NYHA class and number of cardiovascular rehospitalizations are established proxies for CHF progression and can be linked to utilities when used as health states in a Markov model. NYHA class should be used when feasible.
BackgroundAccording to World Health Organization (WHO) prevalence estimates, 1.1 million people in Mexico are infected with Trypanosoma cruzi, the etiologic agent of Chagas disease (CD). However, limited information is available about access to antitrypanosomal treatment. This study assesses the extent of access in Mexico, analyzes the barriers to access, and suggests strategies to overcome them.Methods and FindingsSemi-structured in-depth interviews were conducted with 18 key informants and policymakers at the national level in Mexico. Data on CD cases, relevant policy documents and interview data were analyzed using the Flagship Framework for Pharmaceutical Policy Reform policy interventions: regulation, financing, payment, organization, and persuasion. Data showed that 3,013 cases were registered nationally from 2007–2011, representing 0.41% of total expected cases based on Mexico's national prevalence estimate. In four of five years, new registered cases were below national targets by 11–36%. Of 1,329 cases registered nationally in 2010–2011, 834 received treatment, 120 were pending treatment as of January 2012, and the treatment status of 375 was unknown. The analysis revealed that the national program mainly coordinated donation of nifurtimox and that important obstacles to access include the exclusion of antitrypanosomal medicines from the national formulary (regulation), historical exclusion of CD from the social insurance package (organization), absence of national clinical guidelines (organization), and limited provider awareness (persuasion).ConclusionsEfforts to treat CD in Mexico indicate an increased commitment to addressing this disease. Access to treatment could be advanced by improving the importation process for antitrypanosomal medicines and adding them to the national formulary, increasing education for healthcare providers, and strengthening clinical guidelines. These recommendations have important implications for other countries in the region with similar problems in access to treatment for CD.
With increasing urbanization vector-borne diseases are quickly developing in cities, and urban control strategies are needed. If streets are shown to be barriers to disease vectors, city blocks could be used as a convenient and relevant spatial unit of study and control. Unfortunately, existing spatial analysis tools do not allow for assessment of the impact of an urban grid on the presence of disease agents. Here, we first propose a method to test for the significance of the impact of streets on vector infestation based on a decomposition of Moran's spatial autocorrelation index; and second, develop a Gaussian Field Latent Class model to finely describe the effect of streets while controlling for cofactors and imperfect detection of vectors. We apply these methods to cross-sectional data of infestation by the Chagas disease vector Triatoma infestans in the city of Arequipa, Peru. Our Moran's decomposition test reveals that the distribution of T. infestans in this urban environment is significantly constrained by streets (p<0.05). With the Gaussian Field Latent Class model we confirm that streets provide a barrier against infestation and further show that greater than 90% of the spatial component of the probability of vector presence is explained by the correlation among houses within city blocks. The city block is thus likely to be an appropriate spatial unit to describe and control T. infestans in an urban context. Characteristics of the urban grid can influence the spatial dynamics of vector borne disease and should be considered when designing public health policies.
The declining trend in HIV transmission rates despite ever-growing prevalence indicates prevention success correlated with the national HIV/AIDS program. Data from subgroup analyses provide stronger evidence of prevention success than incidence alone, as this measure demonstrates the effect of efforts and accounts for the burden of disease in the population.
Chronic heart failure (CHF) is a critical public health issue with increasing effect on the healthcare budgets of developed countries. Various decision-analytic modelling approaches exist to estimate the cost effectiveness of health technologies for CHF. We sought to systematically identify these models and describe their structures. We performed a systematic literature review in MEDLINE/PreMEDLINE, EMBASE, EconLit and the Cost-Effectiveness Analysis Registry using a combination of search terms for CHF and decision-analytic models. The inclusion criterion required 'use of a mathematical model evaluating both costs and health consequences for CHF management strategies'. Studies that were only economic evaluations alongside a clinical trial or that were purely descriptive studies were excluded. We identified 34 modelling studies investigating different interventions including screening (n = 1), diagnostics (n = 1), pharmaceuticals (n = 15), devices (n = 13), disease management programmes (n = 3) and cardiac transplantation (n = 1) in CHF. The identified models primarily focused on middle-aged to elderly patients with stable but progressed heart failure with systolic left ventricular dysfunction. Modelling approaches varied substantially and included 27 Markov models, three discrete-event simulation models and four mathematical equation sets models; 19 studies reported QALYs. Three models were externally validated. In addition to a detailed description of study characteristics, the model structure and output, the manuscript also contains a synthesis and critical appraisal for each of the modelling approaches. Well designed decision models are available for the evaluation of different CHF health technologies. Most models depend on New York Heart Association (NYHA) classes or number of hospitalizations as proxy for disease severity and progression. As the diagnostics and biomarkers evolve, there is the hope for better intermediate endpoints for modelling disease progression as those that are currently in use all have limitations.
Adding hs-CRP to traditional risk factors improves risk prediction, but the clinical relevance and cost-effectiveness of this improvement remain unclear.
Abstract. In 2000, the Guatemalan Ministry of Health initiated a Chagas disease program to control Rhodnius prolixus and Triatoma dimidiata by periodic house spraying with pyrethroid insecticides. The aim of this study was to characterize infestation patterns and analyze the contribution of programmatic practices to these patterns. Spatial infestation patterns at three time points were identified using the Getis-Ord Gi*(d) test. Logistic regression was used to assess predictors of reinfestation after pyrethroid insecticide administration. Spatial analysis showed high and low clusters of infestation at three time points. After two rounds of spray, 178 communities persistently fell in high infestation clusters. A time lapse between rounds of vector control greater than 6 months was associated with 1.54 (95% confidence interval = 1.07-2.23) times increased odds of reinfestation after first spray, whereas a time lapse of greater than 1 year was associated with 2.66 (95% confidence interval = 1.85-3.83) times increased odds of reinfestation after first spray compared with localities where the time lapse was less than 180 days. The time lapse between rounds of vector control should remain under 1 year. Spatial analysis can guide targeted vector control efforts by enabling tracking of reinfestation hotspots and improved targeting of resources.
Physical activity (PA) reduces the risk for a number of chronic diseases including heart disease, hypertension, hyperlipidemia, and diabetes mellitus type 2. However, most Americans do not meet expert recommendations for exercise, and minorities and low-income persons are the most inactive. Community-based approaches to promoting PA include primary care exercise referral programs. This study examines patient characteristics associated with utilization of a community health center-based exercise referral program. Adult female patients of a community health center with an affiliated fitness center, in Boston, MA, were included in the study if they received a referral to the fitness center from their primary care provider. Demographic and medical information was abstracted from the medical chart, and fitness records were abstracted to measure activation of a fitness center membership (creation of an account denoting at least an initial visit) and utilization over time. Overall, 503 (40%) of the 1,254 referred women in the study sample activated their membership. Black women were almost 60% more likely to activate their membership (adjusted OR 1.6, 95% CI 1.2-2.2), and women with higher co-morbidity counts were almost 45% more likely to activate (adjusted OR 1.4, 95% CI 1.0-2.0). Once activated, a minority of women participated at levels likely to improve cardiometabolic fitness. Of the 503 activations, 96 (19%) had no participation, 359 (71%) had low participation, and only 48 (10%) had high participation. No independent predictors of participation were identified. These findings suggest that program design may benefit from developing activation, initial participation, and retention strategies that address population-specific barriers.
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