![]() It is important to maintain a comprehensive system for influenza surveillance for the following reasons: Measure the impact influenza is having on illness, hospitalizations, and deaths.Detect changes in influenza viruses and.Determine what influenza viruses are circulating.Find out when and where influenza activity is occurring.Information in five categories is collected from nine data sources in order to: influenza surveillance system is a collaborative effort between CDC and its many partners in state, local, and territorial health departments, public health and clinical laboratories, vital statistics offices, healthcare providers, hospitals, clinics, emergency departments, and long-term care facilities. The data presented each week are preliminary and may change as more data are received. FluView, a weekly influenza surveillance report, and FluView Interactive, an online application which allows for more in-depth exploration of influenza surveillance data, are updated each week. The Influenza Division at CDC collects, compiles, and analyzes information on influenza activity year-round in the United States. Summary of the Geographic Spread of Influenza.Influenza-Associated Pediatric Mortality Surveillance System.National Center for Health Statistics (NCHS) Mortality Surveillance Data.HHS Protect Hospitalization Surveillance.Outpatient Influenza-like Illness Surveillance Network (ILINet) Surveillance for Novel Influenza A Viruses.World Health Organization (WHO) Collaborating Laboratories System and the National Respiratory and Enteric Virus Surveillance System (NREVSS) A quicklook (.png) is also provided for each map. Geographic coverage: global (1/4°x1/4°, cartesian grid),įormat: NetCDF-CF. Use: long-term variability, seasonal and climate studies.Ĭondition of access: please refer to the Licence Agreementĭata access service: these products are delivered through the authenticated FTP and the Opendapĭescription: gridded product in delayed time We obtain one data file and one map for each month.Ĭontents: multimission gridded sea surface heights computed with respect to a twenty-year mean profile, and including the seasonal variability (no annual cycle is removed). Climatological monthly are calculated by averaging the daily maps of delayed-time data over a same month from January 1993 up to the last extension of the Delayed-time products.We obtain one file and one map per season (JFM - AMJ - JAS- OND). Seasonal mean corresponds to the daily maps of delayed-time data averaging season by season.We obtain one file and one map per month since January 1993. Monthly averaged corresponds to the weekly maps of delayed-time data averaging month by month from January 1993.MADT-V (Absolute Dynamics Topography V, surface geostrophic northward sea water velocity).MADT-U (Absolute Dynamics Topography U, surface geostrophic eastward sea water velocity).MADT-H (Absolute Dynamics Topography H : sea surface height above geoid).MSLA-V (Sea Level Anomaly V, surface geostrophic northward sea water velocity assuming sea level for geoid).MSLA-U (Sea Level Anomaly U, surface geostrophic eastward sea water velocity assuming sea level for geoid).MSLA-H (Sea Level Anomaly H, sea surface height above sea level). ![]() (see product sheet for further information). Data are created from daily Ssalto/Duacs and CMEMS products. From January 1993 to the last extension of the Delayed-time products, the long delayed-time dataset allows to compute statistical means of seven variales over different periods of time. Types of dataset: Ssalto/Duacs multimission altimeter products. Monthly mean and Climatology Maps of Sea Level Anomalies Altimetry and Doris applications in videos.Shortcut to Mono and multi-mission processing.Information about mono and multi-mission processing.Cycle calendar (past and current missions).
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