Month: July 2024

Constructing Social Vulnerability Indexes with Increased Data and Machine Learning Highlight the Importance of Wealth Across Global Contexts

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Abstract

We consider the availability of new harmonized data sources and novel machine learning methodologies in the construction of a social vulnerability index (SoVI), a multidimensional measure that defines how individuals’ and communities may respond to hazards including natural disasters, economic changes, and global health crises. The factors underpinning social vulnerability—namely, economic status, age, disability, language, ethnicity, and location—are well understood from a theoretical perspective, and existing indices are generally constructed based on specific data chosen to represent these factors. Further, the indices’ construction methods generally assume structured, linear relationships among input variables and may not capture subtle nonlinear patterns more reflective of the multidimensionality of social vulnerability. We compare a procedure which considers an increased number of variables to describe the SoVI factors with existing approaches that choose specific variables based on consensus within the social science community. Reproducing the analysis across eight countries, as well as leveraging deep learning methods which in recent years have been found to be powerful for finding structure in data, demonstrate that wealth-related factors consistently explain the largest variance and are the most common element in social vulnerability.

Comparative Analysis of Vaginal Microbiome Associated with Oncogenic HPV Infection Among Different Ethnic Groups of Women of the Eastern Region of India

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Abstract

The study aimed to identify the influence of vaginal bacterial composition on HPV infection among tribal women of the eastern region of India compared to non-tribal women of the same region. For this study, 13 tribal women and 12 non-tribal women were recruited. DNA was isolated from vaginal swab samples, and subsequently, 16S rRNA gene analysis was performed. We identified two distinct clusters of samples based on taxonomic profiling and bacterial diversity. One cluster belonged to HPV negative samples and the other to HPV16/18 positive samples. The abundance of three bacterial species was significantly lower (p value < 0.05) among oncogenic HPV positive samples (mean abundance = 4.33, 0, and 0, respectively) compared to HPV negative samples (mean abundance = 29.71, 45.73, and 19.01, respectively) irrespective of their ethnicities, such as Lactobacillus amylolyticus, Bacillus coagulans, and Costridium sensu stricto. HPV16/18 positive samples also represent the differential microbiome composition between the two ethnic groups of women. Ethnicity specific variations in human vaginal microbiome composition might be recommended for geographically tailored microbiome-based therapeutic strategies.

Historical and future extreme climate events in highly vulnerable small Caribbean Islands

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Abstract

Small Caribbean islands are on the frontline of climate change because of sea level rise, extreme rainfall and temperature events, and heavy hurricanes. The Archipelago of San Andrés, Providencia, and Santa Catalina (SAI), are Caribbean islands belonging to Colombia and declared a Biosphere Reserve by UNESCO. SAI is highly vulnerable to climate change impacts but no hydroclimatological study quantified the extreme climatic changes yet. This study analyzes historical (1960s-2020, 7 stations) and future (2071–2100, CMIP6 multi-model ensemble, for four scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) trends in mean and extreme precipitation and temperature duration, frequency, and intensity. We find that heatwaves have more than tripled in frequency and doubled their maximum duration since the end of the ‘80 s. Precipitation is historically reduced by 5%, with a reduction recorded in 5 stations and an increase in 2, while extreme rainfall events significantly increased in frequency and intensity in most stations. The hotter-and-drier climate is amplified in the future for all scenarios, with much drier extremes (e.g., -0.5─-17% wet days, +8%─30% consecutive dry days, and +60%─89% in hot days). Although we show that hurricanes Categories IV and V near SAI (< 600 km) more than doubled since the’60 s, only a small fraction of extreme rainfall in the archipelago is associated with hurricanes or tropical storms. La Niña events also have no substantial influence on extreme precipitation. Interestingly, opposite and heterogeneous historical extreme rainfall trends are found across such small territory (< 30 km2). Thus, downscaled hydrometeorological data and model simulations are essential to investigate future extreme climatic events and strengthen small Caribbean islands' climate change adaptation efforts.

Analysis of the multiple drivers of vegetation cover evolution in the Taihangshan-Yanshan region

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Abstract

The Taihangshan-Yanshan region (TYR) is an important ecological barrier area for Beijing-Tianjin-Hebei, and the effectiveness of its ecological restoration and protection is of great significance to the ecological security pattern of North China. Based on the FVC data from 2000 to 2021, residual analysis, parametric optimal geodetector technique (OPGD) and multi-scale geographically weighted regression analysis (MGWR) were used to clarify the the multivariate driving mechanism of the evolution of FVC in the TYR. Results show that: (1) FVC changes in the TYR show a slowly fluctuating upward trend, with an average growth rate of 0.02/10a, and a spatial pattern of "high in the northwest and low in the southeast"; more than half of the FVC increased during the 22-year period. (2) The results of residual analysis showed that the effects of temperature and precipitation on FVC were very limited, and a considerable proportion (80.80% and 76.78%) of the improved and degraded areas were influenced by other factors. (3) The results of OPGD showed that the main influencing factors of the spatial differentiation of FVC included evapotranspiration, surface temperature, land use type, nighttime light intensity, soil type, and vegetation type (q > 0.2); The explanatory rates of the two-factor interactions were greater than those of the single factor, which showed either nonlinear enhancement or bifactorial enhancement, among which, the interaction of evapotranspiration with mean air and surface temperature has the strongest effect on the spatial and temporal evolution of FVC (q = 0.75). Surface temperature between 4.98 and 10.4 °C, evapotranspiration between 638 and 762 mm/a, and nighttime light between 1.96 and 7.78 lm/m2 favoured an increase in vegetation cover, and vegetation developed on lysimetric soils was more inclined to be of high cover. (4) The correlation between each variable and FVC showed different performance, GDP, elevation, slope and FVC showed significant positive correlation in most regions, while population size, urban population proportion, GDP proportion of primary and secondary industries, and nighttime light intensity all showed negative correlation with FVC to different degrees. The results can provide data for formulating regional environmental protection and restoration policies.

Healthcare leaders navigating complexity: a scoping review of key trends in future roles and competencies

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Abstract

Background

As healthcare systems rapidly become more complex, healthcare leaders are navigating expanding role scopes and increasingly varied tasks to ensure the provision of high-quality patient care. Despite a range of leadership theories, models, and training curricula to guide leadership development, the roles and competencies required by leaders in the context of emerging healthcare challenges (e.g., disruptive technologies, ageing populations, and burnt-out workforces) have not been sufficiently well conceptualized. This scoping review aimed to examine these roles and competencies through a deep dive into the contemporary academic and targeted gray literature on future trends in healthcare leadership roles and competencies.

Methods

Three electronic databases (Business Source Premier, Medline, and Embase) were searched from January 2018 to February 2023 for peer-reviewed literature on key future trends in leadership roles and competencies. Websites of reputable healthcare- and leadership-focused organizations were also searched. Data were analyzed using descriptive statistics and thematic analysis to explore both the range and depth of literature and the key concepts underlying leadership roles and competencies.

Results

From an initial 348 articles identified in the literature and screened for relevance, 39 articles were included in data synthesis. Future leadership roles and competencies were related to four key themes: innovation and adaptation (e.g., flexibility and vision setting), collaboration and communication (e.g., relationship and trust building), self-development and self-awareness (e.g., experiential learning and self-examination), and consumer and community focus (e.g., public health messaging). In each of these areas, a broad range of strategies and approaches contributed to effective leadership under conditions of growing complexity, and a diverse array of contexts and situations for which these roles and competencies are applicable.

Conclusions

This research highlights the inherent interdependence of leadership requirements and health system complexity. Rather than as sets of roles and competencies, effective healthcare leadership might be better conceptualized as a set of broad goals to pursue that include fostering collaboration amongst stakeholders, building cultures of capacity, and continuously innovating for improved quality of care.

Changes to tropical cyclone trajectories in Southeast Asia under a warming climate

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Abstract

The impacts of tropical cyclones (TCs) on Southeast Asia’s coastlines are acute due to high population densities in low-lying coastal environments. However, the trajectories of TCs are uncertain in a warming climate. Here, we assess >64,000 simulated TCs from the nineteenth century to the end of the twenty-first century for both moderate- and high-emissions scenarios. Results suggest changes to TC trajectories in Southeast Asia, including: (1) poleward shifts in both genesis and peak intensification rates; (2) TC formation and fastest intensification closer to many coastlines; (3) increased likelihoods of TCs moving most slowly over mainland Southeast Asia; and (4) TC tracks persisting longer over land. In the cities of Hai Phong (Vietnam), Yangon (Myanmar), and Bangkok (Thailand), these variations result in future increases in both peak TC intensity and TC duration compared to historical TCs.