Contagious Disease

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In many cases, only a handful of suppliers produce vaccines for a given disease.  In fact, for several vaccine types the U.S. has fewer suppliers than countries with a smaller market and a higher level of government purchase.

One reason for this finding could be strict government regulation.  All vaccines must be approved by the FDA.  Further, the CDC provides guidelines to physicians regarding who should get which vaccines.  The CDC also is a large purchaser of vaccines.  Thus, at first glance, it seems that government regulation may be causing industry consolidation in the vaccine market.

A paper by Danzon and Pereira, however, finds this not to be the case.  They find that the likelihood a supplier exits from a particular vaccine market is not effected by whether the CDC is a purchaser of the vaccine, the amount of vaccine the CDC purchases, or the CDC price at the time the firm exits.

The authors propose that the large economies of scale in vaccine production are the cause of the lack of competition in the vaccine market.

The vaccine industry is characterized by large fixed costs of initial vaccine development as well as substantial ‘semifixed’ costs of producing an individual batch (a process that may take 6 to 18 months) but low marginal costs of producing an additional dose, up to the batch limit, and low storability. If there are multiple competing suppliers with large sunk costs and low marginal costs, competition may drive the price low enough that it is relatively unattractive for multiple firms to remain in the market and for new firms to enter.

Further, the demand for vaccines is price sensitive.  Insurers (public and private) typically pay physicians and hospitals a fixed payment per vaccine administered.  Increases in vaccine costs come directly from the provider’s bottom line.

Some observers may point to the 2004-2005 influenza vaccine shortage and claim that government regulation had to cause this shortage.  The authors note that although several suppliers did exit the market before the shortage years, “…this cannot be blamed on government purchase and price controls, as less than 20 percent of the flu vaccine is publicly purchased.”

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I recently finished reading a great book by William Bynum called The History of Medicine: A Very Short Introduction. The book does just what it says: provides a great introduction to the history of medicine.  It is concise and interesting throughout.  The contents are divided into six chapters:

  • Medicine at the bedside
  • Medicine in the library
  • Medicine in the hospital
  • Medicine in the community
  • Medicine in the laboratory
  • Medicine in the modern world.

This chart explains the differences between the first five kinds of medicine.

There are many interesting nuggets of information from this book and picking out a few is difficult.  I’ll settle for two which discuss the unintended consequences of the invention of anesthesia and antibiotics:

Giving surgeons more time to operate made conserving tissues easier, but the longer exposure of the open wounds to the air also increased the possibility of post-operative infection.  Consequently, anaesthesia enlarged the range of operations surgeons could perform, but not necessarily the changes of a patient’s surviving the ordeal.

The causative agents of malaria, tuberculosis, and HIV have all developed resistance to many of their conventional treatments, complicating these major world diseases.  The hospital has not ’caused’ this phenomenon; human agency has.  But drug-resistant pathogens are now so common that modern hospitals sometimes lose their desired epithet, as ‘houses of healing,’ and revert to that old one, ‘gateways to death.’

Here is Amazon’s summary of the book:

Taking a thematic rather than strictly chronological approach, W.F. Bynum, explores the key turning points in the history of Western medicine-such as the first surgical procedures, the advent of hospitals, the introduction of anesthesia, X-Rays, vaccinations, and many other innovations, as well as the rise of experimental medicine. The book also explores Western medicine’s encounters with Chinese and Indian medicine, as well as nontraditional treatments such as homeopathy, chiropractic, and other alternative medicines.

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The Center for Disease Control issued the first official notice of the disease that would become known as AIDS 30 years ago on June 5.  My current home, San Francisco, was especially hard hit.  NPR interviews physicians at the San Francisco General Hospital and the Center of AIDS Research at University of California, San Francisco.

At the beginning, we knew all of the patients that we took care of in San Francisco and we knew all the patients in San Francisco with the disease. But then the numbers started to increase, increase, increase, even in those early years and then we didn’t know their names. And then I said, wow, this is big. I think, let’s say, 1991, San Francisco was just devastated. I mean, men were walking around in the Castro as skeletons suffering from the wasting syndrome.

I remember on a TV interview telling the woman interviewing me that my grandmother complained that all of her friends were demented or dying. And I said, yeah, grandma, so were mine and I’m, you know, quite a bit younger than you are. But it was exhausting but we fought on.

To help fight to cure AIDS, you can donate to UCSF’s AIDS Research Institute or the International AIDS Vaccine Initiative (IAVI).

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CNN reports that H1N1 is still a problem, particularly in the Southeastern U.S.  Traditionally, epidmiologists model the spread of a contagious disease based on two factors: the transmission rate between people and the frequency of contact between individuals.  A study by  Yoo, Kasajima and Bhattacharya (2010) incorporates a third factor that will affect the spread of a disease:

We modify this standard model to incorporate avoidance response—that is, the idea that the frequency of contact among individuals will itself depend on the prevalence of the disease in the population. Unlike the standard [susceptible-infected-recovered] SIR-model, in our model the attack rate changes over time as disease prevalence changes. We assume attack rate to be the product of three factors: a constant baseline attack rate that represents a “biological” transmission rate; a baseline contact frequency which differs among subgroups; and avoidance response parameters which are influenced by the prevalence rate of the disease.

The avoidance response parameters measure the degree to which individuals decide to forego contact with other people. I am curious how the advent of the internet has affected avoidance response.

The internet helps to disseminate information faster.  Thus more people will be aware of a contagious disease and can change their behavior to avoid others.  On the other hand, one potential downside is that people may become desensitized to pandemic information if one is able to access more information on pandemics worldwide.

On the positive side, the internet allows decreases the marginal cost of staying at home.  Office workers can work online from home with little problem; students may be able to “attend” classes through online meetings through Skype or other software.  You can shop, watch video, and of course read blogs to pass the time.

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Today, March 24th, is World Tuberculosis Day.  According to UN Secretary General Ban-Ki Moon, there were 9.4 million new TB cases in 2008 and 1.8 million deaths.  The CDC website has more information on what can be done to stop the spread of TB.

There is lots of coverage of the TB Day activities from around the world including news articles on: Ethiopia, GhanaLesothoPalestine, Pakistan, SingaporeSri LankaU.S.

The Financial Times believes that the private sector must play a role in order to defeat TB: “Governments and their international partners must recognise that health is an investment. The only successful exit strategy in the struggle against the TB, HIV and TB/HIV pandemics is to include them as part of broader development and poverty reduction strategies, and to strengthen health systems to respond more effectively to the needs of the most vulnerable populations. The private sector has a key role in making this happen,”"

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It is sometimes called the Great Swine Flu epidemic and sometimes the Great Spanish Flu epidemic, but in either case it was ferocious.  World War I killed twenty-one million people in four years; swine flu did the same in its first four months.  Almost 80 percent of American causalities in the First World War came not from enemy fire, but from flu.  In some units the mortality rate was as high as 80 percent.

This passage is from an interesting book I am currently reading called A Short History of Nearly Everything by Bill Bryson.  An (unfortunately) prescient passage in the book describes a certain flu virus we all became familiar with last summer:

From time to time certain strains of virus return.  A disagreeable Russian virus known as H1N1 caused severe outbreaks over wide areas in 1933, then again in the 1950s, and yet again in the 1970s.  Where it went in the meantime each time is uncertain.  One suggestion is that viruses hide out unnoticed in populations of wild animals before trying their hand at a new generation of humans.  No one can rule out the possibility that the Great Swine Flu epidemic might once again rear its head.

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As I predicted, the H1N1 influenza virus has returned to the U.S. this fall.  FluTracker gives a visual representation of the spread of the disease.  

In response to the spread of H1N1, President Obama declared the H1N1 outbreak a national emergency.  The declaration will  ”allow a hospital to set up a make-shift satellite facility for swine flu patients in a local armory or other suitably spacious location, or at another hospital, to segregate such cases for treatment.”  Without the waiver, “[u]nder federal law, if the patients are sent off site …the hospital could be refused reimbursement for care as a sanction.”

However, the national emergency declaration won’t help increase the speed of production for the H1N1 vaccine. The state of New York had previously declared that all health care workers must be vaccinated for against H1N1.  However, the state recently waved this mandate, not because of a change of opinion but because of vaccine shortages.  The FDA has approved an experimental intravenous use of peramivir against H1N1 in emergency cases.  The FDA approval states that “peramivir can be used when other drugs have failed or when delivery by a route other than intravenous is not expected to be feasible.” 

Should people with flu-like symptoms go to the doctor?  The answer is yes.  However, you may have H1N1 even if your test gives a negative result.  The rapid-test version will only give a positive test result for  11 out of every 100 people who actually have the H1N1 virus (at best).

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The Washington Post reports that most Americans are not very concerned about swine flu.  Should they be worried?  Maps from the New England Journal of Medicine and RhizaLabs detail that swine flu is still a problem.

The CDC reports that “from April 15, 2009 to July 24, 2009, states reported a total of 43,771 confirmed and probable cases of novel influenza A (H1N1) infection. Of these cases reported, 5,011 people were hospitalized and 302 people died.”  However, the CDC does not seem too concerned either.  The CDC has decided to discontinue confirmed and probable case counts on July 24, 2009 (aggregate national reports of hospitalizations and deaths will continue ).

So it is logical for Americans to not be concerned about H1N1?  I believe that public health officials still need to take H1N1 very seriously.  It is very likely that a second H1N1 outbreak will occur this fall and winter during flu season.  During the traditional flu season, H1N1 monitoring must increase.

For the average American, however, I believe there is little reason to worry.  This is not because they will not get H1N1, but instead because there are only a few steps they can take to prevent it.  The CDC recommends: avoiding sick people, washing your hands frequently and covering your face with a tissue when you sneeze.  The first two steps will help prevent you from getting H1N1, but both are logical and most people should already be doing these.  The third step will not help prevent you from getting H1N1, but will prevent the spread of the disease to others if you have it.

The Healthcare Economist’s advice to you is wash your hands, avoid sick people and–until flu season begins–worry about something else other than H1N1.

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Case and Paxson (2009):

We document the impact of the AIDS crisis on non-AIDS related health services in fourteen sub-Saharan African countries…Regions of countries that have light AIDS burdens have witnessed small or no declines in health care, using the measures noted above, while those regions currently shouldering the heaviest burdens have seen the largest erosion in treatment for pregnant women and children.

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Let us assume that our null hypothesis is that when someone is sick, it is not swine flu.  A type I error is a false positive.  That is, we claim that the person has the swine flu, when actually then do not.  A type II error is a false negative.  This means that the person has swine flu, but we erroneously conclude that they do not.

What is the probability that someone who has flu-like symptoms actually has swine flu?  We can calculate this using Bayes Rule:

  • P(H1N1|symptoms) = P(Symptoms|H1N1)*P(symptoms)/P(H1N1)

Let us assume that all individuals with swine flu have symptoms so that P(Symptoms|H1N1)=1.  Let us assume 2% of the population gets any type of flu each year and displays symptoms.  Let us assume only .02% of the population gets H1N1.  So, P(symptoms)=0.02 and P(H1N1)=.0002.  Thus we have:

  • P(H1N1|symptoms) = 1*0.02/0.002=.01. 

This means that if we see a random person with the flu like symptoms, there is only a 1% chance that they actually have the swine flu.  

This may explain why the CDC and WHO ignored early warnings from a Washington-based biosurveillance company concerning a possible flu outbreak.  Although there was an increase in the number of cases of influenza, the probability that it was an outbreak of H1N1 (or any type of outbreak) was low.  Although  probability of a false positive was high, the cost of a false negative is also large.  Ex-post, it is obvious that the CDC and WHO should have acted quicker to fight the spread H1N1.  Ex-ante, these organizations likely receive numerous reports of potential outbreaks and acting on every single one–most of which turn out to be false–would be very costly.  Identifying the optimal time to initial school closings and public health warnings is very difficult and must take into account both the probabilities and the costs of type I and type II errors.

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