The Impact of Geo-Political Socio-Economic Factors on Vaccine Dissemination Trends: A Case-Study on COVID-19 Vaccination Strategies

Background: The world in recent years has seen a pandemic of global scale. To counter the widespread loss of life and severe repercussions, researchers developed vaccinations at a fast pace to immunize the population. While the vaccines were developed and tested through extensive human trials, historically vaccines have been known to evoke mixed sentiments among the generic demographics. In the proposed study, we aim to reveal the impact of political and socio-economic factors on SARS-Cov-2 vaccination trends observed in two hundred and seventeen countries spread across the six continents.Methods: The study had hypothesized that the citizens who have lower trust in their government would be less inclined towards vaccination programs. To test this hypothesis, vaccination trends of nations under authoritarian rule were compared against democratic nations. Further, the study was proposed with relevance and impacting factor that was considered for vaccine dissemination in comparison with the literacy rate of the nations. Another impacting factor the study focused on for the vaccination dissemination trends was the health expenses of different nations.Results: The comparison of trends showed that dissemination of SARS-Cov-2 vaccines had been comparable between the two-opposing types of governance. The major impact factor behind the wide acceptance of the SARS-Cov-2 vaccine was the expenditure done by a country on healthcare. These nations used a large number of vaccines to administer to their population and the trends showed positive growth. While the nations with the lowest healthcare expenses failed to keep up with the demand and depended on vaccines donated by other countries to protect their population.Conclusions: The analysis revealed strong indicators that the nations which spend more on healthcare were the ones that had the best SARS-Cov-2 vaccination rollout. To further support decision-making in the future, countries should address the trust and sentiment of their citizens towards vaccination. For this, expenses need to be made to develop and promote vaccines and project them as positive health tools. Trial registration: Not Applicable

Non-fatal gunshot injuries during criminal acts in Mexico, 2013–2019

IntroductionAs the volume of firearms (legal and illegal) in Mexico grows, gun violence has become a major public health challenge. While studies have focused on gun-related homicides and robberies, there is a dearth of research addressing non-fatal gunshot injuries. At the same time, official government sources report limited information and undercount these injuries.ObjectiveThe objective of this article is threefold. First, to provide data of non-fatal gunshot injuries sustained during crimes in Mexico; second, to estimate their initial individual healthcare costs; finally, to compare those costs to those resulting from other forms of injuries. This article contributes to discussions on gun violence in Mexico and its impact on public health.MethodsWe analysed Mexico’s National Crime Victimization Survey from 2014 to 2020.FindingsWe estimated that there were approximately 150 415 non-fatal gunshot injuries during crimes perpetrated from 2013 to 2019. We found that most non-fatal criminal gunshot injuries occur during a robbery and that victims tend to be men and young people between 18 and 35 years of age. Most of these injuries occur in urban areas and public spaces. While non-fatal gun-related injuries are not as common during crimes as other non-fatal injuries, their initial individual healthcare expenses are significantly higher. Crimes involving gun-related injuries reported an average expense of 16 643 pesos and crimes involving other forms of injuries reported an average of 1281 pesos. This discrepancy highlights the health burden associated with gun violence.

Review in IoT for Healthcare in Our Life Engineering

Over the previous decade, significant research has been conducted in the field of healthcare services and their technological advancement. To be more precise, the Internet of Things (IoT) has demonstrated potential for connecting numerous medical devices, sensors, and healthcare professionals in order to deliver high-quality medical services in remote locations. This has resulted in an increase in patient safety, a decrease in healthcare expenses, an increase in the healthcare services’ accessibility, and an increase in the industry’s healthcare operational efficiency. This paper provides an overview of the possible healthcare uses of Internet of Things (IoT)-based technologies. The evolution of the HIoT application has been discussed in this article in terms of enabling technology, services of healthcare, and applications for resolving different healthcare challenges. Additionally, effort difficulties and drawbacks with the HIoT system are explored. In summary, this study provides a complete source of information on the many applications of HIoT together the purpose is to help future academics who are interested in working in the field and making advances gain knowledge into the issue.

Financial burden and impact of atopic dermatitis out-of-pocket healthcare expenses among black individuals in the United States

Black race is associated with increased atopic dermatitis (AD) severity and healthcare resource utilization. However, the burden of out-of-pocket (OOP) expenses among black individuals with AD is not well understood. We sought to characterize the categories and impact of OOP healthcare expenses associated with AD management among black individuals. A 25-question voluntary online survey was administered to National Eczema Association members (N = 113,502). Inclusion criteria (US residents age ≥ 18 years; self-report of AD or primary caregivers of individuals with AD) was met by 77.3% (1118/1447) of respondents. Black individuals with AD were younger, had lower household income, Medicaid, urban residence, poor AD control and frequent skin infections (P ≤ 0.02). Blacks vs. non-blacks reported more OOP costs for prescription medications covered (74.2% vs. 63.6%, P = 0.04) and not covered (65.1% vs. 46.5%, P = 0.0004) by insurance, emergency room visits (22.1% vs. 11.8%, P = 0.005), and outpatient laboratory testing (33.3% vs. 21.8%, P = 0.01). Black race was associated with increased household financial impact from OOP expenses (P = 0.0009), and predictors of financial impact included minimally controlled AD (adjusted OR [95% CI] 13.88 [1.63–117.96], P = 0.02), systemic therapy (4.34 [1.63–11.54], 0.003), > $200 monthly OOP expenses (14.28 [3.42–59.60], P = 0.0003), and Medicaid (4.02 [1.15–14.07], P = 0.03). Blacks with Medicaid had higher odds of harmful financial impact (3.32 [1.77–6.24], P = 0.0002) than those of black race (1.81 [1.04–3.15], P = 0.04) or with Medicaid (1.39 [1.02–1.88], P = 0.04) alone. Black race is associated with increased OOP costs for AD and significant household financial impact. Targeted interventions are needed to address financial disparities in AD.

The perceived impact of COVID-19 pandemic on healthcare cost in Bangladesh

The study showed the effect of the COVID-19 pandemic on healthcare expenses including the price of medicines, protective equipment, medical devices, healthcare facilities, and food. A self-administered questionnaire was used as the data collection tool and 400 people from different Bangladesh divisions (Dhaka, Chittagong, Barisal, Khulna, Mymensingh, Rajshahi, and Sylhet) participated in this study. Multiple regression analysis was used to estimate the impact of independent variables on dependent variables. R programming environment was used to perform the statistical analysis. Cronbach’s alpha was used for determination of reliability and found acceptable internal consistency. The price of protective equipment (POPE), the price of a healthcare facilities (POHCF), the consequences of rising prices (CRP), and COVID-19 were independent variables. COVID-19 (CRP) was a dependent variable that measured COVID-19’s impact (IC). The results of the regression analysis indicated a positive and significant impact of POPE, POHCF, and CRP on IC. However, the variance explained was still low (54.4%). Bangladesh should control the prices of all goods and services because of their influence on the impact of COVID-19. Future research should be conducted to discover other variables that affect the impact of COVID-19.

Healthcare expenses for poor households, how can large- scale poverty reduction programs help?

Three articles below show us how can poor households deal with healthcare expense and how can social-economic development programs change the time spending on travel time to healthcare facilities of ethnic minority households.

Out‐of‐pocket Annual Health Expenditures and Financial Toxicity from Healthcare Costs in Patients with Heart Failure in the United States

Background Heart failure (HF) poses a major public health burden in the United States. We examined the burden of out‐of‐pocket healthcare costs on patients with HF and their families. Methods and Results In the Medical Expenditure Panel Survey (MEPS), we identified all families with ≥1 adult member with HF during 2014 – 2018. Total out‐of‐pocket healthcare expenditures included yearly care‐specific costs and insurance premiums. We evaluated two outcomes of financial toxicity: (1) high financial burden – total out‐of‐pocket healthcare expense to post‐subsistence income of >20%, and (2) catastrophic financial burden with the rate of >40% ‐ a bankrupting expense defined by the WHO. There were 788 families in MEPS with a member with HF representing 0.54% (95% CI, 0.48%–0.60%) of all families nationally. The overall mean annual out‐of‐pocket healthcare expenses were $4423 (95% CI, $3908–$4939), with medications and health insurance premiums representing the largest categories of cost. Overall, 14% (95% CI, 11%‐18%) of families experienced a high burden and 5% (95% CI, 3%‐6%) experienced a catastrophic burden. Among the two‐fifths of families considered low‐income, 24% (95% CI, 18%‐30%) experienced a high financial burden, while 10% (95% CI, 6%‐14%) experienced a catastrophic burden. Low‐income families had 4‐fold greater risk‐adjusted odds of high (OR=3.9, 95% CI, 2.3–6.6), and 14‐fold greater risk‐adjusted odds of catastrophic financial burden (OR=14.2, 95% CI, 5.1–39.5) compared with middle/high income families. Conclusions Patients with HF and their families experience large out‐of‐pocket healthcare expenses. A large proportion encounter financial toxicity, with a disproportionate effect on low‐income families.

Prediction of Future Healthcare Expenses of Patients from Chest Radiographs Using Deep Learning: A Pilot Study

Our objective was to develop deep learning models with chest radiograph data to predict healthcare costs and classify top-50% spenders. 21,872 frontal chest radiographs were retrospectively collected from 19,524 patients with at least 1-year spending data. Among the patients, 11,003 patients had 3 years of cost data, and 1678 patients had 5 years of cost data. Model performances were measured with area under the receiver operating characteristic curve (ROC-AUC) for classification of top-50% spenders and Spearman ρ for prediction of healthcare cost. The best model predicting 1-year (N=21,872) expenditure achieved ROC-AUC of 0.806 [95% CI, 0.793-0.819] for top-50% spender classification and ρ of 0.561 [0.536-0.586] for regression. Similarly, for predicting 3-year (N=12,395) expenditure, ROC-AUC of 0.771 [0.750-0.794] and ρ of 0.524 [0.489-0.559]; for predicting 5-year (N=1,779) expenditure ROC-AUC of 0.729 [0.667-0.729] and ρ of 0.424 [0.324-0.529]. Our deep learning model demonstrated the feasibility of predicting health care expenditure as well as classifying top 50% healthcare spenders at 1, 3, and 5 year(s), implying the feasibility of combining deep learning with information-rich imaging data to uncover hidden associations that may allude physicians. Such a model can be a starting point of making an accurate budget in reimbursement models in healthcare industries.