Matching Items (192)
Description
Mathematical epidemiology, one of the oldest and richest areas in mathematical biology, has significantly enhanced our understanding of how pathogens emerge, evolve, and spread. Classical epidemiological models, the standard for predicting and managing the spread of infectious disease, assume that contacts between susceptible and infectious individuals depend on their relative frequency in the population. The behavioral factors that underpin contact rates are not generally addressed. There is, however, an emerging a class of models that addresses the feedbacks between infectious disease dynamics and the behavioral decisions driving host contact. Referred to as “economic epidemiology” or “epidemiological economics,” the approach explores the determinants of decisions about the number and type of contacts made by individuals, using insights and methods from economics. We show how the approach has the potential both to improve predictions of the course of infectious disease, and to support development of novel approaches to infectious disease management.
ContributorsPerrings, Charles (Author) / Castillo-Chavez, Carlos (Author) / Chowell-Puente, Gerardo (Author) / Daszak, Peter (Author) / Fenichel, Eli P. (Author) / Finnoff, David (Author) / Horan, Richard D. (Author) / Kilpatrick, A. Marm (Author) / Kinzig, Ann (Author) / Kuminoff, Nicolai (Author) / Levin, Simon (Author) / Morin, Benjamin (Author) / Smith, Katherine F. (Author) / Springborn, Michael (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / W.P. Carey School of Business (Contributor) / Economics (Contributor) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2015-12-01
Description
Preserving a system’s viability in the presence of diversity erosion is critical if the goal is to sustainably support biodiversity. Reduction in population heterogeneity, whether inter- or intraspecies, may increase population fragility, either decreasing its ability to adapt effectively to environmental changes or facilitating the survival and success of ordinarily rare phenotypes. The latter may result in over-representation of individuals who may participate in resource utilization patterns that can lead to over-exploitation, exhaustion, and, ultimately, collapse of both the resource and the population that depends on it. Here, we aim to identify regimes that can signal whether a consumer–resource system is capable of supporting viable degrees of heterogeneity. The framework used here is an expansion of a previously introduced consumer–resource type system of a population of individuals classified by their resource consumption. Application of the Reduction Theorem to the system enables us to evaluate the health of the system through tracking both the mean value of the parameter of resource (over)consumption, and the population variance, as both change over time. The article concludes with a discussion that highlights applicability of the proposed system to investigation of systems that are affected by particularly devastating overly adapted populations, namely cancerous cells. Potential intervention approaches for system management are discussed in the context of cancer therapies.
ContributorsKareva, Irina (Author) / Morin, Benjamin (Author) / Castillo-Chavez, Carlos (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2015-02-01
Description
Inhibition by ammonium at concentrations above 1000 mgN/L is known to harm the methanogenesis phase of anaerobic digestion. We anaerobically digested swine waste and achieved steady state COD-removal efficiency of around 52% with no fatty-acid or H[subscript 2] accumulation. As the anaerobic microbial community adapted to the gradual increase of total ammonia-N (NH[subscript 3]-N) from 890 ± 295 to 2040 ± 30 mg/L, the Bacterial and Archaeal communities became less diverse. Phylotypes most closely related to hydrogenotrophic Methanoculleus (36.4%) and Methanobrevibacter (11.6%), along with acetoclastic Methanosaeta (29.3%), became the most abundant Archaeal sequences during acclimation. This was accompanied by a sharp increase in the relative abundances of phylotypes most closely related to acetogens and fatty-acid producers (Clostridium, Coprococcus, and Sphaerochaeta) and syntrophic fatty-acid Bacteria (Syntrophomonas, Clostridium, Clostridiaceae species, and Cloacamonaceae species) that have metabolic capabilities for butyrate and propionate fermentation, as well as for reverse acetogenesis. Our results provide evidence countering a prevailing theory that acetoclastic methanogens are selectively inhibited when the total ammonia-N concentration is greater than ~1000 mgN/L. Instead, acetoclastic and hydrogenotrophic methanogens coexisted in the presence of total ammonia-N of ~2000 mgN/L by establishing syntrophic relationships with fatty-acid fermenters, as well as homoacetogens able to carry out forward and reverse acetogenesis.
ContributorsEsquivel Elizondo, Sofia (Author) / Parameswaran, Prathap (Author) / Delgado, Anca (Author) / Maldonado, Juan (Author) / Rittmann, Bruce (Author) / Krajmalnik-Brown, Rosa (Author) / Biodesign Institute (Contributor) / Swette Center for Environmental Biotechnology (Contributor) / Ira A. Fulton Schools of Engineering (Contributor) / School of Sustainable Engineering and the Built Environment (Contributor)
Created2016-08-11
Description
Background
In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends.
Methodology
We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data.
Conclusions
We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.
In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends.
Methodology
We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data.
Conclusions
We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.
ContributorsTowers, Sherry (Author) / Afzal, Shehzad (Author) / Bernal, Gilbert (Author) / Bliss, Nadya (Author) / Brown, Shala (Author) / Espinoza, Baltazar (Author) / Jackson, Jasmine (Author) / Judson-Garcia, Julia (Author) / Khan, Maryam (Author) / Lin, Michael (Author) / Mamada, Robert (Author) / Moreno, Victor (Author) / Nazari, Fereshteh (Author) / Okuneye, Kamaldeen (Author) / Ross, Mary (Author) / Rodriguez, Claudia (Author) / Medlock, Jan (Author) / Ebert, David (Author) / Castillo-Chavez, Carlos (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / Mary Lou Fulton Teachers College (Contributor) / Educational Leadership and Innovation (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Global Security Initiative (Contributor)
Created2015-06-11
Description
Background
Seroepidemiological studies before and after the epidemic wave of H1N1-2009 are useful for estimating population attack rates with a potential to validate early estimates of the reproduction number, R, in modeling studies.
Methodology/Principal Findings
Since the final epidemic size, the proportion of individuals in a population who become infected during an epidemic, is not the result of a binomial sampling process because infection events are not independent of each other, we propose the use of an asymptotic distribution of the final size to compute approximate 95% confidence intervals of the observed final size. This allows the comparison of the observed final sizes against predictions based on the modeling study (R = 1.15, 1.40 and 1.90), which also yields simple formulae for determining sample sizes for future seroepidemiological studies. We examine a total of eleven published seroepidemiological studies of H1N1-2009 that took place after observing the peak incidence in a number of countries. Observed seropositive proportions in six studies appear to be smaller than that predicted from R = 1.40; four of the six studies sampled serum less than one month after the reported peak incidence. The comparison of the observed final sizes against R = 1.15 and 1.90 reveals that all eleven studies appear not to be significantly deviating from the prediction with R = 1.15, but final sizes in nine studies indicate overestimation if the value R = 1.90 is used.
Conclusions
Sample sizes of published seroepidemiological studies were too small to assess the validity of model predictions except when R = 1.90 was used. We recommend the use of the proposed approach in determining the sample size of post-epidemic seroepidemiological studies, calculating the 95% confidence interval of observed final size, and conducting relevant hypothesis testing instead of the use of methods that rely on a binomial proportion.
Seroepidemiological studies before and after the epidemic wave of H1N1-2009 are useful for estimating population attack rates with a potential to validate early estimates of the reproduction number, R, in modeling studies.
Methodology/Principal Findings
Since the final epidemic size, the proportion of individuals in a population who become infected during an epidemic, is not the result of a binomial sampling process because infection events are not independent of each other, we propose the use of an asymptotic distribution of the final size to compute approximate 95% confidence intervals of the observed final size. This allows the comparison of the observed final sizes against predictions based on the modeling study (R = 1.15, 1.40 and 1.90), which also yields simple formulae for determining sample sizes for future seroepidemiological studies. We examine a total of eleven published seroepidemiological studies of H1N1-2009 that took place after observing the peak incidence in a number of countries. Observed seropositive proportions in six studies appear to be smaller than that predicted from R = 1.40; four of the six studies sampled serum less than one month after the reported peak incidence. The comparison of the observed final sizes against R = 1.15 and 1.90 reveals that all eleven studies appear not to be significantly deviating from the prediction with R = 1.15, but final sizes in nine studies indicate overestimation if the value R = 1.90 is used.
Conclusions
Sample sizes of published seroepidemiological studies were too small to assess the validity of model predictions except when R = 1.90 was used. We recommend the use of the proposed approach in determining the sample size of post-epidemic seroepidemiological studies, calculating the 95% confidence interval of observed final size, and conducting relevant hypothesis testing instead of the use of methods that rely on a binomial proportion.
ContributorsNishiura, Hiroshi (Author) / Chowell-Puente, Gerardo (Author) / Castillo-Chavez, Carlos (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2011-03-24
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 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.
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.
ContributorsTowers, Sherry (Author) / Gomez-Lievano, Andres (Author) / Khan, Maryam (Author) / Mubayi, Anuj (Author) / Castillo-Chavez, Carlos (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2015-07-02
Description
Major Depressive Disorder (MDD) is a widespread mood disorder that affects more than 300 million people worldwide and yet, high relapse rates persist. This current study aimed to use an animal model for depression, unpredictable intermittent restraint (UIR), to investigate changes in a subset of neurons within the hippocampus, a region of high susceptibility in MDD. Adult male and female Sprague-Dawley rats were randomly assigned to four treatment groups based on sex (n = 48, n = 12/group). Half of the rats underwent UIR that involved restraint with orbital shaking (30 min or 1 h) for 2-6 consecutive days, followed by one or two days of no stressors; the other half of the rats were undisturbed (CON). UIR rats were stressed for 28 days (21 days of actual stressors) before behavioral testing began with UIR continuing between testing days for nearly 70 days. Rats were then euthanized between 9 and 11 days after the last UIR session. Brains were processed for Golgi stain and long-shaft (LS) neurons within the hippocampal CA3a and CA3b regions were quantified for dendritic complexity using a Camera Lucida attachment. Our findings failed to support our hypothesis that UIR would produce apical dendritic retraction in CA3 hippocampal LS neurons in both males and females. Given that UIR failed to produce CA3 apical dendritic retraction in males, which is commonly observed in the literature, we discuss several reasons for these findings including, time from the end of UIR to when brains were sampled, and the effects of repeated cognitive testing. Given our published findings that UIR impaired spatial ability in males, but not females, we believe that UIR holds validity as a chronic stress paradigm, as UIR attenuated body weight gain in both males and females and produced reductions in thymus gland weight in UIR males. These findings corroborate UIR as an effective stressor in males and warrant further research into the timing of UIR-induced changes in hippocampal CA3 apical dendritic morphology.
ContributorsReynolds, Cindy Marie (Author) / Conrad, Cheryl D. (Thesis director) / Olive, M. Foster (Committee member) / School of Molecular Sciences (Contributor) / Department of English (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
Description
We studied the microbial community structure of pilot two-stage membrane biofilm reactors (MBfRs) designed to reduce nitrate (NO[subscript 3]–) and perchlorate (ClO[subscript 4]–) in contaminated groundwater. The groundwater also contained oxygen (O[subscript 2]) and sulfate (SO[2 over 4]–), which became important electron sinks that affected the NO[subscript 3]– and ClO[subscript 4]– removal rates. Using pyrosequencing, we elucidated how important phylotypes of each “primary” microbial group, i.e., denitrifying bacteria (DB), perchlorate-reducing bacteria (PRB), and sulfate-reducing bacteria (SRB), responded to changes in electron-acceptor loading. UniFrac, principal coordinate analysis (PCoA), and diversity analyses documented that the microbial community of biofilms sampled when the MBfRs had a high acceptor loading were phylogenetically distant from and less diverse than the microbial community of biofilm samples with lower acceptor loadings. Diminished acceptor loading led to SO[2 over 4]– reduction in the lag MBfR, which allowed Desulfovibrionales (an SRB) and Thiothrichales (sulfur-oxidizers) to thrive through S cycling. As a result of this cooperative relationship, they competed effectively with DB/PRB phylotypes such as Xanthomonadales and Rhodobacterales. Thus, pyrosequencing illustrated that while DB, PRB, and SRB responded predictably to changes in acceptor loading, a decrease in total acceptor loading led to important shifts within the “primary” groups, the onset of other members (e.g., Thiothrichales), and overall greater diversity.
ContributorsOntiveros-Valencia, Aura (Author) / Tang, Youneng (Author) / Zhao, Heping (Author) / Friese, David (Author) / Overstreet, Ryan (Author) / Smith, Jennifer (Author) / Evans, Patrick (Author) / Rittmann, Bruce (Author) / Krajmalnik-Brown, Rosa (Author) / Biodesign Institute (Contributor) / Swette Center for Environmental Biotechnology (Contributor) / Julie Ann Wrigley Global Institute of Sustainability (Contributor) / School of Sustainability (Contributor)
Created2014-07-01
Description
Type 2 diabetes mellitus (T2DM) is a life-long disease that affects over 27 million individuals in the United States alone. There are many different risk factors and pre-indicators of T2DM. One of them is insulin resistance. Insulin resistance occurs when the body is unable to appropriately respond to insulin. This in turn leads to increased levels of glucose and insulin in the bloodstream. Unlike T2DM, insulin resistance is a reversible diagnosis. The purpose of this project was to identify the most influential genetic and dietary factors of insulin resistance and to see if individuals have some extent of control to possibly avoid the diagnosis of insulin resistance and possibly T2DM entirely.
A total of 26 human subjects were used in this study. Each subject was classified as either lean or obese, according to their BMI measurement. First, the subjects underwent an oral glucose tolerance test. Blood samples were taken to measure glucose levels in the blood. After the test subject characteristics for each subject was obtained. These included age, BMI, body fat percentage, fat free mass (FFM), height, total mass, waist circumference, hip circumference, and waist to hip ratio. After the subject characteristics and blood glucose were measured the blood samples taken previously were then centrifuged, and the blood plasma was extracted. The blood plasma was then used to undergo an Insulin ELISA test. After extensive analysis, the Matsuda Index of each subject was obtained. Subjects with a Matsuda value of 6.0 or under were considered insulin resistant while subjects with a Matsuda value higher than 6.0 were considered insulin sensitive. Subjects were also required to submit a dietary record over the course of three days. The food intake was then put into a food processing software which gave a daily average of the macro and micro nutrients for each subject. Both the subject and dietary values were put into a multiple regression with a significance factor of p < 0.5 to see which factors contributed most to the Matsuda value.
It was found that BMI, height, total mass, insulin and fat free mass, all of which were subject characteristics, were considered to be significant. Some of these factors an individual has no control over, such as height and insulin. However other factors such as BMI, total mass and fat free mass can be affected by both a healthy diet and frequent exercise. This study validated that diet and physical activity can greatly influence an individual’s susceptibility to insulin resistance and ultimately T2DM.
A total of 26 human subjects were used in this study. Each subject was classified as either lean or obese, according to their BMI measurement. First, the subjects underwent an oral glucose tolerance test. Blood samples were taken to measure glucose levels in the blood. After the test subject characteristics for each subject was obtained. These included age, BMI, body fat percentage, fat free mass (FFM), height, total mass, waist circumference, hip circumference, and waist to hip ratio. After the subject characteristics and blood glucose were measured the blood samples taken previously were then centrifuged, and the blood plasma was extracted. The blood plasma was then used to undergo an Insulin ELISA test. After extensive analysis, the Matsuda Index of each subject was obtained. Subjects with a Matsuda value of 6.0 or under were considered insulin resistant while subjects with a Matsuda value higher than 6.0 were considered insulin sensitive. Subjects were also required to submit a dietary record over the course of three days. The food intake was then put into a food processing software which gave a daily average of the macro and micro nutrients for each subject. Both the subject and dietary values were put into a multiple regression with a significance factor of p < 0.5 to see which factors contributed most to the Matsuda value.
It was found that BMI, height, total mass, insulin and fat free mass, all of which were subject characteristics, were considered to be significant. Some of these factors an individual has no control over, such as height and insulin. However other factors such as BMI, total mass and fat free mass can be affected by both a healthy diet and frequent exercise. This study validated that diet and physical activity can greatly influence an individual’s susceptibility to insulin resistance and ultimately T2DM.
ContributorsBrinkerhoff, Catalina Marie (Author) / Katsanos, Christos (Thesis director) / Shaffer, Zachary (Committee member) / College of Health Solutions (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Coffee is an important link between the United States and Latin America and an important part of Latin America’s culture and economy. This paper looks at the similarities and differences between coffee organizations in Colombia, Ecuador, Peru, and Guatemala. Colombia has the strongest coffee organizations with the most political power. Guatemala and Peru, to a lesser extent, have well organized and powerful organizations that make up their industry. However, Ecuador has a significantly less organized organization. At their core, each country has a similar structure. There is one organization on the national level that watches out for the industry as a whole. Underneath that, there are smaller, often regional organizations made up of cooperatives pooling their resources for export. They function in similar ways as the national organizations, but have less reach. At the bottom, there are individual cooperatives and independent farmers. These cooperatives do not have much reach or connection to international markets.
ContributorsChabin, James Edward (Author) / Janssen, Marco (Thesis director) / Taylor, Keith (Committee member) / School of Sustainability (Contributor) / School of International Letters and Cultures (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05