Spatial inequalities of COVID-19 incidence and associated socioeconomic risk factors in Portugal

COVID-19 hit the world in a sudden and uneven way. Scientific community has provided strong evidence about socioeconomic characteristics of the territory associated with the geographical pattern of COVID-19 incidence. Still, the role played by these factors differs between study areas. Geographically Weighted Regression (GWR) models were applied to explore the spatially varying association between age-standardized COVID-19 incidence rate in 2020 and socioeconomic conditions in Portugal, at the municipality level. The spatial context was defined as a function of the number of neighbours; the bandwidth was determined through AIC. Prior, the validity of the GWR was assessed through ordinary least squares models. Border proximity, proportion of overcrowded living quarters, persons employed in manufacturing establishments and persons employed in construction establishments were found to be significant predictors. It was possible to observe that municipalities are affected differently by the same factor, and that this varying influence has identifiable geographical patterns, the role of each analysed factor varies importantly across the country. This study provides useful insights for policymakers for targeted interventions and for proper identification of risk factors.

Application of Grey-Based SWARA and COPRAS Techniques in Disease Mortality Risk Assessment

The health industry is amongst the most affected systems in terms of multiobjective decision-making, rendering the final solution, vulnerable to errors; however, multicriteria decision analysis (MDCA) emerges as a supportive tool for the process of decision-making. Therefore, the present study seeks to offer an MCDA framework for assessing and identifying the potential influence of socioeconomic risk factors on noncommunicable disease mortality. We adopted a subjective approach of grey-based Step-wise Weight Assessment Ratio Analysis (SWARA) and COmplex PRoportional Assessment (COPRAS) approach to calculate weights of parameters and criteria, respectively, and then rank them based on their degree of significance. The findings reveal that CRD mortality is potentially affected by the selected socioeconomic risk variables followed by IHD and cancer. Implementing MCDA techniques in the present study will assist the public health practitioners and policymakers in drawing decisions on the best strategy to reduce CRD mortality, which contributes significantly to raising overall mortality.

Maternal childhood trauma and prenatal stressors are associated with child behavioral health

Maternal adversity and prenatal stress confer risk for child behavioral health problems. Few studies have examined this intergenerational process across multiple dimensions of stress; fewer have explored potential protective factors. Using a large, diverse sample of mother–child dyads, we examined associations between maternal childhood trauma, prenatal stressors, and offspring socioemotional-behavioral development, while also examining potential resilience-promoting factors. The Conditions Affecting Neurocognitive Development and Learning and Early Childhood (CANDLE) study prospectively followed 1503 mother–child dyads (65% Black, 32% White) from pregnancy. Exposures included maternal childhood trauma, socioeconomic risk, intimate partner violence, and geocode-linked neighborhood violent crime during pregnancy. Child socioemotional-behavioral functioning was measured via the Brief Infant Toddler Social Emotional Assessment (mean age = 1.1 years). Maternal social support and parenting knowledge during pregnancy were tested as potential moderators. Multiple linear regressions (N = 1127) revealed that maternal childhood trauma, socioeconomic risk, and intimate partner violence were independently, positively associated with child socioemotional-behavioral problems at age one in fully adjusted models. Maternal parenting knowledge moderated associations between both maternal childhood trauma and prenatal socioeconomic risk on child problems: greater knowledge was protective against the effects of socioeconomic risk and was promotive in the context of low maternal history of childhood trauma. Findings indicate that multiple dimensions of maternal stress and adversity are independently associated with child socioemotional-behavioral problems. Further, modifiable environmental factors, including knowledge regarding child development, can mitigate these risks. Both findings support the importance of parental screening and early intervention to promote child socioemotional-behavioral health.

Inflammatory pathways amongst people living with HIV in Malawi differ according to socioeconomic status

Background Non-communicable diseases (NCDs) are increased amongst people living with HIV (PLWH) and are driven by persistent immune activation. The role of socioeconomic status (SES) in immune activation amongst PLWH is unknown, especially in low-income sub-Saharan Africa (SSA), where such impacts may be particularly severe. Methods We recruited Malawian adults with CD4<100 cells/ul two weeks after starting ART in the REALITY trial (NCT01825031), as well as volunteers without HIV infection. Clinical assessment, socioeconomic evaluation, blood draw for immune activation markers and carotid femoral pulse wave velocity (cfPWV) were carried out at 2- and 42-weeks post-ART initiation. Socioeconomic risk factors for immune activation and arterial stiffness were assessed using linear regression models. Results Of 279 PLWH, the median (IQR) age was 36 (31–43) years and 122 (44%) were female. Activated CD8 T-cells increased from 70% amongst those with no education to 88% amongst those with a tertiary education (p = 0.002); and from 71% amongst those earning less than 10 USD/month to 87% amongst those earning between 100–150 USD/month (p = 0.0001). Arterial stiffness was also associated with higher SES (car ownership p = 0.003, television ownership p = 0.012 and electricity access p = 0.029). Conversely, intermediate monocytes were higher amongst those with no education compared to a tertiary education (12.6% versus 7.3%; p = 0.01) and trended towards being higher amongst those earning less than 10 USD/month compared to 100–150 USD/month (10.5% versus 8.0%; p = 0.08). Water kiosk use showed a protective association against T cell activation (p = 0.007), as well as endothelial damage (MIP1β, sICAM1 and sVCAM1 p = 0.047, 0.026 and 0.031 respectively). Conclusions Socioeconomic risk factors for persistent inflammation amongst PLWH in SSA differ depending on the type of inflammatory pathway. Understanding these pathways and their socioeconomic drivers will help identify those at risk and target interventions for NCDs. Future studies assessing drivers of inflammation in HIV should include an SES assessment.

The Evolution of Hail Production in Simulated Supercell Storms

Hailstorms pose a significant socioeconomic risk, necessitating detailed assessments of how the hail threat changes throughout their lifetimes. Hail production involves the favorable juxtaposition of ingredients, but how storm evolution affects these ingredients is unknown, limiting understanding of how hail production evolves. Unfortunately, neither surface hail reports nor radar-based swath estimates have adequate resolution or details needed to assess evolving hail production. Instead, we use a novel approach of coupling a detailed hail trajectory model to idealized convective storm simulations to better understand storm evolution’s influence on hail production. Hail production varies substantially throughout storms’ mature phases: maximum sizes vary by a factor of two, and the concentration of severe hail more than fivefold during 45-60-min periods. This variability arises from changes in updraft properties, which come from (i) changes in low-level convergence, and (ii) internal storm dynamics, including anticyclonic vortex shedding/storm splitting, and the response of the updraft’s airflow and supercooled liquid water content to these events. Hodograph shape strongly affects such behaviors. Straighter hodographs lead to more prolific hail production through wider updrafts and weaker mesocyclones, and a periodicity in hail size metrics associated with anticyclonic vortex shedding and/or storm splitting. In contrast, a curved hodograph (favorable for tornadoes) led to a storm with a stronger but more compact updraft, which occasionally produced giant (10-cm) hail, but that was a less-prolific severe hail producer overall. Unless storms are adequately sampled throughout their lifecycles, snapshots from ground reports will insufficiently resolve the true nature of hail production.

Financial indebtedness and suicide: A 1-year follow-up study of a population registered at the Swedish Enforcement Authority

Background: Economic hardship is an established suicidogenic factor. However, very little is known about whether financial difficulties in terms of debt problems, specifically, is related to suicide. This would seem to be an important research gap, not least at a time when the repercussions of the global financial crisis are still being felt by many people. Aims: This study sets out to examine whether experiencing financial indebtedness is related to suicide. Methods: For this purpose, people aged between 18 and 64 with a registration date for a debt in the Swedish Enforcement Authority register between 2015 and 2017 ( n = 180,842) are followed up for a 1-year period for death by suicide and compared with a sample from the general Swedish population ( n = 928,265). The analysis is based on penalized maximum likelihood logistic regressions. Results: Those who had experienced financial indebtedness were two and a half times more likely to commit suicide than those who had not lived through this experience (OR = 2.50), controlling for several demographic, socio-economic, and mental health conditions prior to the date of the registration at the Enforcement Authority. Conclusion: Debt repayment problems have a significant and detrimental impact on individuals’ risk of committing suicide, even when several other socioeconomic risk factors are controlled for. The results reinforce the importance of ongoing attempts to remove the issue of debt problem from its status as a rather hidden suicidogenic risk factor.

Machine Learning based Pricing Methodology for the Logistic Domain: a Preliminary Approach

In this work, we introduce a new methodology to discover logistic regions for pricing. We use value-based characteristics from different sources, such as demographic, socioeconomic, risk, transportation, among others, to find homogeneous and valuable pricing regions. The problem was formulated as a traditional cluster solution, where well-know metrics, such as BIC and silhouette score, were used for technical validation, and business premises and constraints, operational and sales, where used to enrich feature engineering and refine cluster formation. The results presented here are from a preliminary work that was validated through several sessions with stakeholders of interest, but it is still missing the market validation. Indeed, this work will be deployed soon and a more detailed validation process, including client adherence, will be performed and monitored until the end of this year.