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Nevin Manimala Statistics

Modified stochastic diffusion particle-tracking model (MSDPTM) incorporating energy cascade theory and eddy intermittency for suspended sediment transport in open channel flow

Chaos. 2024 Oct 1;34(10):103126. doi: 10.1063/5.0212322.

ABSTRACT

This study presents a modified stochastic diffusion particle tracking model (MSDPTM) that incorporates energy cascade theory to more accurately simulate suspended sediment transport. The impact of turbulent eddies on sediment particles is an intermittent process, which is also considered in this study. The study examines the time correlation between eddies using eddy turnover time and finds that closer-scale eddies exhibit higher correlations than those farther apart. The statistical properties of particle movement, such as the ensemble mean and variance of particle trajectories, have been calculated and compared with the stochastic diffusion particle tracking model (SDPTM) results. Notably, MSDPTM with intermittency demonstrates a significantly larger ensemble mean of particle trajectories in the streamwise direction than other particle tracking models. The proposed model is validated through comparison with available data, showing its enhanced performance. The results of the simulation indicate that MSDPTM outperforms SDPTM, especially when the intermittency effect of eddies is considered.

PMID:39413263 | DOI:10.1063/5.0212322

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Nevin Manimala Statistics

How combined pairwise and higher-order interactions shape transient dynamics

Chaos. 2024 Oct 1;34(10):101102. doi: 10.1063/5.0238827.

ABSTRACT

Understanding how species interactions shape biodiversity is a core challenge in ecology. While much focus has been on long-term stability, there is rising interest in transient dynamics-the short-lived periods when ecosystems respond to disturbances and adjust toward stability. These transitions are crucial for predicting ecosystem reactions and guiding effective conservation. Our study introduces a model that uses convex combinations to blend pairwise and higher-order interactions (HOIs), offering a more realistic view of natural ecosystems. We find that pairwise interactions slow the journey to stability, while HOIs speed it up. Employing global stability analysis and numerical simulations, we establish that as the proportion of HOIs increases, mean transient times exhibit a significant reduction, thereby underscoring the essential role of HOIs in enhancing biodiversity stabilization. Our results reveal a robust correlation between the most negative real part of the eigenvalues of the Jacobian matrix associated with the linearized system at the coexistence equilibrium and the mean transient times. This indicates that a more negative leading eigenvalue correlates with accelerated convergence to stable coexistence abundances. This insight is vital for comprehending ecosystem resilience and recovery, emphasizing the key role of HOIs in promoting stabilization. Amid growing interest in transient dynamics and its implications for biodiversity and ecological stability, our study enhances the understanding of how species interactions affect both transient and long-term ecosystem behavior. By addressing a critical gap in ecological theory and offering a practical framework for ecosystem management, our work advances knowledge of transient dynamics, ultimately informing effective conservation strategies.

PMID:39413260 | DOI:10.1063/5.0238827

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Nevin Manimala Statistics

Characteristics of mpox cases diagnosed in Military Health System beneficiaries, May 2022-April 2024

MSMR. 2024 Sep 20;31(9):7-11.

ABSTRACT

In May 2022, cases of mpox emerged beyond its historically endemic parts of Central and West Africa, primarily affecting men who have sex with men (MSM), and spreading via sexual networks. During this global outbreak the novel clinical and epidemiological characteristics of mpox disease were thoroughly documented in civilian populations but comparable data have not been reported for Military Health System (MHS) populations including beneficiaries. MHS cases were identified through a variety of data sources, including the Disease Reporting System internet (DRSi) and a customized query of ICD-10-CM (International Classification of Diseases, 10th Revision, Clinical Modification) encounter codes. Contemporaneous chart reviews of patients’ electronic health records in the Armed Forces Health Longitudinal Technology Application (AHLTA) and MHS GENESIS were performed to characterize cases. A total of 146 confirmed and probable MHS cases were identified from May 2022 through April 2024. Most cases occurred among MSM, with the majority developing classic prodromal symptoms and some experiencing anogenital and urinary symptoms.

PMID:39413256

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Nevin Manimala Statistics

The resilience of attitude toward vaccination: A web-based randomized controlled trial on the processing of online (mis)information

JMIR Form Res. 2024 Sep 23. doi: 10.2196/52871. Online ahead of print.

ABSTRACT

BACKGROUND: Before the COVID-19 pandemic, it was already recognized that internet-based misinformation and disinformation could influence individuals to refuse or delay vaccination for themselves, their families, or their child(ren). Reinformation, which refers to hyperpartisan and ideologically biased content, can propagate polarizing messages on vaccines, thereby contributing to vaccine hesitancy even if it is not outright disinformation.

OBJECTIVE: This study aimed to evaluate the impact of online reinformation on vaccine hesitancy. Specifically, our goal was to investigate how misinformation presented in the style and layout of a news article could influence the perceived tentativeness (credibility) of COVID-19 vaccine information and confidence in COVID-19 vaccination.

METHODS: We conducted a web-based randomized controlled trial (RCT) by recruiting English-speaking Canadians aged 18 years and above from across Canada through the Qualtrics paid opt-in panel system. Participants were randomly assigned to one of four distinct versions of a news article on COVID-19 vaccines, each featuring variations in writing style and presentation layout. After reading the news article, participants self-assessed the tentativeness of the information provided, their confidence in COVID-19 vaccines, and their attitude toward vaccination in general.

RESULTS: The survey included 537 participants, with 12 excluded for not meeting the task completion time. The final sample comprised 525 participants distributed about equally across the four news article versions. Chi-square (χ2) analyses revealed a statistically significant association between general attitude toward vaccination and the perceived tentativeness of the information about COVID-19 vaccines included in the news article (χ21 = 37.79, P<.0001). The effect size was small to moderate, with Cramer’s V = 0.27. An interaction was found between vaccine attitude and writing style (χ²₁ = 6.17, P= 0.01), with a small effect size, Cramer’s V = 0.11. Additionally, a Pearson correlation revealed a significant moderate-to-strong correlation between perceived tentativeness and confidence in COVID-19 vaccination, r(523) = .48, P<.0001. The coefficient of determination (r²) was 0.23, indicating that 23% of the variance in perceived tentativeness was explained by confidence in COVID-19 vaccines. In comparing participants exposed to a journalistic-style news article with those exposed to an ideologically biased article, Cohen’s d was calculated to be 0.38, indicating a small to medium effect size for the difference in the perceived tentativeness between these groups.

CONCLUSIONS: Exposure to an online news article conveying misinformation may not be sufficient to change an individual’s level of vaccine hesitancy. The study reveals that the predominant factor in shaping individuals’ perception of COVID-19 vaccines is their attitude toward vaccination in general. This attitude also moderates the influence of writing style on perceived tentativeness; the stronger one’s opposition to vaccines, the less pronounced the impact of writing style on perceived tentativeness.

CLINICALTRIAL: The study was part of a broader initiative with a registered protocol. The protocol was recorded on October 17, 2022, under the International Registered Report Identifier (IRRID): DERR1-10.2196/41012.

INTERNATIONAL REGISTERED REPORT: RR2-10.2196/41012.

PMID:39413215 | DOI:10.2196/52871

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Nevin Manimala Statistics

Changes in First and Second Births to U.S. Teenagers From 2000 to 2022

Natl Vital Stat Rep. 2024 Jul 24;(6). doi: 10.15620/cdc/157007.

ABSTRACT

OBJECTIVES: This study examines trends in the numbers, percentages, and rates of first and second and higher-order births to teenagers younger than age 20 and for those ages 15-17 and 18-19 by race and Hispanic origin.

METHODS: Data for this analysis are from the National Vital Statistics System birth data files from 2000 and 2022. Analyses are limited to births to females younger than age 20. Changes in the numbers, percentages, and rates of total, first, and second and higher-order teen births from 2000 to 2022 were calculated for all teenagers and for non-Hispanic American Indian and Alaska Native, non-Hispanic Black, non-Hispanic White, and Hispanic teenagers.

RESULTS: The number of first teen births declined 67% and the number of second and higher-order teen births declined 79%, while the population of female teenagers increased 7% from 2000 to 2022. The declines were greater for younger teenagers compared with older teenagers. First and second and higher-order teen birth rates declined 69% and 80%, respectively. Similar declines were found for each race and Hispanic-origin group. In 2000 and 2022, first and second and higher-order birth rates were lowest among White teenagers. First birth rates were highest among Hispanic teenagers in 2000 and for Hispanic and non-Hispanic American Indian and Alaska Native teenagers in 2022. In 2000, second and higher-order birth rates were highest for non-Hispanic Black and Hispanic teenagers; second and higher-order birth rates were more similar by race and Hispanic-origin group in 2022.

PMID:39412875 | DOI:10.15620/cdc/157007

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Nevin Manimala Statistics

Intention to Use a Mental Health App for Menopause: Health Belief Model Approach

JMIR Form Res. 2024 Oct 16;8:e60434. doi: 10.2196/60434.

ABSTRACT

BACKGROUND: Menopause presents a period of heightened vulnerability for mental health issues. Despite this, mental health screening is not consistently integrated into menopausal health care, and access to psychological interventions is limited. Digital technologies, such as web and smartphone apps, may offer a way to facilitate and improve mental health care provision throughout menopause. However, little is known about potential users’ intention to use such technologies during this critical phase of life.

OBJECTIVE: To examine the factors that impact the intention of potential users to use a mental health app during menopause, we used the Health Belief Model (HBM), a psychological framework widely used to understand and predict individuals’ health-related behaviors.

METHODS: An online survey was generated. Convenience sampling was used, with participants recruited via social media and email, through relevant foundations and support groups, and by word of mouth. Structural equation modeling with maximum likelihood estimation was conducted to explore whether the factor structure of the HBM is a good fit for predicting the intention to use a mental health app for menopause. A Cronbach α value of .05 was used for determining statistical significance.

RESULTS: A total of 1154 participants commenced the survey, of which 82.49% (n=952) completed at least 97% of the survey. Of these, 86.76% (n=826) expressed that their menopausal symptoms had negatively affected their mental health, and went on to answer questions regarding their experiences and interest in using a web or smartphone app for mental health symptoms related to menopause. Data from this subgroup (N=826) were analyzed. In total, 74.09% (n=612) of respondents sought online help for mental health symptoms related to menopause. The most common topics searched for were symptom characteristics (n=435, 52.66%) and treatment or therapy options (n=210, 25.42%). Psychoeducation (n=514, 62.23%) was the most desired mental health app feature, followed by symptom tracking (n=499, 60.41%) and self-help tips (n=469, 56.78%). In terms of the intention to use a mental health app, the Satorra-Bentler-scaled fit statistics indicated a good fit for the model (χ2278=790.44, P<.001; comparative fit index=0.933, root mean square error of approximation=0.047, standardized root mean square residual=0.056), with cues to action emerging as the most significant predictor of intention (β=.48, P<.001). This was followed by perceived barriers (β=-.25, P<.001), perceived susceptibility (β=.15, P<.001), and perceived benefits (β=.13, P<.001). Perceived severity (β=.01, P=.869) and self-efficacy (β=.03, P=.286) were not significantly associated with behavioral intention.

CONCLUSIONS: This study reveals important factors that influence the intention to use a mental health app during menopause. It emphasizes the need to address barriers to app usage, while highlighting the impact of credible endorsements and psychoeducation. Furthermore, the study underscores the significance of improving accessibility for users with lower digital literacy or limited resources.

PMID:39412868 | DOI:10.2196/60434

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Nevin Manimala Statistics

Infant Mortality in the United States, 2022: Data From the Period Linked Birth/Infant Death File

Natl Vital Stat Rep. 2024 Jul 25;(5). doi: 10.15620/cdc/157006.

ABSTRACT

OBJECTIVES: This report presents final 2022 infant mortality statistics by age at death, maternal race and Hispanic origin, maternal age, gestational age, leading causes of death, and maternal state of residence. Trends in infant mortality are also examined.

METHODS: Descriptive tabulations of data are presented and interpreted for infant deaths and infant mortality rates using the 2022 period linked birth/infant death file. The linked birth/infant death file is based on birth and death certificates registered in all 50 states and the District of Columbia.

RESULTS: A total of 20,577 infant deaths were reported in the United States in 2022, up 3% from 2021. The U.S. infant mortality rate was 5.61 infant deaths per 1,000 live births, a 3% increase from the rate of 5.44 in 2021. The neonatal mortality rate increased 3% from 3.49 in 2021 to 3.59 in 2022, and the postneonatal mortality rate increased 4% from 1.95 to 2.02. The overall infant mortality rate increased for infants of American Indian and Alaska Native non-Hispanic, White non-Hispanic, and Dominican women in 2022 compared with 2021; changes in rates for the other race and Hispanic-origin groups were not significant. Infants of Black non-Hispanic women had the highest mortality rate (10.90) in 2022, followed by infants of American Indian and Alaska Native non-Hispanic and Native Hawaiian or Other Pacific Islander non-Hispanic (9.06 and 8.50, respectively), Hispanic (4.89), White non-Hispanic (4.52), and Asian non-Hispanic (3.51) women. Mortality rates increased from 2021 to 2022 among preterm (less than 37 weeks of gestation) infants (33.59 to 34.78) and for infants born term (37 to 41 weeks of gestation) (2.08 to 2.18). The five leading causes of infant death in 2022 were the same as in 2021. Infant mortality rates by state for 2022 ranged from a low of 3.32 in Massachusetts to a high of 9.11 in Mississippi.

PMID:39412861 | DOI:10.15620/cdc/157006

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Nevin Manimala Statistics

U.S. State Life Tables, 2021

Natl Vital Stat Rep. 2024 Aug 21;(7). doi: 10.15620/cdc/157499.

ABSTRACT

OBJECTIVES: This report presents complete period life tables for each of the 50 states and the District of Columbia by sex based on age-specific death rates in 2021.

METHODS: Data used to prepare the 2021 state-specific life tables include: 2021 final mortality statistics; July 1, 2021, population estimates based on the Blended Base population estimates produced by the U.S. Census Bureau; and 2021 Medicare data for people ages 66-99. The methodology used to estimate the state-specific life tables is the same as that used to estimate the 2021 national life tables, with some modifications.

RESULTS: Among the 50 states and District of Columbia, Hawaii had the highest life expectancy at birth, 79.9 years in 2021, and Mississippi had the lowest, 70.9 years. From 2020 to 2021, life expectancy at birth declined for 39 states, increased for 11 states, and remained unchanged for the District of Columbia. In 2021, life expectancy at age 65 ranged from 16.1 years in Mississippi to 20.6 years in Hawaii. Life expectancy at birth was higher for females in all states and the District of Columbia. The difference in life expectancy between females and males ranged from 3.9 years in Utah to 7.6 years in New Mexico.

PMID:39412855 | DOI:10.15620/cdc/157499

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Nevin Manimala Statistics

COVID-19 Vaccine Preferences in General Populations in Canada, Germany, the United Kingdom, and the United States: Discrete Choice Experiment

JMIR Public Health Surveill. 2024 Oct 16;10:e57242. doi: 10.2196/57242.

ABSTRACT

BACKGROUND: Despite strong evidence supporting COVID-19 vaccine efficacy and safety, a proportion of the population remains hesitant to receive immunization. Discrete choice experiments (DCEs) can help assess preferences and decision-making drivers.

OBJECTIVE: We aim to (1) elicit preferences for COVID-19 vaccines in Canada, Germany, the United Kingdom, and the United States; (2) understand which vaccine attributes people there value; and (3) gain insight into the choices that different population subgroups make regarding COVID-19 vaccines.

METHODS: Participants in the 2019nCoV-408 study were aged ≥18 years; self-reported antivaccinationists were excluded. A DCE with a series of 2 hypothetical vaccine options was embedded into a survey to determine participant treatment preferences (primary objective). Survey questions covered vaccine preference, previous COVID-19 experiences, and demographics, which were summarized using descriptive statistics to understand the study participants’ backgrounds. In the DCE, participants were provided choice pairs: 1 set with and 1 without an “opt-out” option. Each participant viewed 11 unique vaccine profiles. Vaccine attributes consisted of type (messenger RNA or protein), level of protection against any or severe COVID-19, risk of side effects (common and serious), and potential coadministration of COVID-19 and influenza vaccines. Attribute level selections were included for protection and safety (degree of effectiveness and side effect risk, respectively). Participants were stratified by vaccination status (unvaccinated, or partially or fully vaccinated) and disease risk group (high-risk or non-high-risk). A conditional logit model was used to analyze DCE data to estimate preferences of vaccine attributes, with the percentage relative importance calculated to allow for its ranking. Each model was run twice to account for sets with and without the opt-out options.

RESULTS: The mean age of participants (N=2000) was 48 (SD 18.8) years, and 51.25% (1025/2000) were male. The DCE revealed that the most important COVID-19 vaccine attributes were protection against severe COVID-19 or any severity of COVID-19 and common side effects. Protection against severe COVID-19 was the most important attribute for fully vaccinated participants, which significantly differed from the unvaccinated or partially vaccinated subgroup (relative importance 34.8% vs 30.6%; P=.049). Avoiding serious vaccine side effects was a significantly higher priority for the unvaccinated or partially versus fully vaccinated subgroup (relative importance 10.7% vs 8.2%; P=.044). Attributes with significant differences in the relative importance between the high-risk versus non-high-risk subgroups were protection against severe COVID-19 (38.2% vs 31.5%; P<.000), avoiding common vaccine side effects (12% vs 20.5%; P<.000), and avoiding serious vaccine side effects (9.7% vs 7.5%; P=.002).

CONCLUSIONS: This DCE identified COVID-19 vaccine attributes, such as protection against severe COVID-19, that may influence preference and drive choice and can inform vaccine strategies. The high ranking of common and serious vaccine side effects suggests that, when the efficacy of 2 vaccines is comparable, safety is a key decision-making factor.

PMID:39412841 | DOI:10.2196/57242

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Nevin Manimala Statistics

Value and Affordability of Shelter-Based Opioid Treatment Among People Experiencing Homelessness

JAMA Netw Open. 2024 Oct 1;7(10):e2437241. doi: 10.1001/jamanetworkopen.2024.37241.

NO ABSTRACT

PMID:39412813 | DOI:10.1001/jamanetworkopen.2024.37241