Matching Items (22)

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Challenges in modeling complexity of neglected tropical diseases: a review of dynamics of visceral leishmaniasis in resource limited settings

Description

Neglected tropical diseases (NTD), account for a large proportion of the global disease burden, and their control faces several challenges including diminishing human and financial resources for those distressed from

Neglected tropical diseases (NTD), account for a large proportion of the global disease burden, and their control faces several challenges including diminishing human and financial resources for those distressed from such diseases. Visceral leishmaniasis (VL), the second-largest parasitic killer (after malaria) and an NTD affects poor populations and causes considerable cost to the affected individuals. Mathematical models can serve as a critical and cost-effective tool for understanding VL dynamics, however, complex array of socio-economic factors affecting its dynamics need to be identified and appropriately incorporated within a dynamical modeling framework. This study reviews literature on vector-borne diseases and collects challenges and successes related to the modeling of transmission dynamics of VL. Possible ways of creating a comprehensive mathematical model is also discussed.

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Created

Date Created
  • 2017-09-18

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Modeling Dynamics of Methamphetamine Markets and Use: A Case Study of Arizona and California

Description

Substance abuse has become a major problem in the USA in the past decade, with immense public health and societal consequences. Methamphetamine (meth) use has grown due to an increased

Substance abuse has become a major problem in the USA in the past decade, with immense public health and societal consequences. Methamphetamine (meth) use has grown due to an increased number of meth production and distribution markets. Border states such as Arizona and California are especially concerned with Mexico’s production and distribution of meth to their residents. A mathematical model for meth use and markets was developed and then analyzed to track multiple types of drug markets and drug-related arrests for possession or distribution. The importance of social influences as a major causal factor in the onset of illicit drug use is explicitly incorporated. The model parameters are then estimated using meth-related data from California and Arizona. A parameter sensitivity analysis on the model output was carried out. The results suggest that law enforcement policy aimed at marketers will be significantly more effective than targeting current users. Moreover, local unorganized markets have a greater role in maintaining the endemic level of meth users. Whereas, global organized markets play a role in initiating meth use outbreaks. Some implications for interventions and health promotion for the two states are also discussed.

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Created

Date Created
  • 2019-05

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Alternative Medicine Perspectives Among 1.5 Generation Indian American Immigrants

Description

This study evaluates medical pluralism among 1.5 generation Indian American immigrants. 1.5 generation Indian Americans (N=16) were surveyed regarding their engagement in complementary and alternative medical systems (CAM), how immigration

This study evaluates medical pluralism among 1.5 generation Indian American immigrants. 1.5 generation Indian Americans (N=16) were surveyed regarding their engagement in complementary and alternative medical systems (CAM), how immigration affected that, and reasons for and for not continuing the use of CAM. Results indicated most 1.5 Indian immigrants currently engage in CAM, given that their parents also engage in CAM. The top reasons respondents indicated continued engagement in CAM was that it has no side effects and is preventative. Reasons for not practicing CAM included feeling out of place, not living with parents or not believing in CAM. After immigration, most participants decreased or stopped their engagement in CAM. More women than men continued to practice CAM after immigration. From the results, it was concluded that CAM is still important to 1.5 generation Indian immigrants.

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Created

Date Created
  • 2020-05

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Optimizing Age Structured Mass Drug Administration Against Soil-transmitted Helminthiasis in Ghana Using Cost-Benefit Analysis

Description

Soil-transmitted helminthiasis (STH), a neglected tropical disease (NTD) remains a major health problem all over the world especially in developing countries such as, Cameroon with a prevalence of 30.8%, Nigeria

Soil-transmitted helminthiasis (STH), a neglected tropical disease (NTD) remains a major health problem all over the world especially in developing countries such as, Cameroon with a prevalence of 30.8%, Nigeria and Ghana with a prevalence of 25.4% (Pullan et. al, 2014). This study touches on transmission patterns and investigates the effectiveness of policies on mass drug administration as a means to control STH in Ghana. The government of Ghana currently focuses mass drug administration efforts on school aged children (SAC) that are children between the ages of 5-14 years. This paper develops and evaluates a different mass drug administration strategy by hypothesizing that it would be more cost-effective to target some percentage of vulnerable adults in MDA efforts as opposed to only targeting SAC between ages 5-14 years in Ghana. This we hypothesize would lead to a faster reduction in prevalence over time, would be cost-effective and would hopefully lead to an eventual reduction in morbidity caused by this disease to a level of no public health significance in Ghana. We conduct three cost-effectiveness analyses based on three different case setups. Given the parameter values from literature, our results suggest that it is most cost-effective to cover 20% of adults while covering at least 24% of children in mass drug administration assuming that the number of individuals covered is equal to 80% a figure which is the current total coverage of school-aged children.

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Created

Date Created
  • 2018-05

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The role of mobility and health disparities on the transmission dynamics of Tuberculosis

Description

Background
The transmission dynamics of Tuberculosis (TB) involve complex epidemiological and socio-economical interactions between individuals living in highly distinct regional conditions. The level of exogenous reinfection and first time infection

Background
The transmission dynamics of Tuberculosis (TB) involve complex epidemiological and socio-economical interactions between individuals living in highly distinct regional conditions. The level of exogenous reinfection and first time infection rates within high-incidence settings may influence the impact of control programs on TB prevalence. The impact that effective population size and the distribution of individuals’ residence times in different patches have on TB transmission and control are studied using selected scenarios where risk is defined by the estimated or perceive first time infection and/or exogenous re-infection rates.
Methods
This study aims at enhancing the understanding of TB dynamics, within simplified, two patch, risk-defined environments, in the presence of short term mobility and variations in reinfection and infection rates via a mathematical model. The modeling framework captures the role of individuals’ ‘daily’ dynamics within and between places of residency, work or business via the average proportion of time spent in residence and as visitors to TB-risk environments (patches). As a result, the effective population size of Patch i (home of i-residents) at time t must account for visitors and residents of Patch i, at time t.
Results
The study identifies critical social behaviors mechanisms that can facilitate or eliminate TB infection in vulnerable populations. The results suggest that short-term mobility between heterogeneous patches contributes to significant overall increases in TB prevalence when risk is considered only in terms of direct new infection transmission, compared to the effect of exogenous reinfection. Although, the role of exogenous reinfection increases the risk that come from large movement of individuals, due to catastrophes or conflict, to TB-free areas.
Conclusions
The study highlights that allowing infected individuals to move from high to low TB prevalence areas (for example via the sharing of treatment and isolation facilities) may lead to a reduction in the total TB prevalence in the overall population. The higher the population size heterogeneity between distinct risk patches, the larger the benefit (low overall prevalence) under the same “traveling” patterns. Policies need to account for population specific factors (such as risks that are inherent with high levels of migration, local and regional mobility patterns, and first time infection rates) in order to be long lasting, effective and results in low number of drug resistant cases.

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Created

Date Created
  • 2017-01-11

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Contagion in Mass Killings and School Shootings

Description

Background
Several past studies have found that media reports of suicides and homicides appear to subsequently increase the incidence of similar events in the community, apparently due to the coverage

Background
Several past studies have found that media reports of suicides and homicides appear to subsequently increase the incidence of similar events in the community, apparently due to the coverage planting the seeds of ideation in at-risk individuals to commit similar acts.
Methods
Here we explore whether or not contagion is evident in more high-profile incidents, such as school shootings and mass killings (incidents with four or more people killed). We fit a contagion model to recent data sets related to such incidents in the US, with terms that take into account the fact that a school shooting or mass murder may temporarily increase the probability of a similar event in the immediate future, by assuming an exponential decay in contagiousness after an event.
Conclusions
We find significant evidence that mass killings involving firearms are incented by similar events in the immediate past. On average, this temporary increase in probability lasts 13 days, and each incident incites at least 0.30 new incidents (p = 0.0015). We also find significant evidence of contagion in school shootings, for which an incident is contagious for an average of 13 days, and incites an average of at least 0.22 new incidents (p = 0.0001). All p-values are assessed based on a likelihood ratio test comparing the likelihood of a contagion model to that of a null model with no contagion. On average, mass killings involving firearms occur approximately every two weeks in the US, while school shootings occur on average monthly. We find that state prevalence of firearm ownership is significantly associated with the state incidence of mass killings with firearms, school shootings, and mass shootings.

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Created

Date Created
  • 2015-07-02

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Identifying and Evaluating the Impact of Ecological Factors on the Patterns of Health Risk Behaviors Among Arizona State University Students

Description

Ecological modeling can be used to analyze health risk behaviors and their relationship to ecological factors, which is useful in determining how social environmental factors influence an individual’s decisions. Environmental

Ecological modeling can be used to analyze health risk behaviors and their relationship to ecological factors, which is useful in determining how social environmental factors influence an individual’s decisions. Environmental interactions shape the way that humans behave throughout the day, either through observation, action, or consequences. Specifically, health risk behaviors can be analyzed in relation to ecological factors. Alcohol drinking among college students has been a long concern and there are many risks associated with these behaviors in this population. Consistent engagement in health risk behaviors as a college student, such as drinking and smoking, can pose a much larger issues later in life and can lead to many different health problems. A research study was conducted in the form of a 27 question survey to determine and evaluate the impact of ecological factors on drinking and smoking behaviors among Arizona State University students. Ecological factors such as demographics, living conditions, contexts of social interactions, and places where students spend most of their time were used to evaluate the relationship between drinking and smoking behaviors and the ecological factors, both on- and off- campus.

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Created

Date Created
  • 2020-05

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Identifying and Evaluating the Impact of Ecological Factors on the Patterns of Health Risk Behaviors Among Arizona State University Students: A Survey-Based Study

Description

Ecological modeling can be used to analyze health risk behaviors and their relationship to ecological factors, which is useful in determining how social environmental factors influence an individual’s decisions. Environmental

Ecological modeling can be used to analyze health risk behaviors and their relationship to ecological factors, which is useful in determining how social environmental factors influence an individual’s decisions. Environmental interactions shape the way that humans behave throughout the day, either through observation, action, or consequences. Specifically, health risk behaviors can be analyzed in relation to ecological factors. Alcohol drinking among college students has been a long concern and there are many risks associated with these behaviors in this population. Consistent engagement in health risk behaviors as a college student, such as drinking and smoking, can pose a much larger issues later in life and can lead to many different health problems. A research study was conducted in the form of a 27 question survey to determine and evaluate the impact of ecological factors on drinking and smoking behaviors among Arizona State University students. Ecological factors such as demographics, living conditions, contexts of social interactions, and places where students spend most of their time were used to evaluate the relationship between drinking and smoking behaviors and the ecological factors, both on- and off- campus. The sample size of this study is 541 students. Statistical tests were conducted using Excel and RStudio to find relationships between patterns of health risk behaviors and various ecological factors. The data from the survey was analyzed to address three main questions. The first question analyzed drinking behaviors in relation to demographics, specifically gender and race. The second question assessed drinking behaviors with participation in Greek life and clubs on campus. The third question evaluated the relationship between health risk behaviors and students’ living conditions, such as living on or off campus. The results show that while gender does not have a statistically significant influence on drinking behaviors, race does. White individuals are more likely to engage in drinking behaviors and are more at risk than non-whites. Participation in Greek life was shown to be statistically significant in determining health risk behaviors, while involvement in clubs was not. Finally, on campus students are less likely to engage in health risk behaviors than off-campus students.

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Agent

Created

Date Created
  • 2019-05

Mathematical Modeling of Honeybee Population Dynamics

Description

Honeybees are important pollinators worldwide and pollinate about one-third of the food we consume. Recently though, honeybee colonies have been under increasing stress due to changing environments, pesticides, mites,

Honeybees are important pollinators worldwide and pollinate about one-third of the food we consume. Recently though, honeybee colonies have been under increasing stress due to changing environments, pesticides, mites, and viruses, which has increased the incidence of
colony collapse. This paper aims to understand how these different factors contribute to the decline of honeybee populations by using two separate approaches: data analysis and mathematical modeling. The data analysis examines the relative impacts of mites, pollen, mites, and viruses on honeybee populations and colony collapse. From the data, low initial bee populations lead to collapse in September while mites and viruses can lead to collapse in December. Feeding bee colonies also has a mixed effect, where it increases both bee and mite populations. For the model, we focus on the population dynamics of the honeybee-mite interaction. Using a system of delay differential equations with five population components, we find that bee colonies can collapse from mites, coexist with mites, and survive without them. As long as bees produce more pupa than the death rate of pupa and mites produce enough phoretic mites compared to their death rates, bees and mites can coexist. Thus, it is possible for honeybee colonies to withstand mites, but if the parasitism is too large, the colony will collapse. Provided
this equilibrium exists, the addition of mites leads to the colony moving to the interior equilibrium. Additionally, population oscillations are persistent if they occur and are connected to the interior equilibrium. Certain parameter values destabilize bee populations, leading to large
oscillations and even collapse. From these parameters, we can develop approaches that can help us prevent honeybee colony collapse before it occurs.

Contributors

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Created

Date Created
  • 2019-05

Estimate of the reproduction number of the 2015 Zika virus outbreak in Barranquilla, Colombia, and estimation of the relative role of sexual transmission

Description

Background
In 2015, the Zika arbovirus (ZIKV) began circulating in the Americas, rapidly expanding its global geographic range in explosive outbreaks. Unusual among mosquito-borne diseases, ZIKV has been shown to

Background
In 2015, the Zika arbovirus (ZIKV) began circulating in the Americas, rapidly expanding its global geographic range in explosive outbreaks. Unusual among mosquito-borne diseases, ZIKV has been shown to also be sexually transmitted, although sustained autochthonous transmission due to sexual transmission alone has not been observed, indicating the reproduction number (R0) for sexual transmission alone is less than 1. Critical to the assessment of outbreak risk, estimation of the potential attack rates, and assessment of control measures, are estimates of the basic reproduction number, R0.
Methods
We estimated the R0 of the 2015 ZIKV outbreak in Barranquilla, Colombia, through an analysis of the exponential rise in clinically identified ZIKV cases (n = 359 to the end of November, 2015).
Findings
The rate of exponential rise in cases was ρ = 0.076 days[superscript −1], with 95% CI [0.066,0.087] days[superscript −1]. We used a vector-borne disease model with additional direct transmission to estimate the R0; assuming the R0 of sexual transmission alone is less than 1, we estimated the total R0 = 3.8 [2.4,5.6], and that the fraction of cases due to sexual transmission was 0.23 [0.01,0.47] with 95% confidence.
Interpretation
This is among the first estimates of R0 for a ZIKV outbreak in the Americas, and also among the first quantifications of the relative impact of sexual transmission.

Contributors

Created

Date Created
  • 2016-10-17