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- All Subjects: Epidemiology
- Creators: Chowell-Puente, Gerardo
Description
Extraordinary medical advances have led to significant reductions in the burden of infectious diseases in humans. However, infectious diseases still account for more than 13 million annual deaths. This large burden is partly due to some pathogens having found suitable conditions to emerge and spread in denser and more connected host populations, and others having evolved to escape the pressures imposed by the rampant use of antimicrobials. It is then critical to improve our understanding of how diseases spread in these modern landscapes, characterized by new host population structures and socio-economic environments, as well as containment measures such as the deployment of drugs. Thus, the motivation of this dissertation is two-fold. First, we study, using both data-driven and modeling approaches, the the spread of infectious diseases in urban areas. As a case study, we use confirmed-cases data on sexually transmitted diseases (STDs) in the United States to assess the conduciveness of population size of urban areas and their socio-economic characteristics as predictors of STD incidence. We find that the scaling of STD incidence in cities is superlinear, and that the percent of African-Americans residing in cities largely determines these statistical patterns. Since disparities in access to health care are often exacerbated in urban areas, within this project we also develop two modeling frameworks to study the effect of health care disparities on epidemic outcomes. Discrepant results between the two approaches indicate that knowledge of the shape of the recovery period distribution, not just its mean and variance, is key for assessing the epidemiological impact of inequalities. The second project proposes to study, from a modeling perspective, the spread of drug resistance in human populations featuring vital dynamics, stochasticity and contact structure. We derive effective treatment regimes that minimize both the overall disease burden and the spread of resistance. Additionally, targeted treatment in structured host populations may lead to higher levels of drug resistance, and if drug-resistant strains are compensated, they can spread widely even when the wild-type strain is below its epidemic threshold.
ContributorsPatterson-Lomba, Oscar (Author) / Castillo-Chavez, Carlos (Thesis advisor) / Towers, Sherry (Thesis advisor) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2014
Description
Background: While research has quantified the mortality burden of the 1957 H2N2 influenza pandemic in the United States, little is known about how the virus spread locally in Arizona, an area where the dry climate was promoted as reducing respiratory illness transmission yet tuberculosis prevalence was high.
Methods: Using archival death certificates from 1954 to 1961, this study quantified the age-specific seasonal patterns, excess-mortality rates, and transmissibility patterns of the 1957 pandemic in Maricopa County, Arizona. By applying cyclical Serfling linear regression models to weekly mortality rates, the excess-mortality rates due to respiratory and all-causes were estimated for each age group during the pandemic period. The reproduction number was quantified from weekly data using a simple growth rate method and generation intervals of 3 and 4 days. Local newspaper articles from The Arizona Republic were analyzed from 1957-1958.
Results: Excess-mortality rates varied between waves, age groups, and causes of death, but overall remained low. From October 1959-June 1960, the most severe wave of the pandemic, the absolute excess-mortality rate based on respiratory deaths per 10,000 population was 17.85 in the elderly (≥65 years). All other age groups had extremely low excess-mortality and the typical U-shaped age-pattern was absent. However, relative risk was greatest (3.61) among children and young adolescents (5-14 years) from October 1957-March 1958, based on incidence rates of respiratory deaths. Transmissibility was greatest during the same 1957-1958 period, when the mean reproduction number was 1.08-1.11, assuming 3 or 4 day generation intervals and exponential or fixed distributions.
Conclusions: Maricopa County largely avoided pandemic influenza from 1957-1961. Understanding this historical pandemic and the absence of high excess-mortality rates and transmissibility in Maricopa County may help public health officials prepare for and mitigate future outbreaks of influenza.
Methods: Using archival death certificates from 1954 to 1961, this study quantified the age-specific seasonal patterns, excess-mortality rates, and transmissibility patterns of the 1957 pandemic in Maricopa County, Arizona. By applying cyclical Serfling linear regression models to weekly mortality rates, the excess-mortality rates due to respiratory and all-causes were estimated for each age group during the pandemic period. The reproduction number was quantified from weekly data using a simple growth rate method and generation intervals of 3 and 4 days. Local newspaper articles from The Arizona Republic were analyzed from 1957-1958.
Results: Excess-mortality rates varied between waves, age groups, and causes of death, but overall remained low. From October 1959-June 1960, the most severe wave of the pandemic, the absolute excess-mortality rate based on respiratory deaths per 10,000 population was 17.85 in the elderly (≥65 years). All other age groups had extremely low excess-mortality and the typical U-shaped age-pattern was absent. However, relative risk was greatest (3.61) among children and young adolescents (5-14 years) from October 1957-March 1958, based on incidence rates of respiratory deaths. Transmissibility was greatest during the same 1957-1958 period, when the mean reproduction number was 1.08-1.11, assuming 3 or 4 day generation intervals and exponential or fixed distributions.
Conclusions: Maricopa County largely avoided pandemic influenza from 1957-1961. Understanding this historical pandemic and the absence of high excess-mortality rates and transmissibility in Maricopa County may help public health officials prepare for and mitigate future outbreaks of influenza.
ContributorsCobos, April J (Author) / Jehn, Megan (Thesis director) / Chowell-Puente, Gerardo (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution and Social Change (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Mortality of 1918 influenza virus was high, partly due to bacteria coinfections. We characterize pandemic mortality in Arizona, which had high prevalence of tuberculosis. We applied regressions to over 35,000 data points to estimate the basic reproduction number and excess mortality. Age-specific mortality curves show elevated mortality for all age groups, especially the young, and senior sparing effects. The low value for reproduction number indicates that transmissibility was moderately low.
ContributorsJenner, Melinda Eva (Author) / Chowell-Puente, Gerardo (Thesis director) / Kostelich, Eric (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Unlike the autosomes, recombination on the sex chromosomes is limited to the pseudoautosomal regions (PARs) at each end of the chromosome. PAR1 spans approximately 2.7 Mb from the tip of the proximal arm of each sex chromosome, and a pseudoautosomal boundary between the PAR1 and non-PAR region is thought to have evolved from a Y-specific inversion that suppressed recombination across the boundary. In addition to the two PARs, there is also a human-specific X-transposed region (XTR) that was duplicated from the X to the Y chromosome. Genetic diversity is expected to be higher in recombining than nonrecombining regions, particularly because recombination reduces the effects of linked selection, allowing neutral variation to accumulate. We previously showed that diversity decreases linearly across the previously defined pseudoautosomal boundary (rather than drop suddenly at the boundary), suggesting that the pseudoautosomal boundary may not be as strict as previously thought. In this study, we analyzed data from 1271 genetic females to explore the extent to which the pseudoautosomal boundary varies among human populations (broadly, African, European, South Asian, East Asian, and the Americas). We found that, in all populations, genetic diversity was significantly higher in the PAR1 and XTR than in the non-PAR regions, and that diversity decreased linearly from the PAR1 to finally reach a non-PAR value well past the pseudoautosomal boundary in all populations. However, we also found that the location at which diversity changes from reflecting the higher PAR1 diversity to the lower nonPAR diversity varied by as much as 500 kb among populations. The lack of genetic evidence for a strict pseudoautosomal boundary and the variability in patterns of diversity across the pseudoautosomal boundary are consistent with two potential explanations: (1) the boundary itself may vary across populations, or (2) that population-specific demographic histories have shaped diversity across the pseudoautosomal boundary.
ContributorsCotter, Daniel Juetten (Author) / Wilson Sayres, Melissa (Thesis director) / Stone, Anne (Committee member) / Webster, Timothy (Committee member) / School of Life Sciences (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
This work examines one dimension of the effect that complex human transport systems have on the spread of Chikungunya Virus (CHIKV) in the Caribbean from 2013 to 2015. CHIKV is transmitted by mosquitos and its novel spread through the Caribbean islands provided a chance to examine disease transmission through complex human transportation systems. Previous work by Cauchemez et al. had shown a simple distance-based model successfully predict CHIKV spread in the Caribbean using Markov chain Monte Carlo (MCMC) statistical methods. A MCMC simulation is used to evaluate different transportation methods (air travel, cruise ships, and local maritime traffic) for the primary transmission patterns through linear regression. Other metrics including population density to account for island size variation and dengue fever incidence rates as a proxy for vector control and health spending were included. Air travel and cruise travel were gathered from monthly passenger arrivals by island. Local maritime traffic is approximated with a gravity model proxy incorporating GDP-per-capita and distance and historic dengue rates were used for determine existing vector control measures for the islands. The Caribbean represents the largest cruise passenger market in the world, cruise ship arrivals were expected to show the strongest signal; however, the gravity model representing local traffic was the best predictor of infection routes. The early infected islands (<30 days) showed a heavy trend towards an alternate primary transmission but our consensus model able to predict the time until initial infection reporting with 94.5% accuracy for islands 30 days post initial reporting. This result can assist public health entities in enacting measures to mitigate future epidemics and provide a modelling basis for determining transmission modes in future CHIKV outbreaks.
ContributorsFries, Brendan F (Author) / Perrings, Charles (Thesis director) / Wilson Sayres, Melissa (Committee member) / Morin, Ben (Committee member) / School of Life Sciences (Contributor) / Department of Military Science (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12