Operational Biosurveillance

The Use of Forecasting to Rapidly Identify Non-Routine Infectious Disease Signatures: Part 2

Our team has been doing a full review of outpatient / inpatient / transfer stats from our department's perspective for Jan-Mar 2012, which was a time period where we saw an epidemic of human metapneumovirus (hMPV) that overlapped an unusually severe season of RSV. We have issued several reports of our experience here in this blog.  In Part 2, we explore further the "so what" of operational infectious disease forecasting coupled to early warning. 

On the 25th of every month the Ascel Bio Black Canyon Infectious Disease Forecasting Station released forecasts for infectious disease activity specific to our county.  RSV and other respiratory pathogens were therefore expected to appear and cause a given level of strain to our medical infrastructure. 

From Jan 4th to Feb 10th, we admitted a low number of patients exhibiting typical RSV infection, where we followed American Academy of Pediatrics (AAP) guidelines for the management of RSV: no antibiotics, steriods, with the rare use of inhalers.  In the midst of these admissions, the Station issued an advisory for unusual human metapneumovirus activity which at the time was primarily disruptive to the outpatient component of our medical infrastructure.

Then, from Feb 12-16th, multiple back to back admissions presented as typical RSV infections but abruptly decompensated on the floor, precipitating transfers for all of them to the Front Range by fixed wing aircraft.  In the midst of this, we were told the Front Range's PICU grid capacity was close to diversion status.  It was during this time we had report from the PICU that received our patients they were coinfected with Haemophilus influenzae.  One of these patients would later be triply infected with Streptococcus pneumoniae while intubated.

On Feb 18th, a warning was issued by the Station, indicating an unusual epidemiological situation now existed for epidemic RSV of high clinical severity.  Our department issued guidance to abandon standard AAP protocol for the treatment of RSV and consider the use of antibiotics prophylactically given the apparent high coinfection rate being seen.

Results:

Before the warning was issued to all providers with pediatric admitting privledges, our hospital exhibited a 33% transfer rate, all of whom were over the course of four days.  Of those transferred, none of the patients were given antibiotics prophylactically upon admission.  Forty-six percent of all admissions pre-warning were provided antibiotics for comorbid conditions such as otitis media.

After the warning was issued, the transfer rate dropped to 8%, as now 88% of RSV admissions were provided antibiotics prophylactically.  Of total admissions to the hospital during the entire epidemic of RSV, 71% of the admissions were seen during the post-warning period.  The 8% who were transferred were placed on antibiotics prophylatically, however it is not clear they were truly infected with RSV.

Adherence to the Station's warning heeded at least a 76% reduction in transfer rates due to RSV during the epidemic. 

This is one of the rare examples of operational validity and proof of performance using near real time surveillance coupled to operational forecasting that altered the outcome of an epidemic.

 

 

 

 

 

 

 

The Operational Biosurveillance Version of the "Arab Spring"

Recently we released documentation provided to the US government regarding the world's first operational National Weather Service-inspired infectious disease forecasting center and the first such station in the United States. 

One scientist from a US national laboratory called this the "SPRING REVOLUTION OF BIOSURVEILLANCE", with reference to the social media-facilitated Arab Spring, one of the biggest social events of the decade.  We tend to agree (albeit with obvious bias), for we now view clinical medicine in an entirely different light. 

I was recently at a Beacon Community conference, where Farzad Mostashari was present as a keynote speaker.  With a bit of mischief in mind, I walked up to him, introduced myself with a small bit of operational background thrown in, and proceeded to tell him the first infectious disease forecasting station in US history was just activated in a Beacon Community participating clinic.  Needless to say that got a few stares. 

We engaged in a back and forth about what one would do with a forecast for asthma exacerbation (which, for some children, is triggered by infectious disease activity).  He suggested a friendly call to the parent to remind them to use their inhaled steroid.  I told him it may be even more compelling than that- in the most brittle asthmatics we may be looking at the prescription of oral steroids before the exacerbation has even begun.  He said, "Prove the case."

 

Fair 'nuff.  The Biosurveillance Spring has arrived.

 

 

 

Official Documentation of the World's First Infectious Disease Forecasting Center

This report was submitted to the US Government in September 2010 for internal publication.  This was official documentation of the existence of the world's first infectious disease forecasting center. 

Detection And Warning Of Biotech Accidents

The recent, ongoing controversy about genetic experimentation with pathogens of high potential consequence for global health raises serious questions about our global capability and capacity to 1) detect events associated with accidents of biological technology ("biotechnology"); 2) recognize those signatures; and 3) issue timely warning of such phenomenon to the world in a transparent process free of political tendencies to withold information. 

First, please refer to prior posts on the difference between signature detection, recognition, and warning.  Here we define capability as the inherent knowledge of how to execute the analytic discipline of biological signature detection, recognition, and warning; and capacity as the global load factor for capability, where obviously a single analyst cannot possibly watch the entire planet.

In regards to the recent reports of deliberate genetic experimentation with H5N1 virus, the root question that should have been asked by the media and anyone astutely watching the controversy is why did the US National Institutes of Health (NIH) authorize the expenditure of US taxpayer funds for the experiment in the first place? 

Funding from NIH does not happen magically.  One has to respond to a Request For Proposals (RFP) with a formal proposal that includes a detailed description of the experiment that is to take place and the justification for that experiment.  There is a rather uncomfortable question to be asked of Dr. Fauci and his staff that goes something like this: "Were you aware of the nature of the experiments about to be conducted by these researchers using US taxpayer funds before the experiments were actually executed?"

However unlikely, it is a well-documented fact that the more infectious an agent, the more likely it is to infect laboratory workers.  In this particular case, the probability for an infection to occur was likely neglible, but there nonetheless.  And trust that the world's public will not accept any excuse should the unthinkable have happened: a laboratory accident that triggered a community outbreak.  The terrible juxtaposition of the highly improbable with the unthinkable consequence again raises its head.

So let's play this scenario out: what is the global capability and capacity to pick up on these kinds of events?  This question is asked because, if we are to believe then the NIH failed to recognize the risk in conducting these experiments in the first place, then how fast do we honestly think we as a global community would have recognized the "oops" should the virus have infected one of the laboratory workers... a worker that went home that night to expose others?  How many chains of transmission would have occurred before it would have been picked up by an astute physician or public health analyst?  How fast would the dots have been connected to trace back to this being an engineered H5N1?  How fast would seed stock have been secured for vaccine production companies?  How fast would those companies be able to grow vaccine stock and execute distribution? 

The answers are very, very bad and uncomfortable.  Let's give some additional data points:

1.  The discovery of Marburg virus in Germany, 1967.  This was a laboratory accident involving a previously unknown lethal, transmissible virus.  Exposed laboratory personnel went home to their families and in turn exposed them.  Note the initial diagnostic confusion, calling the disease "yellow fever", then "monkey disease":

                     Aug 23, 1967                                                                        Sept 13, 1967

 

2.  Laboratory Accident Historical Surveys

It is useful to review the historical records of laboratory accidents.  Figure 1 displays the top diseases and pathogens that infected and killed laboratory workers in the United States from 1930 to 1950, the results of the most comprehensive survey of its kind, conducted by Sulkin and Pike in 1951.

[a]

[b]

Figure 1.  Laboratory infections [a] and case fatality rates [b] by agent / disease for civilian laboratories in the United States from 1930 to 1950.  This is a sampling of the original data.  The entry titled “encephalitis” refers to infections by Western (1), Eastern (1), and Venezuelan (11) equine encephalitis viruses and Russian Far East encephalitis virus (1).  Infections were due to other pathogens as well.

Figure 1 represents a sampling of the total list of agents involved in reported laboratory infections.  Other agents and diseases included:

• actinomycosis
• ascariasis
• B virus
• blastomycosis
• dengue
• giardiasis
• glanders
• gonorrhea
• hookworm
• influenza
• leishmaniasis
• leptospirosis
• louping ill
• measles
• meningococcal meningitis
• mumps
• non-typhoidal salmonella
• Pasturella species
• pinworm
• plague
• ringworm (Candida)
• Rocky Mountain spotted fever
• schistosomiasis
• Serratia marcescens
• sporotrichosis
• Streptococcus pneumoniae
• strongyloidiasis
• syphilis
• tetanus
• vaccinia
• vesicular stomatitis
• viral diarrhea

All manner of infectious agents and their byproducts such as toxins have essentially posed risk for laboratory workers not protected by Biological Safety Cabinets, negative pressure rooms, proper handling protocols, or vaccine.  During the time period covered by the survey, there were few vaccines or antibiotics to mitigate exposure.  It is believed the survey was a gross underestimate of the true number of infections.  There was no systematic reporting mechanism to report laboratory infections in the United States at the time, as is the case now. 

Singh provided an updated perspective based on Pike’s survey in 1976, as shown in Figure 2. 

[a]

[b]

Figure 2.  Laboratory infections [a] and case fatality rates [b] by agent / disease for civilian laboratories in the United States based on updated assessments by Pike in 1976.  This is a sampling of the original data.

When considering biological weapons programs, new hazards were introduced relating to handling of aerosols, mass production, and deployment testing of live agents.  Figure 3 provides summaries of laboratory infections in Fort Detrick personnel during the years of the active United States biological weapons program (1943-69).

[a]

[b]

[c]

[d]

[e]

Figure 3.  Laboratory infections during the years of the active American biological weapons program (1943-1969), showing annual infections due to anthrax [a], tularemia [b], brucellosis [c], Q fever [d], and Venezuelan equine encephalitis [e]. In the case of Venezuelan equine encephalitis, an ineffective live attenuated vaccine candidate was responsible for a number of infections.  Use of Biological Safety Cabinets began in 1950.  Anthrax vaccine was available beginning in 1952.  Tularemia vaccine was available beginning in 1958.  Brucellosis research was decreased beginning in 1953; no vaccine was available.  A vaccine for Q fever was available in 1965.  The TC-83 live attenuated Venezuelan equine encephalitis vaccine was available in 1963.

Other agents and diseases were responsible for laboratory infections at Fort Detrick such as:

• plague (pneumonic)
• glanders
• psittacosis
• botulinum toxin
• staphylococcal enterotoxin B

Aside from the obvious increased risk for a laboratory accident being related to handling live agents, there are several risk characteristics worth noting:

• the infectious agent:
  • causes clinically significant disease in humans
  • is considered a disease of public health significance (especially from an international perspective)
  • is associated with a low infectious dose
  • transmits efficiently from person to person
  • there is no or minimal availability of vaccine, antibiotic, or other effective medical countermeasure
• the laboratory environment:
  • produces or works with aerosols
  • does not utilize Biological Safety Cabinets, negative pressure rooms, hazard suits for personnel, or other protective mechanisms
  • has laboratory workers unfamiliar with proper handling protocols for the agent in question

3.  The epizootic of Venezuelan Equine Encephalitis in Venezuela and Colombia, 1995.  This was a significantly disruptive epidemic involving an estimated 100,000 people that peaked at the same time as a seasonal peak in direct, non-stop air traffic to Florida in 1995.  This was yet another example of warning failure due to failure to detect, recognize, and warn.  Most poignant was the hypothesis the epizootic was due to a laboratory accident- a hypothesis posed only years after the fact.

Download Blake et al VEE in 1995

4.  The accidental distribution of influenza A/H2N2 sample panels:

CAP, the American Association of Bioanalysts, the American College of Family Physicians and the American College of Physician Services all sent proficiency testing surveys containing one or more samples of A/H2N2 to approximately 6,500 labs in the United States. Proficiency testing panels containing A/H2N2 samples were also sent to laboratories in Belgium, Bermuda, Brazil, Canada, Chile, France, Germany, Hong Kong, Israel, Italy, Japan, Lebanon, Mexico, Saudi Arabia, Singapore, South Korea and Taiwan. The World Health Organization has informed the Ministries of Health in these countries.

5.  The still-open case of possible ongoing transmission of polio vaccine-derived virus type 1 in Haiti.  Here translocation of a suspect case to North Carolina went completely undetected by North Carolina's public health officials, CDC, and PAHO/WHO.  The context of social outcry over the suspected accidental introduction of cholera by the United Nations to Haiti provided a strong disincentive for officials to carry out a complete investigation.  The still-open question is whether deployment of Sabin / oral live attenuated polio vaccine in Haiti resulted in the escape of what may be, in essence, an accident of biotechnology out in Haiti's ecosystem continuing to recombine with native enteroviruses.  The lack of a credible investigation into this question remains a concerning point of accountability for PAHO and CDC.  Even more concerning is the multi-million dollar industry interest in continuing to produce, distribute, and vaccine people in extremely vulnerable areas of the world with this agent that has a well-documented nasty habit of causing transmissible disease.

These of course are but some of many examples and observations related to the concern of the proliferation of biological technology.  Accidents should be expected as human-driven processes and procedures are fallable by nature.  And politics certainly have, do, and will cloud situational awareness.

 

 

Alternate Explanations For Bird Die-Offs In the United States

Operational biosurveillance is a "one health" discipline.  As such, we do pay attention to reports of animal die offs, which may indicate infectious disease activity such as West Nile virus or avian influenza.  As we monitor the grid, it is of course useful to understand the broader differential for animal die-offs.  In this case, it is the USDA Bye Bye Blackbird program that should be considered as a key differential for the northern states during the winter.

While the reason for the Bye Bye Blackbird program is understandable, these kinds of practices do reduce the potential biological signature left by an incursion of an important zoonotic infectious agent.

 

Biosurveillance Targeting And Critical Information Requirements

Previously we discussed the difference between detection, recognition (which included prioritization of threat), and warning.

In this case, let's use the example of ProMED, which certainly delves more into the recognition aspect of the detection-warning cycle.  Here you have subject matter experts curating information from the firehose of input available on the internet on a daily basis.  They often provide excellent context and background information, forming collaborative partnerships with such terrific groups as GIDEON.  GIDEON is essentially a "living textbook" of information on infectious disease  worldwide.

But ProMED has had its detractors over the years, having adopted a now-archaic (by social media standards) form of community dialog.  ProMED is heavily moderated, which is a good thing when considering all the potential garbage that could hit the system.  However, it does introduce substantial time delays, which relegates the system to a forensic, after the fact operational posture.  Further, you will often see bias exhibited in displaying "what's hot and sexy" versus a particular subject matter expert's interest.  In other words, it is a mish-mash of things happening around the world without a clear sense of what is truly relevant and important.

But how does one establish relevance?  That is indeed the question, and the same one we dealt with in the DHS National Biosurveillance Integration Center (NBIC).  During that time, we observed that many agencies actually did not even have a prioritized list of issues they monitored on a daily basis.  The concept of critical information requirements from the military operational environment had not permeated the analyst watch cells we interacted with.  Of course, this created tremendous confusion regarding what to warn about on the back end.  ... And it took hours and hours of discussion for people to arrive at an integrated agreement on what pathogens take priority, particularly when having this discussion among physicians, veterinarians, public health officers, etc.

We would see CDC, for instance, obsess about an isolated outbreak of Ebola in Africa that was hundreds of clicks from the nearest airport and completely ignore reports of an unusual respiratory disease in southern China.  When dealing with limited ground verification resources, this poses quite the conundrum when our stateside first responders may encounter the infectious agent in question before warning is issued by a national authority, as what happened during the 2009 H1N1 influenza pandemic.  Certainly Ebola is far more "sexy" than influenza... but one is clearly more acutely and broadly disruptive to a society than the other.

So let's examine some examples:

• Anthrax in Argentina.  In this particular report, it is unclear why the outbreak was brought to the entire world's attention.  Does this outbreak exhibit unusual epidemiological features?  Does it exhibit any suspicious features?  Is it reflective of a concerning long term trend?  It would seem this kind of report should be tagged as a "routine event".
• Oseltamivir-Resistant Pandemic H1N1.  Now this is of casual interest, albeit not at the top of our list.  It is of course good for clinicians to know where we are in terms of drug resistance, but certainly not an unexpected phenomenon.
• NDM-1 Enterobacteriaceae In India's Water Supply.  This is a slow-moving threat of high impact, highlighting the challenge of prioritizing fast-moving, potentially acutely disruptive threats versus slow-moving insidious phenomena.  This is clearly an important warning to the world, however certainly of far greater immediate relevance to the people of New Delhi than here in the United States.  Of course, the definition of a crisis depends entirely on perspective.
• Influenza A/H3N2v In The United States.  This particular issue is at the top of our monitoring list.  But it is an interesting example because we likely would never have noticed this phenomenon just a few short years ago thanks to technology.  This would be an example of the odd dichotomy of better technology yielding greater social vulnerability to anxiety as a result of being able to percieve more threats.  The phrase "ignorance is bliss" of course is relevant here.  But that said, this is a top issue because of the opportunity to explore shortening of the time delta between detection / recognition / warning and response.  While we in the United States are singularly concerned with this issue, the people of Haiti would probably not see this as particularly concerning because they are still dealing with cholera and the myriad of other more morbid and mortal infectious disease endemic to their country.  Again the problem of perspective.

ProMED certainly has a problem trying to be all things to all people, with is a tar pit operationally.  In recent years we have seen multiple appeals for funding vis a vie the Jimmy Wales / Wikipedia Syndrome of proving a great service to the world, creating an expectation for that service, but not establishing a business plan to sustain that service before creating the social expectation in the first place.

Use of prioritized information requirements to structure the outputs is important, as it does create some degree of an edge to the reporting scheme.  It also tightens the screws on the plate of accountability, where issues detected, recognized, prioritized, and warned are more visibly displayed to the international community for their consideration.  But this kind of process requires another level of analysis by moderators and indeed, the user community.  This is ultimately important because we as a global community simply cannot react to all things all the time.

 

 

Biosurveillance: The Difference Between Detection, Signal Recognition, and Warning

For the last 15 or so years, we have seen an explosion of different electronic disease surveillance systems emerge.  Everything from laboratory diagnostics and reporting systems to syndromic surveillance to using the internet for so-called "event-based surveillance".  And there has been a virtual orgy of academic frenzy around the "bright lights and shiny object" effect of the technology.  This is representative of billions of taxpayer dollars over these years dispensed from a variety of federal mechanisms.

Yet, with all of this expenditure (much of which is ongoing), we have still so very little proof of operational value.  The "research and development ice cream cone" continues to lick itself without any apparent metric held by the funders for the operational "so what".  Arthur Reingold's challenge points from 2003 still appear to be unanswered ten years later.  Below, his points have been adjusted to fit a more broad consideration of the topic:

1. Demonstrating that [x, y, z type of] surveillance reduces morbidity and / or mortality following [an infectious disease crisis / disaster].
2. Types of [infectious disease crises / disasters] that [x, y, z type of] surveillance is likely to detect.
3. Response to apparent increases in illnesses signaled by [x, y, z type of] surveillance.
4. Plausibility that [x, y, z type of] surveillance can yield more timely identification of the population at risk in [an infectious disease crisis / disaster].
5. Likelihood that [x, y, z type of] surveillance will produce useful information about naturally occurring infectious diseases.
6. Circumstances under which [x, y, z type of] surveillance is likely to strengthen local and state health departments.

Certainly Reingold was not the only person during the heyday of syndromic surveillance to raise questions about the validity of the approach, but the gist of the above challenges were echoed several times in the literature.  But the academics lept onward undeterred, and the marketing associated with their programs grew to astounding levels of claimed accomplishments.

One such claim was that made by John Brownstein of HealthMap on Aug 3rd at an IARPA OSI Program Proposer's Day, who stated (paraphrased) that HealthMap was "the first surveillance system in the world to detect and publicly report the 2009 H1N1 influenza pandemic".  This impressive claim invokes scrutiny into the defintion of detection and how it applies to evaluating any disease surveillance system... and of course, the taxpayer funds associated with that program.

Merriam Webster defines the word detect as

1. to discover the true character of;
2. to discover or determine the existence, presence, or fact of
   

Webster's definition of recognize goes deeper than detect, however:

1. to acknowledge formally;
2. to acknowledge or take notice of in some definite way;
3. to perceive to be something or someone previously known

However it is the word's Latin origin, cognoscere that brings this point into focus.  Cognoscere means to know.  Of course the word know implies that a human being's mental processes have been engaged.  Which implies 1) there is a human being looking at the data and thinking about it. 

The definition of warning is provided by Webster as:

1. to give notice to beforehand especially of danger or evil
2. to give adminishing advice to
3. to call to one's attention

So this implies a human being, having thought about the data, has recognized and prioritized a concern... and communicated that specific concern to others.

The analytic team that warned the senior health intelligence officer in CDC's Director's Emergency Operations Center (DEOC) noted at the time that HealthMap's information was 1) not posted on their website as fast as the original Mexican source posting 2) was not highlighted in any unusual way to call singular attention to the information among dozens (hundreds?) of other colored pins on their map, and 3) where was no transfer of information to ProMED or CDC from HealthMap evident to suggest that human beings had communicated about the information during early to mid April 2009.  Therefore, the following may be concluded:

1. The first point of detection was actually the Mexican journalist who wrote the first article on the La Gloria situation.  HealthMap simply functioned as a Google News parser- a function anyone could have performed using Google Alerts.  If you happened to click that one pin on the map, you would have 'seen' the report, albeit then you would have to understand whether what was being reported was unusual...
   
2. Human beings were required to recognize unusual indicator patterns in the initial reports (n=1 to 3), not through recognition of simply volume of reporting as captured by HealthMap's Heat Index. 
3. Human to human communication clearly had to occur to push the warning through, as information provided via pull websites and push email notifications were inadequate due to daily information overload at WHO and CDC.

The point of the above is not to singularly criticize HealthMap but to make a point: collection of data is insufficient, by itself, to generate operational impact.  This was a very hard lesson learned by the syndromic surveillance community as well.  And if you are fighting an embedded, decades-old professional culture imbued with a "not invented here" bias (i.e. public health), it is unlikely the data will be exploited properly.

So let's give Brownstein a break for a minute and focus on one of his collaborators: the Canadian Global Public Health Network (GPHIN).  Brownstein's claim at the IARPA meeting was a duplication of GPHIN's claim to the world of having been the first public health system to detect SARS (see attached manuscript, Figure 1). However there was unverified rumor at the time that the web-harvested Chinese media article published on Nov 27, 2002 went unnoticed by GPHIN's staff for some time due to lack of machine translation for Chinese (unverified) and lack of a Chinese linguist.  Even if these rumors were false, and GPHIN's system immediately punched a warning out to its customers, there is no evidence anyone was paying attention.  In the multiple manuscripts and powerpoints given by GPHIN staff, not one contains copies of emails or phone records to indicate human beings had 1) recognized the problem, 2) prioritized the problem (out of the dozens of other reports for the day), and 3) communicated directly with the Canadian PHAC, the US CDC, or WHO specifically about this prioritized problem.  This is concerning when considering how much information was actually missed at the time (see attached report by Polyak et al).

The analogy is football: it's like being thrilled you threw a "Hail Mary" pass, but unawares that 1) no one caught the ball and 2) ran it to the end zone... 3) and thus you lost the game in the process.  Sound familiar?  It should.  These are very similar issues to those in the original 9/11 Commission Report.

Currently the federal government continues to chase its tail, spending more funds on biosurveillance research: the self-licking ice cream cone.  Billions of dollars and 10-15 years later, we still are not holding these systems' collective feet to the fire asking "show me don't tell me".  We continue to reach for the bright lights and shiney objects represented by the latest fad technology ("social media" being the current one) without thinking about how to promote the human process of understanding the data, accumulating knowledge, and using that knowledge to impact the potential outcome of the threat.

These are lessons currently highlighted in the recent IOM report on the DHS National Biosurveillance Integration Center (NBIC), however the problem is far bigger than just NBIC, DHS, or the people funded by DHS.  This is a biosurveillance community-wide problem that affects the credibility of the entire field. 

And if we do not fix it, the funding and public support may eventually disappear.

Download GPHIN Manuscript

Download Emergence of SARS in 2002

 

 

 

False Alarms: A Standard to Strive For

Recently the Germans issued an alarm of what would have been the first publicly recognized translocation of a human Rift Valley fever (RVF) infection from endemic areas in Africa to a temperate zone country.  We applaud them for their proactive release of this information, regardless of it being a false alarm. 

This alarm brought contemplation of the potential impact RVF would have if introduced in a country with transmission-competent mosquitoes and an immunologically naive cloven-hoofed animal and human population.  Many in the agricultural industry consider RVF to be every bit as potentially devastating to livestock exporting country's economy as hoof and mouth disease (FMD) if that country was previously RVF and FMD-free.

It is notable there was not a strong negative reaction (in fact, we have not seen any) to the false alarm.  This is an excellent outcome.  We do not want to get into the habit of penalizing or discouraging reporting if it is later found to be a false alarm.  As general surgeons know, it is good to maintain a 10% rate of normal appendix removals so that none infected are missed.  Same principle here: we cannot afford to miss an introduction of RVF or be slow to react if an introduction is suspected.  Better to react and be wrong than to be slow to respond or hesitate and invoke serious damage to a national economy.

An imprecise but relevant comparison is the example of Vancouver's proactive response to situational awareness during SARS versus Toronto in 2003.  Another example was presented to me just this week where I interviewed an adult infectious disease specialist whose differential diagnosis and index of suspicion was altered to consider West Nile virus as he monitored the westward spread of the virus through the southern states.  He was subsequently the first person to diagnose a case of West Nile in the county in a patient with an unusual presentation of encephalitis.  Presensitization is a key component to successful detection of an index case arriving at the recipient end of a translocation.

This then raises the question of the relevancy of informing local communities in non-endemic countries such as the United States about RVF in South Africa.  When should a local medical or veterinary community be aware of such outbreaks?  Presensitization is key to successful rapid detection of exotic cases.  Therefore, decision points to inform should be biased to inform rather than not.    

As demonstrated during the 2009 influenza pandemic, the introductions of HIV/AIDS, West Nile virus, and several other key infectious disease translocation events, the social reaction to perceived withholding of information is far more severe than the issuance of a false alarm.  This has long been an observation of the disaster sociology community, a point public health after so many decades should internalize and embrace as a standard of practice.

A Tornado Fujita Scale For Infectious Disease Events: The Infectious Disease Impact Scale (IDIS)

Introduction

As discussed in depth in a prior post, our discipline shares substantial historical and methodological parallels with meteorology.  Here we discuss an event impact evaluation system based on peer-reviewed findings of the nearly 100-year old disaster sociology community and the tornado Fujita Scale, including the new "enhanced" version (EF Scale).

Our prior efforts to quantify "biological event evolution" resulted in an approach destined for a full revision and re-imagining: the Wilson-Collmann Scale (WCS):

• Stage 0- conditions favorable to trigger an epidemic
• Stage 1- uni-focal event
• Stage 2- multi-focal event
• Stage 3- infrastructure strain and depletion of local response capacity
• Stage 4- social collapse

The WCS was based on a similar meteorological-inspired premise but the underlying model was derived from a single anthropological study that examined the social impact of epidemics, our own "expert" input, and later a prospective sample of open source media articles.  The word expert was placed in quotes because this preceded operational experience that eventually encompassed tens of thousands of biological events in nearly every country on earth.  The shortcomings of the approach were 1) limited understanding of the broader anthropological and sociological literature, 2) limited operational experience monitoring indicators of infectious disease events, and 3) limited experience monitoring infectious disease events as they manifest in different cultures under different conditions of social sensitivity.

Similar to software versioning, we were compelled to redesign this model several times until a more operationally valid approach was achieved.  The most profound development was a complete abandonment of the WCS and a reanalysis that used nearly 100 years of peer-reviewed literature from the disaster sociology community. 

Depending on the culture and location in the world, we recognized there was a baseline level of resiliency in relation to whatever cultural protection was in place.  For the developed world, this would represent healthcare workers working within an established medical and public health infrastructure.  It is the transition between what is viewed as simply an "event" from the perspective of the local community to transitioning into a crisis or disaster.  It is key to note this process is predicated by local recognition of a problem interpreted to be some form of a threat to the individual(s), organization(s), or the community at large.  The underlying principle is the interplay between local public expectation for a given level of cultural protection in relation to how well that expectation is perceived to have been met under the circumstances.  It is this evolution of community awareness that becomes important when recognizing a deteriorating situation involving an infectious disease.

The Infectious Disease Impact Scale (IDIS)

Our current operational framework for assessing the sociological impact of acute, disruptive infectious disease events is the Infectious Disease Impact Scale (IDIS):

Category 0.  Unreported infectious disease event

Daily, routine infectious diseases are handled at this level, and provision of warning about these diseases is not deemed 'relevant'.

Non-routine infectious disease may also manifest as a Category 0 infectious disease event, implying the "astute clinician" in the local community network has not raised the concern something unusual was observed in the clinic, and nothing unusual was noted in local public health information feeds.  This is the bleeding edge limitation of disease surveillance, where the first case of unusual infectious disease is often missed.

Typical examples include a case of influenza-like illness, non-specific rash, or uncomplicated febrile illness seen by a healthcare provider.

Category 1.  Reported infectious disease event

The typical Category 1 infectious disease event reported by a community reflects a sensitivity to public health or medical significance.  No other significant features indicative of immediate public health or medical infrastructure impact, public anxiety, or civil unrest triggered by the event are noted.

Examples include report of a chickenpox outbreak, limited norovirus outbreak, or a single case of methicillin-resistant Staphylococcus aureus (MRSA).

Category 2.  Infectious disease event associated with routine organized response

Category 2 events often reflect locally well-known diseases that nevertheless generate a demand for organization-level time-sensitive action.  This action is local routine. 

Examples include routine community action for seasonal diarrheal disease or seasonal influenza.  It is important to note non-routine infectious disease may present as a Category 2 event, particularly when it shares similar clinical features with routine disease.  The classic example is the appearance of pandemic influenza in the context of normal seasonal influenza, as was observed in April 2009 with pandemic H1N1.  Early indicators were difficult to distinguish because the level of impact had not reached "critical mass" to allow social recognition of the event as a threat.  Indeed, it is highly likely pandemic H1N1 was transmitting in Mexico well before April 2009, undetected.  Thus, the non-routine may present as routine.

Category 3.  Infectious disease event associated with non-routine organized response

Category 3 events are essentially the beginnings of a community crisis.  The operational definition of a crisis we are working from is the following:

An infectious disease event becomes a crisis when there is a recognized requirement for time-sensitive, non-routine organization-level decisions that may affect a local community’s activities of daily living. It is more common such decision-making falls within the organizational roles and responsibility of a public health institution than a public or private hospital or individual healthcare provider.  This becomes a community level decision-making activity in countries where there is no public health capacity. - Wilson, 2009

It is important to note Category 3 events may be associated with organized response features without significant broader social disruption, as evidenced in a Category 4 event.

Examples of this type of event include a new vaccine-drifted influenza type A variant that appeared before an updated vaccine could be made available to the public.  Another example is the 1999 introduction of West Nile virus to the United States, after recognition of the event to represent a public health threat.  In this category it becomes important to understand the differences between organized response seen in public health versus medical care such as that provided by a hospital.  Monitoring both is crucial.

Category 4.  Infectious disease event associated with social disruption

Category 4 events highlight when organized response has occurred, yet significant social disruption has been documented.  The operational definition of social disruption we are working from is the following:

Social disruption [of community vital processes] refers to the process where a community moves from a given level of integration towards disintegration.  -Wilson, 2009

Coleman’s (1966) original theory of community integration proposed “vital processes” of a community that “keep it alive as a community and prevent its disorganization”.  These processes included:

- work

- education of children

- religiously related activities

- organized leisure activities

- unorganized social play of children and adults

- voluntary activities for charitable or other purposes

- treatment of sickness, birth, death (healthcare)

- buying and selling of property

- buying consumable goods (food, etc.)

- saving and borrowing money

- maintenance of physical facilities (roads, sewers, water, light)

- protection from fire

- protection from criminal acts

It is well recognized infectious disease events may impact a community to the point of straining various aspects of these vital processes.  Category 4 events may be associated with significant strain of multiple community vital processes without inducing community disintegration, which is the indication of a Category 5 event.

Examples of Category 4 events include the 1957, 1968, and 2009 influenza pandemics and the introduction of Chikungunya to India in 2006.

Category 5.  Infectious disease event associated with disaster indicators

The operational definition of a disaster we are working from is the following:

An infectious disease crisis becomes a “disaster” when crisis mode decision making by public health officials or institution fails to control the situation, either from an informational or response perspective and substantial social disruption associated with features of community disintegration occurs as a result.  -Wilson, 2009

This is the typical modern day end-point of social strain experiences when cultural protections fail and individuals of a community physically abandon their dwellings or those vital processes necessary for community integration.  Note this is distinct from prior terminology used to describe the Wilson-Collmann Stage 4 biological event.  In that description, "social collapse" was used to describe an end point, however this terminology is typically used by sociologists and anthropologists to describe the fall of Rome, disappearance of Easter Island's civilization, and the fall of the Incas.  In other words, the collapse of a civilization.  Social collapse certainly is an arguable end-point, however practical use of this consideration is limited to the point of being academic.  Operationally, the more appropriate term is "community disintegration", as it reflects what is usually observed today on a global scale.

The concepts of integration and disintegration are not absolute: each community is associated with a given balance of factors that promote integration and disintegration.  Disasters tip this balance towards disintegration. This concept therefore encompasses more than simply public health response capacity but a broader social context. -Wilson, 2009

Category 5 infectious disease events are classically observed as the so-called "panic evacuations", which is a misnomer.  Observations for years has instead suggested people migrate out of an area of perceived high threat in a manner that attempts to preserve the family unit and other close social ties.  It is often observed these individuals attempt to return to their homes.  Thus, a Category 5 event typically represents transient community disintegration.

Examples include outbreaks of Ebola hemorrhagic fever in Africa, occasional abrupt appearances of cholera in IDP camps in Africa, and measles in Africa.  We have also seen the 2009 H1N1 influenza pandemic induce Category 5 conditions among indigenous peoples in South America.  The key is the intersection between the infectious disease event and violation of cultural protections to the point of inducing community disintegration.

Category 6.  Infectious disease event associated with apocalyptic indicators

This is a largely hypothetical category that acknowledges the exceedingly rare reporting of community disintegration that has progressed to the point of people deciding to either commit suicide or succumb to doomsday feelings where they have dug graves and lie in them to await death.  This type of social behavior has been reported in the anthropological literature only rarely among tribes who live in the most austere conditions, isolated from other communities, experiencing a serious epidemic.

We have not observed this type of event in our years of experience.

Operational Use of the IDIS

The IDIS is a model that serves as a guide to understanding the impact of acutely disruptive infectious disease events through the lens of disaster sociology.  Up to this point, event descriptors of infectious disease events have focused on use of terms like "outbreak" and "epidemic".  This is problematic in the operational setting when valid epidemiological data is often sparse or unreliable.  Here we consider a different perspective that focuses on the interface between an infectious disease hazard and indigenous vulnerability.  This then helps the warning analyst maintain a sense of perspective when attempting to understand which event out of thousands in the world deserves priority attention.

As with the staging of hurricanes and tornadoes, the frequency of Category 1 through 5 events declines dramatically the higher up the scale one goes.  Further, the frequency of seeing higher category events varies not only by pathogen involved but by culture and associated indigenous cultural protections.  Over time, we have seen there are baselines to such events, where the concept of what is considered "routine" and "expected" is challenged.  This is analogous to describing risk due to earthquakes among communities that exist on fault lines, or recognition of certain states in the USA that experience higher frequency of tornadoes, where regular occurrence of such crises may be a baseline onto themselves.

Use of the IDIS requires an experienced analytic viewpoint to make judgment calls during the assessment process often in an environment of uncertainty.  Attempts to categorize an infectious disease event may be challenged not only by uncertainty but also exposure of indigenous socio-economic inequities.  It is well recognized that crises and disasters can often trigger political agendas or social outcry that may provoke civil unrest.  Depending on the context, some infectious disease events begin as seemingly innocuous Category 1 or 2 events but later reach a higher categorization due to civil unrest that is less related to actual disease transmission effects but rather public perception.  In other words, it becomes just as important to pay attention to the epidemiological features of an infectious disease event as the social context because the endpoint of disruption to the community may be as severe.

We have found the IDIS to be operationally practical especially when dealing with austere environments such as post-disaster Haiti, where formal medical surveillance is compromised.  If access to credible epidemiological data is compromised, then there is a tendency to hesitate both in warning the public and responders as well as making the decision to execute a response.  The IDIS offers an alternative approach to monitoring the infectious disease situation in a given area that may not have a robust infrastructure to support comprehensive epidemiological investigation.

As a final point, it should be noted the IDIS does not function as a mechanism to flag unusual events unless a comprehensive local baseline is well understood.  There are other procedures for flagging events early in the evolution process as looking "unusual" that will be discussed in a later post.

Biosurveillance: A Vehicle for Accountability

As discussed previously, biosurveillance outputs become a vehicle for accountability.  We believe this is a major reason for resistance by bureaucratic organizations.  A more extreme consideration of this problem may be seen in closed societies, where one of the key information sectors controlled by totalitarian regimes is public health surveillance data. 

When considering a national security perspective, there was a time when meteorological data was classified because of wartime concerns about informing the enemy of perfect conditions for a bombing run or chemical weapon deployment.  Of course, one of the key objectives of biosurveillance is a comprehensive understanding of the multi-faceted baseline of infectious disease.  This baseline must be understood pan-species, with a full understanding of the entire expanded taxonomy of indicators and how they differ by season, culture, disease, and other contexts.  Only then may the unusual or non-routine events be flagged for closer time-sensitive scrutiny.  It is not difficult to understand when biosurveillance information becomes sensitive given the context.

The public health perspective is driven heavily by direct interaction with the public and all the politics that surrounds that interaction.  For most countries, the public health apparatus is driven towards gold-standard epidemiological investigation and laboratory confirmation prior to communication with the public.  The persistent misconception the public will "panic" upon receipt of health threat information remains a global problem.  The multitude of peer-reviewed literature from the disaster and warning sociology communities remains largely unincorporated in public health.  With this forensic, risk adverse posture, public health becomes the analogy of the pathologist placed in charge of an emergency room.  The very nature of warning is a tolerance of false positive information and an embrace of uncertainty- with effective and timely communication of that uncertainty to the public.  This overlaps heavily with the basic tenets of risk communication.  As readily observed during the 2009 influenza pandemic, effective risk communication relates directly to public health credibility with the public.  This hesitation in issuing warning information plays right into an erosion of public trust.  As mentioned before, we are dealing with active resistance to implementing the Haiti Epidemic Advisory System, the world's first infectious disease forecasting system.

Recently InterAction, a select group of the world's largest NGOs, responded to allegations of donor money withholding and failure to execute proper response on the ground in Haiti.  They declared, "NGOs are part of the solution, not the problem".  As the executive director of an NGO, I am circumspect enough to say, "Perhaps". 

But I sit in a unique position of facilitating operationally sensitive information sharing to save lives.  Specifically in the case of Haiti, children's lives.  The stakes are imminent and high, and I have seen many of the InterAction partners flatly deny sharing information about infectious disease prevalence with the responder community.  How it is done currently is each organization separately send data in a spreadsheet once per week to the Haitian Ministry of Health where over the course of a week, it is analyzed, and presented as aggregated to the city level.  Each organization rarely talks with each in the course of the week to highlight abrupt changes in the disease baseline that may herald the beginning of an epidemic the entire responder community should be aware of as soon as possible.  We have made some degree of progress with this problem in the Haiti Epidemic Advisory System, where three of the major NGOs on the ground in Haiti have shared critically important information about infectious disease prevalence they have documented in their clinics.  They are to be strongly commended for this, and it is our hope we are witnessing a new era in NGO information sharing.

We must arrive at a point where we observe the basic human right of providing an environment of uninhibited access to health information for those we serve.  Let us continue to walk this road, and walk like we have a purpose.