Pertussis: a concise historical review including diagnosis ... - sepeap

86 Reviews in Medical Microbiology 2005, Vol 16 No 3
laboratory tool for the diagnosis of pertussis in both
the individual patient and in epidemiological studies.
Baughman et al. [100] found a cut off 94 U/ml (FDA
units) diagnostic for a recent infection with B. pertussis.
Since 100 Dutch units equals 125 FDA units [101] this cut
off is considerably lower than the one found by the
Melker et al. [99].
The next question is what is the natural course of IgG-PT
after infection. Accordingly, it is necessary to gain insight
into the rise, peak and decline of IgG-PT after natural
infection with B. pertussis.
Our group used different ways of evaluating the decline
of IgG-PT after natural infection with B. pertussis
[99,102,103]. These three methods reflect gradual improvement
and advances in understanding. In response to
an infection, IgG titres typically show a rapid increase,
followed by a steady, slow decline over several years. IgG-
PT responses appear to show considerable variation
among individual patients.
The first model analyses the association between 2 log
IgG-PT levels and time in 2 log days, fitting a straight line
only accounting for the decaying phase of the response.
This requires omission of data from the initial rapid
increase of IgG-PT [99]. In this study the rapid increase of
IgG-PT in the first weeks after illness was not taken in
account, nor were effects of age or vaccination status.
Since there is no clearly defined criterion by which
observations can be excluded, the following study [102]
continued with a response model, which includes the
initial rising phase. The model that was used, a skewed
hyperbola, has asymptotically linear decline on a log–log
scale at long times from infection. In this model there
seemed a significant effect of age or vaccination status, but
because numbers of adults and unvaccinated infants were
small and because there was a wide variation of data it
remained unclear whether this was clinically relevant.
For any individual patient the amount of information in
this study was limited: only a few measurements at best.
Although the previous regression model adequately fitted
the data, this model did not help much in interpreting the
observed immune responses. For that reason a biologically
based model was developed [103]. The longitudinal
responses are described with a dynamic model of the
interaction between bacteria and the immune system.
This so-called predator–prey model is the simplest
possible model for the interaction between host and
pathogen.
In this study, combining data from patients aged 0–94
years, there were no significant differences found in rise,
peak and decline of IgG-PT between different age
groups. There seems a tendency to age-related differences
where older people tend to have a more rapid increase, a
higher peak and a faster decline after infection than
in younger age groups, which could be caused by
immunological memory.
Since B. pertussis infection is especially dangerous in
young children, not or partially vaccinated, and since the
main source of infection for these children are adults with
often atypical clinical manifestations [104] it is important
to gain insight into the incidence of B. pertussis infection
[103]. Is it possible, once knowing the natural course of
IgG-PT, to calculate the incidence of B. pertussis infection
in the Netherlands in different age groups from available
surveillance data on IgG-PT levels in the general
population?
Earlier de Melker et al. showed that an IgG-PT level of at
least 100 U/ml is present in less than 1% of the population
[99]. De Melker et al. [105], using the statistical model
described by Teunis et al. [102] on the IgG-PT data of a
cross-section of the general Dutch population (n ¼ 7756)
[99] showed that B. pertussis infections occur frequently in
the Dutch population, particularly in adults for whom the
reported incidence is very low. On average the estimated
incidence of infection was 6.6% per year for 3–79-yearolds.
The annual incidence of notified cases was 0.01%.
The age distribution of all infections differs notably from
the age distribution of notified cases. Therefore we
suggest that vaccination strategies should not be based on
notification data but on knowledge about the circulation
of B. pertussis in different age groups and contact patterns
between age groups. Especially for the young, not or
incompletely vaccinated children it is important to
develop vaccination strategies focused on adolescents and
adults as they are the most important source of infection
of these infants [106].
From other studies [17–22,24] it is known that, in some
patients there may be evidence of other pathogens
involved in the pertussis syndrome besides B. pertussis and
in others of pertussis-like complaints without proof of
B. pertussis infection. In a retrospective study for mixed
infections we found that in 28% (23/82 patients) there
was evidence of possible mixed infection with other
pathogens such as parainfluenza virus, respiratory
syncytial virus, Mycoplasma pneumoniae, adenovirus or
influenza virus [107]. Then, to investigate the role of
different respiratory pathogens in prolonged coughing in
children, to confirm the data of the previous study and to
analyse the clinical impact of mixed infections of
B. pertussis with other respiratory pathogens we performed
a prospective study in patients aged 0–18 years
with coughing symptoms lasting 1–6 weeks [108]. In 91
of the 136 included patients one (n ¼ 49, 36%) or more
(n ¼ 42, 31%) possible respiratory pathogens were found.
The most frequent pathogens encountered were rhinovirus
(43 patients, 32%), B. pertussis (23 patients, 17%) and
respiratory syncytial virus (15 patients, 11%). In the 42
patients with a mixed infection the most frequent
combination was B. pertussis and rhinovirus (n ¼ 14).