Intended for healthcare professionals

Analysis

Calibrated response to emerging infections

BMJ 2009; 339 doi: https://doi.org/10.1136/bmj.b3471 (Published 03 September 2009) Cite this as: BMJ 2009;339:b3471

Response to emerging infections already calibrated

Peter Doshi presents some interesting thoughts on the current H1N1
outbreak and its wider ramifications for future outbreaks of newly emerged
human pathogens (1).Distilled, the central themes of the paper are:

1. That the response to the pandemic may have been unnecessarily
aggressive;

2. That early response was driven by concern generated by
inappropriate diagnostic laboratory testing producing potentially biased
prevalence estimates; and

3. Response to future outbreaks of novel and emerging infections may
be better targeted by use of a two-dimensional framework, which classifies
such events on disease severity and numbers infected.

Starting with the last of these first, whilst the framework is
interesting as a piece of reflection, as a construct for planning an
urgent response to a newly emerged agent it is, I would argue,
impractical.

Firstly, values that would allow one to place an outbreak correctly
in any four of the described planes are not available at the time a
response is required. For disease severity, even Doshi acknowledges that
decisions on the initial response were being made at a time when such
information was incomplete. In the US a nationwide public health emergency
was declared on April 26 with 20 cases and no deaths, but evidence of
severe disease from Mexico. With the information available at that time,
when response measures were required and public health officials would
have been derelict not to act, where on the x-axis does this pandemic go?

Clinical severity is even more troublesome. There are two qualities
that make the y-axis variable different to the x-axis: the number of cases
is both outbreak duration dependent and reliant on the success of control
efforts. Placement on this axis too early in an outbreak, when cases are
few, may result in an insufficient response resulting in continued disease
transmission and human suffering that may have been stopped with early,
aggressive intervention. At what time-point during the 2003 global SARS
outbreak did it become clear that cases would not exceed 10,000? I would
argue it was many months after the time when action was required and
taken, and that said action greatly limited the spread of the outbreak.
These are features we can only be certain of in the comfort of hindsight.

Doshi implies that the response to the H1N1 pandemic may have been
unnecessarily aggressive. But even now he appears unprepared to place H1N1
pandemic on his framework for guiding action. H1N1 may prove (my emphasis)
to be type 3: if we can’t definitively characterise H1N1 some four months
after the first cases were identified, in what time frame will this
construct allow us to calibrate response?

Finally, Doshi suggests that the increase in diagnostic laboratory
testing may have led to misperceptions about the outbreak and may even
have biased our understanding. Laboratory testing has greatly assisted our
understanding of influenza epidemiology. No distinction could be made
between seasonal and pandemic influenza in 1918 as the viral cause of
influenza was first reported in 1931 (2). The advent of highly sensitive
and specific nucleic acid tests has, in recent years, revolutionised
virology, and real-time RT-PCR assays were available for pandemic (H1N1)
2009 virus within weeks of the discovery of this new variant (3).
Laboratory testing played an important role in informing national response
in Australia during our winter season, including the declaration of phases
and planned responses, in line with the National Pandemic Plan (4).

Doshi suggests that results of laboratory testing drove concern and
anxiety about the H1N1 outbreak and that this, rather than the pandemic
itself, forced potentially unnecessary action. Even a pandemic influenza
virus that causes typical influenza disease will have substantial impact:
in Australia over our flu season we have had 162 identified deaths, and
despite being at the end of our outbreak, 334 people remain in hospital
(5). Indigenous Australians and pregnant women were disproportionately
affected. Laboratory testing reflects what is happening in the community;
it doesn’t generate but merely confirms cases, and given deaths and
hospitalisations occur, it would be unreasonable not to provide this
information to the public, particularly those at increased risk. At the
height of our H1N1 outbreak in Australia influenza was detected in 67% of
specimens submitted, and 91% of typed influenza viruses were the pandemic
strain (6). There was little influenza B around removing a role for point-
of-care testing in artificially increasing the proportion of specimens
positive (1). The worried well effect described would increase the number
of negative specimens collected thereby reducing the proportion of all
specimens positive for the agent of interest. The Swedish data Doshi cites
account for only 79 people coming from endemic countries – this compares
with tens of thousands of specimens collected and tested in such
countries. Whilst interesting, their importance should not be overstated.
Without further detail it is difficult to understand how the suggested
“ongoing randomised sampling” should be performed: is the sampling frame
the entire population or just symptomatic people? If the later, how is
this group to be identified and sampled without feeding into the concern
bias Doshi is attempting to prevent?

Most things are clearer on reflection. Public health authorities
attempting to deal with emerging infections that may have catastrophic
effects on human health and safety need to act promptly with available
information to hand, including laboratory testing data. In such
emergencies, the calibrated response is assessed and adjusted daily.
Doshi’s framework is interesting, but can only be accurately completed in
hindsight, it is not a tool to guide immediate response.

References

1. Doshi P. Calibrated response to emerging infections. BMJ
2009;339:b3471.

2. Shope RE. Swine influenza I: Experimental transmission and
pathology. J Exp Med 1931;54:349-359.

3. Whiley DM, Bialasiewicz S, Bletchly C, et al. Detection of novel
influenza A(H1N1) virus by real-time RT-PCR. J Clin Virol 2009;45:203-204.

4. Commonwealth of Australia. National Action Plan for Human
Influenza Pandemic. 2009. The Department of the Prime Minister and
Cabinet, One National Circuit, Barton ACT 2600 Australia.
http://www.dpmc.gov.au/publications/pandemic/docs/NAP.pdf

5. Commonwealth Department of Health and Ageing. Pandemic (H1N1) 2009
update bulletin. 09 September 2009.
http://www.healthemergency.gov.au/internet/healthemergency/publishing.ns...

6. Kelly H, Grant K. Interim analysis of pandemic influenza (H1N1)
2009 in Australia: surveillance trends, age of infection and effectiveness
of seasonal vaccination. Eurosurv 2009;14:1-5.

Competing interests:
SBL is a co-investigator in a CSL sponsored paediatric swine flu vaccine study and was the WHO team leader in Singapore during the 2003 SARS outbreak.

Competing interests: No competing interests

09 September 2009
Stephen B Lambert
Medical Epidemiologist
Queensland Paediatric Infectious Diseases Laboratory, Royal Children's Hospital, Herston QLD 4029