Today's #hackebola piece is a guest post by Jessie Gunter - follower her @JessieGunter.
A particularly alarming characteristic of the Ebola epidemic is the high infection rates and deaths of healthcare workers. Many community health workers, nurses, doctors, and even hospital administrators have been infected since the outbreak began, sometimes even while taking diligent precautions against exposure to the bodily fluids of the patients whom they are treating (according to this report by the WHO, 401 healthcare workers have been infected since the beginning of the outbreak, and 232 have died).There have been several scenarios that have resulted in the infection of healthcare workers, according to the WHO:
To give you an idea of the number of healthcare worker (HCW) cases in Liberia, this plot shows the cumulative number of HCW cases by county. I included the top five hardest-hit counties:
When it comes to keeping track of Ebola, there are three categories of cases: confirmed, probable, and suspected. A case is confirmed when a biological sample tests positive for the virus. Probable cases have either been seen by a clinician, or have had close contact with a confirmed Ebola patient. Suspected cases have the signs and symptoms of Ebola, but have not been evaluated by a clinician nor had a sample tested.
Keeping accurate records of case counts is important to outbreak control. We need to know how many people are sick in order to plan for how many hospital beds, healthcare workers, PPE kits, etc. will be needed. Without a solid understanding of the disease burden, it's difficult to mount an effective response.
The symptoms of Ebola virus disease are fairly nonspecific, especially in the beginning: fever, headache, muscle aches, malaise. So suspected cases may not have Ebola after all, but may instead be suffering malaria, Lassa Fever, or some other viral illness. However, the World Health Organization cautions that "a substantial proportion of these suspected cases are most probably genuine cases of EVD.".
In order to keep those accurate records, samples from suspected and probable cases must be collected properly, and transported to the laboratories capable of doing the testing. The laboratories must then process the samples, record the results, and return those results to the relevant public health department. Each step is an opportunity for attrition. Sierra Leone and Liberia provide data on the number of cases in each category.
I really like this analysis by Daniel Hoffman comparing the growth rate of the outbreak in Sierra Leone with the fraction of the population that is poor at the county level. He found a significant positive trend - the poorer the county, the faster the spread of Ebola. Go read it.
I think it's somewhat intuitive that Ebola virus disease and poverty are linked. High population density (e.g. slums), poor sanitation, and a dearth of infection control resources in healthcare settings all contribute to transmission. My (naive) assumption though is that these conditions are fairly common in the Ebola-affected countries, so I'm surprised there's a discernible relationship in this outbreak.
The analysis leaves me with several questions. Is this finding robust across regions and cultures? Is there a certain threshold for poverty conducive to sustained transmission? What exactly about impoverished conditions augments risk? In the hospital setting intervention points are obvious (training and PPE), but in the community setting what are the primary drivers of transmission? How can we address those drivers?
Notice: we are hosting a Computing for Ebola Challenge hackathon the week of Oct 6. To learn more and register to participate, visit HackerLeague.
Contact tracing is a classic public health intervention. It's no easy task even during small outbreaks - people who had physical contact with someone with an infectious disease are called or visited every day by a public health worker. If they develop symptoms, they are isolated to prevent them from spreading the disease further. When a single case of MERS-CoV was imported into the United States, over 500 people were under followup.
With an outbreak as large as Ebola, the number of contacts requiring follow up is dramatic. Guinea, Sierra Leone and Liberia combined have accumulated well over 30,000 contacts, each of which needs to be followed daily for 21 days. Some of those have finished their follow up period, but many thousands have not. (Several counties in Liberia are still without vehicles for contact tracing, and I assume the situation is similar in SL and Guinea. But that's a conversation for another day.)
We now have Guinea data! However it is locked in PDF... in French...in irregular tables, so it is not yet digitized. Fear not, I can offer a preview from the most recent situation report, which was published on Sept 17 for data through Sept 16, 2014.
The very first sentence says, "The resistance continues in Forest Guinea with respect to awareness of health and administrative authorities on the Ebola virus Wamey in the Health District Nzerekore." This is not good. Not good at all. A group of health outreach workers were killed on Sept 19 in Nzerekore, two days after this report was published. Reports suggest that security in that region has been unstable for a while now. Changing human behavior is the keystone of infection control for Ebola, so resistance is a major hurdle to stopping transmission.
There appear to be two regions with active outbreaks (the red counties are 'foyers actifs', the green countries are 'foyers calmes'). A two-front war is not ideal, but I don't know too much about how Guinea is handling the outbreak so I'll leave it at that. The red southern counties border Sierra Leone and Liberia. Nzerekore, the location of resistance, is the red county in the southeast.
If you're just joining the #HackEbola series, check out the introduction, and see the other posts by clicking on the Ebola category. All this data is available at github.com/cmrivers/ebola.
Let's skip over to Sierra Leone for a bit. Although there are fewer cases in Sierra Leone, it's still suffering widespread transmission. Kailahun and Kenema counties in particular are hard hit, with 601 and 438 cases respectively, as of Sept 17. However, these counties are relatively populous. Comparing the number of cases in each county to population reveals that both counties are leading in both in relative and absolute terms.
Read about my motivation for this series here.
The number of Ebola cases is growing. Roughly exponentially, in fact. Cases in Liberia continue to grow exponentially (2,712 as of Sept 17). Sierra Leone is a bit slower, but not slow enough (1,603 cases). Guinea looked like it was getting under control until the last several weeks, when case counts have begun to climb again (861 cases).
The Ebola outbreak in West Africa was first recognized in March of 2014, but it likely crossed over from animals to humans in late 2013. In the intervening months, it has grown to an epidemic of unprecedented severity. It has infected more people than every other known Ebola outbreak combined - around 5,500 recognized cases, as of this writing. This species of Ebola has a case fatality risk of 70-90%, so the number of human lives already lost is truly astounding.
Despite the severity of the current situation, the months to come threaten to be even worth. Exponential growth continues unabated in Liberia in particular, which means that every sick person infects two other people on average. That may not sound like a lot, but tens and hundreds of thousands of cases in the forthcoming months is not out of the question. Sierra Leone and Guinea are experiencing less dramatic growth, but are producing a catastrophic number of cases nonetheless.
What looks like a slow trickle of cases in the beginning is simply the way exponential growth works - one to two to four cases isn't all that many. But when you get into hundreds or thousands of cases, the number of new cases produced is staggering. I've seen many media reports claim that the epidemic is accelerating, but that's not the case. It's simply following the trajectory it has been on all along.
What's significant about that point is that the current state (and the situation to come) were foreseeable and foreseen. Ignoring the outbreak for the first six months was folly, but continuing to ignore it is a "threat to global peace and security"
In an effort to help, I have been digitizing data on the Ebola outbreak in West Africa, which is released by the WHO, the Liberia Ministry of Health, and the Sierra Leone Ministry of Health in PDF format. The data are available for download on my github. I haven't seen any analyses of the county-level data online - the PDF format and the multi-dimensional aspect render it a little more inaccessible than a normal data set. Over the next several days and weeks, I will be analyzing these data and publishing my findings here on this blog. I hope that they are useful for helping people to understand the severity of the outbreak, and perhaps they will even be useful for public health planning and response.
You can follow along by searching the ebola category on my blog, adding me to your RSS feed, or monitoring #hackebola on Twitter. I also encourage you to download the data and develop analyses of your own - tag them with the hashtag, and add them to the analyses/ folder on my github too.
Update: If you are just joining us, know that the series has begun. Click the ebola category to see the installments.
I've been doing a lot of emerging infectious disease tracking in the last 18 months. In that time, I've developed a set of tools that make the very time-intensive pursuit go more quickly.
My most important tool is actually Twitter (I'm @cmyeaton), because most news breaks there first these days. I follow other epidemiologists, health organizations like WHO, science journalists, and public health professionals. That's also where I find a lot of the best news stories, blog posts, and information about the diseases I track. I use Vellum to quickly survey the links my Twitter friends are sharing, and usually spend at least half an hour every morning catching up on what's new.
I couldn't live without the Chrome extension Page Monitor, which I rely on to tell me when the WHO, CDC, or Ministry of Health websites are updated. When I learn new data are available, it's often in PDF form (which is a bummer); I use Tabula to extract that data more quickly and with fewer errors than if I did it by hand. I keep all my data on Google Docs so I can access it from any computer, and can share it with my collaborators. I also sometimes keep copies on Figshare or Github so that other people can download it.
When it's time to analyze, I use Python, and (rarely) R. I don't even remember how to code without pandas, so hopefully I'm never stuck on a desert island without it. I also use epipy, but that's probably just because I wrote it. Seaborn is my favorite package for prettifying my plots, although ggplot and mpltools are also nice. All my analyses are usually done in IPython Notebooks, which I share with my collaborators using Google Drive, github, or nbviewer. I recently learned that the notebooks also convert nicely into slides, which is very useful since a lot of presentations are updates of previous work*.
The notebooks capture my results well for preliminary sharing, but when it's time to write manuscripts I like Google Docs or Writelatex, depending on who I'm working with and how much math is involved (LaTeX is better for math). Then it's back to Twitter to share and discuss my results!
*Update: I have since decided that this is a lie. Notebooks convert nicely into slides if you are happy with the default output. Customizing is a huge pain.
I've had several people ask me how they can help to fight the Ebola outbreak in West Africa. I have no particular knowledge about the answer to this question, but I felt it was worth looking into. Here is a roundup of things I have found. Feel free to add any additional information or suggestion in the comments section.
Donate: this outbreak
Medecins Sans Frontiers (aka Doctors Without Borders) is an NGO that, as far as I can tell, one of the primary organizations involved in fighting this outbreak (and innumerable others). They also have an excellent score (92.34 of 100 overall, 89/100 for financial, 100/100 for transparency) on Charity Navigator. Donate using this site.
MAP International "is responding by providing infectious disease protection suits and supplies." They sent 5,600 protective suits as recently as Aug 6. MAP is a Christian-affiliated organization. They also have a great score on Charity Navigator. They have donation links all over their website.
Samaritan's Purse is an evangelical Christian organization that does medical missions (among other things) in the affected area. Instead of donating money, you can choose from a 'gift catalog' for things like emergency food. Their Charity Navigator score is also >95/100.
According to their website, Medical Teams International is mobilizing community health workers, providing infection control training, and supporting health workers. They appear to be operating primarily in Liberia. Their Charity Navigator score is lower than the others, but still decent at 85.
UNICEF is helping by donating supplies and organizing behavior interventions. Their Charity Navigator score is 94, and they are actively seeking donations to help fight the outbreak.
Donate: Other Emerging Infectious DIsease Efforts
ProMED-mail is a mailing list that reports infectious disease outbreaks to 60,000 subscribers daily. They are often the first ones to break news of an outbreak to the global public health community. I donate to ProMED fairly regularly. They are not listed on Charity Navigator. Donate using this link.
EcoHealth Alliance does a lot of great research at the human/animal interface, which is where a majority of emerging infectious diseases originate. A list of the research programs they run is available here, and their donation link is here. Their Charity Navigator score is 90.
Helping without donating
OpenStreetMap has an open-source response going. I'm not familiar with their response, so I can't really provide more details on this one.
Contact your local government and encourage them to devote resources to the outbreak. I poked around and wasn't able to find any specific legislation being considered.
I'm sure that can't be it, but I haven't found too many other crowdsourced Ebola projects. This surprises me, because past disasters (e.g. Hurricane Sandy), a lot of projects popped up. If you have any ideas or know of any projects, please email me or leave a comment.
"Send me your data - PDF is fine," said no one ever
The public health paradox ("When public health works, it's invisible")
Let's make data a civic right
Scholarly impact of open access journals
Six months later, disease detectives still battling fungal meningitis outbreak