Katia Charland

REM sleep behaviour disorder in Parkinson’s disease is associated with specific motor features

Background: Rapid eye movement (REM) sleep behaviour disorder (RBD) is commonly associated with Parkinson’s disease (PD), and recent studies have suggested that RBD in PD is associated with increased cognitive impairment, waking EEG slowing, autonomic impairment and lower quality of life on mental health components. However, it is unclear whether the association of RBD in PD has implications for motor manifestations of the disease. Methods: The study evaluated 36 patients with PD for the presence of RBD by polysomnography. Patients underwent an extensive evaluation on and off medication by a movement disorders specialist blinded to the polysomnography results. Measures of disease severity, quantitative motor indices, motor subtypes, complications of therapy and response to therapy were assessed and compared using regression analysis that adjusted for disease duration and age. Results: Patients with PD and RBD were less likely to be tremor predominant (14% vs 53%; p<0.02) and had a lower proportion of their Unified Parkinson Disease Rating Scale (UPDRS) score accounted for by tremor (8.2% vs 19.0%; p<0.01). An increased frequency of falls was noted among patients with RBD (38% vs 7%; p = 0.04). Patients with RBD demonstrated a lower amplitude response to their medication (UPDRS improvement 16.2% vs 34.8%; p = 0.049). Markers of overall disease severity, quantitative motor testing and motor complications did not differ between groups. Conclusions: The presence of altered motor subtypes in PD with RBD suggests that patients with PD and RBD may have a different underlying pattern of neurodegeneration than PD patients without RBD.

Manifestations of Parkinson disease differ in association with REM sleep behavior disorder

REM sleep behavior disorder (RBD) is commonly associated with Parkinson disease (PD), but it is unclear whether this association has implications for disease manifestations. We evaluated 36 PD patients for the presence of RBD by polysomnography. Patients underwent an extensive evaluation by a movement disorders specialist blinded to polysomnography results. Severity of motor manifestations, autonomic, visual, psychiatric, and olfactory dysfunctions and quality of life (QOL) were assessed, and compared using regression analysis that adjusted for disease duration, age and sex. Severity of motor manifestations did not differ between groups. However, the presence of RBD in PD was strongly associated with symptoms and signs of orthostatic hypotension (systolic blood pressure lying to standing = −25.7 ± 13.0 mmHg vs. −4.9 ±14.1, P < 0.001); and orthostatic symptom prevalence = 71% vs. 27%, P = 0.0076). There was no association between RBD and other autonomic symptoms. Color vision was worse in patients with RBD, but olfactory dysfunction did not differ between groups. The prevalence of depression, hallucinations, paranoia, and impulse disorders did not differ between groups. Emotional functioning and general health QOL measures were lower in those with RBD, but there were no differences between groups on disease‐specific indices or on measures of overall physical QOL. These findings suggest that the pathophysiology of RBD and nonmotor manifestations of PD, particularly autonomic dysfunction, are linked.

Caffeine for treatment of Parkinson disease A randomized controlled trial

Objective: Epidemiologic studies consistently link caffeine, a nonselective adenosine antagonist, to lower risk of Parkinson disease (PD). However, the symptomatic effects of caffeine in PD have not been adequately evaluated. Methods: We conducted a 6-week randomized controlled trial of caffeine in PD to assess effects upon daytime somnolence, motor severity, and other nonmotor features. Patients with PD with daytime somnolence (Epworth >10) were given caffeine 100 mg twice daily ×3 weeks, then 200 mg twice daily ×3 weeks, or matching placebo. The primary outcome was the Epworth Sleepiness Scale score. Secondary outcomes included motor severity, sleep markers, fatigue, depression, and quality of life. Effects of caffeine were analyzed with Bayesian hierarchical models, adjusting for study site, baseline scores, age, and sex. Results: Of 61 patients, 31 were randomized to placebo and 30 to caffeine. On the primary intention-to-treat analysis, caffeine resulted in a nonsignificant reduction in Epworth Sleepiness Scale score (−1.71 points; 95% confidence interval [CI] −3.57, 0.13). However, somnolence improved on the Clinical Global Impression of Change (+0.64; 0.16, 1.13, intention-to-treat), with significant reduction in Epworth Sleepiness Scale score on per-protocol analysis (−1.97; −3.87, −0.05). Caffeine reduced the total Unified Parkinsons Disease Rating Scale score (−4.69 points; −7.7, −1.6) and the objective motor component (−3.15 points; −5.50, −0.83). Other than modest improvement in global health measures, there were no changes in quality of life, depression, or sleep quality. Adverse events were comparable in caffeine and placebo groups. Conclusions: Caffeine provided only equivocal borderline improvement in excessive somnolence in PD, but improved objective motor measures. These potential motor benefits suggest that a larger long-term trial of caffeine is warranted. Classification of evidence: This study provides Class I evidence that caffeine, up to 200 mg BID for 6 weeks, had no significant benefit on excessive daytime sleepiness in patients with PD.

Measures of malaria burden after long-lasting insecticidal net distribution and indoor residual spraying at three sites in Uganda: A prospective observational study

Background Long-lasting insecticidal nets (LLINs) and indoor residual spraying of insecticide (IRS) are the primary vector control interventions used to prevent malaria in Africa. Although both interventions are effective in some settings, high-quality evidence is rarely available to evaluate their effectiveness following deployment by a national malaria control program. In Uganda, we measured changes in key malaria indicators following universal LLIN distribution in three sites, with the addition of IRS at one of these sites. Methods and Findings Comprehensive malaria surveillance was conducted from October 1, 2011, to March 31, 2016, in three sub-counties with relatively low (Walukuba), moderate (Kihihi), and high transmission (Nagongera). Between 2013 and 2014, universal LLIN distribution campaigns were conducted in all sites, and in December 2014, IRS with the carbamate bendiocarb was initiated in Nagongera. High-quality surveillance evaluated malaria metrics and mosquito exposure before and after interventions through (a) enhanced health-facility-based surveillance to estimate malaria test positivity rate (TPR), expressed as the number testing positive for malaria/number tested for malaria (number of children tested for malaria: Walukuba = 42,833, Kihihi = 28,790, and Nagongera = 38,690); (b) cohort studies to estimate the incidence of malaria, expressed as the number of episodes per person-year [PPY] at risk (number of children observed: Walukuba = 340, Kihihi = 380, and Nagongera = 361); and (c) entomology surveys to estimate household-level human biting rate (HBR), expressed as the number of female Anopheles mosquitoes collected per house-night of collection (number of households observed: Walukuba = 117, Kihihi = 107, and Nagongera = 107). The LLIN distribution campaign substantially increased LLIN coverage levels at the three sites to between 65.0% and 95.5% of households with at least one LLIN. In Walukuba, over the 28-mo post-intervention period, universal LLIN distribution was associated with no change in the incidence of malaria (0.39 episodes PPY pre-intervention versus 0.20 post-intervention; adjusted rate ratio [aRR] = 1.02, 95% CI 0.36–2.91, p = 0.97) and non-significant reductions in the TPR (26.5% pre-intervention versus 26.2% post-intervention; aRR = 0.70, 95% CI 0.46–1.06, p = 0.09) and HBR (1.07 mosquitoes per house-night pre-intervention versus 0.71 post-intervention; aRR = 0.41, 95% CI 0.14–1.18, p = 0.10). In Kihihi, over the 21-mo post-intervention period, universal LLIN distribution was associated with a reduction in the incidence of malaria (1.77 pre-intervention versus 1.89 post-intervention; aRR = 0.65, 95% CI 0.43–0.98, p = 0.04) but no significant change in the TPR (49.3% pre-intervention versus 45.9% post-intervention; aRR = 0.83, 95% 0.58–1.18, p = 0.30) or HBR (4.06 pre-intervention versus 2.44 post-intervention; aRR = 0.71, 95% CI 0.30–1.64, p = 0.40). In Nagongera, over the 12-mo post-intervention period, universal LLIN distribution was associated with a reduction in the TPR (45.3% pre-intervention versus 36.5% post-intervention; aRR = 0.82, 95% CI 0.76–0.88, p < 0.001) but no significant change in the incidence of malaria (2.82 pre-intervention versus 3.28 post-intervention; aRR = 1.10, 95% 0.76–1.59, p = 0.60) or HBR (41.04 pre-intervention versus 20.15 post-intervention; aRR = 0.87, 95% CI 0.31–2.47, p = 0.80). The addition of three rounds of IRS at ~6-mo intervals in Nagongera was followed by clear decreases in all outcomes: incidence of malaria (3.25 pre-intervention versus 0.63 post-intervention; aRR = 0.13, 95% CI 0.07–0.27, p < 0.001), TPR (37.8% pre-intervention versus 15.0% post-intervention; aRR = 0.54, 95% CI 0.49–0.60, p < 0.001), and HBR (18.71 pre-intervention versus 3.23 post-intervention; aRR = 0.29, 95% CI 0.17–0.50, p < 0.001). High levels of pyrethroid resistance were documented at all three study sites. Limitations of the study included the observational study design, the lack of contemporaneous control groups, and that the interventions were implemented under programmatic conditions. Conclusions Universal distribution of LLINs at three sites with varying transmission intensity was associated with modest declines in the burden of malaria for some indicators, but the addition of IRS at the highest transmission site was associated with a marked decline in the burden of malaria for all indicators. In highly endemic areas of Africa with widespread pyrethroid resistance, IRS using alternative insecticide formulations may be needed to achieve substantial gains in malaria control.

A scoping review of malaria forecasting: past work and future directions

Objectives There is a growing body of literature on malaria forecasting methods and the objective of our review is to identify and assess methods, including predictors, used to forecast malaria. Design Scoping review. Two independent reviewers searched information sources, assessed studies for inclusion and extracted data from each study. Information sources Search strategies were developed and the following databases were searched: CAB Abstracts, EMBASE, Global Health, MEDLINE, ProQuest Dissertations & Theses and Web of Science. Key journals and websites were also manually searched. Eligibility criteria for included studies We included studies that forecasted incidence, prevalence or epidemics of malaria over time. A description of the forecasting model and an assessment of the forecast accuracy of the model were requirements for inclusion. Studies were restricted to human populations and to autochthonous transmission settings. Results We identified 29 different studies that met our inclusion criteria for this review. The forecasting approaches included statistical modelling, mathematical modelling and machine learning methods. Climate-related predictors were used consistently in forecasting models, with the most common predictors being rainfall, relative humidity, temperature and the normalised difference vegetation index. Model evaluation was typically based on a reserved portion of data and accuracy was measured in a variety of ways including mean-squared error and correlation coefficients. We could not compare the forecast accuracy of models from the different studies as the evaluation measures differed across the studies. Conclusions Applying different forecasting methods to the same data, exploring the predictive ability of non-environmental variables, including transmission reducing interventions and using common forecast accuracy measures will allow malaria researchers to compare and improve models and methods, which should improve the quality of malaria forecasting.

Residential address errors in public health surveillance data: A description and analysis of the impact on geocoding

The residential addresses of persons with reportable communicable diseases are used increasingly for spatial monitoring and cluster detection, and public health may direct interventions based upon the results of routine spatial surveillance. There has been little assessment, however, of the quality of address data in reportable disease notifications and of the corresponding impact of these errors on geocoding and routine public health practices. The objectives of this study were to examine address errors for a selected reportable disease in a large urban center in Canada and to assess the impact of identified errors on geocoding and the estimated spatial distribution of the disease. We extracted data for all notifications of campylobacteriosis from the Montreal public health department from 1995 to 2008 and used an address verification algorithm to determine the validity of the residential address for each case and to suggest corrections for invalid addresses. We assessed the types of address errors as well as the resulting positional errors, calculating the distance between the original address and the correct address as well as changes in disease density. Address errors and missing addresses were prevalent in the public health records (10% and 5%, respectively) and they influenced the observed distribution of campylobacteriosis in Montreal, with address correction changing case location by a median of 1.1 km. Further examination of the extent of address errors in public health data is essential, as is the investigation of how these errors impact routine public health functions.

Socio-Economic Disparities in the Burden of Seasonal Influenza: The Effect of Social and Material Deprivation on Rates of Influenza Infection

Background There is little empirical evidence in support of a relationship between rates of influenza infection and level of material deprivation (i.e., lack of access to goods and services) and social deprivation (i.e. lack of social cohesion and support). Method Using validated population-level indices of material and social deprivation and medical billing claims for outpatient clinic and emergency department visits for influenza from 1996 to 2006, we assessed the relationship between neighbourhood rates of influenza and neighbourhood levels of deprivation using Bayesian ecological regression models. Then, by pooling data from neighbourhoods in the top decile (i.e., most deprived) and the bottom decile, we compared rates in the most deprived populations to the least deprived populations using age- and sex-standardized rate ratios. Results Deprivation scores ranged from one to five with five representing the highest level of deprivation. We found a 21% reduction in rates for every 1 unit increase in social deprivation score (rate ratio [RR] 0.79, 95% Credible Interval [CrI] 0.66, 0.97). There was little evidence of a meaningful linear relationship with material deprivation (RR 1.06, 95% CrI 0.93, 1.24). However, relative to neighbourhoods with deprivation scores in the bottom decile, those in the top decile (i.e., most materially deprived) had substantially higher rates (RR 2.02, 95% Confidence Interval 1.99, 2.05). Conclusion Though it is hypothesized that social and material deprivation increase risk of acute respiratory infection, we found decreasing healthcare utilization rates for influenza with increasing social deprivation. This finding may be explained by the fewer social contacts and, thus, fewer influenza exposure opportunities of the socially deprived. Though there was no evidence of a linear relationship with material deprivation, when comparing the least to the most materially deprived populations, we observed higher rates in the most materially deprived populations.

Forecasting malaria in a highly endemic country using environmental and clinical predictors

BackgroundMalaria thrives in poor tropical and subtropical countries where local resources are limited. Accurate disease forecasts can provide public and clinical health services with the information needed to implement targeted approaches for malaria control that make effective use of limited resources. The objective of this study was to determine the relevance of environmental and clinical predictors of malaria across different settings in Uganda.MethodsForecasting models were based on health facility data collected by the Uganda Malaria Surveillance Project and satellite-derived rainfall, temperature, and vegetation estimates from 2006 to 2013. Facility-specific forecasting models of confirmed malaria were developed using multivariate autoregressive integrated moving average models and produced weekly forecast horizons over a 52-week forecasting period.ResultsThe model with the most accurate forecasts varied by site and by forecast horizon. Clinical predictors were retained in the models with the highest predictive power for all facility sites. The average error over the 52 forecasting horizons ranged from 26 to 128% whereas the cumulative burden forecast error ranged from 2 to 22%.ConclusionsClinical data, such as drug treatment, could be used to improve the accuracy of malaria predictions in endemic settings when coupled with environmental predictors. Further exploration of malaria forecasting is necessary to improve its accuracy and value in practice, including examining other environmental and intervention predictors, including insecticide-treated nets.

Neighborhood Determinants of 2009 Pandemic A/H1N1 Influenza Vaccination in Montreal, Quebec, Canada

Neighborhood-level analyses of influenza vaccination can identify the characteristics of vulnerable neighborhoods, which can inform public health strategy for future pandemics. In this study, the authors analyzed rates of 2009 pandemic A/H1N1 influenza vaccination in Montreal, Quebec, Canada, using individual-level vaccination records from a vaccination registry with census, survey, and administrative data to estimate the population at risk. The neighborhood socioeconomic and demographic determinants of vaccination were identified using Bayesian ecologic logistic regression, with random effects to account for spatial autocorrelation. A total of 918,773 (49.9%) Montreal residents were vaccinated against pandemic A/H1N1 influenza from October 22, 2009, through April 8, 2010. Coverage was greatest among females, children under age 5 years, and health-care workers. Neighborhood vaccine coverage ranged from 33.6% to 71.0%. Neighborhoods with high percentages of immigrants (per 5% increase, odds ratio = 0.90, 95% credible interval: 0.86, 0.95) and material deprivation (per 1-unit increase in deprivation score, odds ratio = 0.93, 95% credible interval: 0.88, 0.98) had lower vaccine coverage. Half of the Montreal population was vaccinated; however, considerable heterogeneity in coverage was observed between neighborhoods and subgroups. In future vaccination campaigns, neighborhoods that are materially deprived or have high percentages of immigrants may benefit from focused interventions.

Relationship between community prevalence of obesity and associated behavioral factors and community rates of influenza-related hospitalizations in the United States

Please cite this paper as: Charland et al.(2012) Relationship between community prevalence of obesity and associated behavioral factors and community rates of influenza‐related hospitalizations in the United States. Influenza and Other Respiratory Viruses DOI: 10.1111/irv.12019.