. We observed sentiments toward key aspects related to COVID-19 vaccination, and investigated how sentiments toward “vaccination” changed over time. In addition, we analyzed the most retweeted or liked tweets by observing most frequent nouns and sentiments toward key aspects. ResultsAfter applying the ABSA system, we obtained 170 aspect terms (eg, “immunity” and “pfizer”) and 6775 opinion terms (eg, “trustworthy” for the positive sentiment and “jeopardize” for the negative sentiment). While manually verifying or editing these terms, our public health experts selected 20 key aspects related to COVID-19 vaccination for analysis. The sentiment analysis results for the 20 key aspects revealed negative sentiments related to “vaccine distribution,” “side effects,” “allergy,” “reactions,” and “anti-vaxxer,” and positive sentiments related to “vaccine campaign,” “vaccine candidates,” and “immune response.” These results indicate that the Twitter users express concerns about the safety of vaccines but still consider vaccines as the option to end the pandemic. In addition, compared to the sentiment of the remaining tweets, the most retweeted or liked tweets showed more positive sentiment overall toward key aspects (P

ObjectiveCurrent guidelines in British Columbia recommend prenatal screening for hepatitis C antibodies (anti-HCV) if risk factors are present. We aimed to estimate frequency of prenatal anti-HCV testing, new diagnoses, repeated and follow-up testing among BC women.MethodsBC Centre for Disease Control Public Health Laboratory data estimated the number of BC women (assigned female at birth or unknown sex) aged 13-49 who received routine prenatal serological screening (HIV, hepatitis B, syphilis and rubella) from 2008-2019. Anti-HCV tests ordered the same day as routine prenatal screens were considered prenatal anti-HCV tests. Assessment of follow-up was based on HCV RNA and/or genotype testing within one year of new prenatal anti-HCV diagnoses.ResultsIn 2019, 55,202 routine prenatal screens were carried out for 50,392 BC women. Prenatal anti-HCV tests increased significantly, from 19.6% (9,704/49,515) in 2008 to 54.6% (27,516/50,392) in 2019 (pConclusionPrenatal anti-HCV testing increased substantially over the study period. However, new HCV diagnoses remained relatively stable, suggesting that a considerable proportion of BC women with low or no risk are being screened as part of prenatal care. The vast majority of women with new HCV diagnoses receive appropriate follow-up HCV RNA and genotype testing, which may indicate interest in HCV treatment. These findings contribute to the discussion around potential for prenatal anti-HCV screening in an effort to eliminate HCV.

This study examined the HPV vaccine landscape in Kenya and the USA with a focus on if differences exist in the perceptions of HPV knowledge, vaccine attitudes, subjective norms, perceived behavioural control, and vaccine intention among students across country and gender. It also provides useful findings that can inform the design of persuasive health messages to promote the uptake of HPV vaccines among college students in Kenya and the USA. The study used surveys to recruit 1,033 participants (511 Kenyan and 522 USA students). The two-way MANOVA analysis revealed that the multivariate main effects showed no significant differences for gender, but the results revealed a significant main effect for the country. However, the interaction between gender and country of the participants was not significant. The univariate analysis revealed that the participants of the two countries had small significant differences in their subjective norms about HPV vaccination, and perceived behavioural control. The correlation analysis showed that HPV knowledge correlates with knowledge about the HPV vaccine and country, but not with gender. The results also revealed that knowledge about the HPV vaccine correlates with both gender and country. These results highlight the most salient predictors of vaccination intentions among college students that health communicators can focus on when designing and implementing HPV vaccination campaigns targeting students in Kenya and the USA. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical optimization framework for the strategic placement of quasi-dynamic wireless charging (QWC) stations within road networks to address the charging needs of battery electric buses (BEBs). This study evaluates two scenarios for powering the buses. In the first scenario, a grid-connected system is considered. The optimization aims to minimize annual costs related to capital, operation, and energy losses of the electric bus fleet. This involves determining the optimal locations for QWC stations, the length of power transmitters, and the corresponding battery capacities for the BEBs. Using MATLAB-based optimization tools Casadi and Yalmip, with solvers Bonmin and Fmincon, the optimal configuration includes a 13 kWh battery capacity and a 300 m power transmitter distributed across five bus stop areas. The second scenario employs a chance-constrained optimization approach for an isolated solar photovoltaic (PV) and battery energy storage system (BESS). This system is designed to reliably meet the BEBs' energy requirements throughout the day, considering different seasonal data (winter, summer, all seasons/year-round). The optimization results for the PV and BESS capacities vary with the seasons: 394.247 kW and 2012.6 kWh using summer data, 1762.1 kW and 2738.2 kWh using winter data, and 1610.8 kW and 2741.9 kWh using year-round data. Additionally, the paper examines the impact of varying bus fleet sizes on the optimal battery size and power transmitter combination using a real-world example of the bus route between Khalifa City and Abu Dhabi Downtown in the UAE. The findings suggest that larger batteries with fewer or no charging stations are more economical for smaller fleets. Conversely, as the fleet size increases, a combination of smaller battery sizes and a greater number (and length) of QWC (power transmitters) becomes more cost-effective. This research offers significant insights into the efficient deployment of QWC stations and the integration of renewable energy and energy storage for sustainable urban electric bus networks. The proposed optimization models provide a systematic approach to designing and operating charging infrastructure, contributing to sustainable urban transportation systems. Moreover, the study highlights the influence of seasonal data on PV system sizing and costs.

Abstract Background Malaria remains a major public health concern around the world, particularly in resource-constrained countries. Malaria still accounts for 40% of all Out-Patient Department (OPD) cases in Ghana, with children under the age of five being the most vulnerable group. The study assessed the knowledge, attitudes, and practices of malaria preventive measures among mothers with children under 5 years old in a rural setting in Ghana. Methods A cross-sectional study design with a quantitative approach was used in this study. The study was facility based and involved the use of interviewer administered questionnaires to collect data from 281 mothers with children under the age of five. Simple random sampling method was used to select the respondents. The data collected was analysed using the statistical package for the social sciences (SPSS) version 22 and results presented in tables. Results There were 281 mothers, with 59.4% having children at the age of a year. The findings revealed that the majority of participants have a high level of knowledge about malaria’s causes, signs, and symptoms. Again, the majority of participants demonstrated a positive attitude toward malaria prevention, such as seeking treatment at a hospital within 24 h of suspecting their children had malaria and demonstrating good knowledge of malaria prevention practices. Despite this, 35.5% of respondents were not actively engaged in malaria prevention practices in a day prior to the interview. Respondents’ occupation, level of education, and religion had a statistically significant association with mothers’ attitude towards prevention (p-values

Recent motivation to cut greenhouse gas emissions to combat climate change has led to increasing transportation electrification. However, electric vehicle proliferation comes with a number of challenges such as battery capacities and the range anxiety of electric vehicles. In this paper, a review of the main components that affect electric vehicle adoption, which are charging infrastructure and energy resources, is presented. We discuss the categories of electric vehicle charging infrastructure, based on the location-of-charge and the charging technology. In addition, a review of the energy resources required for electric vehicles is also presented. The key features of these batteries are also discussed.

We propose a forecasting technique based on multi-feature data fusion to enhance the accuracy of an electric vehicle (EV) charging station load forecasting deep-learning model. The proposed method uses multi-feature inputs based on observations of historical weather (wind speed, temperature, and humidity) data as multiple inputs to a Long Short-Term Memory (LSTM) model to achieve a robust prediction of charging loads. Weather conditions are significant influencers of the behavior of EV drivers and their driving patterns. These behavioral and driving patterns affect the charging patterns of the drivers. Rather than one prediction (step, model, or variables) made by conventional LSTM models, three charging load (energy demand) predictions of EVs were made depending on different multi-feature inputs. Data fusion was used to combine and optimize the different charging load prediction results. The performance of the final implemented model was evaluated by the mean absolute prediction error of the forecast. The implemented model had a prediction error of 3.29%. This prediction error was lower than initial prediction results by the LSTM model. The numerical results indicate an improvement in the performance of the EV load forecast, indicating that the proposed model could be used to optimize and improve EV load forecasts for electric vehicle charging stations to meet the energy requirements of EVs.