Monkeypox: a review of epidemiological modelling studies and how modelling has led to mechanistic insight.

Human monkeypox (mpox) virus is a viral zoonosis that belongs to the Orthopoxvirus genus of the Poxviridae family, which presents with similar symptoms as those seen in human smallpox patients. Mpox is an increasing concern globally, with over 80,000 cases in non-endemic countries as of December 2022. In this review, we provide a brief history and ecology of mpox, its basic virology, and the key differences in mpox viral fitness traits before and after 2022. We summarize and critique current knowledge from epidemiological mathematical models, within-host models, and between-host transmission models using the One Health approach, where we distinguish between models that focus on immunity from vaccination, geography, climatic variables, as well as animal models. We report various epidemiological parameters, such as the reproduction number, R0, in a condensed format to facilitate comparison between studies. We focus on how mathematical modelling studies have led to novel mechanistic insight into mpox transmission and pathogenesis. As mpox is predicted to lead to further infection peaks in many historically non-endemic countries, mathematical modelling studies of mpox can provide rapid actionable insights into viral dynamics to guide public health measures and mitigation strategies.

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.

Biobehavioral Aspects of the COVID-19 Pandemic: A Review.

OBJECTIVE: This review highlights the scope and significance of the coronavirus disease 2019 (COVID-19) pandemic with a focus on biobehavioral aspects and critical avenues for research. METHODS: A narrative review of the published research literature was undertaken, highlighting major empirical findings emerging during the first and second waves of the COVID-19 pandemic. RESULTS: Interactions among biological, behavioral, and societal processes were prominent across all regions of the globe during the first year of the COVID-19 emergency. Affective, cognitive, behavioral, socioeconomic, and technological factors all played a significant role in the spread of infection, response precautions, and outcomes of mitigation efforts. Affective symptoms, suicidality, and cognitive dysfunction have been widely described consequences of the infection, the economic fallout, and the necessary public health mitigation measures themselves. The impact of COVID-19 may be especially serious for those living with severe mental illness and/or chronic medical diseases, given the confluence of several adverse factors in a manner that appears to have syndemic potential. CONCLUSIONS: The COVID-19 pandemic has made clear that biological and behavioral factors interact with societal processes in the infectious disease context. Empirical research examining mechanistic pathways from infection and recovery to immunological, behavioral, and emotional outcomes is critical. Examination of how emotional and behavioral factors relate to the pandemic-both as causes and as effects-can provide valuable insights that can improve management of the current pandemic and future pandemics to come.

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.

The impact of SVR from direct-acting antiviral- and interferon-based treatments for HCV on hepatocellular carcinoma risk.

We evaluated the effect of sustained virologic response (SVR) from direct-acting antiviral (DAA)- and interferon-based treatments on hepatocellular carcinoma (HCC) risk in a large population-based cohort in Canada. We used data from the BC Hepatitis Testers Cohort, which includes ~1.3 million individuals tested for HCV since 1990, linked with healthcare administrative and registry datasets. Patients were followed from the end of HCV treatment to HCC, death or 31 December 2016. We assessed HCC risk among those who did and did not achieve SVR by treatment type using proportional hazard models. Of 12 776 eligible individuals, 3905 received DAAs while 8871 received interferon-based treatments, followed for a median of 1.0 [range: 0.6-2.7] and 7.9 [range: 4.4-17.1] years, respectively. A total of 3613 and 6575 achieved SVR with DAAs- and interferon-based treatments, respectively. Among DAAs-treated patients, HCC incidence rate was 6.9 (95%CI: 4.7-10.1)/1000 person yr (PY) in SVR group (HCC cases: 26) and 38.2 (95%CI: 20.6-71.0) in the no-SVR group (HCC cases: 10, P < .001). Among interferon-treated individuals, HCC incidence rate was 1.8 (95%CI: 1.5-2.2) in the SVR (HCC cases: 99) and 13.9 (95%CI: 12.3-15.8) in the no-SVR group (HCC cases: 239, P < .001). Compared with no-SVR from interferon, SVR from DAA- and interferon-based treatments resulted in significant reduction in HCC risk (adjusted subdistribution hazard ratio (adjSHR) DAA = 0.30, 95%CI: 0.19-0.48 and adjSHR interferon = 0.2, 95%CI: 0.16-0.26). Among those with SVR, treatment with DAAs compared to interferon was not associated with HCC risk (adjSHR = 0.93, 95%CI: 0.51-1.71). In conclusion, similar to interferon era, DAA-related SVR is associated with 70% reduction in HCC risk.

Loss to follow-up: A significant barrier in the treatment cascade with direct-acting therapies.

Effectiveness of direct-acting antiviral (DAA) therapies could be influenced by patient characteristics such as comorbid conditions, which could lead to premature treatment discontinuation and/or irregular medical follow-ups. Here, we evaluate loss to follow-up and treatment effectiveness of sofosbuvir/ledipasvir ± ribavirin (SOF/LDV ± RBV), ombitasvir/paritaprevir/ritonavir + dasabuvir ± ribavirin (OBV/PTV/r + DSV ± RBV) for hepatitis C virus (HCV) genotype 1 (GT1) and sofosbuvir + ribavirin (SOF + RBV) for genotype 3 (GT3) in British Columbia Canada: The British Columbia Hepatitis Testers Cohort includes data on individuals tested for HCV since 1992, integrated with medical visit, hospitalization and prescription drug data. HCV-positive individuals who initiated DAA regimens, irrespective of treatment completion, for GT1 and GT3 until 31 December, 2017 were included. Factors associated with sustained virological response (SVR) and loss to follow-up were assessed by using multivariable logistic regression models. In total 4477 individuals initiated DAAs. The most common prescribed DAA was SOF/LDV ± RBV with SVR of 95%. The highest SVR of 99.5% was observed among OBV/PTV/r + DSV-treated patients. Overall, 453 (10.1%) individuals were lost to follow-up. Higher loss to follow-up was observed among GT1 patients treated with OBV (17.8%) and GT3 patients (15.7%). The loss to follow-up rate was significantly higher among individuals aged <60 years, those with a history of injection drug use (IDU), on opioid substitution therapy and with cirrhosis. Our findings indicate that loss to follow-up exceeds viral failure in HCV DAA therapy and its rate varies significantly by genotype and treatment regimen. Depending on the aetiology of lost to follow-up, personalized case management for those with medical complications and supporting services among IDU are needed to achieve the full benefits of effective treatments.

Considerations for an Individual-Level Population Notification System for Pandemic Response: A Review and Prototype.

The outbreak of the coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, spread worldwide after its emergence in China. Whether rich or poor, all nations are struggling to cope with this new global health crisis. The speed of the threat's emergence and the quick response required from public health authorities and the public itself makes evident the need for a major reform in pandemic surveillance and notification systems. The development and implementation of a graded, individual-level pandemic notification system could be an effective tool to combat future threats of epidemics. This paper describes a prototype model of such a notification system and its potential advantages and challenges for implementation. Similar to other emergency alerts, this system would include a number of threat levels (level 1-5) with a higher level indicating increasing severity and intensity of safety measures (eg, level 1: general hygiene, level 2: enhanced hygiene, level 3: physical distancing, level 4: shelter in place, and level 5: lockdown). The notifications would be transmitted to cellular devices via text message (for lower threat levels) or push notification (for higher threat levels). The notification system would allow the public to be informed about the threat level in real time and act accordingly in an organized manner. New Zealand and the United Kingdom have recently launched similar alert systems designed to coordinate the ongoing COVID-19 pandemic response more efficiently. Implementing such a system, however, faces multiple challenges. Extensive preparation and coordination among all levels of government and relevant sectors are required. Additionally, such systems may be effective primarily in countries where there exists at least moderate trust in government. Advance and ongoing public education about the nature of the system and its steps would be an essential part of the system, such that all members of the public understand the meaning of each step in advance, similar to what has been established in systems for other emergency responses. This educational component is of utmost importance to minimize adverse public reaction and unintended consequences. The use of mass media and local communities could be considered where mobile phone penetration is low. The implementation of such a notification system would be more challenging in developing countries for several reasons, including inadequate technology, limited use of data plans, high population density, poverty, mistrust in government, and tendency to ignore or failure to understand the warning messages. Despite the challenges, an individual-level pandemic notification system could provide added benefits by giving an additional route for notification that would be complementary to existing platforms.

Correction: Considerations for an Individual-Level Population Notification System for Pandemic Response: A Review and Prototype.

[This corrects the article DOI: 10.2196/19930.].

Applying core theory and spatial analysis to identify hepatitis C virus infection "core areas" in British Columbia, Canada.

"Core areas" of transmission for bacterial sexually transmitted infections have been identified. However, it is unclear whether core areas apply to viral infections, such as hepatitis C virus (HCV). We used geographic mapping and spatial analysis to identify distinct core areas of HCV infection in British Columbia (BC) using the BC Hepatitis Testers Cohort (BC-HTC), 1990-2013. The BC-HTC includes all BC residents tested for HCV (~1.5 million; 1990-2013). Core HCV infection areas were identified spatially and temporally for five time periods (1990-1993, 1994-1998, 1999-2003, 2004-2008 and 2009-2013) through thematic mapping, Kernel Density Estimation, Hotspot analysis and cluster analysis at the Census dissemination area level in ArcGIS and SatScan. HCV infection core areas were consistently identified. HCV core areas expanded from the downtown of major cities in different regions of BC (Metro Vancouver, Vancouver Island, and Northern BC; 1990-1998), to smaller cities in Metro Vancouver and Interior BC (2000 onwards). Statistically significant clusters, or hotspots, were also observed for downtown Vancouver, Northern BC (Prince George) and Vancouver Island from 1990 to 2008 with expansion to other urban areas in Metro Vancouver from 1990-2013. Statistically significant clusters persisted after adjustment for injection drug use, number of HCV tests, age, sex, material and social deprivation. Persistence of areas with high HCV diagnoses rates in Vancouver and Prince George supports the theory of core areas of HCV transmission. Identification of core areas can inform prevention, care and treatment programme interventions and evaluate their impact over time.

Hepatitis C virus reinfection after successful treatment with direct-acting antiviral therapy in a large population-based cohort.

BACKGROUND & AIMS: Direct-acting antiviral therapies (DAA) are an important tool for hepatitis C virus (HCV) elimination. However, reinfection among people who inject drugs (PWID) may hamper elimination targets. Therefore, we estimated HCV reinfection rates among DAA-treated individuals, including PWID. METHODS: We analyzed data from the British Columbia Hepatitis Testers Cohort which included ∼1.7 million individuals screened for HCV in British Columbia, Canada. We followed HCV-infected individuals treated with DAAs who achieved a sustained virologic response (SVR) and had ≥1 subsequent HCV RNA measurement to April 22nd, 2018. Reinfection was defined as a positive RNA measurement after SVR. PWID were identified using a validated algorithm and classified based on recent (<3 years) or former (≥3 years before SVR) use. Crude reinfection rates per 100 person-years (PYs) were calculated. Poisson regression was used to model adjusted incidence rate ratios (IRRs) and 95% CIs. RESULTS: Of 4,114 individuals who met the inclusion criteria, most were male (n = 2,692, 65%), born before 1965 (n = 3,411, 83%) and were either recent (n = 875, 21%) or former PWID (n = 1,793, 44%). Opioid-agonist therapy (OAT) was received by 19% of PWID. We identified 40 reinfections during 2,767 PYs. Reinfection rates were higher among recent (3.1/100 PYs; IRR 6.7; 95% CI 1.9-23.5) and former PWID (1.4/100 PYs; IRR 3.7; 95% CI 1.1-12.9) than non-PWID (0.3/100 PYs). Among recent PWID, reinfection rates were higher among individuals born after 1975 (10.2/100 PYs) and those co-infected with HIV (5.7/100 PYs). Only one PWID receiving daily OAT developed reinfection. CONCLUSIONS: Population-level reinfection rates remain elevated after DAA therapy among PWID because of ongoing exposure risk. Engagement of PWID in harm-reduction and support services is needed to prevent reinfections. LAY SUMMARY: Direct-acting antivirals are an effective tool for the treatment of hepatitis C virus, enabling the elimination of the virus. However, some patients who have been successfully treated with direct-acting antivirals are at risk of reinfection. Our findings showed that the risk of reinfection was highest among people with recent injection drug use. Among people who inject drugs, daily use of opioid-agonist therapy was associated with a lower risk of reinfection.

Estimating the impact of early hepatitis C virus clearance on hepatocellular carcinoma risk.

Although achieving sustained virological response (SVR) through antiviral therapy could reduce the risk of hepatocellular carcinoma (HCC) attributable to hepatitis C virus (HCV) infection, the impact of early viral clearance on HCC is not well defined. In this study, we compared the risk of HCC among individuals who spontaneously cleared HCV (SC), the referent population, with the risk in untreated chronic HCV (UCHC), those achieved SVR, and those who failed interferon-based treatment (TF). The BC Hepatitis Testers Cohort (BC-HTC) includes individuals tested for HCV between 1990-2013, integrated with medical visits, hospitalizations, cancers, prescription drugs and mortality data. This analysis included all HCV-positive patients with at least one valid HCV RNA by PCR on or after HCV diagnosis. Of 46 666 HCV-infected individuals, there were 12 527 (26.8%) SC; 24 794 (53.1%) UCHC; 5355 (11.5%) SVR and 3990 (8.5%) TF. HCC incidence was lowest (0.3/1000 person-years (PY)) in the SC group and highest in the TF group (7.7/1000 PY). In a multivariable model, compared to SC, TF had the highest HCC risk (hazard ratio (HR):14.52, 95% confidence interval (CI): 9.83-21.47), followed by UCHC (HR: 5.85; 95% CI: 4.07-8.41). Earlier treatment-based viral clearance similar to SC could decrease HCC incidence by 69.4% (95% CI: 57.5-78.0), 30% (95% CI: 10.8-45.1) and 77.5% (95% CI: 69.4-83.5) among UCHC, SVR and TF patients, respectively. In conclusion, using SC as a real-world comparator group, it showed that substantial reduction in HCC risk could be achieved with earlier treatment initiation. These analyses should be replicated in patients who have been treated with direct acting antiviral therapies.

Long-term effect of sustained virological response on hepatocellular carcinoma in patients with hepatitis C in Canada.

BACKGROUND & AIMS: Evidence is limited on hepatocellular carcinoma (HCC) risk after sustained virological response (SVR) to interferon-based treatment of hepatitis C virus (HCV) infection. We evaluated the effect of SVR on the risk of HCC and estimated its incidence in post-SVR HCV patients from a large population-based Canadian cohort. METHODS: The British Columbia Hepatitis Testers Cohort includes individuals tested for HCV between 1990-2013 linked with data on their medical visits, hospitalizations, cancers, prescription drugs and mortality. Patients receiving interferon-based HCV treatments were followed from the end of treatment to HCC diagnosis, death or December 31, 2012. We examined HCC risk among those who did and did not achieve SVR using multivariable proportional hazard models with the Fine and Gray modification for competing risks. RESULTS: Of 8147 individuals who received HCV treatment and were eligible for analysis, 4663 (57%) achieved SVR and 3484 (43%) did not. Each group was followed for a median of 5.6years (range: 0.5-12.9) for an HCC incidence rate of 1.1/1000 person-years (PY) among the SVR and 7.2/1000 PY among the no SVR group. The HCC incidence rate was higher among those with cirrhosis (SVR: 6.4, no SVR: 21.0/1000 PY). In the multivariable model, SVR was associated with a lower HCC risk (subdistribution hazard ratio [SHR]=0.20, 95% CI: 0.13-0.3), while cirrhosis (SHR=2.61, 95% CI: 1.68-4.04), age ⩾50years, being male and genotype 3 infection were associated with a higher HCC risk. Among those who achieved SVR, cirrhosis, age ⩾50years and being male were associated with a higher HCC risk. CONCLUSION: SVR after interferon-based treatment substantially reduces but does not eliminate HCC risk, which is markedly higher among those with cirrhosis and age ⩾50years at treatment initiation. Treatment of patients at an advanced fibrosis stage with new highly effective drugs will warrant continued surveillance for HCC post-SVR. LAY SUMMARY: We assessed the effect of successful hepatitis C treatment with older interferon-based treatment on the occurrence of liver cancer (hepatocellular carcinoma) and found that successful treatment prevents liver cancer. However, more people with cirrhosis and older age continued to develop liver cancer after successful treatment. Thus, treatment with new drugs among those with cirrhosis will require continued monitoring for liver cancer.

Tackling The Co-Epidemic Of Diabetes And Tuberculosis: From Evidence To Policy And Practice.

With the global increase in the diabetic population there is a resurgence of interest in the dual epidemic of diabetes mellitus (DM) and tuberculosis (TB), which has a bidirectional detrimental relationship with negative consequences for co-infected patients. Pakistan is feared to be hit the hardest, occupying fifth position amidst the 22 high burden TB countries, and ranking seventh in the global diabetic burden. The diabetes tuberculosis treatment outcome (DITTO) study was undertaken to determine the impact of diabetes on tuberculosis treatment outcome in Pakistan. The generation of such scientific evidence is useless if it is not utilized for policy making and practice, especially in a developing country like ours with a dearth of resources. In this paper, we have developed a framework for the transfer of scientific evidence regarding the impact of diabetes on TB treatment outcomes into policy and practice. The framework is divided into three components namely; generation of scientific evidence harnessing international and national efforts, informing health policy and practice and addressing other concerns such as social protection, health education and future research.

Validating part of the social media infodemic listening conceptual framework using structural equation modelling.

Background: The literature has identified various factors that promote or hinder people's intentions towards COVID-19 vaccination, and structural equation modelling (SEM) is a common approach to validate these associations. We propose a conceptual framework called social media infodemic listening (SoMeIL) for public health behaviours. Hypothesizing parameters retrieved from social media platforms can be used to infer people's intentions towards vaccination behaviours. This study preliminarily validates several components of the SoMeIL conceptual framework using SEM and Twitter data and examines the feasibility of using Twitter data in SEM research. Methods: A total of 2420 English tweets in Toronto or Ottawa, Ontario, Canada, were collected from March 8 to June 30, 2021. Confirmatory factor analysis and SEM were applied to validate the SoMeIL conceptual framework in this cross-sectional study. Findings: The results showed that sentiment scores, the log-numbers of favourites and retweets of a tweet, and the log-numbers of a user's favourites, followers, and public lists had significant direct associations with COVID-19 vaccination intention. The sentiment score of a tweet had the strongest relationship, whereas a user's number of followers had the weakest relationship with the intention of COVID-19 vaccine uptake. Interpretation: The findings preliminarily validate several components of the SoMeIL conceptual framework by testing associations between self-reported COVID-19 vaccination intention and sentiment scores and the log-numbers of a tweet's favourites and retweets as well as users' favourites, followers, and public lists. This study also demonstrates the feasibility of using Twitter data in SEM research. Importantly, this study preliminarily validates the use of these six components as online reaction behaviours in the SoMeIL framework to infer the self-reported COVID-19 vaccination intentions of Canadian Twitter users in two cities. Funding: This study was supported by the 2023-24 Ontario Graduate Scholarship.

Application of artificial intelligence in active assisted living for aging population in real-world setting with commercial devices - A scoping review.

BACKGROUND: The aging population is steadily increasing, posing new challenges and opportunities for healthcare systems worldwide. Technological advancements, particularly in commercially available Active Assisted Living devices, offer a promising alternative. These readily accessible products, ranging from smartwatches to home automation systems, are often equipped with Artificial Intelligence capabilities that can monitor health metrics, predict adverse events, and facilitate a safer living environment. However, there is no review exploring how Artificial Intelligence has been integrated into commercially available Active Assisted Living technologies, and how these devices monitor health metrics and provide healthcare solutions in a real-world environment for healthy aging. This review is essential because it fills a knowledge gap in understanding AI's integration in Active Assisted Living technologies in promoting healthy aging in real-world settings, identifying key issues that require to be addressed in future studies. OBJECTIVE: The aim of this overview is to outline current understanding, identify potential research opportunities, and highlight research gaps from published studies regarding the use of Artificial Intelligence in commercially available Active Assisted Living technologies that assists older individuals aging at home. METHODS: A comprehensive search was conducted in six databases-PubMed, CINAHL, IEEE Xplore, Scopus, ACM Digital Library, and Web of Science-to identify relevant studies published over the past decade from 2013 to 2024. Our methodology adhered to the PRISMA extension for scoping reviews to ensure rigor and transparency throughout the review process. After applying predefined inclusion and exclusion criteria on 825 retrieved articles, a total of 64 papers were included for analysis and synthesis. RESULTS: Several trends emerged from our analysis of the 64 selected papers. A majority of the work (39/64, 61%) was published after the year 2020. Geographically, most of the studies originated from East Asia and North America (36/64, 56%). The primary application goal of Artificial Intelligence in the reviewed literature was focused on activity recognition (34/64, 53%), followed by daily monitoring (10/64, 16%). Methodologically, tree-based and neural network-based approaches were the most prevalent Artificial Intelligence algorithms used in studies (32/64, 50% and 31/64, 48% respectively). A notable proportion of the studies (32/64, 50%) carried out their research using specially designed smart home testbeds that simulate the conditions in real-world. Moreover, ambient technology was a common thread (49/64, 77%), with occupancy-related data (such as motion and electrical appliance usage logs) and environmental sensors (indicators like temperature and humidity) being the most frequently used. CONCLUSION: Our results suggest that Artificial Intelligence has been increasingly deployed in the real-world Active Assisted Living context over the past decade, offering a variety of applications aimed at healthy aging and facilitating independent living for the older adults. A wide range of smart home indicators were leveraged for comprehensive data analysis, exploring and enhancing the potentials and effectiveness of solutions. However, our review has identified multiple research gaps that need further investigation. First, most research has been conducted in controlled testbed environments, leaving a lack of real-world applications that could validate the technologies' efficacy and scalability. Second, there is a noticeable absence of research leveraging cloud technology, an essential tool for large-scale deployment and standardized data collection and management. Future work should prioritize these areas to maximize the potential benefits of Artificial Intelligence in Active Assisted Living settings.

National burden of rheumatoid arthritis in Canada, 1990-2019: findings from the Global Burden of Disease Study 2019 - a GBD collaborator-led study.

OBJECTIVE: The objectives of this study were: (1) to describe burden of rheumatoid arthritis (RA) and trends from 1990 to 2019 using the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) data, (2) to describe age and sex differences in RA and (3) to compare Canada's RA burden to that of other countries. METHODS: Disease burden indicators included prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs) and disability-adjusted life-years (DALYs). GBD estimated fatal and non-fatal outcomes using published literature, survey data and health insurance claims. Data were analysed by Bayesian meta-regression, cause of death ensemble model and other statistical methods. DALYs for Canada were compared with DALYs of countries with similarly high Socio-Demographic Index values. RESULTS: In Canada, the RA prevalence rate increased by 27% between 1990 and 2019, mortality rate decreased by 27%, YLL rate decreased by 30%, YLD increased by 27% and DALY rate increased by 13%, all age standardised. The decline in RA mortality and YLL rates was especially pronounced after 2002. The disease burden was higher in females for all indicators, and DALY rates were higher among older age groups, peaking at age 75-79 years. Prevalence and DALYs were higher in Canada compared with global rates. CONCLUSION: Trends in RA burden indicators over time and differences by age and sex have important implications for Canadian policy-makers, researchers and care providers. Early identification and management of RA in women may help reduce the overall burden of RA in Canada.

Health trends in Canada 1990-2019: An analysis for the Global Burden of Disease Study.

OBJECTIVE: Monitoring trends in key population health indicators is important for informing health policies. The aim of this study was to examine population health trends in Canada over the past 30 years in relation to other countries. METHODS: We used data on disability-adjusted life years (DALYs), years of life lost (YLL), years lived with disability, life expectancy (LE), and child mortality for Canada and other countries between 1990 and 2019 provided by the Global Burden of Disease Study. RESULTS: Life expectancy, age-standardized YLL, and age-standardized DALYs all improved in Canada between 1990 and 2019, although the rate of improvement has leveled off since 2011. The top five causes of all-age DALYs in Canada in 2019 were neoplasms, cardiovascular diseases, musculoskeletal disorders, neurological disorders, and mental disorders. The greatest increases in all-age DALYs since 1990 were observed for substance use, diabetes and chronic kidney disease, and sense organ disorders. Age-standardized DALYs declined for most conditions, except for substance use, diabetes and chronic kidney disease, and musculoskeletal disorders, which increased by 94.6%, 14.6%, and 7.3% respectively since 1990. Canada's world ranking for age-standardized DALYs declined from 9th place in 1990 to 24th in 2019. CONCLUSION: Canadians are healthier today than in 1990, but progress has slowed in Canada in recent years in comparison with other high-income countries. The growing burden of substance abuse, diabetes/chronic kidney disease, and musculoskeletal diseases will require continued action to improve population health.

RéSUMé: OBJECTIF: La surveillance des tendances des indicateurs clés de la santé de la population est importante pour éclairer les politiques de santé. Dans cette étude, nous avons examiné les tendances de la santé de la population au Canada au cours des 30 dernières années par rapport à d'autres pays. MéTHODES: Nous avons utilisé des données sur les années de vie ajustées en fonction de l'incapacité (DALY), les années de vie perdues (YLL), les années vécues avec un handicap, l'espérance de vie (LE) et la mortalité infantile pour le Canada et d'autres pays entre 1990 et 2019, fournies par l'Étude mondiale sur le fardeau de la maladie. RéSULTATS: L'espérance de vie, les YLL ajustées selon l'âge et les DALY ajustées selon l'âge ont tous connu une amélioration au Canada entre 1990 et 2019, bien que le taux d'amélioration se soit stabilisé depuis 2011. Les cinq principales causes des DALY pour tous les âges au Canada en 2019 étaient les néoplasmes, les maladies cardiovasculaires, les affections musculosquelettiques, les affections neurologiques et les troubles mentaux. Les plus fortes augmentations des DALY pour tous les âges depuis 1990 ont été observées pour l'usage de substances, le diabète et les maladies rénales chroniques, ainsi que les troubles des organes sensoriels. Les DALY ajustées selon l'âge ont diminué pour la plupart des conditions, à l'exception de l'usage de substances, du diabète et des maladies rénales chroniques, ainsi que des troubles musculosquelettiques, qui ont augmenté de 94,6 %, 14,6 % et 7,3 % respectivement depuis 1990. Le classement mondial du Canada pour les DALY ajustées selon l'âge est diminué de la 9ième place en 1990 à la 24ième place en 2019. CONCLUSION: Les Canadiens sont en meilleure santé aujourd'hui qu'en 1990, mais les progrès se sont ralentis ces dernières années par rapport à d'autres pays à revenu élevé. La croissance du fardeau lié à l'abus de substances, au diabète/maladies rénales chroniques et aux affections musculosquelettiques exigera des actions continues pour améliorer la santé de la population.

Investigating Canadian Public Attitudes Toward COVID-19 Vaccine Mandates with a Nested Analysis Framework.

BACKGROUND: Social media is an important medium for studying public attitudes toward COVID-19 vaccine mandates in Canada, and Reddit network communities are a good source for this. METHODS: This study applied a "nested analysis" framework. We collected 20378 Reddit comments via the Pushshift API and developed a BERT-based binary classification model to screen for relevance to COVID-19 vaccine mandates. We then used a Guided Latent Dirichlet Allocation (LDA) model on relevant comments to extract key topics and assign each comment to its most relevant topic. RESULTS: There were 3179 (15.6%) relevant and 17199 (84.4%) irrelevant comments. Our BERT-based model achieved 91% accuracy trained with 300 Reddit comments after 60 epochs. The Guided LDA model had an optimal coherence score of 0.471 with four topics: travel, government, certification, and institutions. Human evaluation of the Guided LDA model showed an 83% accuracy in assigning samples to their topic groups. CONCLUSION: We develop a screening tool for filtering and analyzing Reddit comments on COVID-19 vaccine mandates through topic modelling. Future research could develop more effective seed word-choosing and evaluation methods to reduce the need for human judgment.

Digital Disease Surveillance for Emerging Infectious Diseases: An Early Warning System Using the Internet and Social Media Data for COVID-19 Forecasting in Canada.

BACKGROUND: Emerging Infectious Diseases (EID) are a significant threat to population health globally. We aimed to examine the relationship between internet search engine queries and social media data on COVID-19 and determine if they can predict COVID-19 cases in Canada. METHODS: We analyzed Google Trends (GT) and Twitter data from 1/1/2020 to 3/31/2020 in Canada and used various signal-processing techniques to remove noise from the data. Data on COVID-19 cases was obtained from the COVID-19 Canada Open Data Working Group. We conducted time-lagged cross-correlation analyses and developed the long short-term memory model for forecasting daily COVID-19 cases. RESULTS: Among symptom keywords, "cough," "runny nose," and "anosmia" were strong signals with high cross-correlation coefficients >0.8 ( rCough = 0.825, t - 9; rRunnyNose = 0.816, t - 11; rAnosmia = 0.812, t - 3 ), showing that searching for "cough," "runny nose," and "anosmia" on GT correlated with the incidence of COVID-19 and peaked 9, 11, and 3 days earlier than the incidence peak, respectively. For symptoms- and COVID-related Tweet counts, the cross-correlations of Tweet signals and daily cases were rTweetSymptoms = 0.868, t - 11 and tTweetCOVID = 0.840, t - 10, respectively. The LSTM forecasting model achieved the best performance (MSE = 124.78, R2 = 0.88, adjusted R2 = 0.87) using GT signals with cross-correlation coefficients >0.75. Combining GT and Tweet signals did not improve the model performance. CONCLUSION: Internet search engine queries and social media data can be used as early warning signals for creating a real-time surveillance system for COVID-19 forecasting, but challenges remain in modelling.