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Objectives: This study aimed to summarize validity estimates of International Classification of Diseases (ICD) codes in identifying opioid overdose (OOD) among patient data from emergency rooms, emergency medical services, inpatient, outpatient, administrative, medical claims, and mortality, and estimate the sensitivity and specificity of the algorithms in the absence of a perfect reference standard., Methods: We systematically reviewed studies published before December 8, 2023, and identified with Medline and Embase. Studies reporting sufficient details to recreate a 2 × 2 table comparing the ICD algorithms to a reference standard in diagnosing OOD-related events were included. We used Bayesian latent class models (BLCM) to estimate the posterior sensitivity and specificity distributions of five ICD-10 algorithms and of the imperfect coroner's report review (CRR) in detecting prescription opioid-related deaths (POD) using one included study., Results: Of a total of 1990 studies reviewed, three were included. The reported sensitivity estimates of ICD algorithms for OOD were low (range from 25.0% to 56.8%) for ICD-9 in diagnosing non-fatal OOD-related events and moderate (72% to 89%) for ICD-10 in diagnosing POD. The last included study used ICD-9 for non-fatal and fatal and ICD-10 for fatal OOD-related events and showed high sensitivity (i.e. above 97%). The specificity estimates of ICD algorithms were good to excellent in the three included studies. The misclassification-adjusted ICD-10 algorithm sensitivity estimates for POD from BLCM were consistently higher than reported sensitivity estimates that assumed CRR was perfect., Conclusion: Evidence on the performance of ICD algorithms in detecting OOD events is scarce, and the absence of bias correction for imperfect tests leads to an underestimation of the sensitivity of ICD code estimates., (© 2024. The Author(s).)

Background: Commercial air travel can result in global dispersal of infectious diseases. During the coronavirus disease 2019 (COVID-19) pandemic, many countries implemented border measures, including restrictions on air travel, to reduce the importation risk of COVID-19. In the context of inbound air travel to Canada, this study aimed to: 1) characterize travel trends before and during the pandemic, and 2) statistically assess the association between travel volumes and travel restrictions during the pandemic., Methods: Monthly commercial air travel volume data from March 2017 to February 2023 were obtained from the International Air Transport Association (IATA). National and airport-level travel trends to Canada were characterized by inbound travel volumes, the number of countries contributing travellers and the ranking of the top ten countries contributing travellers across the study period, by six year-length subperiod groupings (three pre-pandemic and three pandemic). Using seasonal autoregressive integrated moving average (SARIMA) models, interrupted time series (ITS) analyses assessed the association between major travel restrictions and travel volumes by including variables to represent changes to the level and slope of the time series., Results: The pre-pandemic inbound travel volume increased by 3% to 7% between consecutive subperiods, with three seasonal peaks (July-August, December-January, March). At the onset of the pandemic, travel volume decreased by 90%, with the number of contributing countries declining from approximately 200 to 140, followed by a slow recovery in volume and seasonality. A disruption in the ranking of countries that contributed travellers was also noticeable during the pandemic. Results from the ITS analysis aligned with the timing of travel restrictions as follows: implementation in March 2020 coincided with a sharp reduction in volumes, while the easing of major restrictions, starting with the authorization of fully vaccinated travellers from the United States to enter Canada in August 2021, coincided with an increase in the slope of travel volumes. Descriptive and statistical results suggest a near-return of pre-pandemic travel patterns by the end of the study period., Conclusion: Study results suggest resilience in commercial air travel into Canada. Although the COVID-19 pandemic led to a disruption in travel trends, easing of travel restrictions appeared to enable pre-pandemic trends to re-emerge. Understanding trends in air travel volumes, as demonstrated here, can provide information that supports preparedness and response regarding importation risk of infectious pathogens., Competing Interests: Competing interests The authors declare no competing interests.

Rabies occurs throughout the Arctic, representing an ongoing public health concern for residents of northern communities. The Arctic fox (Vulpes lagopus) is the main reservoir of the Arctic rabies virus variant, yet little is known about the epidemiology of Arctic rabies, such as the ecological mechanisms driving where and when epizootics in fox populations occur. In this study, we provide the first portrait of the spatio-temporal spread of rabies across northern Canada. We also explore the impact of seasonal and multiannual dynamics in Arctic fox populations and climatic factors on rabies transmission dynamics. We analysed data on rabies cases collected through passive surveillance systems in the Yukon, Northwest Territories, Nunavut, Nunavik and Labrador from 1953 to 2014. In addition, we analysed a large and unique database of trapped foxes tested for rabies in the Northwest Territories and Nunavut from 1974 to 1984 as part of active surveillance studies. Rabies cases occurred in all Arctic regions of Canada and were relatively synchronous among foxes and dogs (Canis familiaris). This study highlights the spread of Arctic rabies virus variant across northern Canada, with contrasting rabies dynamics between different yet connected areas. Population fluctuations of Arctic fox populations could drive rabies transmission dynamics in a complex way across northern Canada. Furthermore, this study suggests different impacts of climate and sea ice cover on the onset of rabies epizootics in northern Canada. These results lay the groundwork for the development of epidemiological models to better predict the spatio-temporal dynamics of rabies occurrence in both wild and domestic carnivores, leading to better estimates of human exposure and transmission risk., (© 2021 Wiley-VCH GmbH.)

The robust estimate and forecast capability of random forests (RF) has been widely recognized, however this ensemble machine learning method has not been widely used in mosquito-borne disease forecasting. In this study, two sets of RF models were developed at the national (pooled department-level data) and department level in Colombia to predict weekly dengue cases for 12-weeks ahead. A pooled national model based on artificial neural networks (ANN) was also developed and used as a comparator to the RF models. The various predictors included historic dengue cases, satellite-derived estimates for vegetation, precipitation, and air temperature, as well as population counts, income inequality, and education. Our RF model trained on the pooled national data was more accurate for department-specific weekly dengue cases estimation compared to a local model trained only on the department's data. Additionally, the forecast errors of the national RF model were smaller to those of the national pooled ANN model and were increased with the forecast horizon increasing from one-week-ahead (mean absolute error, MAE: 9.32) to 12-weeks ahead (MAE: 24.56). There was considerable variation in the relative importance of predictors dependent on forecast horizon. The environmental and meteorological predictors were relatively important for short-term dengue forecast horizons while socio-demographic predictors were relevant for longer-term forecast horizons. This study demonstrates the potential of RF in dengue forecasting with a feasible approach of using a national pooled model to forecast at finer spatial scales. Furthermore, including sociodemographic predictors is likely to be helpful in capturing longer-term dengue trends., Competing Interests: The authors have declared that no competing interests exist.

Lyme disease, the most commonly reported vector-borne disease in North America, is caused by the spirochete Borrelia burgdorferi sensu stricto, which is transmitted by Ixodes scapularis in eastern Canada and Ixodes pacificus in western Canada. Recently, the northward range expansion of I. scapularis ticks, in south-eastern Canada, has resulted in a dramatic increase in the incidence of human Lyme disease. Detecting emerging areas of Lyme disease risk allows public health to target disease prevention efforts. We analysed passive tick surveillance data from Ontario and Manitoba to i) assess the relationship between the total numbers of I. scapularis submissions in passive surveillance from humans, and the number of human Lyme disease cases, and ii) develop province-specific acarological indicators of risk that can be used to generate surveillance-based risk maps. We also assessed associations between numbers of nymphal I. scapularis tick submissions only and Lyme disease case incidence. Using General Estimating Equation regression, the relationship between I. scapularis submissions (total numbers and numbers of nymphs only) in each census sub-division (CSD) and the number of reported Lyme disease cases was positively correlated and highly significant in the two provinces (P ≤ 0.001). The numbers of I. scapularis submissions over five years discriminated CSDs with ≥ 3 Lyme disease cases from those with < 3 cases with high accuracy when using total numbers of tick submission (Receiver Operating Characteristics area under the curve [AUC] = 0.89) and moderate accuracy (AUC = 0.78) when using nymphal tick submissions only. In Ontario the optimal cut-off point was a total 12 tick submissions from a CSD over five years (Sensitivity = 0.82, Specificity = 0.84), while in Manitoba the cut-off point was five ticks (Sensitivity = 0.71, Specificity = 0.79) suggesting regional variability of the risk of acquiring Lyme disease from an I. scapularis bite. The performances of the acarological indicators developed in this study for Ontario and Manitoba support the ability of passive tick surveillance to provide an early signal of the existence Lyme disease risk areas in regions where ticks and the pathogens they transmit are expanding their range., Competing Interests: The authors have declared that no competing interests exist.

Seagrasses are ecosystem engineers of essential marine habitat. Their populations are rapidly declining worldwide. One potential cause of seagrass population declines is wasting disease, which is caused by opportunistic pathogens in the genus Labyrinthula. While infection with these pathogens is common in seagrasses, theory suggests that disease only occurs when environmental stressors cause immunosuppression of the host. Recent evidence suggests that host factors may also contribute to disease caused by opportunistic pathogens. In order to quantify patterns of disease, identify risk factors, and investigate responses to infection, we surveyed shoot density, shoot length, epiphyte load, production of plant defenses (phenols), and wasting disease prevalence in eelgrass Zostera marina across 11 sites in the central Salish Sea (Washington state, USA), a region where both wasting disease and eelgrass declines have been documented. Wasting disease was diagnosed by the presence of necrotic lesions, and Labyrinthula cells were identified with histology. Disease prevalence among sites varied from 6 to 79%. The probability of a shoot being diseased was higher in longer shoots, in patches of higher shoot density, and in shoots with higher levels of biofouling from epiphytes. Phenolic concentration was higher in diseased leaves. We hypothesize that this results from the induction of phenols during infection. Additional research is needed to evaluate whether phenols are an adaptive defense against Labyrinthula infection. The high site-level variation in disease prevalence emphasizes the potential for wasting disease to be causing some of the observed decline in eelgrass beds.

Telomere length and telomerase activity have received increased attention as markers of cellular aging, but the determinants of inter-individual variation in these markers are incompletely understood. Cytomegalovirus (CMV) infection may be particularly important for telomere and telomerase dynamics due to its dramatic impact on peripheral blood lymphocyte composition, i.e., increasing the number and proportions of highly differentiated T cells that are characterized by shorter telomere length (TL) and lowered telomerase activity (TA). However, the possible relationship between CMV infection and leukocyte TL and TA has not been well-examined in vivo. This study examined the associations of CMV seropositivity and CMV IgG antibodies with leukocyte (TL) and (TA) in a sample of 434 healthy individuals (ages 53-76) from the Whitehall II cohort. Positive CMV serostatus was significantly associated with lower TA among women, and higher CMV IgG antibody levels were associated with lower TA in the overall sample. However, neither CMV seropositivity nor CMV IgG antibody levels (reflecting subclinical reactivation) among the seropositive were significantly associated with TL. These associations were robust to adjustment for age, employment grade, BMI, and smoking status. The results demonstrate that CMV seropositivity and subclinical reactivation predict lower TA. Future longitudinal studies should test whether the association of CMV with lower TA contributes to accelerated telomere shortening over time., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Objectives: We have described vaccine coverage of Michigan young adolescents immunized with tetanus, diphtheria, and pertussis; meningococcal conjugate; and human papillomavirus vaccines during 2006-2008., Methods: We obtained data from the Michigan Care Improvement Registry, a state-based immunization information system that included more than 57 million vaccination records. We examined 3 overlapping cohorts of 11- and 12-year-old children (n > 350 000 in each) to assess temporal trends in vaccination coverage, characteristics of those immunized, funding sources, and vaccination sites., Results: Vaccine uptake increased during 2006 through 2008, peaking in the summer months. More than half of children receiving more than 1 vaccine received the vaccines simultaneously. Older age, receipt of Medicaid, and prior completion of early childhood immunizations were associated with greater odds of vaccination., Conclusions: Vaccine coverage among Michigan young adolescents is increasing but continues to be relatively low. Coverage of 11- and 12-year-old children may improve with efforts to encourage vaccination at all health care visits, an increase in public funding in support of adolescent vaccination, and continued monitoring of adolescent vaccination levels through school-based assessments.