HLS 6070 DF9: Assisting USAID and the UN World Food Organization

Comment on these two post as if you were me with a 100 words each, and put 3 references for each post and please seperate the references
Daniel Divincenzo 
Role Play - Assisting USAID and the UN World Food Organization
For areas at risk for food shortages, there are many layers that would assist our identifying of high risk locations. One layer would be precipitation levels. . Rain is obviously needed to keep crops alive, also for grazing plants and drinking water for cattle and other domestic animals used for food. Another layer to look at would be the ground water levels of certain locations. Even if an area had high levels of precipitation, if that rain is not being absorbed it isn't helping. The groundwater needs to be there even after the rainfall to keep animals, plants, and humans with needed water. Groundwater allows humans to tap wells for additional water resources. The measurement of the sun being absorbed by plant life, without regular sunlight plants wouldn't be able to photosynthesize and would eventually die. A key combination of layers could included flood zones combined with crop producing regions. this would be an ideal combo so that areas that meet both criteria would be more at risk for a larger food shortage, becuase the majority of food producing regions lie near sources of freshwater, which could flood.
For disease tracking and management there are also a number of different layers that would assist us figure out high risk areas. One layer to show possible disease spreading capabilities would be transportation maps, including.railways, major road ways and air flight traffic. Also included in these transportation maps would include boat shipping containers, because the majority of things that area shipped still go by boat. These transportation maps would be able to show us possible vectors where the disease could spread to and when quantified could be able to determine the rate at which the disease could spread. For example when Mad Cow Disease first started popping up. measures were made to track where potentially infected cattle could have gone. Another example would be swine flu which started in Southeast Asia and quickly became an epidemic. Some diseases are waterborn and when a community starts reporting mass outbreak the first main source checked is the water source. In a Civil Action a comunity was experiencing a high rate of children with cancer, and it was determined that the source was a contaminated water supply.
Susan Schiller 
RE: Role Play - Assisting USAID and the UN World Food Organization
When considering the monitoring of food security and disease tracking, several primary data layers are critical to an early warning system.
Rainfall
Vegetation / Crops health
Potable water availability (Water treatment facilities)
Flood plains / Coastal incursions ( as a function of contaminated potable water in underdeveloped regions)
Sanitation infrastructure (Sewer systems)
Healthcare Access (Clinics and Hospitals)
Population Density
Transit Systems (migration patterns)
Rainfall data is critical for anticipating drought conditions which directly impacts vegetation and crop availability. Potable water must be available through connected treatment plants and intact, well-conditioned pipes to ensure adequate amounts for hydration and maintenance of sanitary living conditions. In underdeveloped regions/countries, seawater incursion from coastal flooding may significantly impact potable water availability. So too flooding may bring sewage overflow that acts as a health hazard in itself as well as reducing the ability to maintain an aseptic environment for further infection control (CDC, 2016).
Standard false-color composite layers may offer the greatest clarity on a concept that may seem counterintuitive; flooding may reduce water availability rather than increase it. By demarcating salinized and raw sewage contamination, standard false-color flood imagery can offer a dramatic visual representation of contaminated water sources. Furthermore, SWIR offers “sorting and surveillance” (Edmund, 2016) capabilities beyond that of the visible spectrum which offers additional analytic depth to assess aridity, crop health, and water access. Consider countries mapped with low precipitation layered over salinized water sources might be excellent candidates for desalination projects (Kitsara, 2016) offering those regions both prevention and resilience forecasting. 
Regarding disease tracing, sufficient infection control requires access to clinics and health centers both for prevention, in the form of vaccinations and education, and mitigation, in the case of outbreak. Population density can be combined with the aforementioned attribute tables to run resource scarcity algorithms derived from the other datasets. Finally, transit corridors and migratory patterns are important in anticipating spread beyond communal and regional borders.
Susan
Works Cited
CDC. (2016). Water, Sanitation, and Hygiene (WASH) Related Emergencies and Outbreaks. Retrieved from Centers for Disease Control and Prevention: http://www(dot)cdc(dot)gov/healthywater/emergency/extreme-weather/floods-standingwater.html
Edmund. (2016). What is SWIR. Retrieved from Edmund Optics: http://www(dot)edmundoptics(dot)com/resources/application-notes/imaging/what-is-swir/
Kitsara, I. (2016). Mapping Desalination Technologies. Retrieved from WIPO: http://www(dot)wipo(dot)int/wipo_magazine/en/2012/03/article_0007.html