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.
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