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Estimating the reproduction number of the novel
influenza A virus (H1N1) in a Southern Hemisphere setting: preliminary estimate
in New Zealand
On 11 June 2009, the World Health Organization raised the
influenza pandemic alert level from phase 5 to phase 6, declaring that the newly
emerged influenza caused by a novel influenza A virus (H1N1) had reached
pandemic levels. Although summer conditions in the Northern Hemisphere might be
impeding the spread of this pandemic, in some Southern Hemisphere countries
(including New Zealand) there appears to be very active and widespread
transmission.
The first imported cases in New Zealand arrived on 25 April
in a group of students returning from a visit to Mexico. On 30 April, this novel
pandemic influenza became a notifiable and quarantinable disease in New Zealand,
and widespread indigenous transmission became evident in June. By 6 July, 1059
confirmed cases had been reported, including 3 deaths (and subsequently
additional deaths have occurred).
To assess the transmissibility of this pandemic influenza
virus in New Zealand (i.e. the expected magnitude of an epidemic), we
investigated the time-evolution of confirmed and probable cases in New Zealand
up to the end of June 2009. In particular, we estimated the reproduction number,
R, which is the average number of secondary cases generated by a single
primary case. R is a summary measure of the transmission potential in a
given epidemic setting, and has been estimated to range from 1.4–1.6 in
Mexico1 and 2.0–2.6 in
Japan2 for this current pandemic.
Methods—We analysed the temporal
distribution of novel influenza A virus (H1N1) cases notified to medical
officers of health and recorded on the national surveillance system (EpiSurv).
Figure 1 shows the observed temporal distribution from 28 May to 28 June 2009,
including 585 confirmed cases and 38 probable
cases.3
The time-evolution is illustrated by the earliest date
entered in EpiSurv, which is either date of symptom onset, hospitalisation,
death, or reporting, because the date of onset has not been available for all
cases (though in fact no deaths occurred in this time period).
A confirmed case was defined as a person with
laboratory-confirmed novel influenza A (H1N1) virus infection by means of
real-time PCR, viral culture or 4-fold rise in specific neutralising antibodies.
A probable case was defined as a person with an influenza-like illness (i.e. [i]
history of fever, chills, and sweating or clinically documented fever greater or
equal to 38°C, plus [ii] cough or sore throat) who has a strong
epidemiological link to a confirmed case or defined cluster.
To estimate R we first removed 63 imported cases
from the epidemic curve and assessed the growth of the remaining cases who were
healthcare workers, those with known contact/s, or those with unknown contact/s.
Second, we investigated the initial growth phase which was counted from 2 June
when the first indigenous secondary case was reported.
The exponential growth phase was assumed to have a mean
duration of 15 days (from 2–16 June) but windows in the 15±2 days
were also used. It should be noted that the latest time points of the
exponential growth phase were before 22 June, when constraints on testing began
to occur due to high demand. This was also the day when health authorities
switched from a containment to a “manage it” phase of pandemic
control.
Assuming that the reporting delay (from onset to reporting
and from onset to hospitalisation) was independent of calendar time, the growth
rate of reported cases in the epidemic curve (Figure 1) mirrors the exponential
growth rate of infections.4
Figure 1. Epidemic curve of the novel influenza
A virus (H1N1) infection in New Zealand
![]() The horizontal axis represents the earliest date
entered in EpiSurv, which is either date of symptom onset, hospitalisation,
death, or reporting. Imported cases from early April to early May are not
shown.
Third, we estimated the intrinsic growth rate r,
which is also referred to as the Malthusian growth rate. We estimated r
based on a pure birth process.5,6 Given our
observations of the cumulative number of cases, C(0), C(1),
C(2), ..., C(t), we have
which was used to construct a likelihood function for
r,
Equation (2) was used for estimating
r.2,6 The 95% confidence intervals
(CIs) were derived from profile likelihood. Fourth, assuming that the generation
time follows a gamma distribution with mean μ = 2.8 days and
coefficient of variation k = 0.471, the reproduction number was
estimated using the following estimator.7
Since the generation time of the ongoing pandemic influenza
has yet to be fully clarified, we investigated the sensitivity of R to
different μ ranging from 1.6 to 4.0 days.
Results—Figure 2 compares the
observed and predicted number of indigenous cases during the first 15 days of
the pandemic in New Zealand. The maximum likelihood estimate of r was
0.26 (95% CI: 0.23–0.30) per day, and thus, R was estimated as
1.96 (95% CI: 1.80–2.15).
Figure 2. Temporal distribution of the novel
influenza A virus (H1N1) infection in New Zealand during the initial growth
phase of indigenous cases
![]() Dots, observed number of cases; Continuous line,
expected number of cases; Dashed lines, uncertainty bounds of expectation based
on the confidence limits of the intrinsic growth rate.
Figure 3A illustrates the sensitivity of R to
variations in the mean generation time in the range of 1.6 to 4.0 days. The
corresponding maximum likelihood estimates of R lie in the 1.49 to 2.55
range. 7 The observed pattern was consistent
with our analytical understanding; the longer the mean generation time, the
greater the estimate of R we will obtain.
Figure 3B shows the sensitivity of R to variations
in the initial growth phase (i.e. taking 14 June to 18 June as the latest time
point of reporting to observe exponential growth). The intrinsic growth rate
ranged from 0.20 to 0.29 per day, and accordingly, maximum likelihood estimate
of R ranged from 1.69 to 2.11.
Figure 3. Estimates of the reproduction number
of the novel influenza A virus (H1N1) infection in New Zealand.
![]() A) Estimated reproduction number by different mean
generation times, based on the initial growth phase of the epidemic (i.e. first
15 days). B) Estimated reproduction number by different dates at the end of the
initial growth phase. The mean generation time was assumed to be 2.8 days.
Discussion—The present study is the
first to report R in a Southern Hemisphere setting for the ongoing
pandemic, caused by a novel influenza A virus (H1N1). The estimates for R
are generally in between the two existing estimates for Northern Hemisphere
settings but were closer to the higher estimate in
Japan.1,2,8 It should be noted that our
estimate of R is greater than published estimates for seasonal
influenza in temperate countries.9 Moreover,
our estimate is slightly greater than that of Spanish influenza pandemic from
1918–19 in New Zealand.6
We are aware of three plausible reasons to obtain a higher
estimate of R than that in Mexico:
(i) higher virus fitness to the winter season in the
Southern Hemisphere setting;
(ii) possible large clustering of cases in certain settings
(e.g. healthcare workers in hospital settings, extended families and large
gatherings in Pacific People’s communities); and
(iii) possibly time-variations in the frequency of
ascertaining infected individuals during the early phase of the pandemic (i.e.
potential increase in the diagnostic coverage of infected individuals as a
function of time).
We are actively investigating ways of improving the
robustness and generalisability of R estimates for New Zealand.
Addressing the impact of heterogeneous mixing on the estimate of R as
well as potential under-reporting of symptomatic cases may provide more detailed
insights into the transmission dynamics of pandemic influenza in this country.
Clarification of the heterogeneous patterns of transmission
(e.g. age-specificity) would also permit optimising the distribution of upcoming
pandemic vaccines to different age- and risk-groups. In addition, it would also
be useful to explore the transmission potential using epidemic data for other
outbreak-settings (to address uncertainties with respect to time, space and
other risk-attributes of sub-populations).
Given that R is estimated to be 1.96 in a randomly
mixing population, this would suggest that 78.6% of the population will
experience infection by the end of the pandemic. Nevertheless, a smaller
estimate may be more likely in a realistically-structured heterogeneously mixing
population and if public health interventions around hygiene behaviours and
social distancing are effective.
Thus, the transmission potential of this virus in this
Southern Hemisphere setting should be regarded as relatively high. Therefore, in
the context of some serious morbidity and mortality, these findings support the
continuing promotion of public health interventions in this and other Southern
Hemisphere countries.
Hiroshi Nishiura
Postdoctoral Research Fellow Theoretical Epidemiology, University of Utrecht Utrecht, The Netherlands h.nishiura@uu.nl Nick Wilson
Senior Lecturer, Department of Public Health, University of Otago, Wellington, New Zealand Michael G Baker
Associate Professor, Department of Public Health University of Otago, Wellington, New Zealand Acknowledgements: The authors thank
the numerous health workers who have contributed information to the surveillance
system and to ESR for their high quality work in collecting and distributing
EpiSurv data.
References:
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