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ebolaexpedition  
- What kind of preconceptions do we have regarding ebola stories/narratives?
- How does the media provide information about ebola?
- What can we learn from the datasets we already have?
- Can we find more references from our datasources? Microdata?
- Do we have expertise/skills/technical language to describe what we're looking for?
- Should we use only verified/official data?
- Do crowdsources report ebola cases earlier than official ones?
- WHO response map x Cases map http://www.who.int/csr/disease/ebola/maps/en/

    

    * http://www.healthmap.org/ebola/#timeline
    *  https://wiki.openstreetmap.org/wiki/2014_West_Africa_Ebola_Response
    
    * Center for Disease Control: What is "contact tracing"? "Even one missed contact can keep the outbreak growing.":  http://www.cdc.gov/vhf/ebola/outbreaks/what-is-contact-tracing.html 
    * http://www.cbc.ca/news/ebola-and-contact-tracing-1.2725577
    
    
    
    - Natalia Mazotte: ncortezrj@gmail.com
    zara.rahman@okfn.org 
    
    
    
    Notes for blog post 
    
                                   
Two sources found – CDC and WHO

Linking ebola outbreak to human development index of the countries and mortality rates -  

political question: break down of political systems vs treatment, capacity of country governments to react to it

Cases under 100 people – how was it contained it so easily?  

For some cases it was 80% fatality, when numbers went up, it's still high – still an awful way to die but definitely not a sure 'death sentence'  

Eg. what's different about this political moment in international situation – why sensationalised coverage now?  

Before – rural areas, now increased number of people travelling? It's now in cities...  

MSF said it was out of control for the first time – what does this mean? Didn't know exactly which areas were contaminated – fear of the unknown.  

Group 2:  

Thought about questions – integrity of 'contact' tracing method – what kinds of preconceptions do we have on different data sources, crowd sourced data, media coverage. 'established' sources of data which might flow a bit more slowly...  

What can we learn from data that does exist? What can we glean from the limitations of the data, where are the gaps? Simply: we don't have enough. What can we know, based on existing data sources, what is slipping through the cracks?  

Scout work : we had some data sources, interesting maps – http://pad.okfn.org/p/ebolaexpedition

Information about contact tracing methodology: CDC puts guidance on it, but even from Nigeria – scientists saying that the contact tracing method was being applied very inconsistently. Where people get the disease, stay home, die without ever contacting the health system.  

Risks of stigma: underreporting. If we were to report on data available

How much information presented as a map in a PDF – wow.  

Incredibly messy data – eg. CDC, sometimes start to end, or months, years, asterisks, numbers of cases with an asterisk there – needs lots of time to clean.  

Nobody worried about providing not just machine readable data, but clean data – presented for a human reader, not a machine.  
Lots of data presented super simplified, so don't know what is getting lost.  
Nigeria - * to say – we don't have good or consistent tools for this,  

Trying to absorb yourself in the topic – before you can really start making any conclusions, is clear. Good research practice, looking at what can be triangulated and what can't.  

Different interpretations of open data – transparency on research methods, judgements on quality, what you would want is to have every step documented, with syntax that took you from step A to step B – choose at what level you want to dive in.