A model for use by local public health departments to evaluate pandemic influenza plans

The events of the 1990's and early 2000's demonstrated the need for effective planning and response to natural and man-made disasters. One of those potential natural disasters is pandemic flu. Once defined, the CDC stated that program, or plan, effectiveness is improved through the process of program evaluation. (Centers for Disease Control and Prevention, 1999) Program evaluation should be accomplished not only periodically, but in the course of routine administration of the program. (Centers for Disease Control and Prevention, 1999) Accomplishing this task for a "rare, but significant event" is challenging. (Herbold, John R., PhD., 2008) To address this challenge, the RAND Corporation (under contract to the CDC) developed the "Facilitated Look-Backs" approach that was tested and validated at the state level. (Aledort et al., 2006).^ Nevertheless, no comprehensive and generally applicable pandemic influenza program evaluation tool or model is readily found for use at the local public health department level. This project developed such a model based on the "Facilitated Look-Backs" approach developed by RAND Corporation. (Aledort et al., 2006) Modifications to the RAND model included stakeholder additions, inclusion of all six CDC program evaluation steps, and suggestions for incorporating pandemic flu response plans in seasonal flu management implementation. Feedback on the model was then obtained from three LPHD's—one rural, one suburban, and one urban. These recommendations were incorporated into the final model. Feedback from the sites also supported the assumption that this model promotes the effective and efficient evaluation of both pandemic flu and seasonal flu response by reducing redundant evaluations of pandemic flu plans, seasonal flu plans, and funding requirement accountability. Site feedback also demonstrated that the model is comprehensive and flexible, so it can be adapted and applied to different LPHD needs and settings. It also stimulates evaluation of the major issues associated with pandemic flu planning. ^ The next phase in evaluating this model should be to apply it in a program evaluation of one or more LPHD's seasonal flu response that incorporates pandemic flu response plans.^

Malaria prevention in Kenyan women of childbearing age

The objective of this program is to reduce malaria incidence in Kenya. Malaria poses a large public health challenge in Kenya, and although public health efforts have traditionally been focused on treatment of infected patients, due to increased drug resistance and lack of drug-adherence, prevention strategies are needed. This program targets Kenyan women, the likely caretakers in the home, and promotes malaria prevention behaviors through health education. ^ A planning group will be assembled and a needs assessment will be performed, verifying risk factors and conditions associated with malaria, as well as personal and external determinants. Behavioral and environmental outcomes will be determined, and performance objectives for each outcome will be established. Matrices of change objectives will be created, and detailed methods and strategies will be linked to each change objective. Program elements include media, education, and incentives. All materials used in this program will be subjected to pre-test to ensure cultural relevance and fidelity. Matrices of change objectives will be created for program adopters and implementers, as well as correlating methods and strategies associated with each change objective. Performance objectives will also be compiled for program maintainers. A program evaluation plan will follow "Pre-Post Comparison Group" design. Outcome evaluation and process evaluation will be conducted. The sample population will be screened based on age and gender so as to maintain comparability to the target population. Measurements will be taken before the program to establish baseline, directly following the program to determine short-term effects, and three months after the program is completed to determine long-term effects. ^ One limitation of this program is selection bias, due to the nature of quasi-experimental studies. Thorough screening prior to sample selection will minimize selection bias and ensure group homogeneity. Another limitation is attrition, and this will be minimized where possible through the use of incentives. In cases where loss to follow-up is not avoidable, such as death or natural disasters, the attrition effect will be estimated using structural equation modeling after reviewing the sample size, differential attrition and total attrition. ^ This intervention is based heavily on health promotion theories, but it is important to remember that in the field, the program plan will likely include only the necessary practical strategies. The target population, Kenyan women of childbearing age, will be significant in decreasing the malaria disease burden in Kenya.^

Health impacts of extreme weather: Flood fatalities in Texas

Floods are the leading cause of fatalities related to natural disasters in Texas. Texas leads the nation in flash flood fatalities. From 1959 through 2009 there were three times more fatalities in Texas (840) than the following state Pennsylvania (265). Texas also leads the nation in flood-related injuries (7753). Flood fatalities in Texas represent a serious public health problem. This study addresses several objectives of Healthy People 2010 including reducing deaths from motor vehicle accidents (Objective 15-15), reducing nonfatal motor vehicle injuries (Objective 15-17), and reducing drownings (Objective 15-29). The study examined flood fatalities that occurred in Texas between 1959 and 2008. Flood fatality statistics were extracted from three sources: flood fatality databases from the National Climatic Data Center, the Spatial Hazard Event and Loss Database for the United States, and the Texas Department of State Health Services. The data collected for flood fatalities include the date, time, gender, age, location, and type of flood. Inconsistencies among the three databases were identified and discussed. Analysis reveals that most fatalities result from driving into flood water (77%). Spatial analysis indicates that more fatalities occurred in counties containing major urban centers – some of the Flash Flood Alley counties (Bexar, Dallas, Travis, and Tarrant), Harris County (Houston), and Val Verde County (Del Rio). An intervention strategy targeting the behavior of driving into flood water is proposed. The intervention is based on the Health Belief model. The main recommendation of the study is that flood fatalities in Texas can be reduced through a combination of improved hydrometeorological forecasting, educational programs aimed at enhancing the public awareness of flood risk and the seriousness of flood warnings, and timely and appropriate action by local emergency and safety authorities.^

Statistical and methodological challenges for disaster preparedness and medical needs assessment in Rio Grande Valley of Texas

In recent years, disaster preparedness through assessment of medical and special needs persons (MSNP) has taken a center place in public eye in effect of frequent natural disasters such as hurricanes, storm surge or tsunami due to climate change and increased human activity on our planet. Statistical methods complex survey design and analysis have equally gained significance as a consequence. However, there exist many challenges still, to infer such assessments over the target population for policy level advocacy and implementation. ^ Objective. This study discusses the use of some of the statistical methods for disaster preparedness and medical needs assessment to facilitate local and state governments for its policy level decision making and logistic support to avoid any loss of life and property in future calamities. ^ Methods. In order to obtain precise and unbiased estimates for Medical Special Needs Persons (MSNP) and disaster preparedness for evacuation in Rio Grande Valley (RGV) of Texas, a stratified and cluster-randomized multi-stage sampling design was implemented. US School of Public Health, Brownsville surveyed 3088 households in three counties namely Cameron, Hidalgo, and Willacy. Multiple statistical methods were implemented and estimates were obtained taking into count probability of selection and clustering effects. Statistical methods for data analysis discussed were Multivariate Linear Regression (MLR), Survey Linear Regression (Svy-Reg), Generalized Estimation Equation (GEE) and Multilevel Mixed Models (MLM) all with and without sampling weights. ^ Results. Estimated population for RGV was 1,146,796. There were 51.5% female, 90% Hispanic, 73% married, 56% unemployed and 37% with their personal transport. 40% people attained education up to elementary school, another 42% reaching high school and only 18% went to college. Median household income is less than $15,000/year. MSNP estimated to be 44,196 (3.98%) [95% CI: 39,029; 51,123]. All statistical models are in concordance with MSNP estimates ranging from 44,000 to 48,000. MSNP estimates for statistical methods are: MLR (47,707; 95% CI: 42,462; 52,999), MLR with weights (45,882; 95% CI: 39,792; 51,972), Bootstrap Regression (47,730; 95% CI: 41,629; 53,785), GEE (47,649; 95% CI: 41,629; 53,670), GEE with weights (45,076; 95% CI: 39,029; 51,123), Svy-Reg (44,196; 95% CI: 40,004; 48,390) and MLM (46,513; 95% CI: 39,869; 53,157). ^ Conclusion. RGV is a flood zone, most susceptible to hurricanes and other natural disasters. People in the region are mostly Hispanic, under-educated with least income levels in the U.S. In case of any disaster people in large are incapacitated with only 37% have their personal transport to take care of MSNP. Local and state government’s intervention in terms of planning, preparation and support for evacuation is necessary in any such disaster to avoid loss of precious human life. ^ Key words: Complex Surveys, statistical methods, multilevel models, cluster randomized, sampling weights, raking, survey regression, generalized estimation equations (GEE), random effects, Intracluster correlation coefficient (ICC).^

Policy implications of public health workforce development for disaster preparedness in the United States

Public health efforts were initiated in the United States with legislative actions for enhancing food safety and ensuring pure drinking water. Some additional policy initiatives during the early 20th century helped organize and coordinate relief efforts for victims of natural disasters. By 1950's the federal government expanded its role for providing better health and safety to the communities, and its disaster relief activities became more structured. A rise in terrorism related incidents during the late 1990's prompted new proactive policy directions. The traditional policy and program efforts for rescue, recovery, and relief measures changed focus to include disaster preparedness and countermeasures against terrorism.^ The study took a holistic approach by analyzing all major disaster related policies and programs, in regard to their structure, process, and outcome. Study determined that United States has a strong disaster preparedness agenda and appropriate programs are in place with adequate policy support, and the country is prepared to meet all possible security challenges that may arise in the future. The man-made disaster of September 11th gave a major thrust to improve security and enhance preparedness of the country. These new efforts required large additional funding from the federal government. Most existing preparedness programs at the local and national levels are run with federal funds which is insufficient in some cases. This discrepancy arises from the fact that federal funding for disaster preparedness programs at present are not allocated by the level of risks to individual states or according to the risks that can be assigned to critical infrastructures across the country. However, the increased role of the federal government in public health affairs of the states is unusual, and opposed to the spirit of our constitution where sovereignty is equally divided between the federal government and the states. There is also shortage of manpower in public health to engage in disaster preparedness activities, despite some remarkable progress following the September 11th disaster.^ Study found that there was a significant improvement in knowledge and limited number of studies showed improvement of skills, increase in confidence and improvement in message-mapping. Among healthcare and allied healthcare professionals, short-term training on disaster preparedness increased knowledge and improved personal protective equipment use with some limited improvement in confidence and skills. However, due to the heterogeneity of these studies, the results and interpretation of this systematic review may be interpreted with caution.^

A descriptive study on Hurricanes Katrina and Rita evacuees participating in the Harris County Housing Authority Disaster Housing Assistance Program

Natural disasters occur in various forms such as hurricanes, tsunamis, earthquakes, outbreaks, etc. The most unsettling aspect of a natural disaster is that it can strike at any moment. Over the past decade, our society has experienced an alarming increase of natural disasters. How to expeditiously respond and recover from natural disasters has become a precedent question for public health officials. To date, the most recent natural disaster was the January 12, 2010 earthquake in Haiti; however the most memorable was that of Hurricane Katrina (“Haiti Earthquake”, 2010). ^ This study provides insight on the need to develop a National Disaster Response and Recovery Program which effectively responds to natural disasters. The specific aims of this paper were to (1) observe the government’s role on federal, state and local levels in assisting Hurricanes Katrina and Rita evacuees, (2) assess the prevalence of needs among Hurricanes Katrina and Rita families participating in the Disaster Housing Assistance Program (DHAP) and (3) describe the level of progress towards “self sufficiency” for the DHAP families receiving case management social services. ^ Secondary data from a cross-sectional “Needs Assessment” questionnaire were analyzed. The questionnaire was administered initially and again six months later (follow-up) by H.A.U.L. case managers. The “Needs Assessment” questionnaire collected data regarding participants’ education, employment, transportation, child care, health resources, income, permanent housing and disability needs. Case managers determined the appropriate level of social services required for each family based on the data collected from the “Needs Assessment” questionnaire. ^ Secondary data provided by the H.A.U.L. were analyzed to determine the prevalence of needs among the DHAP families. In addition, differences measured between the initial and follow-up (at six months) questionnaires were analyzed to determine statistical significance between case management services provided and prevalence of needs among the DHAP families from initial to 6 months later at follow-up. The data analyzed describe the level of progress made by these families to achieve program “self sufficiency” (see Appendix A). Disaster assistance programs which first address basic human needs; then socioeconomic needs may offer an essential tool in aiding disaster affected communities quickly recover from natural disasters. ^