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    "title": "Predicting Malaria Outbreaks With NASA Satellites",
    "description": "In the Amazon Rainforest, few animals are as dangerous to humans as mosquitos that transmit malaria. The tropical disease can bring on severe fever, headaches and chills and is particularly severe for children and the elderly and can cause complications for pregnant women. In rainforest-covered Peru the number of malaria cases has spiked such that, in the past five years, it has had on average the second highest rate in the South American continent. In 2014 and 2015 there were 65,000 reported cases in the country.Containing malaria outbreaks is challenging because it is difficult to figure out where people are contracting the disease. As a result, resources such as insecticide-treated bed nets and indoor sprays are often deployed to areas where few people are getting infected, allowing the outbreak to grow.To tackle this problem, university researchers have turned to data from NASA’s fleet of Earth-observing satellites, which are able to track the types of human and environmental events that typically precede an outbreak. With funding from NASA’s Applied Sciences Program, they are working in partnership with the Peruvian government to develop a system that uses satellite and other data to help forecast outbreaks at the household level months in advance and prevent outbreaks.Additional imagery from: Christopher B. Plunkett FortJames GathanyFábio Medeiros da Costa || ",
    "release_date": "2017-09-13T11:00:00-04:00",
    "update_date": "2023-05-03T13:47:22.583191-04:00",
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        "alt_text": "Complete transcript available.Music credits: ‘Inner Confusion’ by Laurent Levesque [SACEM], ‘The Awakening’ by Benjamin Krause [GEMA], Scott Goodman [ASCAP], ‘Cellular Signals’ by Laurent Levesque [SACEM]Watch this video on the NASA Goddard YouTube channel.",
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            "description": "In the Amazon Rainforest, few animals are as dangerous to humans as mosquitos that transmit malaria. The tropical disease can bring on severe fever, headaches and chills and is particularly severe for children and the elderly and can cause complications for pregnant women. In rainforest-covered Peru the number of malaria cases has spiked such that, in the past five years, it has had on average the second highest rate in the South American continent. In 2014 and 2015 there were 65,000 reported cases in the country.<p>\rContaining malaria outbreaks is challenging because it is difficult to figure out where people are contracting the disease. As a result, resources such as insecticide-treated bed nets and indoor sprays are often deployed to areas where few people are getting infected, allowing the outbreak to grow.<p>\rTo tackle this problem, university researchers have turned to data from NASA’s fleet of Earth-observing satellites, which are able to track the types of human and environmental events that typically precede an outbreak. With funding from NASA’s Applied Sciences Program, they are working in partnership with the Peruvian government to develop a system that uses satellite and other data to help forecast outbreaks at the household level months in advance and prevent outbreaks.<br><br>Additional imagery from: <br>Christopher B. Plunkett Fort<br>James Gathany<br>Fábio Medeiros da Costa",
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            "description": "<p><a href=\"/vis/a010000/a012600/a012603/script_23593_00.html\">Complete transcript</a> available.</p><p><p>Music credits: ‘Inner Confusion’ by Laurent Levesque [SACEM], ‘The Awakening’ by Benjamin Krause [GEMA], Scott Goodman [ASCAP], ‘Cellular Signals’ by Laurent Levesque [SACEM]<p><p><p><b>Watch this video on the <a href=\"https://www.youtube.com/watch?v=c6g2ILL--Rw&feature=youtu.be\" target=\"_blank\" >NASA Goddard YouTube channel</a>.</b><p>",
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            "description": "See [https://www.nasa.gov/feature/goddard/2017/using-nasa-satellite-data-to-predict-malaria-outbreaks](https://www.nasa.gov/feature/goddard/2017/using-nasa-satellite-data-to-predict-malaria-outbreaks)",
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            "title": "Using Satellite and Ground-based Data to Develop Malaria Risk Maps",
            "description": "Malaria is a major problem in the Amazon where malaria mosquitoes tend to prefer wet, hot areas with more standing water. Seasonal occupational movement along rivers and in forested areas increases transmission and concentrates malaria in specific regions. The objective of Malaria Project, an ongoing study led by William Pan and Ben Zaitchik, is to develop a detection and early warning system for malaria risk in the Amazon. Using data from NASA satellites and a Land Data Assimilation System (LDAS), the scientists hope that their research can help health officials pinpoint where to deploy resources and what resources to deploy during a disease outbreak.  By incorporating NASA data such as precipitation, soil moisture, air temperature, and humidity into their new system, scientists are better able to predict where malaria-spreading mosquitoes are breeding. These climate factors in conjunction with a population density and human movement model will help scientists better understand where and when people are at high risk for malaria. The malaria warning system will predict outbreaks and simulate response to help a country's health care system to more strategically determine where to deploy their resources.  Visualizations focus on Peru, one of the central areas of malaria transmission in the Amazon.  Four LDAS data sets -- precipitation, soil moisture, air temperature, and humidity are illustrated below. Combined with public health data, the animations show how these factors may affect the outbreak and evolvement of the disease. || ",
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                "filename": "comp_malariaCase_mask_mmddyy_1080p30.00302_print.jpg",
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            "description": "Animation of precipitation rates over the Amazon Rain Forest as it pulsates with the diurnal cycle. Notice how during the day precipitation amounts increase and then decrease nightly. || amazon_w_sun_dated.0264_print.jpg (1024x576) [131.3 KB] || amazon_w_sun_dated.0264_print_thm.png (80x40) [6.8 KB] || amazon_w_sun_dated.0264_searchweb.png (320x180) [83.7 KB] || amazon_w_sun_dated_1080p30.mp4 (1920x1080) [19.9 MB] || Amazon_with_dates (1920x1080) [32.0 KB] || amazon_w_sun.mp4 (1920x1080) [19.7 MB] || Amazon_without_dates (1920x1080) [32.0 KB] || amazon_w_sun_dated_1080p30.webm (1920x1080) [3.6 MB] || date_overlay (350x80) [32.0 KB] || ",
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