1000 resultados para Hurricane Opal, 1995


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Malaria poses a significant public health problem worldwide. The World Health Organization indicates that approximately 40% of the world's population and almost 85% of the population from the South–East Asian region is at risk of contracting malaria. India being the most populous country in the region, contributes the highest number of malaria cases and deaths attributed to malaria. Orissa is the state that has the highest number of malaria cases and deaths attributable to malaria. A secondary data analysis was carried out to evaluate the effectiveness of the World bank-assisted Malaria Action Program in the state of Orissa under the health sector reforms of 1995-96. The secondary analysis utilized the government of India's National Anti Malaria Management Information System's (NAMMIS) surveillance data and the National Family Health Survey (NFHS–I and NFHS–II) datasets to compare the malaria mortality and morbidity in the state between 1992-93 and 1998-99. Results revealed no effect of the intervention and indicated an increase of 2.18 times in malaria mortality between 1992-1999 and an increase of 1.53 times in malaria morbidity between 1992-93 and 1998-99 in the state. The difference in the age-adjusted malaria morbidity in the state between the time periods of 1992-93 and 1998-99 proved to be highly significant (t = 4.29 df=16, p<. 0005) whereas the difference between the increase of age-adjusted malaria morbidity during 1992-93 and 1998-99 between Orissa (with intervention) and Bihar (no intervention) proved to be non significant (t=.0471 df=16, p<.50). Factors such as underutilization of World Bank funds for the malaria control program, inadequate health care infrastructure, structural adjustment problems, poor management, poor financial management, parasite resistance to anti-malarial drugs, inadequate supply of drugs and staff shortages may have contributed to the failure of the program in the state.^

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Southeast Texas, including Houston, has a large presence of industrial facilities and has been documented to have poorer air quality and significantly higher cancer rates than the remainder of Texas. Given citizens’ concerns in this 4th largest city in the U.S., Mayor Bill White recently partnered with the UT School of Public Health to determine methods to evaluate the health risks of hazardous air pollutants (HAPs). Sexton et al. (2007) published a report that strongly encouraged analytic studies linking these pollutants with health outcomes. In response, we set out to complete the following aims: 1. determine the optimal exposure assessment strategy to assess the association between childhood cancer rates and increased ambient levels of benzene and 1,3-butadiene (in an ecologic setting) and 2. evaluate whether census tracts with the highest levels of benzene or 1,3-butadiene have higher incidence of childhood lymphohematopoietic cancer compared with census tracts with the lowest levels of benzene or 1,3-butadiene, using Poisson regression. The first aim was achieved by evaluating the usefulness of four data sources: geographic information systems (GIS) to identify proximity to point sources of industrial air pollution, industrial emission data from the U.S. EPA’s Toxic Release Inventory (TRI), routine monitoring data from the U.S. EPA Air Quality System (AQS) from 1999-2000 and modeled ambient air levels from the U.S. EPA’s 1999 National Air Toxic Assessment Project (NATA) ASPEN model. Further, once these four data sources were evaluated, we narrowed them down to two: the routine monitoring data from the AQS for the years 1998-2000 and the 1999 U.S. EPA NATA ASPEN modeled data. We applied kriging (spatial interpolation) methodology to the monitoring data and compared the kriged values to the ASPEN modeled data. Our results indicated poor agreement between the two methods. Relative to the U.S. EPA ASPEN modeled estimates, relying on kriging to classify census tracts into exposure groups would have caused a great deal of misclassification. To address the second aim, we additionally obtained childhood lymphohematopoietic cancer data for 1995-2004 from the Texas Cancer Registry. The U.S. EPA ASPEN modeled data were used to estimate ambient levels of benzene and 1,3-butadiene in separate Poisson regression analyses. All data were analyzed at the census tract level. We found that census tracts with the highest benzene levels had elevated rates of all leukemia (rate ratio (RR) = 1.37; 95% confidence interval (CI), 1.05-1.78). Among census tracts with the highest 1,3-butadiene levels, we observed RRs of 1.40 (95% CI, 1.07-1.81) for all leukemia. We detected no associations between benzene or 1,3-butadiene levels and childhood lymphoma incidence. This study is the first to examine this association in Harris and surrounding counties in Texas and is among the first to correlate monitored levels of HAPs with childhood lymphohematopoietic cancer incidence, evaluating several analytic methods in an effort to determine the most appropriate approach to test this association. Despite recognized weakness of ecologic analyses, our analysis suggests an association between childhood leukemia and hazardous air pollution.^

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The recent hurricanes of Katrina, Rita, and Dolly have brought to light the precarious situation populations place themselves in when they are unprepared to face a storm, or do not follow official orders to evacuate when a destructive hurricane is poised to hit the area. Three counties in southern Texas lie within 60 miles of the Gulf of Mexico, and along the Mexican border. Determining the barriers to hurricane evacuation in this distinct and highly impoverished area of the United States would help aid local, state, and federal agencies to respond more effectively to persons living here.^ The aim of this study was to examine intention to comply with mandatory hurricane evacuation orders among persons living in three counties in South Texas by gender, income, education, acculturation and county of residence. A questionnaire was administered to 3,088 households across the three counties using a two-stage cluster sampling strategy, stratified by all three counties. The door-to-door survey was a 73-item instrument that included demographics, reasons for and against evacuation, and preparedness for a hurricane. Weighted data were used for the analyses.^ Chi-square tests were run to determine whether differences between observed and expected frequencies were statistically significant. A logistic regression model was developed based on that univariate analysis. Results from the logistic regression estimated odds ratios and their 95 percent confidence intervals for the independent variables.^ Logistic regression results indicate that females were less likely than men to follow an evacuation order. Having a higher education meant more likelihood of evacuating. Those respondents with a higher affiliation with Spanish than English were more likely to follow the evacuation orders. Hidalgo County residents were less likely to evacuate than Cameron or Willacy Counties' residents. Local officials need to implement communication efforts specifically tailored for females, residents with less of an affiliation with Spanish, and Hidalgo County residents to ensure their successful evacuation prior to a strong hurricane's landfall.^

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This study examined both changing call volume and type with resulting effect of TeleHealth Nurse, the Houston Fire Department's (HFD) telephone nurse line, on call burden during Hurricane Ike. On September 13, 2008, Hurricane Ike made landfall in the Galveston area and continued north through Houston resulting in catastrophic damages in infrastructure and posing a public health threat. The overall goal of this study looked at data from Houston Fire Department to obtain a better understanding of the needs of citizens before, during, and after a hurricane. This study looked at four aspects of emergency response from HFD. The first section looked at call volumes surrounding the time of Hurricane Ike in 2008 compared to the same time period in 2007. The data showed a 12% increase in calls surrounding Hurricane Ike compared to previous years with a p value <.001. Next, the study evaluated the types of calls prevalent during Hurricane Ike compared to the same time period in 2007. The data showed a statistically significant increase in chronic health problems such as diabetes and cardiac events, Obstetric calls and an increase in breathing problems, falls, and lacerations during the days following Hurricane Ike. There was also a statistically significant increase in auto med alerts and check patients surrounding Hurricane Ike's landfall. The third section analyzed the change in call volume sent to HFD's Telephone Nurse Line during Hurricane Ike and compares this to earlier time periods while the fourth and final section looks at the types of calls sent to the nurse line during Hurricane Ike. The data showed limited use of the TeleHealth Nurse line before Hurricane Ike, but when the winds were at their strongest and ambulances were unable to leave the station, the nurse line was the only functioning medical help some people were able to receive. These studies bring a better understanding to the number and types of calls that a city might experience during a natural disaster, such as a hurricane. This study also shows the usefulness of an EMS Telephone Nurse Line during a natural disaster.^

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Entire issue (large pdf file) Articles include: Family Preservation and Support: Past, Present, and Future. Katharine Hooper-Briar,C. Anne Broussard, John Ronnau, and Alvin Sallee An Examination of Treatment Fidelity in an Intensive Family Preservation Program. Marianne Berry Intensive Family Reunification Services: A Conceptual Framework and Case Example. Elaine Walton, Mark W. Fraser, Catherin Harlin, and Robert E. Lewis Intensive Family Preservation Services: Do They Have Any Impact on Family Functioning? Roy W. Rodenhiser, Joseph Chandy, Kazi Ahmed Institutionalizing Intensive Family Preservation Services: A Strategy for Creating Staffing Standards Based on Projections of At-Risk Children from Referral sources. Robert E. Lewis

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This investigation compares two different methodologies for calculating the national cost of epilepsy: provider-based survey method (PBSM) and the patient-based medical charts and billing method (PBMC&BM). The PBSM uses the National Hospital Discharge Survey (NHDS), the National Hospital Ambulatory Medical Care Survey (NHAMCS) and the National Ambulatory Medical Care Survey (NAMCS) as the sources of utilization. The PBMC&BM uses patient data, charts and billings, to determine utilization rates for specific components of hospital, physician and drug prescriptions. ^ The 1995 hospital and physician cost of epilepsy is estimated to be $722 million using the PBSM and $1,058 million using the PBMC&BM. The difference of $336 million results from $136 million difference in utilization and $200 million difference in unit cost. ^ Utilization. The utilization difference of $136 million is composed of an inpatient variation of $129 million, $100 million hospital and $29 million physician, and an ambulatory variation of $7 million. The $100 million hospital variance is attributed to inclusion of febrile seizures in the PBSM, $−79 million, and the exclusion of admissions attributed to epilepsy, $179 million. The former suggests that the diagnostic codes used in the NHDS may not properly match the current definition of epilepsy as used in the PBMC&BM. The latter suggests NHDS errors in the attribution of an admission to the principal diagnosis. ^ The $29 million variance in inpatient physician utilization is the result of different per-day-of-care physician visit rates, 1.3 for the PBMC&BM versus 1.0 for the PBSM. The absence of visit frequency measures in the NHDS affects the internal validity of the PBSM estimate and requires the investigator to make conservative assumptions. ^ The remaining ambulatory resource utilization variance is $7 million. Of this amount, $22 million is the result of an underestimate of ancillaries in the NHAMCS and NAMCS extrapolations using the patient visit weight. ^ Unit cost. The resource cost variation is $200 million, inpatient is $22 million and ambulatory is $178 million. The inpatient variation of $22 million is composed of $19 million in hospital per day rates, due to a higher cost per day in the PBMC&BM, and $3 million in physician visit rates, due to a higher cost per visit in the PBMC&BM. ^ The ambulatory cost variance is $178 million, composed of higher per-physician-visit costs of $97 million and higher per-ancillary costs of $81 million. Both are attributed to the PBMC&BM's precise identification of resource utilization that permits accurate valuation. ^ Conclusion. Both methods have specific limitations. The PBSM strengths are its sample designs that lead to nationally representative estimates and permit statistical point and confidence interval estimation for the nation for certain variables under investigation. However, the findings of this investigation suggest the internal validity of the estimates derived is questionable and important additional information required to precisely estimate the cost of an illness is absent. ^ The PBMC&BM is a superior method in identifying resources utilized in the physician encounter with the patient permitting more accurate valuation. However, the PBMC&BM does not have the statistical reliability of the PBSM; it relies on synthesized national prevalence estimates to extrapolate a national cost estimate. While precision is important, the ability to generalize to the nation may be limited due to the small number of patients that are followed. ^

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Congenital anomalies have been a leading cause of infant mortality for the past twenty years in the United States. Few registry-based studies have investigated the mortality experience of infants with congenital anomalies. Therefore, a registry-based mortality study was conducted of 2776 infants from the Texas Birth Defects Registry who were born January 1, 1995 to December 31, 1997, with selected congenital anomalies. Infants were matched to linked birth-infant death files from the Texas Department of Health, Bureau of Vital Statistics. One year Kaplan-Meier survival curves, and mortality estimates were generated for each of the 23 anomalies by maternal race/ethnicity, infant sex, birth weight, gestational age, number of life-threatening anomalies, prenatal diagnosis, hospital of birth and other variables. ^ There were 523 deaths within the first year of life (mortality rate = 191.0 per 1,000 infants). Infants with gastroschisis, trisomy 21, and cleft lip ± palate had the highest first year survival (92.91%, 92.32%, and 87.59%, respectively). Anomalies with the lowest survival were anencephaly (5.13%), trisomy 13 (7.41%), and trisomy 18 (10.29%). ^ Infants born to White, Non-Hispanic women had the highest first year survival (83.57%; 95% CI: 80.91, 85.88), followed by African-Americans (82.43%; 95% CI: 76.98, 86.70) and Hispanics (79.28%; 95% CI: 77.19, 81.21). Infants with birth weights ≥2500 grams and gestational ages ≥37 weeks also had the highest first year survival. First year mortality drastically increased as the number of life-threatening anomalies increased. Mortality was also higher for infants with anomalies that were prenatally diagnosed. Slight differences existed in survival based on infant's place of delivery. ^ In logistic regression analysis, birth weight (<1500 grams: OR = 7.48; 95% CI: 5.42, 10.33; 1500–2499 grams: OR = 3.48; 95% CI: 2.74, 4.42), prenatal diagnosis (OR = 1.92; 95% CI: 1.43, 2.58) and number of life-threatening anomalies (≥3: OR = 22.45; 95% CI: 11.67, 43.18) were the strongest predictors of death within the first year of life for all infants with selected congenital anomalies. To achieve further reduction in the infant mortality rate in the United States, additional research is needed to identify ways to reduce mortality among infants with congenital anomalies. ^