The filovirus tree has been shooting wildly

While there are not a lot of new branches, there are many, many new leaves on this growing tree. That is overwhelmingly due to the fantastic work of Dr Pardis Sabeti, and Stephen Gire at the Sabeti lab, Harvard University, and their many collaborators. 

It sounds like even more sequences will be coming out in the future. This group is the face of the molecular epidemiology of history's largest Ebola virus disease epidemic in Sierra Leone. If a team of scientists could be said to embody an aspect of an epidemic, it has been these guys and their virus characterization. Hugely impressive stuff.

I only wish we could see more Guinean and Liberian sequences - they are both hugely under-represented in this tree of complete genomes downloaded from GenBank a week or so ago.

Click on tree to enlarge even further.
Coloured boxes surround those sequences generated during the
2014 EVD epidemic. Orange boxes point out the nearest neighbours
and the year from which the sample that was sequenced, originated.
The West African Ebola virus Makona variant has been
traced back to sharing an ancestor in common with a 2007
variant in 2004.

References

1. Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak. Gire SK, Goba A, Andersen KG, Sealfon RS, Park DJ, Kanneh L, Jalloh S, Momoh M, Fullah M, Dudas G, Wohl S, Moses LM, Yozwiak NL, Winnicki S, Matranga CB, Malboeuf CM, Qu J, Gladden AD, Schaffner SF, Yang X, Jiang PP, Nekoui M, Colubri A, Coomber MR, Fonnie M, Moigboi A, Gbakie M, Kamara FK, Tucker V, Konuwa E, Saffa S, Sellu J, Jalloh AA, Kovoma A, Koninga J, Mustapha I, Kargbo K, Foday M, Yillah M, Kanneh F, Robert W, Massally JL, Chapman SB, Bochicchio J, Murphy C, Nusbaum C, Young S, Birren BW, Grant DS, Scheiffelin JS, Lander ES, Happi C, Gevao SM, Gnirke A, Rambaut A, Garry RF, Khan SH, Sabeti PC.
   Science. 2014 Sep 12;345(6202):1369-72. doi: 10.1126/science.1259657. Epub 2014 Aug 28.

Are fewer Ebola virus disease cases being confirmed than previously?

A very quick graph plotting the proportion (percentage, %) of laboratory-confirmed Ebola virus disease (EVD) cases reported by the WHO over time. That is, the of samples taken from clinically suspected EVD cases that are RT-PCR positive for Ebola virus in a given report, divided by the total number of suspected + probable + confirmed cases in that report.

Taken from my static
EVD tallies and graphs
page here. Updated
28JAN2015 AEST.Click on graph to enlarge. 

Looking at the graph below, it seems like a lower proportion of total cases are being confirmed now compared to before the total case load began decreasing (especially from December onwards-see adjacent graphic). 

Presumably this is due to the larger number of other infectious diseases in the region that cause signs and symptoms, especially early signs and symptoms, that cannot be easily clinically differentiated from EVD; more suspect cases that don't test positive for EVD than before.

When considered in the context of the now smaller number of EVD cases overall, the non-EVD infection's background "noise" has become louder.

But the bottom line is that EVD cases are steadily declining thanks to the many efforts of many people and the changes to habits, traditions and practices that increased risky contact.

The proportion (%) of EVD detection that are laboratory confirmed at each World Health Organization Situation Report or Situation Summary. Anomalous values have been removed. Click on graph to enlarge.

Societal change and H7N9..

The importance of societal change for controlling infectious disease outbreaks really cannot be over-stated. 

For Ebola virus disease, it came down to stopping the tradition of direct contact with the body of those who have died and dircet contact in general. For MERS it

seems that occasional camel contact triggers insertion of the MERS-CoV virus into hospitals where lax infection prevention and control practices add to the case load. 

For influenza A(H7N9) virus cases, it is the habit of obtaining live poultry from retail markets where rare virus-laden chooks are culled and handed over because of a desire to see, choose and purchase the tastiest fresh chicken. 

There is a common thread among these stories about direct contact or inefficiently droplet-transmitting virus infections: we can stop their spread. 

But we also amplify and prolong their spread. 

However, when it comes to human-adapted, efficient droplet-spread or airborne-transmitted viruses - well, then we're in trouble. Of course we could all just lock ourselves in a room for a few weeks but that won't ever happen.

So its very important to head off these "emerging" viruses while we still have a modicum of control over them. Once they get away from that control, and theoretically that could happen in the blink of an eye-right now even-no amount of fancy infra red cameras, poorly donned surgical masks or fancy hospitals laden with machines that blink and go ping, will stop them from spreading globally.

Cheery.

In the meantime - here's hoping China speeds up the closure of those live poultry markets. Habits can be changed but death is forever.

Click on image to enlarge.

Some changes to my Ebola virus disease (EVD) graphs...

To perhaps provide clearer info and to accommodate the changes in the epidemic, namely the reduction in cases and the focus on ridding Guinea, Liberia and Sierra Leone from any and all cases of EVD, I've made some tweaks to my Tableau data visualizations (or dashboards). Briefly...

The dots take their leave.

Was this.

Gone are the dots in my cumulative chart, to be replaced by a third "area under the curve" style graph. 

This brings out the importance of the confirmed cases-more on why that matters later. This week Cedric Moro @Moro_Cedric) asked why we seem to have a relatively large number of suspect and probable cases released in each report World Health Organization situation report (WHO SitRep) or summary (SitSumm). I imagine this is due to the turnaround time once the sample arrives, occasions when results may need to be repeated to confirm strange results, time between seeing a patient and sampling them for Ebola virus testing...but there are probably more obvious reasons. Chime in.

Is now this.

Plot the right data for now.

I'm not an epidemiologist - yes, I know you epidemiologists out there already know that. But I like to play with numbers and pretty colours. So this week I got some information that I didn't have before - the reason why use of cumulative curves was frowned upon by the excellent numbers communicator, Prof Hans Rosling (@HansRosling). 

I had read previously that Prof Rosling was no fan of cumulative curves in graphically explaining progress in ridding west Africa of EVD. But I like them - I've even explained, in my epidemiologically unprofessional opinion - how a flat plateau on a cumulative curve clearly shows the stalling of an outbreak or epidemic. Turns out I either didn't read all of that quote, or the text I read didn't contain the key fact. 

It's not really that cumulative curves are at fault, it's what they are plotting that can mislead. The important thing to plot, especially now that cases are fewer and laboratory capacity is in place, are the confirmed cases, not the total cases which include suspected+probable+confirmed cases.

Confirmed cases are Ebola virus, unconfirmed cases may never be.

In the last WHO SitRep (14-Jan-15) it was noted..

All 54 EVD-affected districts (those that have ever reported a probable or confirmed case) have access to laboratory support within 24 hours of sample collection.

"Access" doesn't mean a result will appear 24 hours after sampling though. But even with this shorter access period, suspected and probable cases are in fact still making up a decent proportion of the total cases reported in even the most recent reports. For example...

• In Guinea the numbers between 14-Jan-2015 and 15-Jan-2015 saw suspected cases rise by 3, probables stayed the same and confirmed cases lifted by 8; 27% of the total cases reported between this pair of reports were not confirmed to be Ebola virus infections, at the time of reporting. 
• In Liberia over this period, suspected cases rose by 29, probables by 2 and confirmed case numbers did not change-so none of the 31 cases were laboratory confirmed as an Ebola virus infection. 
• In Sierra Leone over this period, suspected cases rose by 10, probables remained the same and confirmed cases lifted by 16; 38% of the total cases were not confirmed to be Ebola virus infections.

If we compare those figures to 2 SitReps from well before the WHO had declared the 24 hour laboratory support, dated 24-Sept-2014 and 26-Sept-2014, we find that Guinea only had 8% of its tally unable to be confirmed, Sierra Leone was at 12% not confirmed while 87% of EVD-like cases added to Liberia's tally between reports were not confirmed as due to and Ebola virus infection. 

This may not be a fair comparison of course and it's not one that accounts for every report - just the 2 pairs of reports I arbitrarily chose as being from 'now' and 'back then'. Nonetheless, I expected there to be a bigger and more obvious difference in the proportion of cases that were now being quickly confirmed-I thought that percentage would have gone up as the unconfirmed cases were less frequent. Instead, it seems that the proportion is not that much better. Perhaps this is an indication of the other diseases which mimic EVD early on, that normally emerge at this time of year or have emerged because of the state of healthcare in the countries blasted by the EVD epidemic. As I said above, it may also just be the time it takes to observe, collect a good history and make a clinical decision before a sample is collected. It may also be that laboratory turnaround times (including testing, verifying and reporting) take a bit longer than we naively expect from reading that quote from the WHO above.

More visualizations of confirmed case numbers.

So for the reasons above, I've added the changes I've mentioned and I've also duplicated some of the "total case" graphs by creating versions that only include confirmed cases. 

In the example below I'm showing that it looked like Liberia was experiencing an uptick in cases for 2 consecutive reporting weeks (blue bar graph, right column). I tweeted about this during the week. In fact, those rises were due to unconfirmed cases. The confirmed case plots (green titles in the right-hand column of graphs) show the consistent decline in new EVD cases we had been hearing about. 

Live and learn.

Graphs plotting total EVD cases (including suspected, probable and laboratory confirmed;
brown title bars, left-hand column) versus graphs plotting only the laboratory confirmed cases
(green title bars, right-hand column). 
Data are from WHO SitReps and SitSumms
Click on image to enlarge.

MERS-CoV snapdate on canaries...

MERS-CoV detections among healthcare workers (HCWs)

HCWs are akin to the canary in the coal mine - when HCWs get sick with a particular bug, this can signal that the bug may well be more active in the the wider community. 

This graph looks at the canaries and suggest that there has been a relatively long period in which they have been getting infected.

Healthcare workers positive for MERS-CoV over time.
Some reported or hypothesized clusters and outbreaks are flagged.
Click on image to enlarge.

A quick look at my database shows that most of the MERS-CoV-positive HCWs reported since October have been from Riyadh in Ar Riyadh region and Taif in Makkah region. 

Just before that, in early September, there were 2 HCWs from Jubail in the Ash Sharqiyah (eastern) region. 

If we look at the new time-based occurrence heatmap I have on my MERS-CoV static page here, the recent group of HCWs come from the areas with most cases. No big surprise there. Perhaps more surprising is why these HCWs are, presumably, still acquiring there infection in hospital settings given eh attention that infection prevention and control practices had, especially (before?) during and after the Jeddah outbreak last year.

A recent paper from Profs Drosten and Memish speaks to this topic of infection control and hospital spread of MERS-CoV a little.[1] 

It reports finding a 40-year old female (40F) nurse who, despite MERS-CoV being such a wimpy transmitter between humans, became infected after attending an infected patient. 40F did not perform any aerosol-generating procedures  but also wore only a surgical mask and gloves - it reads as though she was not fully protected against droplet, and certainly not against airborne, exposure. 

The 40F HCW then went on to shed virus for a 42-day period as determined by MERS-CoV specific RT-PCR. She was not ill during this time. Hard to contain much?

So with all that in mind, it's no longer hard to imagine how spread of MERS-CoV virus occurs within, around and between hospital settings. Also helps to explain how some of the new cases might seem strange - if not testing for subclinical or asymptomatic cases as a routine. I recall that in Saudi Arabia routine testing of milder cases is not occurring, but I cannot find a source for that recollection just now so I stand to be corrected (please send if you know if a reference that alludes to that).

A couple of quick questions spring to mind:

1. Just how widespread is this lengthy shedding period?
2. What does this say about how mild a virus MERS-CoV is when comorbidities are not a factor?
3. What role do genetics play in the host's containment and clearance of MERS-CoV infection?

Heatmap of MERS-CoV detection by date and region
within the Kingdom of Saudi Arabia
Click on image to enlarge.

Reference..

1. A Case of Long-term Excretion and Subclinical Infection With Middle East Respiratory Syndrome Coronavirus in a Healthcare Worker. Manal Al-Gethamy, Victor M. Corman, Raheela Hussain, Jaffar A. Al-Tawfiq, Christian Drosten and Ziad A. Memish.
   http://cid.oxfordjournals.org/content/early/2015/01/01/cid.ciu1135.long

MERS-CoV snapdate...

MERS-CoV detections by month and year

As can be seen from the graph below, the peaks of MERS-CoV detection have been driven by humans and their infection prevention and control issues - but what maintains the virus in between those lapses? 

It seems clear that MERS-CoV is entrenched among camels in the Middle East and Africa but how is it getting to humans, and how is it dong that in such small numbers over such a wide area? These have been questions for 148 weeks. 

It's a good thing this infection transmits so poorly between humans.

Click on image to enlarge.

Case->outbreak->epidemic->publication->learn a lesson...repeat

The global cumulative curve of suspect+probable+confirmed
cases EVD cases (orange) , suspect+probable+confirmed
EVD deaths (red) and the confirmed cases (yellow dots)
Updated from last WHO data posted 10JAN2015 AEST.
Click on image to enlarge.

When looking at the PubMed database search results for 'ebola', one can have no doubt that something big must have happened lately to drive such a massive number of science doers and writers to their keyboards. 

And of course something did - the world's largest, most widespread, multinational and longest running epidemic of Ebola virus disease (EVD) which roared through Guinea, Sierra Leone and Liberia. At the end of 2014 there were 20,000 cases and 8,000 fatalities - and those were just the cases we have seen added to official lists and made public.

A tally downloaded from the PubMed search engine
based on numbers returned using the search term 'ebola'.
Click on graph to enlarge.

The adjacent image shows what the US National Library of Medicine's search engine generates when one searches for 'ebola'. The search engine, called PubMed because it makes the MEDLINE database public (MEDLINE being the Medical Literature Analysis and Retrieval System Online, or MEDLARS Online), lists many of the world's life science and biomedical publications that meet the PubMed standards; currently >24,000,000 citations. In 2014, a lot was written about EVD.

While a lot of the 'ebola' publications in 2014 were commentaries and a lot of reviews that mostly presented the same information, these were necessary to feed many different groups of readers and specialities hungering for background on EVD and the ebolaviruses and how these related to them and their roles, patients and lives. 

I had cause to scan the literature on a daily basis for a few weeks and was particularly impressed with the New England Journal of Medicine's clinical papers and the BMJ's summaries and updates. Of course Science/Sciencexpress and Nature had some beautifully informative articles as well - delving into the humanity behind the numbers and seeking answers to questions we were all asking. I thought PLOS Current Outbreaks (although I'll never enjoy reading that layout), Lancet, Lancet Infectious Diseases and Morbidity and Mortality Weekly Report also stood out in 2014. 

Some of these articles came out very quickly and many were available without the need to breach a paywall. But some of the research...I can't help but wonder how many lives could have been saved if studies detailing and reinforcing the apparent benefits to survival from the aggressive use of intravenous fluids and electrolytes could have come out sooner-through whatever venue. What if we'd talked about, researched or actually published better personal protective gear designs earlier? Imagine if the world had registered that Ebola virus seemed to be in the region years ago, when research papers suggested it. Would any of this knowledge have saved more lives? Who knows? Would the focus on what needed to be delivered to West Africa have changed because of earlier dissemination of need? Would more point of care chemistry instruments have been prioritised? Would the urgency about the need for more healthcare workers have been stepped up if more specific examples of why they were needed were out there for our leaders to be briefed on? Probably unanswerable questions.

Why can't humans ever seem to learn enough to prevent the event sneaking up and whacking us senseless? Why is it always after the event that the light dawns and processes are created for 'next time'?

There will be many more publications to come in 2015, spinning out of this epidemic and the events yet to unravel. Hopefully they will create enough memory for the world to be better prepared for next time. Prepared for a little...uooh - goober fish...

H7N9 outbreak #3 underway?

What better way to start 2015 than a snapdate!! For those who are new to them here on VDU, they were initiated here and defined here as snap updates - posts that don't have lots of detail and chat...although they almost always end up having lots of chat!

Figure 1. H7N9 cases by week of onset (or hospitalisation
or reporting dates of the preferred onset date was
not made public).
Click on image to enlarge.

This one is an update of the situation of one of the many avian influenza viruses ("bird flus" if you must) around again - avian influenza A(H7N9) virus, or just 'H7N9'.

In Figure 1, I've taken the huge liberty of adding in the start and end dates of the 3 outbreaks of H7N9 to date; and in doing so, I've said that China is in the early stages of one right now. I may well be wrong of course - this is a blog and these are my opinions - but it looks that way to me. 

Figure 2. China's northern laboratory network influenza
surveillance data up to Week 51 of 2014. [1].
Click on image to enlarge.

The case numbers for H7N9 in Figure 1 have been above zero for a little while and in particular November looked like a busy month (see weekly and monthly tallies here). Keep in mind that there is also a reporting lag - the time between date of onset (obtained from more detailed World Health Organization data) and the date the case was publicly reported (I rely on FluTrackers line list for these details). That delay can be a month or more on occasion; up to 38-days in late December. I suspect this is because China reports cases to the WHO in batches, something instigated toward the end of the 1st and 2nd outbreaks. So I suspect we will see more cases assigned to December, during reports that come out in January.

But it look like 'tis the season for influenza in humans in China (see figure 2 and the Chinese National Influenza Centre [2]) - and as some of us have discussed on Twitter, this is most probably due to the changes in weather (environmental conditions) which result in sustained viral survival on cough and sneeze-contaminated surfaces and in wet and dry propelled droplets and droplet nuclei; in both man and bird (see Hong Kong avian influenza detection report dates [3]). 

That sustained survival may well be all it takes for more of us to pick up an infectious viral dose.

Once the seasonal influenza viruses get a foothold in us, they spread well, causing disease in those who are susceptible and probably a bunch of unnoticed infections in those with previous exposure to that strain plus a healthy immune memory of that intrusion. By "seasonal influenza virus, I mean those that replicate in and circulate efficiently among humans, as opposed to the relatively inefficient avian subtypes.

So stay tuned to H7N9; it's not yet very good at spreading between humans but its established in birds and has been spilling over into humans since at least the beginning of 2013. We know how influenza can deal us a rough hand if the stars and its genetic segments align favourably (for it). Oh, and the continued reliance on fresh chicken obtained from and killed at live poultry markets. The majority of cases have very clearly had contact with poultry as defined by the WHO. 

References...

1. http://www.cnic.org.cn/eng/show.php?contentid=738
2. http://www.cnic.org.cn/eng/surveillance.php
3. http://www.chp.gov.hk/files/pdf/global_statistics_avian_influenza_e.pdf

Influenza A (H5N6) virus in humans...

Provinces hosting human cases of H5N6
Adapted from [8]
Click on image to enlarge.

After late December's announcement of a human infection with another avian influenza subtype, H5N6. The tally of human infections by this subtype of FluA stands at 2 - that are reported anyway.

The ever vigilant @FluTrackers (and their line lists, news posts and commentary) and the always alert @Fla_Medic (and his Avian Flu Diary blog) have these cases well covered.

I just wanted to make a summary here for my own reference in making some slides for a talk next month.

1. ~23-April-2014. [1,4,5] 49-year old male (49M) from Nanchong City, Sichuan Province.
   Acute severe pneumonia, died 5-May-2014
   Exposed to dead poultry
2. 3-December 2014. [2] 58M from Guangzhou City in Guangdong province.
   Critical condition in hospital since 9-Dec-2014
   Exposed to live poultry but not ill contacts [3]

There have also been plenty of lethal animal infections by this and other highly pathogenic avian influenza (HPAI; referring specifically to the bird's outcome) subtypes and strains [7], including:

From an OIE Report 21-Oct-2014. [6]

1. 12,000 quails in Quang Nai Province, Vietnam in 18-Dec-2014
   http://en.vietnamplus.vn/Home/Quang-Ngai-destroys-12000-AH5N6-infected-quails/201412/59394.vnplus
2. 1,338 birds on a farm in Nanbu, Nanchoing City, Sichuan Province, China
   http://www.oie.int/wahis_2/public%5C..%5Ctemp%5Creports/en_fup_0000015698_20140731_162951.pdf
3. 20,550 (17,790 fatal) birds on a farm in Shuangcheng District, Heilongjiang Province, China, 23-Aug-2014
   http://www.oie.int/wahis_2/public%5C..%5Ctemp%5Creports/en_fup_0000016060_20141024_193420.pdf
4. Birds in Muang Nan and Muang Xayabouly Districts, Luang Prabang and Xayabouly Provinces, Laos in 12:14-Mar-2014
   http://wwwnc.cdc.gov/eid/article/21/3/14-1488_article#r4

No sign of anything like sustained human-to-human transmission of this viral subtype to date. But another for the influenza virus Rubik's cube.

References..

1. https://flutrackers.com/forum/forum/china-h5n1-h5n8-h5n6-h5n3-h5n2-h10n8-outbreak-tracking/164419-china-man-49-with-acute-severe-pneumonia-died-from-h5n6-nanchong-city-nanbu-county-sichuan-province?t=222782
2. http://www.who.int/csr/don/28-december-2014-avian-influenza/en/
3. http://news.xinhuanet.com/english/china/2014-12/23/c_133874590.htm
4. http://afludiary.blogspot.com.au/2014/05/sichuan-china-1st-known-human-infection.html
5. http://www.promedmail.org/direct.php?id=2451125
6. http://www.oie.int/wahis_2/public%5C..%5Ctemp%5Creports/en_fup_0000016060_20141024_193420.pdf
7. UPDATE ON HIGHLY PATHOGENIC AVIAN INFLUENZA IN ANIMALS (TYPE H5 and H7) from the Office International des Epizooties (OIE), otherwise known as the World Organisation for Animal Health
   http://www.oie.int/animal-health-in-the-world/update-on-avian-influenza/2014/
8. http://en.wikipedia.org/wiki/File:China_administrative_claimed_included.svg#filelinks

Bats in a tree...

Meliandou and the burnt tree that
once housed a bat colony (from Fig 3, [1]).

While not snakes on a plane, I'm fairly sure the level of swearing has at times been at least as bad among those suffering from and dealing with the possible fall-out from these bats - if in fact they were the source for the biggest Ebola virus disease (EVD) epidemic on record.

A recent animal counting, trapping and testing study in Guinea included sampling in and around the village of Meliandou.[1] This village is, to the best of our knowledge, the site of the first animal-to-human, or zoonotic, transmission of the Ebola virus variant called Makona.[2]

The study team, made up of researchers affiliated with Germany, Sweden, Core d'Ivoire and Canada, did not find any decline in numbers of usually susceptible larger mammals around the index village; a sign during other outbreaks, of active local ebolavirus "activity". The team also found that primate hunting was not a big thing in this region, which is rather devoid of these and other Ebola virus mammalian host animals (including few of the Duiker, or forest antelope). Fruit bat hunting was common though.

The team captured 169 bats representing at least 13 different species and 6 families. But in the house of the 2-year old boy considered the epidemic's index case, fruits bats were not eaten and no bat hunters resided there. No Ebola virus RNA was detected in any bats and antibody screening results from bat blood were inconclusive. 

These findings led the authors to study Meliandou, resulting in an hypothesis that a nearby hollow tree that once housed a large colony of free-tailed bats [locally described as lolibelo - small and smelly bats - otherwise known to belong to the species of insectivorous bat, Mops condylurus of the family Molossidea; [3], may have been the source of  infection. Why only one child was infected this way when the tree was a site of frequent play by many children is not known. The tree was burned out in March 2014 which caused many bat deaths, some of which were collected for consumption. Sequencing of a PCR-amplified mitochondrial DNA segment found that in 5 of 11 ash and soil samples from around the tree, contained traces of Mops condylurus genetic material. So that species was at least there.

So, this is all quite far from a conclusive link between the 2-year old boy and these bats. But it does read as though every avenue has been tested in this village, perhaps apart from better animal antibody testing (serology), and some serology on the blood of those villagers who remain alive in Meliandou. 

Serology testing is going to be very important for answering many questions around EVD and this outbreak and epidemic. 

Of course this will raise the usual question of whether we cull all bats to prevent this from ever happening again. Don't be ignorant! Bats have very important roles in pollinating and thus in keeping our ecosystem going. Should we kill all bees because they sting us? I'm pretty sure I've been stung by a bee more times than I've had Ebola/Hendra/SARS/Nipah/MERS/Lyssavirus or any other bat-hosted virus infection. Killing off everything to prevent a very rare zoonotic event when better knowledge can resolve the problem is just a typically short-sighted and knee-jerk human reaction (not a fan-can you guess?).

One question that does still remain, and one that is of extreme interest to me, is how often mild disease results from an Ebola virus infection? Good, robust serology methods to the rescue.


References...

1. Investigating the zoonotic origin of the West African Ebola epidemic. EMBO Molecular Medicine(2014). http://embomolmed.embopress.org/content/embomm/early/2014/12/29/emmm.201404792.full.pdf
2. Nomenclature- and Database-Compatible Names for the Two Ebola Virus Variants that Emerged in Guinea and the Democratic Republic of the Congo in 2014. Viruses 2014, 6(11), 4760-4799.
   http://www.mdpi.com/1999-4915/6/11/4760
3. Mops condylurus via the IUCN Red List of threatened species (listed as of least concern)
   http://www.iucnredlist.org/details/full/13838/0