No abstract

Flash floods are one of the most dangerous weather-related natural disasters in the world. These events develop less than six hours after a rainfall event and create hazardous situations for people and extensive damage to property. It is critical for flash flood conditions to be warned of in a timely manner to minimize impacts. There is currently a knowledge gap between flood experts and the general public about the level of perceived risk that the latter has toward the powerful flood waters and how events should be warned of, which affects the communication capabilities and efficiency of the warning process. Prior research has addressed risk perception of natural disasters, but there is little emphasis on flash floods within flood-prone regions of the United States. This research utilizes an online survey of 300 respondents to determine the current state of flash flood awareness and preparation in southwest Virginia. Analysis of trends involved the use of chi-squared tests (chi2) and simple frequency and percentage calculations. Results reveal that a knowledge base of flash floods does exist, but is not advanced enough for proper awareness. Young adults have a lower understanding and are not as concerned about flood impacts. Increased exposure and perceived risk play a key role in shaping the way a person approaches flash floods. People do monitor flood events, but they are unaware of essential guidance and communication mechanisms. Finally, results suggest that the current method of warning about flash floods is not provided at an appropriate level of detail for effective communication.

Valley fever (coccidioidomycosis) is a disease endemic to arid regions within the Western Hemisphere, and is caused by a soil-dwelling fungus, Coccidioides immitis. Incidence data for Pima County, reported to the Arizona Department of Health Services as new cases of valley fever, were used to conduct exploratory analyses and develop monthly multivariate models of relationships between valley fever incidence and climate conditions and variability in Pima County, Arizona, USA. Bivariate and compositing analyses conducted during the exploratory portion of the study revealed that antecedent temperature and precipitation in different seasons are important predictors of incidence. These results were used in the selection of candidate variables for multivariate predictive modeling, which was designed to predict deviation from mean incidence on the basis of past, current, and forecast climate conditions. The models were specified using a backward stepwise procedure, and were most sensitive to key predictor variables in the winter season and variables that were time-lagged 1 year or more prior to the month being predicted. Model accuracy was generally moderate (r 2 values for the monthly models, tested on independent data, ranged from 0.15 to 0.50), and months with high incidence can be predicted more accurately than months with low incidence.

Natural hazards and major land-use/land-cover change can have significant impacts on humans around the world. If these two concerns exist together in a coastal area, the consequences for people and the environment may be severe. This study investigated the combined effects of land-use changes and natural disasters in the southwest coastal area of Bangladesh. Satellite images were analyzed to detect changes in land cover in the study period of 13 years (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012). Three areas were selected for ground data collection. Household surveys and focus groups were conducted to discover the type, level and effects of disasters. Probit regression analysis was performed to assess the relationship between various disasters with overall income, agricultural production and outward migration. Results from image analysis showed an overall 30 % increase in shrimp culture ponds in the past 13 years. Agricultural land and vegetation decreased by 48 and 3 %, respectively. Barren and built-up areas increased by 73 % due to both land-use activity and natural hazards. Analysis of household data showed cyclones and storm surges had important effects on income, agricultural production and migration. Sustainable management and enhancement of resilience capacity of this area will be crucial in the near future.

Lyme disease is the United States' most significant vector-borne illness. Virginia, on the southern edge of the disease's currently expanding range, has experienced an increase in Lyme disease both spatially and temporally, with steadily increasing rates over the past decade and disease spread from the northern to the southwestern part of the state. This study used a Geographic Information System and a spatial Poisson regression model to examine correlations between demographic and land cover variables, and human Lyme disease from 2006 to 2010 in Virginia. Analysis indicated that herbaceous land cover is positively correlated with Lyme disease incidence rates. Areas with greater interspersion between herbaceous and forested land were also positively correlated with incidence rates. In addition, income and age were positively correlated with incidence rates. Levels of development, interspersion of herbaceous and developed land, and population density were negatively correlated with incidence rates. Abundance of forest fragments less than 2 hectares in area was not significantly correlated. Our results support some findings of previous studies on ecological variables and Lyme disease in endemic areas, but other results have not been found in previous studies, highlighting the potential contribution of new variables as Lyme disease continues to emerge southward.