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Tuberculosis (TB) causes an economic impact on the patients and their households. Although Thailand has expanded the national health benefit package for TB treatment, there was no data on out-of-pocket payments and income losses due to TB from patients and their household perspectives. This national TB patient cost survey was conducted to examine the TB-related economic burden, and assess the proportion of TB patients and their households facing catastrophic total costs because of TB disease. A cross-sectional TB patient cost survey was employed following WHO methods. Structured interviews with a paper-based questionnaire were conducted from October 2019 to July 2021. Both direct and indirect costs incurred from the patient and their household perspective were valued in 2021 and estimated throughout pre- and post-TB diagnosis episodes. We assessed the proportion of TB-affected households facing costs > 20% of household expenditure due to TB. We analyzed 1400 patients including 1382 TB (first-line treatment) and 18 drug-resistant TB patients (DR-TB). The mean total costs per TB episode for all study participants were 903 USD (95% confident interval; CI 771–1034 USD). Of these, total direct non-medical costs were the highest costs (mean, 402 USD, and 95%CI 334–470 USD) incurred per TB-affected household followed by total indirect costs (mean, 393 USD, and 95%CI 315–472 USD) and total direct medical costs (mean, 107 USD, and 95%CI 81–133 USD, respectively. The proportion of TB-affected households facing catastrophic costs was 29.5% (95%CI 25.1–34.0%) for TB (first-line), 61.1% (95%CI 29.6–88.1%) for DR-TB and 29.9% (95%CI 25.6–34.4%) overall. This first national survey highlighted the economic burden on TB-affected households. Travel, food/nutritional supplementation, and indirect costs contribute to a high proportion of catastrophic total costs. These suggest the need to enhance financial and social protection mechanisms to mitigate the financial burden of TB-affected households. [ABSTRACT FROM AUTHOR]

A global disaster, such as the recent Covid-19 pandemic, affects every aspect of our lives and there is a need to investigate these highly complex phenomena if one aims to diminish their impact in the health of the population, as well as their socio-economic stability. In this paper we present an attempt to understand the role of the governmental authorities and the response of the rest of the population facing such emergencies. We present a mathematical model that takes into account the epidemiological features of the pandemic and also the actions of people responding to it, focusing only on three aspects of the system, namely, the fear of catching this serious disease, the impact on the economic activities and the compliance of the people to the mitigating measures adopted by the authorities. We apply the model to the specific case of Spain, since there are accurate data available about these three features. We focused on tourism as an example of the economic activity, since this sector of economy is one of the most likely to be affected by the restrictions imposed by the authorities, and because it represents an important part of Spanish economy. The results of numerical calculations agree with the empirical data in such a way that we can acquire a better insight of the different processes at play in such a complex situation, and also in other different circumstances. [ABSTRACT FROM AUTHOR]

Insect biodiversity and abundance are in global decline, potentially leading to a crisis with profound ecological and economic consequences. Methods and technologies to monitor insect species to aid in preservation efforts are rapidly being developed yet their adoption has been slow and focused on specific use cases. We propose a computer vision model that works towards multi-objective insect species identification in real-time and on a large scale. We leverage an image data source with 16 million instances and a recent improvement in the YOLO computer vision architecture to present a quick and open-access method to develop visual AI models to monitor insect species across climatic regions. [ABSTRACT FROM AUTHOR]

The gradual progress in aligning financial flows with the adoption of clean technologies reveals a persistent funding gap, signaling a global misallocation of capital. Addressing this challenge necessitates political leadership and robust policies to counteract the insecurities impeding the redirection of financial flows. This study investigates into the impact of energy-related public–private partnership investments (PPPIE) and macro-environmental variables on the attainment of Sustainable Development Goal 7 (SDG7) across Association of Southeast Asian Nations (ASEAN) member countries from 1999 to 2021. Employing the Dynamac command technique, we conduct autoregressive distribution lag analysis and the Bounds Cointegration Test to evaluate ASEAN's efforts in achieving SDG7. Results indicate that a ten-year exogenous shock to the GDP growth rate initially causes a temporary decline in both GDP and PPPIE, albeit not statistically significant. However, in the long run, the shock becomes statistically significant, correlating with a negative decline in the GDP growth rate. This underscores the negative impact of external factors like the COVID-19 pandemic on the economic growth of ASEAN member countries. Specifically, a percentage increase in PPPIE leads to an 8.3% reduction in the GDP growth rate, revealing a detrimental and unsustainable impact on the economy. This signifies that energy investments in the ASEAN region, are predominantly unsustainable and adversely impact economic growth. Moreover, these energy investments contribute to a significant 52.6% increase in greenhouse gas emissions, indicating a substantial setback in the region's progress towards meeting SDG7's clean energy objectives by 2030. This suggests the present state of PPPIE does not align with sustainable clean energy goals of the region. Therefore, recommendations should include diversifying energy sources and investment strategies to enhance sustainable clean energy. Also, policymakers and researchers should reassess the terms and conditions of PPPIE, refining frameworks for private sector involvement to align with long-term economic sustainability goals. [ABSTRACT FROM AUTHOR]

Excess sugar is considered one of the primary factors contributing to overweight status. In Brazil, sugar-sweetened beverages (SSBs) contain a significant amount of this nutrient and are consumed excessively. These beverages are associated with adverse health outcomes and impose costs on the healthcare system. The literature currently lacks studies that aim to attribute specific nutrients or foods as causes of diseases and also evaluate their economic impact, especially in middle- and low-income countries. This study aims to estimate the direct and indirect costs of obesity, stratified by sex and age group, resulting from the excessive consumption of sugar-sweetened beverages in Brazil from 2008 to 2020, and to project these costs for the year 2036. The estimation of obesity costs attributable to excessive consumption of SSBs was based on relative risks and the population prevalence of obesity, considering expenditures on hospitalizations and outpatient procedures in the Unified Health System (SUS). Cost information was obtained from the health information systems available at SUS. The highest burden attributable to the consumption of SSBs was observed among younger individuals and progressively decreased with advancing age. The total direct costs in the period between 2008 and 2020 amounted to approximately US$ 6.33 million, 87% of which was related to expenses for females. Additionally, deaths resulting from the consumption of SSBs cost the economy US$ 40 million due to the premature loss of productivity. The total costs of obesity attributable to the consumption of SSBs are substantial, impacting public spending and generating social and productivity losses that burden the economy. It is crucial to develop and implement cost-effective fiscal and regulatory policies aimed at preventing and combating obesity. [ABSTRACT FROM AUTHOR]

Regional population mortality correlates with regional socioeconomic development. This study aimed to identify the key socioeconomic factors influencing mortality patterns in Chinese provinces. Using data from the Seventh Population Census, we analyzed mortality patterns by gender and urban‒rural division in 31 provinces. Using a functional regression model, we assessed the influence of fourteen indicators on mortality patterns. Main findings: (1) China shows notable gender and urban‒rural mortality variations across age groups. Males generally have higher mortality than females, and rural areas experience elevated mortality rates compared to urban areas. Mortality in individuals younger than 40 years is influenced mainly by urban‒rural factors, with gender becoming more noticeable in the 40–84 age group. (2) The substantial marginal impact of socioeconomic factors on mortality patterns generally becomes evident after the age of 45, with less pronounced differences in their impact on early-life mortality patterns. (3) Various factors have age-specific impacts on mortality. Education has a negative effect on mortality in individuals aged 0–29, extending to those aged 30–59 and diminishing in older age groups. Urbanization positively influences the probability of death in individuals aged 45–54 years, while the impact of traffic accidents increases with age. Among elderly people, the effect of socioeconomic variables is smaller, highlighting the intricate and heterogeneous nature of these influences and acknowledging certain limitations. [ABSTRACT FROM AUTHOR]

Economic costs of climate change are conventionally assessed at the aggregated global and national levels, while adaptation is local. When present, regionalised assessments are confined to direct damages, hindered by both data and models' limitations. This article goes beyond the aggregated analysis to explore direct and indirect economic consequences of sea level rise (SLR) at regional and sectoral levels in Europe. Using a dynamic computable general equilibrium model and novel datasets, we estimate the distribution of losses and gains across regions and sectors. A comparison of a high-end scenario against a no-climate-impact baseline suggests a GDP loss of 1.26% (€871.8 billion) for the whole EU&UK. Conversely our refined assessments show that some coastal regions lose 9.56–20.84% of GDP, revealing striking regional disparities. Inland regions grow due to the displaced demand from coastal areas, but the GDP gains are small (0–1.13%). While recovery benefits the construction sector, public services and industry face significant downturns. We show that prioritising recovery of critical sectors locally reduces massive regional GDP losses, at negligible costs to the overall European economy. Our analysis traces regional economic restructuring triggered by SLR, underscoring the necessity of region-specific adaptation policies that embrace uneven geographic impacts and unique sectoral profiles to inform resilient strategy design. [ABSTRACT FROM AUTHOR]