A space-time analysis of reported shigellosis and salmonellosis cases in Texas from 2000 to 2004

Background. The purpose of this study was to describe the risk factors and demographics of persons with salmonellosis and shigellosis and to investigate both seasonal and spatial variations in the occurrence of these infections in Texas from 2000 to 2004, utilizing time series analyses and the geographic information system digital mapping methods. ^ Methods. Spatial Analysis: MapInfo software was used to map the distribution of age-adjusted rates of reported shigellosis and salmonellosis in Texas from 2000–2004 by zip codes. Census data on above or below poverty level, household income, highest level of educational attainment, race, ethnicity, and urban/rural community status was obtained from the 2000 Decennial Census for each zip code. The zip codes with the upper 10% and lower 10% were compared using t-tests and logistic regression to determine whether there were any potential risk factors. ^ Temporal analysis. Seasonal patterns in the prevalence of infections in Texas from 2000 to 2003 were determined by performing time-series analysis on the numbers of cases of salmonellosis and shigellosis. A linear regression was also performed to assess for trends in the incidence of each disease, along with auto-correlation and multi-component cosinor analysis. ^ Results. Spatial analysis: Analysis by general linear model showed a significant association between infection rates and age, with young children aged less than 5 and those aged 5–9 years having increased risk of infection for both disease conditions. The data demonstrated that those populations with high percentages of people who attained a higher than high school education were less likely to be represented in zip codes with high rates of shigellosis. However, for salmonellosis, logistic regression models indicated that when compared to populations with high percentages of non-high school graduates, having a high school diploma or equivalent increased the odds of having a high rate of infection. ^ Temporal analysis. For shigellosis, multi-component cosinor analyses were used to determine the approximated cosine curve which represented a statistically significant representation of the time series data for all age groups by sex. The shigellosis results show 2 peaks, with a major peak occurring in June and a secondary peak appearing around October. Salmonellosis results showed a single peak and trough in all age groups with the peak occurring in August and the trough occurring in February. ^ Conclusion. The results from this study can be used by public health agencies to determine the timing of public health awareness programs and interventions in order to prevent salmonellosis and shigellosis from occurring. Because young children depend on adults for their meals, it is important to increase the awareness of day-care workers and new parents about modes of transmission and hygienic methods of food preparation and storage. ^

Temporal and spatial regulation of cell division by the nucleoid in Escherichia coli

Selection of division sites and coordination of cytokinesis with other cell cycle events are critical for every organism to proliferate. In E. coli, the nucleoid is proposed to exclude division from the site of the chromosome (nucleoid occlusion model). We studied the effect of the nucleoid on timing and placement of cell division. An early cell division protein, FtsZ, was used to follow development of the division septum. FtsZ forms a ring structure (Z ring) at potential division sites. The dynamics of Z ring was visualized in live cells by fusing FtsZ with a green fluorescent protein (GFP). Emanating FtsZ-GFP polymers from the constricted septum or aggregates in daughter cells were also observed, probably representing the FtsZ depolymerization and immature FtsZ nucleation processes. We next examined the nucleoid occlusion model. Mutants carrying abnormally positioned chromosomes were employed. In chromosomal partition mutants, replicated chromosomes cannot segregate. The Z ring was excluded from midcell to the edge of the nucleoid. This negative effect of nucleoids was further confirmed in replication deficient dnaA mutants, in which only a single chromosome is present in the cell center. These results suggest that the nucleoid, replicating or not, inhibits division in the area where the chromosome occupies. In addition, increasing the level of FtsZ does not overcome nucleoid inhibition. Interestingly in anucleate cells produced by both mutants, the Z ring was localized in the central part of the cell, which indicates that the nucleoid is not required for FtsZ assembly. Relaxation of chromosomes by reducing the gyrase activity or disruption of protein translation/translocation did not abolish the division inhibition capacity of the nucleoid. However, preventing transcription did compromise the nucleoid occlusion effect, leading to formation of multiple FtsZ rings above the nucleoid. In summary, we demonstrate that nucleoids negatively regulate the timing and position of division by inhibiting FtsZ assembly at unselected sites. Relief of this inhibition at midcell is coincident with the completion of DNA replication. On the other hand, FtsZ assembly does not require the nucleoid. ^

Performance tiers: Implementing comparative effectiveness analysis in the health care setting through operations research and spatial methods

This dissertation develops and tests a comparative effectiveness methodology utilizing a novel approach to the application of Data Envelopment Analysis (DEA) in health studies. The concept of performance tiers (PerT) is introduced as terminology to express a relative risk class for individuals within a peer group and the PerT calculation is implemented with operations research (DEA) and spatial algorithms. The analysis results in the discrimination of the individual data observations into a relative risk classification by the DEA-PerT methodology. The performance of two distance measures, kNN (k-nearest neighbor) and Mahalanobis, was subsequently tested to classify new entrants into the appropriate tier. The methods were applied to subject data for the 14 year old cohort in the Project HeartBeat! study.^ The concepts presented herein represent a paradigm shift in the potential for public health applications to identify and respond to individual health status. The resultant classification scheme provides descriptive, and potentially prescriptive, guidance to assess and implement treatments and strategies to improve the delivery and performance of health systems. ^

Studies of biological rhythms in responses to influenza infection and vaccination

Three studies examined seasonal or circadian variations in selected responses to influenza infection or vaccination. The first, a seroepidemiologic study, evaluated temporal patterns of antibody titers to influenza A/Texas. Human umbilical cord bloods were sampled over a two-year period when the virus was not present in the community. No endogenous seasonal pattern was detected. The second study included three experiments on circadian rhythms in mice. Neither susceptibility nor protection from inactivated or attenuated vaccine varied significantly according to time of administration. A slight effect, however, was suggested with inactivated vaccine. Three human vaccine trials comprised the third study. Outcome variables included rise in antibody titer, final antibody titer, incidence of adverse reactions, and protection from community infection. Patterns in antibody response and protection variables were inconsistent, and generally not clinically significant. Local reactions to inactivated vaccine were more frequent if injections were received in the afternoon as compared to morning. This was true to adults that had been previously vaccinated. ^

A STUDY OF INFLUENZA AND OF STATISTICAL METHODS USED TO REPORT INFLUENZA

This paper defines and compares several models for describing excess influenza pneumonia mortality in Houston. First, the methodology used by the Center for Disease Control is examined and several variations of this methodology are studied. All of the models examined emphasize the difficulty of omitting epidemic weeks.^ In an attempt to find a better method of describing expected and epidemic mortality, time series methods are examined. Grouping in four-week periods, truncating the data series to adjust epidemic periods, and seasonally-adjusting the series y(,t), by:^ (DIAGRAM, TABLE OR GRAPHIC OMITTED...PLEASE SEE DAI)^ is the best method examined. This new series w(,t) is stationary and a moving average model MA(1) gives a good fit for forecasting influenza and pneumonia mortality in Houston.^ Influenza morbidity, other causes of death, sex, race, age, climate variables, environmental factors, and school absenteeism are all examined in terms of their relationship to influenza and pneumonia mortality. Both influenza morbidity and ischemic heart disease mortality show a very high relationship that remains when seasonal trends are removed from the data. However, when jointly modeling the three series it is obvious that the simple time series MA(1) model of truncated, seasonally-adjusted four-week data gives a better forecast.^

Using spatial linear models with SAR and CAR structure to examine Texas lung cancer incidence rates

Scholars have found that socioeconomic status was one of the key factors that influenced early-stage lung cancer incidence rates in a variety of regions. This thesis examined the association between median household income and lung cancer incidence rates in Texas counties. A total of 254 individual counties in Texas with corresponding lung cancer incidence rates from 2004 to 2008 and median household incomes in 2006 were collected from the National Cancer Institute Surveillance System. A simple linear model and spatial linear models with two structures, Simultaneous Autoregressive Structure (SAR) and Conditional Autoregressive Structure (CAR), were used to link median household income and lung cancer incidence rates in Texas. The residuals of the spatial linear models were analyzed with Moran's I and Geary's C statistics, and the statistical results were used to detect similar lung cancer incidence rate clusters and disease patterns in Texas.^