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Case number changes between Ebola virus disease reports...

This is one of my favourite charts for following the Ebola virus disease outbreak in West Africa because it shows how things are changing from report to report. 

It plots the total number of suspected, probable and laboratory-confirmed cases between reports - which is a measure of change over time that is not cumulative.

That's not to say that understanding this chart is easy for everyone...as with everything, what you take away from it may be heavily influenced by your own perspective and your background in reading graphs. I have written something about how to read some of the graphs on my blog here, which may be helpful too.

Uses World Health Organization data up to and including the Situation Report from the 5th-Sept, 2014.
Click on chart to enlarge.
I've marked up the last three periods between reports to highlight that the time changes differently. You can see this for yourself if you look carefully at the horizontal or "x" axis (the one that has the dates) and look at where each dot lines up with its date. Some are further apart than others. 

You can also mouse over the dots on the interactive version of the graph here. That will tell you the dates. THe subtraction is up to you though!

The lines joining the dots here suggest what is happening between the WHO Reports, but the line do not actually use any real collected values...because we don't have them to plot. 

Technically, a bar graph would be more accurate, but I find a line graph easier to read at a glance. So do remember - we don't know what is happening between those dots. We're just presuming it.

Editor's Note #20: Tweepidemiology...

Updated 05JUL2015
Followers of my @MackayIM Twitter account (and this blog which gets promoted through it) since I started tweeting. It shows the cumulative rise and rise of followers and the relationship of the rate of those rises to very active periods of infectious disease outbreaks and epidemics over the past 18-months or so.
Click on the graph to enlarge

While it's hard to separate whether I pick up followers because of the delivery of specific content or because as you pick up followers, they help spread the word and you pick up more followers, to simple old me this cumulative graph looks like MERS-CoV and the West African Ebola virus disease outbreaks drove people to seek information. Sometimes those people have done me the honour of following me on Twitter, accompanying me on my own journey to understand what's going on. I'm constantly amazed at that, let me assure you.

I thought it worth having a look at the Tweepidemiology of my Twitter account. That is, the epidemiology of my Twitter followers - a bit of a long bow - but you follow me because I talk about infectious disease outbreaks and stuff and because I like my new word...I'm keeping with it!

I paid Twitter Counter to get my Twitter data, plotted it in Excel, tidied it using Illustrator and here it is. 

I started Tweeting a little after I started blogging - this Twitter thing is for the young people and their constant need to take selfies and update the world on their lives...live and learn. 

Despite VDU blog posts on the emergence of influenza A(H7N9) virus in China dating back further in time, I came to Twitter well after H7N9's Wave 1 was engaged. So the slow burn could have been due to that or just because no-one knew me or that I could generally be trusted and generally don't spout drivel. 

Generally.

So there ya go - Tweepidemiology - a way of looking at when and perhaps why one gains followers through social media when it's used to engage the public and try and help people understand what's happening with new or emerging viruses and diseases . Perhaps I should check what happens when I post photos of my cat too.

Updates...

  1. Corrected some typos and grammatical errors


Ebola: Blood, sweat and tears...

This post follows up the recent one on convalescent semen being able to harbour infectious Ebola virus (EBOV; although I am not aware of any infection resulting from this route of transmission there has been at least one report for Marburg virus [4]).

I thought I'd give the same treatment to tears and sweat which are also fluids intermittently listed as possible sources of EBOV infection for humans. Some examples of the scientific literature which support the risk messaging, follow.

Blood...

I think we are all pretty clear that the blood of an advanced case of Ebola virus disease (EVD) is heavily laden with virus and is the most serious of the risk factors for acquiring infection by an ebolavirus.

Viral loads (amount of virus in the sample) in blood can be above 106-108 plaque forming units or copies (pfu; a measure of infectious virus present using a lab test that measure the impact of virus on infected cells; copies measure viral genome and cannot prove infectious virus is present) per millilitre of blood in acute phase disease patients and non-human primates.[5,6]

Sweat...

There is not a lot on sweat containing signs of an ebolavirus.
  • Bausch and colleagues found no trace of EBOV in a single acute sweat sample.[1]
  • Jaax and colleagues found that in experimentally infected non-human primates (NHPs; rhesus macaques), that connective tissues next to hair follicles and sweat glands in the skin as well as the cells lining ducts of glands in the skin were sometimes positive for EBOV antigens (proteins).[2]
  • Davis and colleagues infected NHPs (African green monkeys) and found signs of EBOV antigens in the cells lining the sweat gland ducts and in cells in the connective tissues next to hair follicles, but no virus particles by electron microscopy.[3]
  • Zaki and colleagues found heavy signs of EBOV antigens (proteins) in the tissues around the sweat glands, but rarely also within sweat glands and ducts.[8] No virus particles were seen in the sweat glands or ducts when examined by electron microscopy.
Tears...

There is also very little I have found on this one.

  • Bausch and colleagues found EBOV RNA in tears from 1 sample, but no infectious virus could be isolated.[1]
  • Jaax and colleagues found some signs of virus in macrophages in the ciliary body of the eye of experimentally infected NHPs
Spit...
  • Bausch and colleagues found infectious EBOV in 1 of 12 acute saliva samples (from 10 patients; none from 4 convalescent samples) and EBOV RNA in 8 of 12 (67%) of acute samples (none from convalescent samples).[1] RT-PCR positivity was significantly associated with fatal outcome.
  • Formenty and colleagues found EBOV antigens and EBOV RNA in oral fluids from fatal cases and those who survived infection.[7]
References...
  1. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2395567/pdf/bullwho00439-0113.pdf
  2. http://www.ncbi.nlm.nih.gov/pubmed/8712894
  3. http://www.ncbi.nlm.nih.gov/pubmed/9278608
  4. http://link.springer.com/article/10.1007/BF01734141
  5. http://www.sciencemag.org/content/suppl/2014/08/27/science.1259657.DC1/Gire.SM.pdf
  6. http://www.nature.com/nature/journal/vnfv/ncurrent/pdf/nature13777.pdf
  7. http://www.ncbi.nlm.nih.gov/pubmed/16652308
  8. http://www.ncbi.nlm.nih.gov/pubmed/9988163


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