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Abstract Aims Previous studies have examined risk factors for the development of heart failure (HF) subsequent to acute coronary syndrome (ACS). Our study seeks to clarify the clinical variables that best characterize patients who remain free from HF after coronary artery bypass grafting (CABG) surgery for ACS to determine novel biological factors favouring freedom from HF in prospective translational studies. Methods and results Nova Scotia residents (1995–2012) undergoing CABG within 3 weeks of ACS were included. The primary outcome was freedom from readmission to hospital due to HF. Descriptive statistics were generated, and a Cox proportional hazards model assessed outcome with adjustment for clinical characteristics. Of 11 936 Nova Scotians who underwent isolated CABG, 3264 (27%) had a recent ACS and were included. Deaths occurred in 210 (6%) of subjects prior to discharge. A total of 3054 patients were included in the long-term analysis. During follow-up, HF necessitating readmission occurred in 688 (21%) subjects with a hazard ratio of 12% at 2 years. The adjusted Cox model demonstrated significantly better freedom from HF for younger, male subjects without metabolic syndrome and no history of chronic obstructive pulmonary disease, renal insufficiency, atrial fibrillation, or HF. Conclusions Our findings have outlined important clinical variables that predict freedom from HF. Furthermore, we have shown that 12% of patients undergoing CABG after ACS develop HF (2 years). Our findings support our next phase in which we plan to prospectively collect blood and tissue specimens from ACS patients undergoing CABG in order to determine novel biological mechanism(s) that favour resolution of post-ACS inflammation.

Identifying factors that drive among-individual variation in mixed parasitic infections is fundamental to understanding the ecology and evolution of host–parasite interactions. However, a lack of non-invasive diagnostic tools to quantify mixed infections has restricted their investigation for host populations in the wild. This study applied DNA metabarcoding on parasite larvae cultured from faecal samples to characterize mixed strongyle infections of 320 feral horses on Sable Island, Nova Scotia, Canada, in 2014 to test for the influence of host (age, sex and reproductive/social status) and environmental (location, local density and social group membership) factors on variation. Twenty-five strongyle species were identified, with individual infections ranging from 3 to 18 species with a mean richness (±1 s.d. ) of 10.8 ± 3.1. Strongyle eggs shed in faeces were dominated by small strongyle (cyathostomins) species in young individuals, transitioning to large strongyles ( Strongylus spp.) in adults. Egg counts were highest in young individuals and in the west or centre of the island for most species. Individuals in the same social group had similar parasite communities, supporting the hypothesis that shared environment may drive parasite assemblages. Other factors such as local horse density, sex, date and reproductive/social status had minimal impacts on infection patterns. This study demonstrates that mixed infections can be dynamic across host ontogeny and space and emphasizes the need to consider species-specific infection patterns when investigating mixed infections.

Background While there is increasing interest in identifying pregnancies at risk for adverse outcome, existing prediction models have not adequately assessed population-based risks, and have been based on conventional regression methods. The objective of the current study was to identify predictors of fetal growth abnormalities using logistic regression and machine learning methods, and compare diagnostic properties in a population-based sample of infants. Methods Data for 30,705 singleton infants born between 2009 and 2014 to mothers resident in Nova Scotia, Canada was obtained from the Nova Scotia Atlee Perinatal Database. Primary outcomes were small (SGA) and large for gestational age (LGA). Maternal characteristics pre-pregnancy and at 26 weeks were studied as predictors. Logistic regression and select machine learning methods were used to build the models, stratified by parity. Area under the curve was used to compare the models; relative importance of predictors was compared qualitatively. Results 7.9% and 13.5% of infants were SGA and LGA, respectively; 48.6% of births were to primiparous women and 51.4% were to multiparous women. Prediction of SGA and LGA was poor to fair (area under the curve 60–75%) and improved with increasing parity and pregnancy information. Smoking, previous low birthweight infant, and gestational weight gain were important predictors for SGA; pre-pregnancy body mass index, gestational weight gain, and previous macrosomic infant were the strongest predictors for LGA. Conclusions The machine learning methods used in this study did not offer any advantage over logistic regression in the prediction of fetal growth abnormalities. Prediction accuracy for SGA and LGA based on maternal information is poor for primiparous women and fair for multiparous women.

Intervention Street reallocation interventions in three Canadian mid-sized cities: Victoria (British Columbia), Kelowna (British Columbia), and Halifax (Nova Scotia) related to the COVID-19 pandemic. Research question What street reallocation interventions were implemented, and what were the socio-spatial equity patterns? Methods We collected data on street reallocations (interventions that expand street space for active transportation or physical distancing) from April 1 to August 15, 2020 from websites and media. For each city, we summarized length of street reallocations (km) and described implementation strategies and communications. We assessed socio-spatial patterning of interventions by comparing differences in where interventions were implemented by area-level mobility, accessibility, and socio-demographic characteristics. Results Two themes motivated street reallocations: supporting mobility, recreation, and physical distancing in populous areas, and bolstering COVID-19 recovery for businesses. The scale of responses ranged across cities, from Halifax adding an additional 20% distance to their bicycle network to Kelowna closing only one main street section. Interventions were located in downtown cores, areas with high population density, higher use of active transportation, and close proximity to essential destinations. With respect to socio-demographics, interventions tended to be implemented in areas with fewer children and areas with fewer visible minority populations. In Victoria, the interventions were in areas with lower income populations and higher proportions of Indigenous people. Conclusion In this early response phase, some cities acted swiftly even in the context of massive uncertainties. As cities move toward recovery and resilience, they should leverage early learnings as they act to create more permanent solutions that support safe and equitable mobility.

Cancer is rapidly increasing worldwide and urgent global action towards cancer control is required. Consistent with global trends, Canada is expected to experience a near doubling in new cases and cancer deaths between 2020–2040; population growth and ageing being the primary drivers. The projected increased cancer incidence and its associated costs is expected to further exacerbate socioeconomic inequities. Focused actions to prevent cancer, to detect it earlier when more treatable, and, to lower the risk of recurrence, must be prioritized. Almost half of all cancers are preventable, caused by risk factors that are potentially avoidable and modifiable. Integrating cancer prevention with care-based models is necessary and represents the most cost-effective and sustainable approach to control cancer. To be effective, prevention efforts must consider the cancers impacting local populations and understand how community and individual factors interact within the spatial and temporal contexts in which people live. This study is part of the Nova Scotia Community Cancer Matrix project which profiles the cancers impacting communities over time; measuring associations between cancer and socioeconomic status (SES); and determining how the joint spatial distribution of cancers can be used to address inequities, identify priority populations and strengthen prevention efforts. Using Bayesian inference to model spatio-temporal variations in 58,206 cases diagnosed in 301 communities between 2001–2017, across 10 preventable cancer types, we report significant disparities in cancer risk across communities based on sex and community SES. The work highlights the utility of small-area mapping to identify at-risk communities and understand how community-SES impacts risk. It also uncovers significant inequities rooted in the differential distribution of material and social capacity, operating beyond the control of individuals. The approach is implementable to other regions to inform and strengthen prevention efforts aiming at reducing the burden of cancer or that of other diseases.

Addiction treatment and harm reduction services reduce risks of death and re-infection among patients with injection drug use-associated infective endocarditis (IDU-IE), but these are not offered at many hospitals. Among hospitalized patients with IDU-IE at the two tertiary-care hospitals in the Canadian Maritimes, we aimed to identify (1) the availability of opioid agonist treatment (OAT) and sterile drug injecting equipment, and (2) indicators of potential unmet addiction care needs. Retrospective review of IDU-IE hospitalizations at Queen Elizabeth II Health Sciences Centre (Halifax, Nova Scotia) and the Saint John Regional Hospital (Saint John, New Brunswick), October 2015 -March 2017. In Halifax, there are no addiction medicine providers on staff; in Saint John, infectious diseases physicians also practice addiction medicine. Inclusion criteria were: (1) probable or definite IE as defined by the modified Duke criteria; and (2) injection drug use within the prior 3 months. We identified 38 hospitalizations (21 in Halifax and 17 in Saint John), for 30 unique patients. Among patients with IDU-IE and untreated opioid use disorder, OAT was offered to 36% (5/14) of patients in Halifax and 100% (6/6) of patients in Saint John. Once it was offered, most patients at both sites initiated OAT and planned to continue it after discharge. In Halifax, no patients were offered sterile injecting equipment, and during five hospitalizations staff confiscated patients' own equipment. In Saint John, four patients were offered (and one was provided) injecting equipment in hospital, and during two hospitalizations staff confiscated patients' own equipment. Concerns regarding undertreated pain or opioid withdrawal were documented during 66% (25/38) of hospitalizations, and in-hospital illicit or non-medical drug use during 32% (12/38). Two patients at each site (11%; 4/38) had self-directed discharges against medical advice. Patients with IDU-IE in the Canadian Maritimes have unequal access to evidence-based addiction care depending on where they are hospitalized, which differs from the community-based standard of care. Indicators of potential unmet addiction care needs in hospital were common.

There is growing evidence that seasonal influenza vaccination in pregnancy has benefits for mother and baby. We determined influenza vaccination rates among pregnant women during the 2 nonpandemic influenza seasons following the 2009 H1N1 pandemic, explored maternal factors as predictors of influenza vaccination status and evaluated the association between maternal influenza vaccination and neonatal outcomes. We used a population-based perinatal database in the province of Nova Scotia, Canada, to examine maternal vaccination rates, determinants of vaccination status and neonatal outcomes. Our cohort included women who gave birth between Nov. 1, 2010, and Mar. 31, 2012. We compared neonatal outcomes between vaccinated and unvaccinated women using logistic regression analysis. Overall, 1958 (16.0%) of 12,223 women in our cohort received the influenza vaccine during their pregnancy. Marital status, parity, location of residence (rural v. urban), smoking during pregnancy and maternal influenza risk status were determinants of maternal vaccine receipt. The odds of preterm birth was lower among infants of vaccinated women than among those of nonvaccinated women (adjusted odds ratio [OR] 0.75, 95% confidence interval [CI] 0.60-0.94). The rate of low-birth-weight infants was also lower among vaccinated women (adjusted OR 0.73, 95% CI 0.56-0.95). Despite current guidelines advising all pregnant women to receive the seasonal influenza vaccine, influenza vaccination rates among pregnant women in our cohort were low in the aftermath of the 2009 H1N1 pandemic. This study and others have shown an association between maternal influenza vaccination and improved neonatal outcomes, which supports stronger initiatives to promote vaccination during pregnancy.

Stroke outcomes research requires risk-adjustment for stroke severity, but this measure is often unavailable. The Passive Surveillance Stroke SeVerity (PaSSV) score is an administrative data-based stroke severity measure that was developed in Ontario, Canada. We assessed the geographical and temporal external validity of PaSSV in British Columbia (BC), Nova Scotia (NS) and Ontario, Canada. We used linked administrative data in each province to identify adult patients with ischemic stroke or intracerebral hemorrhage between 2014-2019 and calculated their PaSSV score. We used Cox proportional hazards models to evaluate the association between the PaSSV score and the hazard of death over 30 days and the cause-specific hazard of admission to long-term care over 365 days. We assessed the models' discriminative values using Uno's c-statistic, comparing models with versus without PaSSV. We included 86,142 patients ( = 18,387 in BC, = 65,082 in Ontario, = 2,673 in NS). The mean and median PaSSV were similar across provinces. A higher PaSSV score, representing lower stroke severity, was associated with a lower hazard of death (hazard ratio and 95% confidence intervals 0.70 [0.68, 0.71] in BC, 0.69 [0.68, 0.69] in Ontario, 0.72 [0.68, 0.75] in NS) and admission to long-term care (0.77 [0.76, 0.79] in BC, 0.84 [0.83, 0.85] in Ontario, 0.86 [0.79, 0.93] in NS). Including PaSSV in the multivariable models increased the c-statistics compared to models without this variable. PaSSV has geographical and temporal validity, making it useful for risk-adjustment in stroke outcomes research, including in multi-jurisdiction analyses.

The spread of viral pathogens is inherently a spatial process. While the temporal aspects of viral spread at the epidemiological level have been increasingly well characterized, the spatial aspects of viral spread are still understudied due to a striking absence of theoretical expectations of how spatial dynamics may impact the temporal dynamics of viral populations. Characterizing the spatial transmission and understanding the factors driving it are important for anticipating local timing of disease incidence and for guiding more informed control strategies. Using a unique data set from Nova Scotia, Canada, the objective of this study is to apply a new novel method that recovers a spatial network of the influenza-like viral spread where the regions in their dominance are identified and ranked. We, then, focus on identifying regional predictors of those dominant regions. Our analysis uncovers 18 key regional drivers among 112 regions, each distinguished by unique community-level vulnerability factors such as demographic and economic characteristics. These findings offer valuable insights for implementing targeted public health interventions and allocating resources effectively.

The effect of the COVID-19 pandemic on the diagnosis and management of lung cancer in Canada is not fully understood. We sought to quantify the provincial volume of diagnostic imaging, thoracic surgeon referrals, time to surgery after referral, and pathologic staging for curative surgery in the context of the pandemic, as well as explore the effect of a pooled patient model, which was implemented to prioritize surgeries for lung cancer and mitigate the effects of the pandemic. We conducted a retrospective cohort study of patients who underwent diagnostic imaging in Nova Scotia and were subsequently referred to a thoracic surgeon at the province's only tertiary care centre for surgical management of their primary lung cancer before (Mar. 1, 2019, to Feb. 29, 2020) and during (Mar. 1, 2020, to Feb. 28, 2021) the COVID-19 pandemic. We conducted a survey to capture the patient and surgeon experience with a pooled patient model of managing surgical oncology cases. Compared with the pre-COVID-19 period, the overall volume of chest radiography and chest computed tomography decreased by 30.9% ( < 0.001) and 18.7% ( = 0.002), respectively, in the COVID-19 period. Thoracic surgeon referrals, operative approach, extent of resection, length of hospital stay, and pathologic staging did not significantly differ. Time from referral to surgery was significantly shorter during the COVID-19 period (mean 196.8 d v. 157.9 d, = 0.04). A pooled patient approach contributed to positive patient satisfaction. The COVID-19 pandemic was associated with reductions in rates of diagnostic imaging and referrals to thoracic surgeons for management of pulmonary cancer. A pooled patient model was used to mitigate the effects of the pandemic on lung cancer management and was positively received by patients. An extended study period is needed to determine the full effect of this redistribution of resources.