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"description": "The visualization featured on this page showcases the relationship between increase in vegetation and outbreaks of Rift Valley fever (RVF) over Middle East and the African continent for the period of 2000-2018. The data visualized in this animation are: a) Normalized Difference Vegetation Index (NDVI) (low/brown to high/green) over Africa and Middle East and b) locations of Rift Valley fever outbreaks (orange pins). We can see spikes of RVF outbreaks in various regions such as in Middle East, West, East and South Africa. These outbreaks are linked to El Niño-Southern Oscillation (ENSO) teleconnections.
ENSO is an irregularly recurring climate pattern characterized by warmer (El Niño) and colder (La Niña) than usual ocean temperatures in the equatorial Pacific, which creates a ripple effect of anticipated weather changes in far-spread regions of our planet. Weather changes associated with the El Niño-Southern Oscillation phenomenon result in climate anomalies related to each other, such as rainfall, and vegetation anomaly conditions that trigger outbreaks of infectious diseases of public health concern in different regions around the world. These distant weather effects are called teleconnections. Therefore the effects of ENSO are called ENSO teleconnections, highlighting that warmer or colder than usual ocean temperatures in equatorial pacific with extents (5N-5S, 120W-170W) affect areas far from the source typically 2-3 months after.
During the last 20 years NASA scientist Dr. Assaf Anyamba and colleagues have been studying ENSO teleconnections by monitoring various climate datasets, among them Sea Surface Temperature and precipitation anomaly datasets from NASA and National Oceanic and Atmospheric Administration (NOAA) and vegetation data from NASA’s Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra (EOS AM-1) spacecraft. At the same time, the science team has been collecting, cataloguing and analyzing patterns and sources of disease outbreaks worldwide. To learn more, please refer to entry: Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018 (4K version)\r
\r
The relationship between ENSO induced anomalous rainfall and disease outbreaks is clearly illustrated by outbreak patterns of Rift Valley fever (RVF). Typically, during El Niño (Eastern Africa) and La Niña (Southern Africa) events, Africa receives persistent and above normal rainfall, which floods habitats of RVF mosquito vectors triggering hatching of RVF virus infected eggs. The above-normal rainfall is followed by an increase in vegetation creating appropriate habitats for the mosquito vectors setting the stage for RVF outbreak activity, which in simple terms means an uptick in mosquito populations that cause infections of domestic livestock and human populations with the RVF virus.\r
To learn more about the impacts of weather patterns and teleconnections for the region of South Africa during 2008-2011, please see the following data visualizations:
\r
Data Sources:\r
\r
This visualization was created on October 2019, to support Dr. Assaf Anyamba’s interview and filming of the upcoming documentary titled Connected produced by Netflix. [Citation: \"Clouds\". Connected - The Hidden Science of Everything, Season 1, Episode 5, 2 Aug. 2020, Netflix]
Supported with funding from the Defense Health Agency-Armed Forces Health Surveillance Branch (AFHSB) Global Emerging Infections Surveillance and Response System (GEIS) under Project #P0072_19_NS
The rest of this webpage offers frames, layers and colorbar information associated with the development of this data-driven visualization.",
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"title": "Vegetation Index Anomalies and Rift Valley fever (RVF) outbreaks in South Africa region: 2008-2011",
"description": "This visualization with corresponding data dashboard shows the relationship between vegetation index anomalies and outbreaks of Rift Valley fever (RVF) during 2008 and 2011 in the South Africa region. The sequence starts in 2007 looking at the entire continent of Africa and zooms in the region of South Africa to take a closer look at the patterns between ENSO events (El Niño and La Niña), above normal vegetaion over land (green) and RVF outbreak locations (orange pins). || NDVI_RVF_SAfrica_Composite_3840x2160_2657_print.jpg (1024x576) [102.7 KB] || NDVI_RVF_SAfrica_Composite_3840x2160_2657_searchweb.png (320x180) [57.8 KB] || NDVI_RVF_SAfrica_Composite_3840x2160_2657_thm.png (80x40) [5.0 KB] || NDVI_RVF_SAfrica_Composite_1920x1080p30.mp4 (1920x1080) [35.6 MB] || NDVI_RVF_SAfrica_Composite_1920x1080p30.webm (1920x1080) [7.1 MB] || Composite (3840x2160) [0 Item(s)] || Composite (3840x2160) [0 Item(s)] || NDVI_RVF_SAfrica_Composite_3840x2160_p30.mp4 (3840x2160) [72.6 MB] || NDVI_RVF_SAfrica_Composite_3840x2160_2657.tif (3840x2160) [31.6 MB] || ",
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"alt_text": "This visualization with corresponding data dashboard shows the relationship between vegetation index anomalies and outbreaks of Rift Valley fever (RVF) during 2008 and 2011 in the South Africa region. The sequence starts in 2007 looking at the entire continent of Africa and zooms in the region of South Africa to take a closer look at the patterns between ENSO events (El Niño and La Niña), above normal vegetaion over land (green) and RVF outbreak locations (orange pins).",
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"title": "Precipitation Anomaly and Rift Valley fever (RVF) outbreaks in South Africa: 2008-2011",
"description": "This visualization with corresponding data dashboard shows the relationship between precipitation anomalies and outbreaks of Rift Valley fever (RVF) during 2008 and 2011 in the South Africa region. The sequence starts in 2007 looking at the entire continent of Africa and zooms in the region of South Africa to take a closer look at the patterns between ENSO events (El Niño and La Niña), above normal precipitation over land (blue) and RVF outbreak locations (orange pins). || PrecipRVF_SAfrica_Composite_3840x2160_3422_print.jpg (1024x576) [97.8 KB] || PrecipRVF_SAfrica_Composite_3840x2160_3422_searchweb.png (320x180) [57.6 KB] || PrecipRVF_SAfrica_Composite_3840x2160_3422_thm.png (80x40) [5.2 KB] || PrecipRVF_SAfrica_Composite_1920x1080p30.mp4 (1920x1080) [31.5 MB] || Composite (3840x2160) [0 Item(s)] || Composite (3840x2160) [0 Item(s)] || PrecipRVF_SAfrica_Composite_3840x2160_p30.mp4 (3840x2160) [68.2 MB] || PrecipRVF_SAfrica_Composite_3840x2160_3422.tif (3840x2160) [4.0 MB] || PrecipRVF_SAfrica_Composite_3840x2160_p30.webm (3840x2160) [14.1 MB] || ",
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"url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004783/PrecipRVF_SAfrica_Composite_3840x2160_3422_print.jpg",
"filename": "PrecipRVF_SAfrica_Composite_3840x2160_3422_print.jpg",
"media_type": "Image",
"alt_text": "This visualization with corresponding data dashboard shows the relationship between precipitation anomalies and outbreaks of Rift Valley fever (RVF) during 2008 and 2011 in the South Africa region. The sequence starts in 2007 looking at the entire continent of Africa and zooms in the region of South Africa to take a closer look at the patterns between ENSO events (El Niño and La Niña), above normal precipitation over land (blue) and RVF outbreak locations (orange pins). ",
"width": 1024,
"height": 576,
"pixels": 589824
}
},
{
"id": 4747,
"url": "https://svs.gsfc.nasa.gov/4747/",
"page_type": "Visualization",
"title": "Vegetation index anomalies and Rift Valley fever (RVF) outbreaks in South Africa during 2009-2011",
"description": "This visualization shows the relationship between vegetation index anomalies (Normalized Difference Vegetation Index - NDVI) data and outbreak locations of Rift Valley fever (RVf) during 2008 and 2011. The sequence starts in 2007 looking at the entire continent of Africa and zooms in the region of South Africa slowly to take a closer look at the above normal vegetation (green) and RVF outbreak locations (orange pins). Frames are provided in 4K resolution. || SAfrica_NDVIRVFwDates_3840x2160_1263_print.jpg (1024x576) [86.2 KB] || SAfrica_NDVIRVFwDates_3840x2160_1263_searchweb.png (320x180) [56.0 KB] || SAfrica_NDVIRVFwDates_3840x2160_1263_thm.png (80x40) [4.5 KB] || SAfrica_NDVIRVFComposite_1080p30.mp4 (1920x1080) [31.6 MB] || SAfrica_NDVIRVFComposite_1080p30.webm (1920x1080) [7.0 MB] || Composite (3840x2160) [0 Item(s)] || SAfrica_NDVIRVFwDates_3840x2160_1263.tif (3840x2160) [7.6 MB] || SAfrica_NDVIRVFComposite_3840x2160_p30.mp4 (3840x2160) [96.4 MB] || ",
"release_date": "2020-02-21T00:00:00-05:00",
"update_date": "2025-02-02T00:12:35.273066-05:00",
"main_image": {
"id": 392107,
"url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004747/SAfrica_NDVIRVFwDates_3840x2160_1263_print.jpg",
"filename": "SAfrica_NDVIRVFwDates_3840x2160_1263_print.jpg",
"media_type": "Image",
"alt_text": "This visualization shows the relationship between vegetation index anomalies (Normalized Difference Vegetation Index - NDVI) data and outbreak locations of Rift Valley fever (RVf) during 2008 and 2011. The sequence starts in 2007 looking at the entire continent of Africa and zooms in the region of South Africa slowly to take a closer look at the above normal vegetation (green) and RVF outbreak locations (orange pins). Frames are provided in 4K resolution.",
"width": 1024,
"height": 576,
"pixels": 589824
}
},
{
"id": 4784,
"url": "https://svs.gsfc.nasa.gov/4784/",
"page_type": "Visualization",
"title": "ENSO Teleconnections and Rift Valley fever (RVF) Outbreaks",
"description": "During the 2008-2011 period, ENSO events brought changes to weather conditions across the globe that triggered infectious disease outbreaks, such as mosquito-borne Rift Valley fever (RVF) in South Africa. This visualization with corresponding data dashboard shows how Sea Surface Temperature (SST) anomalies in the equatorial Pacific Ocean (left) gave rise to Precipitation (center) and Vegetation (right) Index Anomalies in South Africa. During La Niña events, Southern Africa receives persistent and above normal rainfall, which floods habitats of RVF mosquito vectors triggering hatching of RVF virus infected eggs. The above-normal rainfall is followed by an increase in vegetation creating appropriate habitats for the mosquito vectors setting the stage for RVF outbreak activity, which in simple terms means an uptick in mosquito populations that cause infections of domestic livestock and human populations with the RVF virus. However, in rare cases there is a departure from this canonical response, as we can observe in 2009-2010, when a mild El Niño event resulted in above normal vegetaton and a large RVF outbreak in South Africa. || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_2960_print.jpg (1024x576) [107.8 KB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525_searchweb.png (320x180) [63.0 KB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525_thm.png (80x40) [6.5 KB] || ENSO_Teleconnections (1920x1080) [0 Item(s)] || SST_Precip_NDVI_Dashboard_2008_2011_1920x1080_p30.mp4 (1920x1080) [22.7 MB] || ENSO_Teleconnections (3840x2160) [0 Item(s)] || ENSO_Teleconnections (3840x2160) [0 Item(s)] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_p30.mp4 (3840x2160) [56.0 MB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_p30.webm (3840x2160) [10.2 MB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_2960.tif (3840x2160) [3.4 MB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525.tif (3840x2160) [3.4 MB] || ",
"release_date": "2020-02-21T00:00:00-05:00",
"update_date": "2025-02-02T00:13:13.644499-05:00",
"main_image": {
"id": 386811,
"url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004784/ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525_searchweb.png",
"filename": "ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525_searchweb.png",
"media_type": "Image",
"alt_text": "During the 2008-2011 period, ENSO events brought changes to weather conditions across the globe that triggered infectious disease outbreaks, such as mosquito-borne Rift Valley fever (RVF) in South Africa. This visualization with corresponding data dashboard shows how Sea Surface Temperature (SST) anomalies in the equatorial Pacific Ocean (left) gave rise to Precipitation (center) and Vegetation (right) Index Anomalies in South Africa. During La Niña events, Southern Africa receives persistent and above normal rainfall, which floods habitats of RVF mosquito vectors triggering hatching of RVF virus infected eggs. The above-normal rainfall is followed by an increase in vegetation creating appropriate habitats for the mosquito vectors setting the stage for RVF outbreak activity, which in simple terms means an uptick in mosquito populations that cause infections of domestic livestock and human populations with the RVF virus. However, in rare cases there is a departure from this canonical response, as we can observe in 2009-2010, when a mild El Niño event resulted in above normal vegetaton and a large RVF outbreak in South Africa.",
"width": 320,
"height": 180,
"pixels": 57600
}
},
{
"id": 4785,
"url": "https://svs.gsfc.nasa.gov/4785/",
"page_type": "Visualization",
"title": "Sea Surface Temperature Anomalies and Patterns of Global Disease Outbreaks: 2009-2018 (4K version)",
"description": "This webpage provides the 4K version of: Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018 (updated), released on January 6, 2020.Content has been created for 4K display systems that can handle finer resolution and details. It is recommended to use content from this version for HD (1920x1080) and lower resolutions. || ",
"release_date": "2020-01-09T00:00:00-05:00",
"update_date": "2025-02-02T00:13:15.129941-05:00",
"main_image": {
"id": 388258,
"url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004785/CompositeWLabel_2009_2018_3840x2160_30fps_0852_print.jpg",
"filename": "CompositeWLabel_2009_2018_3840x2160_30fps_0852_print.jpg",
"media_type": "Image",
"alt_text": "This visualization shows the variability in global sea surface temperature anomalies, the associated ENSO index timeline and locations of infectious disease outbreaks over the global land surface. Content is available in 4K resolution.",
"width": 1024,
"height": 576,
"pixels": 589824
}
},
{
"id": 4781,
"url": "https://svs.gsfc.nasa.gov/4781/",
"page_type": "Visualization",
"title": "Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018 (updated)",
"description": "This visualization shows the variability in global sea surface temperature anomalies, the associated ENSO index timeline and locations of infectious disease outbreaks over the global land surface. || CompositeWLabel_2009_2018_1920x108060fps_1705_print.jpg (1024x576) [135.9 KB] || CompositeWLabel_2009_2018_1920x108060fps_1705_searchweb.png (320x180) [82.6 KB] || CompositeWLabel_2009_2018_1920x108060fps_1705_thm.png (80x40) [7.1 KB] || Composite_StrongElNino (1920x1080) [0 Item(s)] || Composite_StrongElNino (1920x1080) [0 Item(s)] || CompositeWLabel_2009_2018_1920x1080_p30.mp4 (1920x1080) [22.1 MB] || CompositeWLabel_2009_2018_1920x108060fps_1705.tif (1920x1080) [1.3 MB] || CompositeWLabel_2009_2018_1920x1080_p30.webm (1920x1080) [4.6 MB] || CompositeWLabel_2009_2018_1920x1080_p30.mp4.hwshow [205 bytes] || ",
"release_date": "2020-01-06T00:00:00-05:00",
"update_date": "2025-02-02T00:13:06.818408-05:00",
"main_image": {
"id": 388349,
"url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004781/CompositeWLabel_2009_2018_1920x108060fps_1705_print.jpg",
"filename": "CompositeWLabel_2009_2018_1920x108060fps_1705_print.jpg",
"media_type": "Image",
"alt_text": "This visualization shows the variability in global sea surface temperature anomalies, the associated ENSO index timeline and locations of infectious disease outbreaks over the global land surface. ",
"width": 1024,
"height": 576,
"pixels": 589824
}
},
{
"id": 4765,
"url": "https://svs.gsfc.nasa.gov/4765/",
"page_type": "Visualization",
"title": "Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018",
"description": "El Niño is an irregularly recurring climate pattern characterized by warmer than usual ocean temperatures in the equatorial Pacific, which creates a ripple effect of anticipated weather changes in far-spread regions. This visualization captures monthly Sea Surface Temperature (SST) anomalies around the world from 2009-2018, along with locations of global disease outbreaks and a corresponding timeline showcasing the Niño 3.4 Index. The Niño 3.4 Index represents average equatorial sea surface temperatures in the Pacific Ocean from about the International Date Line to the coast of South America. Highlighted in the timeline are the above average El Niño years, in which sea surface temperature anomalies peaked during 2015-2016. || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_print.jpg (1024x576) [130.6 KB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_searchweb.png (320x180) [79.7 KB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_thm.png (80x40) [7.0 KB] || Composite (1920x1080) [0 Item(s)] || Composite (1920x1080) [0 Item(s)] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_p30.mp4 (1920x1080) [23.0 MB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769.tif (1920x1080) [1.3 MB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_p30.webm (1920x1080) [4.7 MB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_p30.mp4.hwshow [211 bytes] || ",
"release_date": "2019-12-10T00:00:00-05:00",
"update_date": "2025-02-02T00:12:46.498564-05:00",
"main_image": {
"id": 388873,
"url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004765/SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_print.jpg",
"filename": "SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_print.jpg",
"media_type": "Image",
"alt_text": "El Niño is an irregularly recurring climate pattern characterized by warmer than usual ocean temperatures in the equatorial Pacific, which creates a ripple effect of anticipated weather changes in far-spread regions. This visualization captures monthly Sea Surface Temperature (SST) anomalies around the world from 2009-2018, along with locations of global disease outbreaks and a corresponding timeline showcasing the Niño 3.4 Index. The Niño 3.4 Index represents average equatorial sea surface temperatures in the Pacific Ocean from about the International Date Line to the coast of South America. Highlighted in the timeline are the above average El Niño years, in which sea surface temperature anomalies peaked during 2015-2016.",
"width": 1024,
"height": 576,
"pixels": 589824
}
},
{
"id": 4693,
"url": "https://svs.gsfc.nasa.gov/4693/",
"page_type": "Visualization",
"title": "Precipitation Anomaly and Dengue Outbreaks in South East Asia: 2015-2016",
"description": "The 2015-2016 El Niño event brought changes to weather conditions across the globe that triggered regional disease outbreaks, including mosquito-borne dengue fever in Southeast Asia. This visualization with corresponding timeplot graph reveals the relationship between precipitation anomaly in Southeast Asia and dengue outbreaks. Drier than normal habitats drew mosquitoes into populated, urban areas containing the open water needed for laying eggs. As the air warmed, mosquitoes also grew hungrier and reached sexual maturity more quickly, resulting in an increase in mosquito bites. || SEAsia_PrecipDengueComposite_1920x1080_1211_print.jpg (1024x576) [75.8 KB] || SEAsia_PrecipDengueComposite_1920x1080_1211_searchweb.png (320x180) [52.9 KB] || SEAsia_PrecipDengueComposite_1920x1080_1211_thm.png (80x40) [5.4 KB] || SEAsia_PrecipDengueComposite_1920x1080_p30.webm (1920x1080) [6.4 MB] || SEAsia_PrecipDengue_Composite (1920x1080) [0 Item(s)] || SEAsia_PrecipDengueComposite_1920x1080_p30.mp4 (1920x1080) [14.8 MB] || SEAsia_PrecipDengueComposite_1920x1080_1211.tif (1920x1080) [1.5 MB] || SEAsia_PrecipDengueComposite (3840x2160) [0 Item(s)] || ",
"release_date": "2019-02-28T09:00:00-05:00",
"update_date": "2025-02-02T00:11:30.105895-05:00",
"main_image": {
"id": 397408,
"url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004693/SEAsia_PrecipDengueComposite_1920x1080_1211_print.jpg",
"filename": "SEAsia_PrecipDengueComposite_1920x1080_1211_print.jpg",
"media_type": "Image",
"alt_text": "The 2015-2016 El Niño event brought changes to weather conditions across the globe that triggered regional disease outbreaks, including mosquito-borne dengue fever in Southeast Asia. This visualization with corresponding timeplot graph reveals the relationship between precipitation anomaly in Southeast Asia and dengue outbreaks. Drier than normal habitats drew mosquitoes into populated, urban areas containing the open water needed for laying eggs. As the air warmed, mosquitoes also grew hungrier and reached sexual maturity more quickly, resulting in an increase in mosquito bites.",
"width": 1024,
"height": 576,
"pixels": 589824
}
},
{
"id": 4695,
"url": "https://svs.gsfc.nasa.gov/4695/",
"page_type": "Visualization",
"title": "Niño 3.4 Index and Sea Surface Temperature Anomaly Timeline: 1982-2017",
"description": "This visualization captures Sea Surface Temperature (SST) anomalies around the world from 1982 to 2017, along with a corresponding timeplot graph focusing on the Niño 3.4 SST Index region (5N-5S, 120W-170W), which represents average equatorial sea surface temperatures in the Pacific Ocean from about the International Date Line to the coast of South America. Highlighted in the timeline are the El Niño years, in which sea surface temperature anomalies peaked: 1982-1983, 1997-1998, and 2015-2016. || NINO3.4SST_FlatMapComposite_1920x1080_00932_print.jpg (1024x576) [104.9 KB] || NINO3.4SST_FlatMapComposite_1920x1080_00932_searchweb.png (320x180) [72.1 KB] || NINO3.4SST_FlatMapComposite_1920x1080_00932_thm.png (80x40) [6.8 KB] || SST_Nino3.4Index_1982_2017_Composite (1920x1080) [0 Item(s)] || NINO3.4SST_FlatMapComposite_1920x1080_p30.mp4 (1920x1080) [57.2 MB] || NINO3.4SST_FlatMapComposite_1920x1080_00932.tif (1920x1080) [1.4 MB] || NINO3.4SST_FlatMapComposite_1920x1080_p30.webm (1920x1080) [9.3 MB] || SSTNino3.4Index_1982_2017_Composite (3840x2160) [0 Item(s)] || ",
"release_date": "2019-02-28T09:00:00-05:00",
"update_date": "2025-02-02T22:39:44.671922-05:00",
"main_image": {
"id": 398258,
"url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004695/NINO3.4SST_FlatMapComposite_1920x1080_00932_print.jpg",
"filename": "NINO3.4SST_FlatMapComposite_1920x1080_00932_print.jpg",
"media_type": "Image",
"alt_text": "This visualization captures Sea Surface Temperature (SST) anomalies around the world from 1982 to 2017, along with a corresponding timeplot graph focusing on the Niño 3.4 SST Index region (5N-5S, 120W-170W), which represents average equatorial sea surface temperatures in the Pacific Ocean from about the International Date Line to the coast of South America. Highlighted in the timeline are the El Niño years, in which sea surface temperature anomalies peaked: 1982-1983, 1997-1998, and 2015-2016.",
"width": 1024,
"height": 576,
"pixels": 589824
}
},
{
"id": 4696,
"url": "https://svs.gsfc.nasa.gov/4696/",
"page_type": "Visualization",
"title": "Land Surface Temperature Anomaly and Dengue Outbreaks in South East Asia Region: 2015-2016",
"description": "The 2015-2016 El Niño event brought changes to weather conditions across the globe that triggered regional disease outbreaks, including mosquito-borne dengue fever in Southeast Asia. This visualization with corresponding timeplot graph reveals the relationship between land surface temperature anomaly in Southeast Asia and dengue outbreaks. Higher than normal land surface temperatures results in an increase of dengue reported locations. || SEAsia_LSTDiseases_1920x1080_1730_print.jpg (1024x576) [85.1 KB] || SEAsia_LSTDiseases_1920x1080_1730_searchweb.png (320x180) [54.4 KB] || SEAsia_LSTDiseases_1920x1080_1730_thm.png (80x40) [5.3 KB] || SEAsia_LSTDengue_Composite (1920x1080) [0 Item(s)] || SEAsia_LSTDiseases_1920x1080_p30.mp4 (1920x1080) [33.8 MB] || SEAsia_LSTDiseases_1920x1080_1730.tif (1920x1080) [1.7 MB] || SEAsia_LSTDiseases_1920x1080_p30.webm (1920x1080) [6.2 MB] || SEAsia_LSTDengue_Composite (3840x2160) [0 Item(s)] || ",
"release_date": "2019-02-28T09:00:00-05:00",
"update_date": "2025-02-02T00:11:33.263475-05:00",
"main_image": {
"id": 397244,
"url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004696/SEAsia_LSTDiseases_1920x1080_1730_print.jpg",
"filename": "SEAsia_LSTDiseases_1920x1080_1730_print.jpg",
"media_type": "Image",
"alt_text": "The 2015-2016 El Niño event brought changes to weather conditions across the globe that triggered regional disease outbreaks, including mosquito-borne dengue fever in Southeast Asia. This visualization with corresponding timeplot graph reveals the relationship between land surface temperature anomaly in Southeast Asia and dengue outbreaks. Higher than normal land surface temperatures results in an increase of dengue reported locations.",
"width": 1024,
"height": 576,
"pixels": 589824
}
},
{
"id": 4697,
"url": "https://svs.gsfc.nasa.gov/4697/",
"page_type": "Visualization",
"title": "ENSO teleconnections in South East Asia for the period of 2015-2016",
"description": "The 2015-2016 strong El Niño event brought changes to weather conditions across the globe that triggered regional infectious disease outbreaks, including mosquito-borne dengue fever in South East Asia. This visualization with corresponding multi-plot graph shows how Sea Surface Temperature anomalies in the equatorial Pacific Ocean (left), resulted in anomalous drought conditions (center) and increase in land surface temperatures (right) in South East Asia. During the 2015-2016 El Niño event, the South East Asia region received below than normal precipitation resulting in drier and warner than normal conditions, which increased the populations of mosquito vectors in urban areas, where there are open water storage containers providing ideal habitats for mosquito production. In addition, the higher than normal temperature on land shortens the maturation time of larvae to adult mosquitos and induces frequent blood feeding/biting of humans by mosquito vectors resulting in the amplification of dengue disease outbreaks over the South East Asia region. || SST_LST_Precip_2014_2016_Comp_print.jpg (1024x576) [82.9 KB] || SST_LST_Precip_2014_2016_Comp_searchweb.png (320x180) [51.5 KB] || SST_LST_Precip_2014_2016_Comp_thm.png (80x40) [6.0 KB] || SST_Precip_LST_Plot_Composite (1920x1080) [0 Item(s)] || SST_LST_Precip_2014_2016_Comp_1080p30.mp4 (1920x1080) [9.7 MB] || SST_LST_Precip_2014_2016_Comp.tif (1920x1080) [1.1 MB] || SST_LST_Precip_2014_2016_Comp_1080p30.webm (1920x1080) [4.2 MB] || TeleconnectionsSEAsia (3840x2160) [0 Item(s)] || SST_LST_Precip_2014_2016_Comp_1080p30.mp4.hwshow [203 bytes] || ",
"release_date": "2019-02-28T09:00:00-05:00",
"update_date": "2025-02-02T00:11:35.977656-05:00",
"main_image": {
"id": 398276,
"url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/SST_LST_Precip_2014_2016_Comp_print.jpg",
"filename": "SST_LST_Precip_2014_2016_Comp_print.jpg",
"media_type": "Image",
"alt_text": "The 2015-2016 strong El Niño event brought changes to weather conditions across the globe that triggered regional infectious disease outbreaks, including mosquito-borne dengue fever in South East Asia. This visualization with corresponding multi-plot graph shows how Sea Surface Temperature anomalies in the equatorial Pacific Ocean (left), resulted in anomalous drought conditions (center) and increase in land surface temperatures (right) in South East Asia. During the 2015-2016 El Niño event, the South East Asia region received below than normal precipitation resulting in drier and warner than normal conditions, which increased the populations of mosquito vectors in urban areas, where there are open water storage containers providing ideal habitats for mosquito production. In addition, the higher than normal temperature on land shortens the maturation time of larvae to adult mosquitos and induces frequent blood feeding/biting of humans by mosquito vectors resulting in the amplification of dengue disease outbreaks over the South East Asia region.",
"width": 1024,
"height": 576,
"pixels": 589824
}
}
],
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}