1 / 22

CE -DAT: The Complex Emergencies Database

CE -DAT: The Complex Emergencies Database. CE-DAT. A Database on Complex Emergencies Crisis Situations Armed conflicts Political Instability Post-Conflict Reconstruction / Transitions A Database on the Human Impact Public Health Epidemiology. Objectives.

edena
Download Presentation

CE -DAT: The Complex Emergencies Database

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. CE-DAT: The Complex Emergencies Database

  2. CE-DAT • A Database on Complex Emergencies • Crisis Situations • Armed conflicts • Political Instability • Post-Conflict Reconstruction / Transitions • A Database on the Human Impact • Public Health • Epidemiology

  3. Objectives • Support decision making on humanitarian aid • Quantitative data • Multi-sourced data • Available online • To promote effectiveness of prevention and response • Evidence-based trends • Impact briefings • Periodic reporting • Country Profiles

  4. CE-DAT Pilot Countries • Iraq • Afghanistan • Ethiopia • Sudan • Sierra Leone • Côte d’Ivoire • Angola • Democratic Republic of Congo

  5. What Data for CE-DAT? • Mortality Data • Crude Mortality Rate • Under-5, Maternal, Infant Mortality • Nutrition Data • Under-5 Acute Malnutrition • Chronic malnutrition, undernourished, oedema, MUAC, etc... • Morbidity Data • Battle or Mine/UXO injuries, measles, diarrhoeal diseases, meningitis, respiratory infections, etc...

  6. Building the Database • Identifying the fields • Geographical/locality data • Country, admin1, admin 2, city, camp name, given name, comments • Indicator data • Category, indicator name, value, scale, population type, start date, end date, comments • Sample information • Sample size, size of total population, population status, country of origin, locality of origin, comments • Methodology information • Sampling method, study unit, study type, study method, study context

  7. Building the Database... • Study information • Study done by, study start date, study end date, comments • Source information • Source ID, source name, article title, year, authors, URL, • Indicator based on other source, name, year • Comments

  8. Populating the Database • Data mining • Data extraction • Data entry • Data validation • Data archiving

  9. Data Mining • Identifying sources • Online • Peer-reviewed journals • UN Publications • NGO reports • Press releases • Collaborations • UN/International agencies • National governmental agencies • NGOs • Academics/Experts “bad data is better than no data”

  10. Data Extraction • Identifying variables in text • Highlighting in yellow - CE-DAT essential data • Highlighting in blue - comments • Other colours: • water & sanitation • Sexually Based Gender Violence • Political & social information • Any relevant information

  11. Data Entry • Enter Data through data entry sheet • Obligatory fields • Country name • Indicator category, name, value, scale, date • Source name, title, year • Optional fields • Sample information • Methodology information • Study information

  12. Data Validation & Archiving • Validation • Print source • Comparison of • Data entered • Data as included in source • Validate data entry • Archiving by • Country • ID Record • Supplementary/contextual data

  13. Difficulties • Entering the data - the “as is” approach • Geographical information • Duplication of data • Ensuring same source entered only once • Data across many sources • Adding and subtracting fields • Limiting the comments field • Cause of death data

  14. “as is” approach difficulties Global Acute Malnutrition Severe Malnutrition Global Chronic Malnutrition Severe Acute Malnutrition Global Malnutrition Severe Chronic Malnutrition Global underweight Severe Underweight Malnourished Severe Wasting moderate malnourished Severely Malnourished Moderate Wasting Stunting Oedema Undernourished Oedematous malnutrition Wasting Severe Acute Malnutrition

  15. Internal Errors Category Indicator value scale Mortality undernourished 407 /100,000 live-births Mortality Infant Mortality 94 % Importance of validation

  16. CE-DAT Database • Search indicators • Definitions • Baseline

  17. Searching indicators

  18. Looking Forward • Integration of CE-DAT Format with SMART Format • Use of GIS and Second Administrative Level Boundaries • Increasing the number of countries and data • Water & Sanitation • Vaccination coverage • Sexual and Gender Based Violence • Getting the data straight from the source • Use of optical readers for data entry

  19. Thank you...

More Related