Conceptualizing Bio-warfare

The popular image of Biological Warfare engages our attention through references to exotic illness that cause rapid death, and are extremely contagious. The Ebola or Marburg Hemorrhagic Virus is typical of those that are mentioned on CDC’s special pathogen branch lists. Descriptions of civilization-killing diseases in the popular media are similar: consider, for example, the book Oryx and Crake, the film 28 Days After, The Stand by Stephen King. Other books that I have read include The White Plague by Frank Herbert and Earth Abides by George R. Stewart, and they all have a similarly rapid plague that sweeps through and destabilizes/destroys civilization.

However that isn’t the way a really serious biological incident would likely unfold, because any fast moving disease would also admit the possibility of isolation/quarantine/travel restrictions which could stop its spread, and because it existence would be quickly identified. The really dangerous disease would be something that is very quickly spread, but which have a very long prodrome, that is the time between infection and the point at which the clinical features of the disease become apparent.

Such a disease could even arise naturally, and not be the result of bio-warfare. There are examples of diseases like this that are found in the wild, existing without any human intervention. Consider, for example, the Feline leukemia virus which can have a time to apparent lethality period of about a year, and the initial symptoms are not very alarming, just seem to be a bad cold. Equine Herpes virus, for example has initial respiratory tract symptoms, but then attacks the nervous system. There is no reason a similar disease might not exist, somewhere in the world that would be transmissible between humans. The prospect that there exist small well-funded groups who would like very much to engineer such a disease should be a cause for concern.  The reason why such a disease is much more of a threat now is that many, many more people are traveling now than ever in the past.  If such a disease had arisen in the past, it would have stayed in the area it had developed, and those populations exposed would have, over time, developed some degree of immunity.  Not so in the age of jet travel.

A way to get a more intuitive grasp of this is to travel over to this website: http://alife.co.uk/eosex

Now change the death rate from slow to rapid, and see how much less deadly the epidemics are, and how many more survive. Also, its interesting to model different topologies by drawing walls, etc. The most deadly epidemics are those that are highly infectious, but with a very slow disease process, as long as the disease process is under a certain fraction of the life span. Extra credit: what’s the proportion of the drop off? (italicized text added 8 December 2006)

However, as I had written over at Freedom to Tinker, one of the most important components of the defense against such a disease would be a syndromic surveillance system.

The systems that have been used to detect disease outbreaks to date primarily rely on the recognition and reporting of health statistics that fit recognized disease patterns. (See, e.g., the summary for the CDC’s Morbidity and Mortality weekly Report.) These disease surveillance systems works well enough for outbreaks of recognized and ‘reportable’ diseases which, by virtue of having a long clinically described history, have distinct and well-known symptoms and, in almost all cases, definitive tests exist for their diagnosis. But what if an emerging infectious disease or a bio-terrorist attack used an agent that did not fit a recognized pattern, and therefore there existed no well-defined set of symptoms, let alone a clinically meaningful test for identifying it?

If the initial symptoms are severe enough, as in the case of S.A.R.S., the disease will quickly come to light. (Although it is important to note that that did not happen in China, where the press was tightly controlled) If the initial symptoms are not severe, however, the recognition that an attack has even occurred may be delayed many months (or using certain types of agents, conceivably even years) after the event had occurred. To give Health Authorities the ability to see events that are outside the set of diseases that are required to be reported, the creation of a large database, which would collate information such as: workplace and school absenteeism, prescription and OTC (over the counter) medicine sales, symptoms reported at schools, numbers of doctor and Emergency Department visits, even weather patterns and veterinary conditions reported could serve a very useful function in identifying a disease outbreak, and bringing it to the attention of Public Health Authorities. Such a data monitoring system has been given the name ‘Syndromic Surveillance,’ to separate it from the traditional ‘Disease Surveillance’ programs.

You don’t need to invoke the specter of bioterrorism to make a strong case for the value of such a system. The example frequently cited is a 1993 outbreak in Milwaukee of cryptosporidium (an intestinal parasite) which eventually affected over 400,000 people. In that case, sales of anti-diarrhea medicines spiked some three weeks before officials became aware of the outbreak. If the sales of OTC medications had been monitored, perhaps officials could have been alerted to the outbreak earlier.

Note that this system, as currently proposed does not necessarily create or require records that can be tied to particular individuals, although certain data about each individual such as place of work and residence, occupation, recent travel are all of interest. The data would probably tie individual reports to census tract, or perhaps census block. So the concerns about individual privacy being violated seem to be less then in the case of the NSA data mining of telephone records, since the information is not tied to an individual and the type of information is very different from that harvested by the NSA program.

There are three interesting problems created by the database used by a Syndromic Surveillance system: (1) The problem of False Positives, (2) Issues relating to access to and control of the data base & (3) What to do if the Syndromic Surveillance system actually works.

First with regard to the false positives, even a very minor rate error rate can lead to many false alarms, and the consequences of a false alarm are much greater than in the case of the NSA data filtering program:

For instance, thousands of syndromic surveillance systems soon will be running simultaneously in cities and counties throughout the United States. Each might analyze data from 10 or more data series—symptom categories, separate hospitals, OTC sales, and so on. Imagine if every county in the United States had in place a single syndromic surveillance system with a 0.1 percent false-positive rate; that is, the alarm goes off inappropriately only once in a thousand days. Because there are about 3,000 counties in the United States, on average three counties a day would have a false-positive alarm. The costs of excessive false alarms are both monetary, in terms of resources needed to respond to phantom events, and operational, because too many false events desensitize responders to real events….

There are obviously many issues relating to public policy regarding to access and dissemination of information generated by such a public health database, but there are two particular items providing contradictory information which I’d like to present, and hear your reactions and thoughts:

Livingston, NJ -When news of former President Bill Clinton’s experience with chest pains and his impending cardiac bypass surgery hit the streets, hospital emergency departments and urgent care centers in the Northeast reportedly had an increase in cardiac patients. Referred to as “the Bill Clinton Effect,” the talked-about increase in cardiac patients seeking care has now been substantiated by Emergency Medical Associates’ (EMA) bio-surveillance system.

Reports of Clinton’s health woes were first reported on September 3rd, with newspaper accounts appearing nationally in September 4th editions. On September 6th, EMA’s bio-surveillance noted an 11% increase in emergency department visits with patients complaining of chest pain (over the historical average for that date), followed by a 76% increase in chest pain visits on September 7th, and a 53% increase in chest pain visits on September 8th.

The second story has to do with my own personal experience and observation of the Public Health authorities’ actions in Warsaw immediately following the Chernobyl accident. In Warsaw, the authorities had prepared for the event, and children were immediately given iodine to prevent the uptake of radioactive iodine. This has been widely credited with preventing many deaths due to cancer. In Warsaw, the Public Health Authorities also very promptly informed the public about the level of ambient radiation. Certainly, there was great concern among the populace but panic was largely averted. My empirical evidence is of course limited, but my gut feeling is that much dislocation was averted by (1) the obvious signs of organized preparation for such an event, and (2) the transparency with which data concerning public health were disseminated.

Links:
article summarizing ‘Syndromic Surveillance’
CDC article
epi-x, CDC’s epidemic monitoring program

NOTE: This post contains substantial portions of my guest post from Freedom to Tinker.

Conceptualizing Bio-warfare

One thought on “Conceptualizing Bio-warfare

  1. I’m intrigued by your comparisons between Syndromic Surveillance and SIGINT collection (NSA activities). Just to scratch the surface here…

    It makes sense that SS is more susceptible to false positives than SIGINT. The latter is a highly evolved discipline that has developed over the years a number of methods to screen out false positives. For example consider a hypothetical attempt by terrorists to trigger a false positive at NSA, perhaps to determine if they are actually under surveillance. There is no way to do this effectively since it will always necessarily lack some of the elements that occur in a real terrorist plot (I’d rather not go into further detail on this point).

    As well, obviously, NSA has funding commensurate with its role, whereas SS does not yet (just wait until after the next pandemic…). The diference in personnel and material resources is enormous (NSA has the largest concentration of math PhDs on earth) and the results reflect that situation.

    So then, the question of how to refine SS. We might take a few lessons from SIGINT in this regard. Obviously we need sufficient breadth and depth of coverage, which is easy to say and hard to do. We need accurate information going in: for example, we need an increase in early-stage diagnostic testing to rule out less alarming diagnoses, and this in turn requires an increase in the sensitivity and specificity of diagnostic testing, as well as greater funding for public health clinics and diagnostic labs. We need the public to buy in at the level of being willing to go get tested for every little thing that might be a cold or might be a big deal. The latter point would be more likely in the event of a nationial single-payer health coverage system that does not impose paperwork burden on patients and health care providers. We need the math talent to develop algorithms that will have the kind of sensitivity and specificity to detect emerging diseases amidst the mass of data, and filter out routine minor illness.

    But in the end, even with all that, any disease that has a long contagious prodromal period is going to turn into a pandemic. AIDS is the archetypal case. And frankly I don’t know that in such cases, there is anything that could be done.

    Last but not least, if you want to get real real scared, think about the new extreme drug-resistant varieties of tuberculosis, with their easy casual transmissibility and their high fatality rates.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s