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Abstract Background Diabetes is associated to a high financial and disease burden, explaining a large proportion of expenditure of the health system in one year. The purpose of this study was to estimate long-term costs and health outcomes of recently diagnosed patients with type 2 diabetes in Chile. Methods Cost and consequence study based on mathematical discrete event simulation (DES) model. We modelled expected costs (USD) and quality-adjusted life-years (QALYs) from diagnosis to death (or the age of 95) of a hypothetical cohort of 100,000 incident cases, simulated based on the Chilean National Health Survey 2018. The incidence of twelve complications was estimated assuming the hazard functions provided by the United Kingdom Prospective Diabetes Study. We explore heterogeneity across patients based on their baseline risk covariates and their impact on costs and QALYs. Results The expected cost and QALY of a recently diagnosed type 2 diabetes patient in Chile were USD 8660 and 12.44 QALYs. Both costs and QALYs were independently determined by baseline risk and the patient's life expectancy from the diagnosis. Length of life since diagnosis showed the major impact on costs (5.2% increase for every additional year). Myocardial infarction was the most frequent complication (47.4%) and the most frequent cause of death. Conclusion Diabetes type 2 determines a significant expenditure of the health system and substantial health losses. Although the control of cardiovascular risk factors and the metabolic control of the disease, both have an important impact on costs and outcomes, the main impact is achieved by postponing the age of onset of the disease.

Background: Diabetes is associated to a high financial and disease burden, explaining a large proportion of expenditure of the health system in one year. The purpose of this study was to estimate long-term costs and health outcomes of recently diagnosed patients with type 2 diabetes in Chile. Methods: Cost and consequence study based on mathematical discrete event simulation (DES) model. We modelled expected costs (USD) and quality-adjusted life-years (QALYs) from diagnosis to death (or the age of 95) of a hypothetical cohort of 100,000 incident cases, simulated based on the Chilean National Health Survey 2018. The incidence of twelve complications was estimated assuming the hazard functions provided by the United Kingdom Prospective Diabetes Study. We explore heterogeneity across patients based on their baseline risk covariates and their impact on costs and QALYs. Results: The expected cost and QALY of a recently diagnosed type 2 diabetes patient in Chile were USD 8660 and 12.44 QALYs. Both costs and QALYs were independently determined by baseline risk and the patient's life expectancy from the diagnosis. Length of life since diagnosis showed the major impact on costs (5.2% increase for every additional year). Myocardial infarction was the most frequent complication (47.4%) and the most frequent cause of death. Conclusion: Diabetes type 2 determines a significant expenditure of the health system and substantial health losses. Although the control of cardiovascular risk factors and the metabolic control of the disease, both have an important impact on costs and outcomes, the main impact is achieved by postponing the age of onset of the disease. [ABSTRACT FROM AUTHOR]

The social environment in which individuals live affects their fitness and in turn population dynamics as a whole. Birds with facultative cooperative breeding can live in social groups with dominants, subordinate helpers that assist with the breeding of others, and subordinate non‐helpers. Helping behaviour benefits dominants through increased reproductive rates and reduced extrinsic mortality, such that cooperative breeding might have evolved in response to unpredictable, harsh conditions affecting reproduction and/or survival of the dominants. Additionally, there may be different costs and benefits to both helpers and non‐helpers, depending on the time‐scale. For example, early‐life costs might be compensated by later‐life benefits. These differential effects are rarely analysed in the same study.We examined whether helping behaviour affects population persistence in a stochastic environment and whether there are direct fitness consequences of different life‐history tactics adopted by helpers and non‐helpers.We parameterised a matrix population model describing the population dynamics of female Seychelles warblers Acrocephalus sechellensis, birds that display facultative cooperative breeding. The stochastic density‐dependent model is defined by a (st)age structure that includes life‐history differences between helpers and non‐helpers and thus can estimate the demographic mechanisms of direct benefits of helping behaviour.We found that population dynamics are strongly influenced by stochastic variation in the reproductive rates of the dominants, that helping behaviour promotes population persistence and that there are only early‐life differences in the direct fitness of helpers and non‐helpers.Through a matrix population model, we captured multiple demographic rates simultaneously and analysed their relative importance in determining population dynamics of these cooperative breeders. Disentangling early‐life versus lifetime effects of individual tactics sheds new light on the costs and benefits of helping behaviour. For example, the finding that helpers and non‐helpers have similar lifetime reproductive outputs and that differences in reproductive values between the two life‐history tactics arise only in early life suggests that overall, helpers and non‐helpers have a similar balance of costs and benefits when analysing direct benefits. We recommend analysing the consequence of different life‐history tactics, during both early life and over the lifetime, as analyses of these different time frames may produce conflicting results. [ABSTRACT FROM AUTHOR]

As an extension to an activity introducing Year 5 students to the practice of statistics, the softwareTinkerPlotsmade it possible to collect repeated random samples from a finite population to informally explore students’ capacity to begin reasoning with a distribution of sample statistics. This article provides background for the sampling process and reports on the success of students in making predictions for the population from the collection of simulated samples and in explaining their strategies. The activity provided an application of the numeracy skill of using percentages, the numerical summary of the data, rather than graphing data in the analysis of samples to make decisions on a statistical question. About 70% of students made what were considered at least moderately good predictions of the population percentages for five yes–no questions, and the correlation between predictions and explanations was 0.78. [ABSTRACT FROM AUTHOR]

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