Many insurance policies expressly grant business interruption coverage, but a key to coverage is often found in extensions that require there be “actual not suspected presence of communicable disease.” Attorneys from McCarter & English LLP examine how businesses can prove their case.
The deluge of articles addressing coronavirus business interruption coverage has tended to obscure the fact that many policies expressly grant coverage for such losses. Some policies have extensions for “communicable disease” that trump any potentially applicable virus or pathogen exclusions.
A key coverage provision that may be found in those extensions is the requirement that there be “actual not suspected presence of communicable disease.” What, pray tell, does that mean?
Obviously, testimony from employees or customers that they were sick while at the covered facility should suffice. Likewise, a policyholder with nurses in full PPE taking nasal swabs at the facility’s reception desk can demonstrate the actual presence of Covid-19. And presumably analysis of surface samples taken from door handles or railings that shows SARS-CoV-2 would also demonstrate “actual presence.”
But suppose those indicia were unavailable because no one reported being sick, and the insured’s facility—closed for two months—was never tested, and the insured’s consultant advises that the short survival time of the virus makes it very unlikely that current sampling will show the presence of SARS-CoV-2. Is demonstrating the “actual not suspected” presence of Covid-19 foreclosed? Of course not.
Inference is a commonplace tool for understanding our world. If your colleague walks into your interior office, peels off his sodden coat and shakes out his umbrella, you will conclude correctly that it was actually raining outside, even though you could not see it or hear it. Your colleague’s direct evidence is part of the circumstantial evidence of a storm. “To render circumstantial evidence admissible, it is only necessary that it tend to prove the issue …; it must lead to a reasonable inference and not a mere suspicion of the existence of the fact sought to be proved.” 29 Am. Jur. 2d Evidence § 303 (2020).
Direct Evidence Constituting Circumstantial Evidence
So what direct evidence could constitute circumstantial evidence of the actual presence of communicable disease? Let us suggest a few:
- The disease is present in the general population.
- Members of the general population access the relevant facility at a particular rate and time.
At some point, one moves beyond suspicion and concludes that the disease is actually present in the facility.
Experts are often utilized to make the connection between the facts proved, and the facts at issue. The timing of a release of a hazardous substance is a useful example. For example, in State Auto. Ins. Co. v. DMY Realty Co., 977 N.E.2d 411 (Ind. App. 2012), the insured sought to prove the date of the release of contaminants in order to establish which insurance policies were triggered.
The insured had no direct evidence of when the chlorinated solvents escaped into the environment. Its expert, relying on an EPA model, used information regarding the extent of the contaminant plume to calculate the date of the release. Following a technical analysis incorporating various pieces of information into the “Darcy seepage velocity flow equation” and a “3-D contaminant transport analytical solution,” the expert provided a sufficiently robust explanation that the trial court accepted the release dates offered, which ruling was affirmed by the court of appeals.
In another case, the insurer asserted that the insured had not demonstrated property damage during the policy period and that summary judgment in the insurer’s favor was appropriate. Aetna Cas. & Sur. Co. v. Dow Chemical Co., 10 F. Supp. 2d 771, 794-95 (E.D. Mich. 1998). The insured successfully offered the opinion of its expert to defeat the motion.
The expert used computerized groundwater modeling in combination with relevant documentary evidence to analyze the time of soil and groundwater contamination; he placed the release during the insurer’s policy period. Thus, insurance disputes are not strangers to the use of modeling to establish as fact circumstances which were not measured, identified or otherwise confirmed at the time of their occurrence.
Expert proofs, of course, are not limited to insureds. Indeed, when necessary, insurers offer expert testimony to support their own positions. E.g., Twin Cnty. Reg’l Healthcare Inc. v. Chartis Claims Inc., (insurer’s uncontested expert testimony established date of release).
To be sure, circumstantial proof of the timing of a release of a hazardous substance in connection with a liability policy is different from the proof needed to establish the actual presence of a communicable disease under a property policy. But any difference in the nature of the proof required is irrelevant here. The general proposition remains the same: expert proofs are an appropriate approach by an insured to meet its burden when contemporaneous evidence is not available.
Under one form of the communicable disease extension, coverage is available where there is the “actual not suspected” presence of Covid-19. Of course, insureds should not concede any obligation to obtain expert proofs to conform to an insurer’s “narrowly-parsed definition.” See Wakefern Food Corp. v. Liberty Mut. Ins. Co., 968 A.2d 724, 735 (N.J. Super. 2009) (considering meaning of “physical damage”).
This is particularly so where there may be other ways of demonstrating the presence of SARS-CoV-2, as, for example, direct evidence of the virus or of the disease. However, an insured could also demonstrate the presence of Covid-19 using expert testimony.
Modeling disease prevalence in a community and the dispersal of infected persons into a particular facility can serve as reliable evidence that Covid-19 was actually present in the facility. The fact that no one admitted to illness or that there are no contemporaneous samples of coronavirus in the facility is not dispositive. Insureds should be guided accordingly.