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- All Subjects: Epidemiology
- Creators: Jehn, Megan
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
Homelessness is a pervasive in American society. The causes of homelessness are complex, but health and homelessness are inextricably linked. Student-run free clinics care for underserved populations, including people experiencing homelessness, but they have multiple agendas—to provide care but also to give students hands-on experience. It is plausible that these two agendas may compete and give patients sub-par quality of care.
This study examines patient care in the SHOW free clinic in Phoenix, Arizona, which serves adults experiencing homelessness. This study asks two questions: First, do clinicians in Phoenix’s SHOW free clinic discuss with patients how to pay for and where to access follow-up services and medications? Second, how do the backgrounds of patients, measured by scales based on the Gelberg-Anderson behavioral model for vulnerable populations, correlate with patient outcomes, including number of unmet needs in clinic, patient satisfaction with care, and patient perceived health status? To answer these questions, structured surveys were administered to SHOW clinic patients at the end of their visits. Results were analyzed using Pearson’s correlations and odds ratios. 21 patients completed the survey over four weeks in February-March 2017. We did not identify any statistically significant correlations between predisposing factors such as severity/duration of homelessness, mental health history, ethnicity, or LGBTQ status and quality of care outcomes. Twenty nine percent of surveyed patients reported having one or more unmet needs following their SHOW clinic visit suggesting an important area for future research. The results from this study indicate that measuring unmet needs is a feasible alternative to patient satisfaction surveys for assessing quality of care in student-run free clinics for homeless populations.
This study examines patient care in the SHOW free clinic in Phoenix, Arizona, which serves adults experiencing homelessness. This study asks two questions: First, do clinicians in Phoenix’s SHOW free clinic discuss with patients how to pay for and where to access follow-up services and medications? Second, how do the backgrounds of patients, measured by scales based on the Gelberg-Anderson behavioral model for vulnerable populations, correlate with patient outcomes, including number of unmet needs in clinic, patient satisfaction with care, and patient perceived health status? To answer these questions, structured surveys were administered to SHOW clinic patients at the end of their visits. Results were analyzed using Pearson’s correlations and odds ratios. 21 patients completed the survey over four weeks in February-March 2017. We did not identify any statistically significant correlations between predisposing factors such as severity/duration of homelessness, mental health history, ethnicity, or LGBTQ status and quality of care outcomes. Twenty nine percent of surveyed patients reported having one or more unmet needs following their SHOW clinic visit suggesting an important area for future research. The results from this study indicate that measuring unmet needs is a feasible alternative to patient satisfaction surveys for assessing quality of care in student-run free clinics for homeless populations.
ContributorsWilson, Ethan Sinead (Author) / Jehn, Megan (Thesis director) / Harrell, Susan (Committee member) / School of Human Evolution and Social Change (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
The current coronavirus disease 2019 (COVID-19) pandemic has highlighted the crucial role of mathematical models in predicting, assessing, and controlling potential outbreaks. Numerous modeling studies using statistics or differential equations have been proposed to analyze the COVID-19 dynamics, with network analysis and cluster analysis also being adapted to understand disease transmission from multiple perspectives. This dissertation explores the use of network science and mathematical models to improve the understanding of infectious diseases. Chapter 1 provides an introduction to infectious disease modeling, its history, importance, and challenges. It also introduces network science as a powerful tool for understanding the complex interactions between individuals that can facilitate disease spread. Chapter 2 develops a statistical model that describes HIV infection and disease progression in a men who have sex with men cohort in Japan receiving a Pre-Exposure Prophylaxis (PrEP) program. The cost-effectiveness of the PrEP programwas evaluated by comparing the incremental cost-effectiveness ratio over a 30-year period against the willingness to pay threshold. Chapter 3 presents an ordinary differential equations model to describe disease transmission and the effects of vaccination and mobility restrictions. Chapter 4 extends the ODE model to include spatial heterogeneity and presents partial differential equations models. These models describe the combined effects of local transmission, transboundary transmission, and human intervention on COVID-19 dynamics. Finally, Chapter 5 concludes the dissertation by emphasizing the importance of developing relevant disease models to understand and predict the spread of infectious diseases by combining network science and mathematical tools.
ContributorsYamamoto, Nao (Author) / Wang, Haiyan (Thesis advisor) / Lampert, Adam (Thesis advisor) / Jehn, Megan (Committee member) / Arizona State University (Publisher)
Created2023
Description
Objective: To provide insight into the World Health Organization SAGE Working Group Vaccine Hesitancy Survey by applying the tool to populations across Maricopa County, Arizona. Design: An online survey was conducted using the Qualtrics Survey Software, of individuals residing in Maricopa County, Arizona during the month of October 2019. Results: Of 209 respondents, the followed demonstrated to be the top 3 reasons for either having not received the flu shot yet or having not planned to receive the flu shot: “I’m healthy, I don’t need it”(20.1%); “Worried I might get the flu from it”(17.7%); “I don’t think it works”(17.7%) Statistical analysis demonstrated that vaccine hesitant and non-hesitant respondents are likely to respond differently to topics covering: safety of vaccines; self-perceived health status; importance of the flu shot among one’s peers; flu vaccine related knowledge Conclusions: The WHO VHS applied to the population of Maricopa County, Arizona reported little hesitancy towards the seasonal flu vaccine. Statistical analysis of Vaccine Hesitant respondents vs. Non-Hesitant respondents demonstrates that specified public health education focused on the immunological implications of vaccines may be needed for the hesitant population to gain confidence in vaccine efficacy. A more diverse respondent group that consists of residents beyond the county lines of Maricopa is needed to understand the full scope of vaccine hesitancy that exists in Arizona.
ContributorsMaroofi, Hanna (Co-author, Co-author) / Jehn, Megan (Thesis director) / Muabyi, Anuj (Committee member) / School of International Letters and Cultures (Contributor) / School of Life Sciences (Contributor) / School of Human Evolution & Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05