Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0-100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target-1 billion more people benefiting from UHC by 2023-we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2-47·5) in 1990 to 60·3 (58·7-61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9-3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010-2019 relative to 1990-2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6-421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0-3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5-1040·3]) residing in south Asia. The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people-the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close-or how far-all populations are in benefiting from UHC. Bill & Melinda Gates Foundation.

Snakebite envenoming is an important cause of preventable death. The World Health Organization (WHO) set a goal to halve snakebite mortality by 2030. We used verbal autopsy and vital registration data to model the proportion of venomous animal deaths due to snakes by location, age, year, and sex, and applied these proportions to venomous animal contact mortality estimates from the Global Burden of Disease 2019 study. In 2019, 63,400 people (95% uncertainty interval 38,900–78,600) died globally from snakebites, which was equal to an age-standardized mortality rate (ASMR) of 0.8 deaths (0.5–1.0) per 100,000 and represents a 36% (2–49) decrease in ASMR since 1990. India had the greatest number of deaths in 2019, equal to an ASMR of 4.0 per 100,000 (2.3—5.0). We forecast mortality will continue to decline, but not sufficiently to meet WHO’s goals. Improved data collection should be prioritized to help target interventions, improve burden estimation, and monitor progress.

The paper describes diagnostic criteria, clinical presentation and types of hallucinogen persisting perception disorder (HPPD), as well as current approaches to the treatment of this phenomenon using available scientific sources. Three case reports are also presented to demonstrate different types of this disorder. The first case report describes a 23-year old patient with a previous history of cannabis consumption who reported HPDD type I after the use of psilocybin mushrooms with small amounts of alcohol and hash. A month later, after cannabis use, the same visual and auditory distortions appeared again. During the following year, hallucinations recurred with the consumption of natural cannabinoids but not with alcohol intake. The symptoms have reduced within a year. Surprisingly, both other cases belonging to HPDD type II appeared in patients who consumed ecstasy, although MDMA is generally not considered a hallucinogen and hallucinations are not frequently reported after MDMA consumption. In both cases of HPPD type II after the use of ecstasy, the condition was very stressful and frightening. Both patients sought medical help and received tofisopam, lamotrigine and sertraline. After that, in both cases visual impairments have smoothed, but have not passed completely. Scientific sources suggest that HPPD may affect more than 50% of hallucinogen users and this disorder is often underdiagnosed. Therefore, patients suffering from HPPD can present in various clinical settings, and clinicians should be aware of this condition.

Introduction: Although pharmacogenetic tests provide the information on a genotype and the predicted phenotype, these tests themselves do not provide the interpretation of data for a physician. There are currently approximately two dozen pharmacogenomic clinical decision support systems used in psychiatry. Implementation of clinical decision support systems capable of forming recommendations on drug and dose selection according to the results of pharmacogenetic testing is an urgent task. Fulfillment of this task may allow increasing the efficacy of therapy and decreasing the risk of undesirable side effects. Materials and methods: The study included 51 male patients (21 in the main group and 30 in the control group) with alcohol withdrawal syndrome. To evaluate the efficacy and safety of therapy, several international psychometric scales and rating scales to measure side effects were used. Genotyping was performed using real‐time polymerase chain reaction with allele‐specific hybridization. Pharmacogenetic test results were interpreted using free software PGX2 ( www.pgx2.com ). Results: Statistically significant differences between the scores derived from all psychometric scales were revealed. For instance, the total score on CIWA‐Ar scale by day 3 was 13.5 [11.2; 16.0] for the main group and 18.0 [17.0; 22.0] ( p < 0.001) for the control group; by day 5, it was 6.5 [4.2; 8.0] for the main group and 15.0 [14.0; 16.0] ( p < 0.001) for the control group. The UKU side effect rating scale (UKU) also revealed a statistically significant difference. The total score on UKU scale by day 3 was 6.0 [5.0; 7.0] for the main group and 7.0 [6.0; 8.0] ( p < 0.001) for the control group; by day 5, this difference grew significantly: 5.5 [3.0; 9.0] for the main group and 14.0 [12.0; 19.0] ( p < 0.001) for the control group. The groups were representative (there was no difference between the scores at the inclusion of patients). Conclusion: Pharmacogenetic‐guided personalization of drug dose in patients with alcohol withdrawal syndrome can reduce the risk of undesirable side effects and pharmacoresistance. It allows recommending the use of pharmacogenomic clinical decision support systems for optimizing drug dosage.

Undergraduate students typically cope with various changes in their lives and experience many stressors associated with academic issues. Distress can make them more vulnerable to particular behavioral patterns in order to cope with negative affect. The association of problematic gambling with particular emotion regulation characteristics—some of which are developmentally dependent—becomes a recent focus of research with clinical and preventive implications. We carried out a pilot study enrolling voluntarily young adults of a public university in the Lisbon area, and 117 Portuguese-speaking individuals were interviewed. Participants, mainly female (M = 20.6; SD = 3.9), were investigated taking into consideration their gambling practices, characteristics of impulsivity and alexithymia, along with the symptoms of depression and anxiety. Portuguese versions of the South Oaks Gambling Scale (SOGS) and Short-Version of Impulsive Behavior Scale (S-UPPSP) were prepared (i.e., translation and back-translation of the original versions were performed). The prevalence of gambling problems in this sample is modest, although they were associated with negative urgency and sensation-seeking, as well as with depression symptoms. Multiple correspondence analysis, a particular multivariate model associating gambling problems with socio-demographic and psychological variables, allowed identifying different profiles of individuals. Trace and state emotional dysregulation features are selectively associated with distinctive gambling patterns, according to some previous findings in studies with other groups. Results may address new findings in terms of morbidity, risk factors and the design of future preventive strategies among such individuals.