Tag Archives: epidemiology

Infectious Disease

More On Flu

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There is a nice video piece at the New York Times website done by science reporter Donald G. McNeil Jr.  In it, he makes a number of important points that I have been trying to emphasize in my latest posts on the topic. McNeil is to be congratulated.  This is the kind of reporting we need now and in the coming months on swine flu.

The New Scientist also has an editorial (which I just found because I'm behind on my RSS reader) which notes the distinct possibility that H1N1 could come back with a vengeance this Fall.  Note that most of the deaths in the pandemic of 1918 occurred in September of 1918 even though the first cases were reported in March of 1918.  The pandemic of 1918 (which was really the pandemic of 1918-1920) killed 50 million people, perhaps as many as 100 million.  The world population in 1920 was 1.86 billion, which means there were around 1.78 billion or so in 1918.  The case fatality ratio for the 1918 flu was >2.5%, and perhaps as high as 5%, which means that 25-50 people died out of 1000 infected with the flu.  All in all, this means that anywhere from 0.5% to 2% of the world's population died during the pandemic of 1918 (though if 100,000,000 people really died, then the overall world mortality rate was actually over 5%!).  The following figure (from Taubenberger and Morens 2006) shows the time series of deaths from flu for 1918-1919.  

Taubenberger and Morens (2006), Figure 1.

The most striking feature of this figure is the pronounced spike in mortality in the Fall of 1918.  We are currently a month before this time series starts in our current potential pandemic. Note that the death rate in June of 1918 was not too dissimilar from the mortality rate estimated from Mexican outbreak data by Fraser et al. (2009).

The New Scientist also reports that a flu vaccine incorporating the new A(H1N1) is unlikely to be available by the Fall of next year.  This is, of course, distressing news.  So, what can we do?

It seems to me that the best plan is to follow D.G. Margaret Chan's call for international solidarity.  She has rightly noted that the people likely to be hardest hit by the an H1N1 pandemic (or any other infectious disease for that matter) are the citizens of the world's poor countries.  They are the ones who bear 85% of the infectious disease burden, after all.  So, why should we in the developed north care about this other half (homage to Yogi Berra intended)?

For the time-being the strain of A(H1N1) is relatively benign (just as it was in 1918 at this point), but influenza has an incredible capacity to mutate, recombine with other co-circulating flu strains, and respond to selection (the part that you don't typically hear about in news reports). Let us not forget that there is currently another highly pathogenic strain of flu out there. Highly pathogenic Influenza A(H5N1) -- remember bird flu? -- has an overall mortality rate of approximately 60%. Yes, that's an order of magnitude greater than the high-ball estimate for the 1918 flu.  Of course, this variant of influenza has only infected a total of 424 people in the world since 2003.  141 of those have been in Indonesia (where 115 have died for a case fataility ratio of 81.5%).  We have gotten very lucky so far with H5N1 because it is not efficiently transmitted from person-to-person.  The emergent H1N1, however, is.  It's basic reproduction ratio is substantially greater than that of seasonal flu, which indicates it is very efficiently transmitted. God help us if a recombinant strain with the pathogenicity of bird flu and the transmissibility of swine flu were to evolve.

This suggests to me that a little bit of financial and technical assistance from the north to the countries of the south might be a very good investment at this point. Let's help developing countries entering their flu season control swine flu to the absolute best degree we can manage. Minimizing the number of cases also minimizes the evolutionary potential of the virus -- fewer infections, fewer opportunities for mutation and subsequent selection. I realize that we are in the throes of a major economic crisis, the likes of which we haven't seen since 1929.  But, do you have any idea what losing 5% of the world's population would do to the economy?

Infectious Disease

Keep Washing Your Hands

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As the potential pandemic fades into the obscurity of a couple weeks' worth of the 24-hour news cycle, cases continue to mount.  New York City reported its first swine-flu death, an assistant principal in a NYC public school. As with most of the other deaths so far, this particular victim had medical complications that contributed to his especially severe illness.  This is typical for influenza and other serious respiratory illnesses like SARS.  One of the greatest risk factors for dying of SARS during the outbreak of 2003 was being a diabetic (Chan et al. 2003).   Flu is dangerous.  As noted by Thomas R. Frieden, New York City's health commissioner and Obama appointee to head CDC, “We should not forget that the flu that comes every year kills about 1,000 New Yorkers.”  As I noted in a previous post, analysis of the outbreak data from Mexico suggests that the current influenza A(H1N1) has a case fatality ratio a little bit higher than the usual seasonal flu, so we should expect it to kill more people, though not dramatically more.

The number of cases continues to rise in Japan, another northern hemisphere country with high-functioning public health infrastructure, despite how late in the season it is. The Japanese government has closed over a thousand schools around the western cities of Kobe and Osaka in an attempt to curtail transmission.  So far, there does not appear to be sustained community transmission, but again, it is remarkable that there is any  transmission to speak of this late in the flu season.  One other troubling part of this particular outbreak is that the school cluster around Kobe and Osaka is not associated with overseas travel as clusters in the United States and Europe have been.

WHO Director General Margaret Chan announced at the recent meeting of the World Health Assembly that the apparent quiescence of flu activity now -- even as WHO has kept its pandemic alert at level 5 -- could still be “just the calm before the storm.”  She urged countries to work together to continue to control the current outbreak of A(H1N1), noting that those most vulnerable remain the poorest of the world's citizens. As quoted in the NY TImes, “I strongly urge the international community to use this grace period wisely. I strongly urge you to look closely at anything and everything we can do, collectively, to protect developing countries from, once again, bearing the brunt of a global contagion.”

Just to highlight the fact that, despite the media silence, the swine flu outbreak continues to grow globally, I will post an updated plot of the WHO case counts for today.

Yes, cases continue to rise.  Let's continue to take reasonable personal precautions, help with the battle against flu in countries of the southern hemisphere, and prepare for the next flu season here.  It never hurt anyone to wash their hands a couple more times a day.

Infectious Disease

Pssst, Swine Flu is Still Here

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The coming Aporkalypse appears to have faded into last week's obscurity. With WHO raising the pandemic alert from 3 to 5 in the span of about 24 hours, it seemed that Oinkmageddon was upon us.  But now it's hard to find a news piece on swine flu, let alone an inflammatory one. This is something that worries me and lots of other public health professionals. Not so much the lack of inflammatory new pieces. More, I worry that people are going to see this incident of just another case of health officials needlessly pushing the panic button.  There is always the possibility that the public health measures enacted to control extensive spread of Influenza A(H1N1) may have actually worked! The epidemic fizzling when the alert goes to level 5 is really the best possible case, right? Alas, I doubt that it's really the case.  As I noted before, it seems unlikely that we will have extensive sustained transmission in the northern hemisphere at this late date. But case counts continue to grow globally and the austral flu season starts in the not-too-distant future.  

WHO publishes case counts each day, and I have plotted them from 30 April through 13 May.  These are the worldwide confirmed cases as of this morning.

WHO worldwide confirmed A(H1N1) cases as of 14 May 2009We can see that the case count does, in fact, increase each day and shows no sign of slowing down. This is true, incidentally, whether one plots the cumulative number of the incident number -- clearly this plot is more dramatic, but the incidence does not show any obvious sign of decline. Of course, there is an inherent lag in the reporting of confirmed cases, so it is at least possible that the number of cases has peaked.  But I doubt it.  Recent analysis by an international team of epidemiologists suggests that the reproduction number (the average number of secondary cases produced by a single primary case in a completely susceptible population) is substantially greater than that of seasonal flu.  The reproduction number tells us how fast and how far an infectious disease will spread and how many people will ultimately be infected and higher values of the reproduction number mean faster, further and more. This team also found that the estimated case fatality ratio is less than that of the 1918 pandemic strain but comparable to the 1957 pandemic strain.  So, given proper environmental conditions for transmission, this variant of the flu looks like it could spread rapidly, widely, and cause a decent amount of mortality.  It seems entirely possible that this is exactly what will happen in the southern hemisphere in the coming months, after which it will come back and hit here in the north.

As I noted before, I can hope is that people have not become inured to warnings of epidemics because of our recent experience with H5N1 bird flu and this new H1N1 swine flu (there is also the last swine flu scare of 1976).  Some saner press coverage would help. Of course, it would mean less grist for the mills of John Stewart and Stephen Colbert, but it might mean a public better prepared for a potentially real public health emergency that we still may face.

Infectious Disease

On Swine Flu

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A lot has happened in the last week.  I was frantically preparing for a big talk that I had to give at the end of the week when the news about swine flu started heating up.  As of the most recent posting from the Pan-American Health Organization, there are 1118 confirmed cases and 27 deaths in 18 countries worldwide. The United States has had 279 laboratory-confirmed cases and one death.  As I write, it sounds like the epidemiological situation is much better than it could have been.

But last Monday things were looking like they were going to get very serious. While I should have been preparing for my talk, I spent the day working out the details for an internet-based survey on people's knowledge, attitudes, and behavior regarding the emerging H1N1 (a.k.a. "swine") flu. Marcel Salathé and I realized that we had an historic opportunity to field a survey and learn something about people's responses as the public health emergency unfolded.  Our survey has been online since the morning of Wednesday, April 29th (and is available here for anyone interested in taking it -- it's only 16 questions long and takes less than five minutes to complete) and we have gotten well over 5,000 responses so far. Vijoy Abraham at the Institute for Research in the Social Sciences was amazingly helpful in helping us get the survey online in a hurry, and IRiSS very kindly hosted the survey.

Marcel posted a nice blog piece on the survey and it was later picked up by Carl Zimmer on his blog, and then the big-time: we got written about on boing boing.  This idea clearly resonates with people.  Stanford put out a press release and now Marcel and I have done a number of interviews for various local and international media outlets (links forthcoming).  All this before we've even done any analysis!

We will keep the survey online as long as it is relevant, though we will begin doing some exploratory data analysis shortly. The thing about flu is that, even though it seems like it is fizzling out already, it could actually kick around for months. I was speaking with a prominent disease ecologist this past week who predicted that this particular outbreak would fizzle in the northern hemisphere for the time-being. You see, by May, we are pretty well past flu season in the north.  For whatever reason, flu shows marked seasonality in transmission.  Jeff Shaman at Oregon State has shown pretty convincingly that this seasonality is a matter of absolute humidity, which is lowest in the winter in temperate regions and is presumably more conducive for influenza transmission and virus survival. The disease ecologist who made the prediction for northern-hemisphere fizzle also suggested that the southern hemisphere might be in for a hard flu season during the austral winter.  Extensive and sustained transmission could be bad news for those of us who feel like we've dodged a bullet here in the north because when flu season rolls back around here, we might get slammed on the rebound.  A very interesting paper by Cécile Viboud and colleagues shows that it was the second influenza season that had the higher mortality rates during the last influenza pandemic of 1968.  The moderator on ProMED-mail wrote "Even if the present A/H1N1 has pandemic potential it is therefore highly likely that the outbreak will fade out within the next 2 to 3 weeks, but it will reappear in the autumn."  Time to get cracking on getting this H1N1 strain incorporated into the next flu vaccine, I'd say.

This means that we will probably need to keep our survey up for a while to come.  It will be interesting -- and hopefully informative -- to see how people's anxieties and knowledge about swine flu wax and wane as this system evolves. 

That's all for now though I suspect this won't be the last post I write about swine flu. Oh, and the talk turned out fine; thanks for asking...

Infectious Disease

New SARS on Trans-Siberian Railway?

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Scary.  A woman traveling from Blagoveshchensk to Moscow by rail died, apparently of pneumonia, and all the people riding in her carriage (about 60) have to taken to a hospital for observation and quarantine.  Officials think this could be a case of SARS.  From the RIA Novosti Report:

The train was stopped in the central Russian city of Kirov and around 60 train passengers were sent to a local hospital. 6 of them are reported as running fevers, the source said, although Kirov Region officials have said that none of them were suffering from SARS. The carriage in which the woman was travelling was disconnected from the rest of the train. The train then continued on its way to Moscow. Russia's [public health] watchdog spokesman was unable to confirm that the woman had died from SARS. "Doctors are currently establishing a preliminary diagnosis," he said.

This is definitely something to keep our collective eye on.  Full report, and any new developments can be found on ProMED.

Infectious Disease, R, Social Network Analysis

Platform for Developing Mathematical Models of Infectious Disease

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Every once in a while someone asks me for advice on the platform to use for developing models of infectious disease.  I typically make the same recommendations -- unless the person asking has something very specific in mind. This happened again today and I figured I would turn it into a blog post.

The answer depends largely on (1) what types of models you want to run, (2) how comfortable you are with programming, and (3) what local resources (or lack thereof) you might have to help you when you inevitably get stuck.  If you are not comfortable with programming and you want to stick to fairly basic compartmental models, then something like Stella or Berkeley Madonna would work just fine.  There are a few books that provide guidance on developing models in these systems.  I have a book by Hannon and Ruth that is ten years old now but, if memory serves me correctly, was a pretty good introduction both to STELLA and to ecological modeling. They have a slightly newer book as well.  Models created in both systems appear in the primary scientific literature, which is always a good sign for the (scientific) utility of a piece of software.  These graphical systems lack a great deal of flexibility and I personally find them cumbersome to use, but they match the cognitive style of many people quite nicely, I think, and probably serve as an excellent introduction to mathematical modeling.

Moving on to more powerful, general-purpose numerical software...

Based on my unscientific convenience sample, I'd say that most mathematical epidemiologists use Maple.  Maple is extremely powerful software for doing symbolic calculations.  I've tried Maple a few times but for whatever reason, it never clicked for me.  Because I am mostly self-taught, the big obstacle for me using Maple has always been the lack of resources either print or internet for doing ecological/epidemiological models in this system. Evolutionary anthropologist Alan Rogers does have some excellent notes for doing population biology in Maple.

Mathematica has lots of advantages but, for the beginner, I think these are heavily outweighed by the start-ups costs (in terms of learning curve). I use Mathematica some and even took one of their courses (which was excellent if a little pricey), but I do think that Mathematica handles dynamic models in a rather clunky way. Linear algebra is worse.  I would like Mathematica more if the notebook interface didn't seem so much like Microsoft Word.  Other platforms (see below) either allow Emacs key bindings or can even be run through Emacs (this is not a great selling point for everyone, I realize, but given the likely audience for Mathematica, I have always been surprised by the interface). The real power of Mathematica comes from symbolic computation and some of the very neat and eclectic programming tools that are part of the Mathematica system. I suspect I will use Mathematica more as time goes on.

Matlab, for those comfortable with a degree of procedural-style programming, is probably the easiest platform to use to get into modeling. Again, based on my unscientific convenience sample, my sense is that most quantitative population biologists and demographers use Matlab. There are some excellent resources.  For infectious disease modeling in particular, Keeling and Rohani have a relatively new book that contains extensive Matlab code. In population biology, books by Caswell and Morris and Doak, both contain extensive Matlab code.  Matlab's routines for linear algebra and solving systems of differential equations are highly optimized so code is typically pretty fast and these calculations are relatively simple to perform.  There is a option in the preferences that allows you to set Emacs key bindings.  In fact, there is code that allows you to run Matlab from Emacs as a minor mode.  Matlab is notably bad at dealing with actual data.  For instance, you can't mix and match data types in a data frame (spreadsheet-like structure) very easily and forget about labeling columns of a data frame or rows and columns of a matrix. While its matrix capabilities are unrivaled, there is surprisingly little development of network models, a real growth area in infectious disease modeling. It would be really nice to have some capabilities in Matlab to import and export various network formats, thereby leveraging Matlab's terrific implementation of sparse matrix methods.

Perhaps not surprisingly, the best general tool, I think, is R.  This is where the best network tools can be found (outside of pure Java). R packages for dealing with social networks include the statnet suite (sna, network, ergm), igraph, graph, blockmodeling, RGBL, etc. (the list goes on).  It handles compartmental models in a manner similar to Matlab using the deSolve package, though I think Matlab is generally a little easier for this.  One of the great things about R is that it makes it very easy to incorporate C or Fortran code. Keeling and Rohani's book also contains C++ and Fortran code for running their models (and such code is generally often available).  R and Matlab are about equally easy/difficult (depending on how you see it) to learn.  Matlab is somewhat better with numerically solving systems of differential equations and R is much better at dealing with data and modeling networks.  R can be run through Emacs using ESS (Emacs Speaks Statistics).  This gives you all the text-editing benefits of a state-of-the-art text editor plus an effectively unlimited buffer size.  It can be very frustrating indeed to lose your early commands in a Matlab session only to realize that you forgot to turn on the diary function. No such worries when your run R through Emacs using ESS.

One of the greatest benefits of R is its massive online (and, increasingly, print publishing) help community. I think that this is how R really trumps all the other platforms to be the obvious choice for the autodidacts out there.

I moved from doing nearly all my work in Matlab to doing most work in R, with some in Mathematica and a little still in Matlab.  These are all amazingly powerful tools.  Ultimately, it's really a matter of taste and the availability of help resources that push people to use one particular tool as much as anything else.  This whole discussion has been predicated on the notion that one wants to use numerical software.  There are, of course, compelling reasons to use totally general programming tools like C, Java, or Python, but this route is definitely not for everyone, even among those who are interested in developing mathematical models.

Conservation, Demography, Evolution, Infectious Disease, Primates

Always a Bridesmaid, Never a Bride

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Well, it's happened again.  My work has been written up in Science but I am not mentioned.  I'm actually not that concerned this time -- we're going to submit the paper for publication soon. I've been telling myself (and other people) that this thing we've ben working on (all the while being very cryptic about what this thing exactly is) is important.  Every once in a while, I wonder if I've just been fooling myself.  The fact that this work has been written up in Science the day after the paper was presented at the Montreal Conference on Retroviruses and Opportunistic Infections suggests to me that it is, indeed, important.