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This white paper serves as an accumulation of research to guide needle exchange program (NEP) policies in the state of Arizona to decrease the transmission of infectious diseases such as HIV and HCV.
Many women are subject to role conflict. Between participating in their jobs and social expectations about duties as a mother, they might experience considerable stress trying to fulfill both those demanding roles. Data was analyzed from 182,617 women in 38 low- and middle-income countries from MICS surveys, using linear regression to examine how a number of children and working status interact to predict life satisfaction and happiness. Having more children was almost always associated with lower life satisfaction and happiness. The only exception was that among women who worked, more children to a point was associated with greater life satisfaction. Notably, work had different associations with emotional well-being depending on how it was measured. Having a job was generally associated with lower happiness, but greater life satisfaction. There is little evidence of an interaction between work and children indicating role conflict. Indeed, for life satisfaction, working seems to counteract the negative effect of having more children. Determining how large the effect of having both children and jobs are in women's lives can help determine the burden placed on women today and how that burden can be alleviated.
With the accelerated emergence of telehealth systems being deployed with promises to access unreachable populations in today’s socially distant environment, it is increasingly important to understand the barriers that underprivileged populations face when trying to access healthcare through digital platforms. This research investigates the use of telehealth in social and cultural sub-populations, focusing on how the diverse student population at Arizona State University (ASU) use the recently-launched ASU Telehealth system. Statistical analysis of demographic factors spanning the five categories of social determinants of health were coupled with population studies of the ASU student body to evaluate the reach of services and patient diversity across telehealth and in person health platforms. Results show that insurance, racial and international student identity influence the percentage of students within these demographic categories Also, though the ASU Telehealth patient body reflects ASU’s general student population, the platform did not increase the reach of Health Services and the magnitude of students served. using ASU Telehealth. Due to the COVID-19 pandemic, it is difficult to determine the validity and reliability of these findings. However, the findings and background research point to targeted marketing campaigns, intentional policy decision-making, post-pandemic telehealth resilience, and the continuation of quantitative and qualitative data collection as means to expand the impact and equity of ASU Telehealth into future iterations of the platform. Outputs of this study include web communication materials and qualitative data collection mechanisms for future use and implementation by ASU Health Services.
The SARS-CoV-2 (Covid-19) virus has had severe impacts on college students' ways of life. To examine how students were coping and perceiving the Covid-19 pandemic, a secondary analysis of an online survey across the three Arizona public universities investigated students’ knowledge about Covid-19, engagement with preventive strategies, pandemic preparedness and gauged their risk perception. Results from our analysis indicate that the students were knowledgeable about Covid-19 and were changing their habits and engaging with preventive measures. Results further suggest that students were prepared for the pandemic in terms of resources and were exhibiting high-risk perceptions. The data also revealed that students who were being cautious and engaging with preventive behaviors had a higher risk-perception than individuals who were not. As for individuals who were prepared for the pandemic in terms of supplies, their risk perception was similar to those who did not have supplies. Individuals who were prepared and capable of providing a single caretaker to tend to their sick household members and isolate them in a separate room had a higher risk perception than those who could not. These results can help describe how college students will react to a future significant event, what resources students may be in need of, and how universities can take additional steps to keep their students safe and healthy. The results from this study and recommendations will provide for a stronger and more understanding campus community during times of distress and can improve upon already established university protocols for health crises and even natural disasters.
The SARS-CoV-2 (Covid-19) virus has had severe impacts on college students' ways of life. To examine how students were coping and perceiving the Covid-19 pandemic, a secondary analysis of an online survey across the three Arizona public universities investigated students’ knowledge about Covid-19, engagement with preventive strategies, pandemic preparedness and gauged their risk-perception. Results from our analysis indicate that the students were knowledgeable about Covid-19 and were changing their habits and engaging with preventive measures. Results further suggest that students were prepared for the pandemic in terms of resources and were exhibiting high-risk perceptions. The data also revealed that students who were being cautious and engaging with preventive behaviors had a higher risk-perception than individuals who were not. As for individuals who were prepared for the pandemic in terms of supplies, their risk perception was similar to those who did not have supplies. Individuals who were prepared and capable of providing a single caretaker to tend to their sick household members and isolate them in a separate room had a higher risk perception than those who could not. These results can help describe how college students will react to a future significant event, what resources students may be in need of, and how universities can take additional steps to keep their students safe and healthy. The results from this study and recommendations will provide for a stronger and more understanding campus community during times of distress and can improve upon already established university protocols for health crises and even natural disasters.
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.
