Filtering by
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.
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.
Breast cancer affects about 12% of women in the US. Arguably, it is one of the most advertised cancers. Mammography became a popular tool of breast cancer screening in the 1970s, and patient-geared guidelines came from the American Cancer Society (ACS) and the US Preventative Task Force (USPSTF). This research focuses on ACS guidelines, as they were the earliest as well as the most changed guidelines. Mammography guidelines changed over time due to multiple factors. This research has tracked possible causes of those changes. Research began with an extensive literature search of clinical trials, the New York Times and the Washington Post archives, systematic reviews, ACS and USPSTF archives.
Science fiction works can reflect the relationship between science and society by telling stories that are set in the future of ethical implications or social consequences of scientific advancements. This thesis investigates how the concept of reproduction is depicted in popular science fiction works.
By questioning methods of sex selection since their early development, and often discovering that they are unreliable, scientists have increased the creative and technological capacity of the field of reproductive health. The presentation of these methods to the public, via published books on timing methods and company websites for sperm sorting, increased interest in, and influence of, sex selection within the global society. The purpose of explaining the history, interest, development, and impact of various sex selection methods in the mid-twentieth century based on the information that is available on them today is to show couples which methods have failed and provide them with the knowledge necessary to make an informed decision on how they choose to go about utilizing methods of sex selection.
By demonstrating the struggle for sound standard of care for non-medical reproductive health care providers during the nineteenth and early twentieth century, this project emphasizes what the standards of reproductive health care for abortion and contraception might be like if the organizations that made them so readily available, like Planned Parenthood, were defunded or criminalized in our modern setting.