Spatio-temporal dispersion of Aedes taeniorhynchus in Florida

Aedes taeniorhynchus is normally associated in high numbers with salt marshes along coastal areas in North, Central and South America. It has the potential to be a critical vector of important human and animal arboviruses. St. Louis encephalitis, Everglades, and West Nile viruses have been isolated from it in Florida, and can transmit epizootic strains of Venezuelan equine encephalomyelitis, eastern equine encephalitis, and Rift Valley fever viruses in the lab. To better identify the threat from these viruses we are attempting to better understand the spatio-temporal patterns of Aedes taeniorhynchus in Florid

Flexibility in cash-flow classification under IFRS: determinants and consequences

International Financial Reporting Standards (IFRS) allow managers flexibility in classifying interest paid, interest received, and dividends received within operating, investing, or financing activities within the statement of cash flows. In contrast, U.S. Generally Accepted Accounting Principles (GAAP) requires these items to be classified as operating cash flows (OCF). Studying IFRSreporting firms in 13 European countries, we document firms’ cash-flow classification choices vary, with about 76%, 60%, and 57% of our sample classifying interest paid, interest received, and dividends received, respectively, in OCF. Reported OCF under IFRS tends to exceed what would be reported under U.S. GAAP. We find the main determinants of OCF-enhancing classification choices are capital market incentives and other firm characteristics, including greater likelihood of financial distress, higher leverage, and accessing equity markets more frequently. In analyzing the consequences of reporting flexibility, we find some evidence that the market’s assessment of the persistence of operating cash flows and accruals varies with the firm’s classification choices, and the results of certain OCF prediction models are sensitive to classification choices

Earnings quality: evidence from Canadian firms’ choice between IFRS and U.S. GAAP

For fiscal years starting on or after January 1, 2011, Canada abandoned Canadian Generally Accepted Accounting Principles (GAAP) and adopted International Financial Reporting Standards (IFRS), but permitted firms cross-listed in the U.S. to adopt U.S. GAAP instead. We document that the number of Canadian firms reporting under U.S. GAAP increased after Canada adopted IFRS. We find that cross-listed firms are more likely to choose IFRS if IFRS is the standard most commonly used by the leading global firms in their industry. In addition, we find that firms more likely to choose IFRS are larger, of civil law legal origin, have less U.S. operations, report exploration expense, have fewer U.S. shareholders and report higher stockholders’ equity under Canadian GAAP than under U.S. GAAP. Of these, we find that the convergence benefits of comparability with industry peers is the most significant determinant in firms’ choice of standard. Further, we are unable to document changes in earnings quality from cross-listed firms adopting IFRS or U.S. GAAP or that earnings quality changed for firms adopting IFRS relative to firms adopting U.S. GAAP

DoD-GEIS Rift Valley Fever Monitoring and Prediction System as a Tool for Defense and US Diplomacy

Over the last 10 years the Armed Forces Health Surveillance Center's Global Emerging Infections Surveillance and Response System (GEIS) partnering with NASA'S Goddard Space Flight Center and USDA's USDA-Center for Medical, Agricultural & Veterinary Entomology established and have operated the Rift Valley fever Monitoring and Prediction System to monitor, predict and assess the risk of Rift Valley fever outbreaks and other vector-borne diseases over Africa and the Middle East. This system is built on legacy DoD basic research conducted by Walter Reed Army Institute of Research overseas laboratory (US Army Medical Research Unit-Kenya) and the operational satellite environmental monitoring by NASA GSFC. Over the last 10 years of operation the system has predicted outbreaks of Rift Valley fever in the Horn of Africa, Sudan, South Africa and Mauritania. The ability to predict an outbreak several months before it occurs provides early warning to protect deployed forces, enhance public health in concerned countries and is a valuable tool use.d by the State Department in US Diplomacy. At the international level the system has been used by the Food and Agricultural Organization (FAD) and the World Health Organization (WHO) to support their monitoring, surveillance and response programs in the livestock sector and human health. This project is a successful testament of leveraging resources of different federal agencies to achieve objectives of force health protection, health and diplomacy

Biologically Informed Individual-Based Network Model for Rift Valley Fever in the US and Evaluation of Mitigation Strategies

Citation: Scoglio, C. M., Bosca, C., Riad, M. H., Sahneh, F. D., Britch, S. C., Cohnstaedt, L. W., & Linthicum, K. J. (2016). Biologically Informed Individual-Based Network Model for Rift Valley Fever in the US and Evaluation of Mitigation Strategies. Plos One, 11(9), 26. doi:10.1371/journal.pone.0162759Rift Valley fever (RVF) is a zoonotic disease endemic in sub-Saharan Africa with periodic outbreaks in human and animal populations. Mosquitoes are the primary disease vectors; however, Rift Valley fever virus (RVFV) can also spread by direct contact with infected tissues. The transmission cycle is complex, involving humans, livestock, and multiple species of mosquitoes. The epidemiology of RVFV in endemic areas is strongly affected by climatic conditions and environmental variables. In this research, we adapt and use a network-based modeling framework to simulate the transmission of RVFV among hypothetical cattle operations in Kansas, US. Our model considers geo-located livestock populations at the individual level while incorporating the role of mosquito populations and the environment at a coarse resolution. Extensive simulations show the flexibility of our modeling framework when applied to specific scenarios to quantitatively evaluate the efficacy of mosquito control and livestock movement regulations in reducing the extent and intensity of RVF outbreaks in the United States

Postepizootic Persistence of Venezuelan Equine Encephalitis Virus, Venezuela

Etiologic subtype IC of virus persists, 5 years after the major 1995 epidemic

Recent Weather Extremes and Impacts on Agricultural Production and Vector-Borne Disease Outbreak Patterns

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused,10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations

Climate Teleconnections and Recent Patterns of Human and Animal Disease Outbreaks

Interannual climate variability associated with the El Niño/Southern Oscillation (ENSO) phenomenon and regional climatic circulation mechanisms in the equatorial Indian Ocean result in significant rainfall and ecological anomaly patterns that are major drivers of spatial and temporal patterns of mosquito-borne disease outbreaks. Correlation and regression analyses of long time series rainfall, vegetation index, and temperature data show that large scale anomalies occur periodically that may influence mosquito vector populations and thus spatial and temporal patterns of Rift Valley fever and chikungunya outbreaks. Rift Valley fever outbreak events occurred after a period of ∼3–4 months of persistent and above-normal rainfall that enabled vector habitats to flourish. On the other hand, chikungunya outbreaks occurred during periods of high temperatures and severe drought over East Africa and the western Indian Ocean islands. This is consistent with highly populated environmental settings where domestic and peri-domestic stored water containers were the likely mosquito sources. However, in Southeast Asia, approximately 52% of chikungunya outbreaks occurred during cooler-than-normal temperatures and were significantly negatively correlated with drought. Besides climate variability, other factors not accounted for such as vertebrate host immunity may contribute to spatio-temporal patterns of outbreaks