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The 2009 H1N1 influenza pandemic was the first pandemic of the twenty-first century, as declared by the World Health Organization in June 2009. During the first weeks of the main pandemic wave in Norway in October 2009, it appeared that Norway was experiencing a higher mortality rate associated with the influenza A(H1N1)pdm09 virus than other European countries. However, by the end of the pandemic period, it was widely reported that there had been much fewer influenza-related deaths than in previous years.
It is often hard to discern between influenza and other risk factors as the cause of death for patients with chronic diseases. Therefore, one can differentiate between two main approaches used to assess the mortality burden. One approach is to count the number of deaths reported to death registries with influenza as one of the registered direct or underlying causes of death, with or without laboratory confirmation. The true mortality burden is assumed to be much higher than what is reported by these registries[1, 2] because most often influenza is not recognized as a contributing factor to death due to varying clinical presentation of influenza, low awareness among clinicians and varying practices and availability of testing for influenza.
The other approach for assessing the mortality burden of influenza as a contributing factor is by using statistical models. Typically, these models estimate the excess mortality as the difference between the observed mortality during an influenza season and the expected baseline mortality in the same period if no influenza were present. There are different ways to determine the baseline mortality, but it is typically made using a regression or time series method.[2-5] In Norway, both these approaches have been undertaken for the first year of the influenza A(H1N1)pdm09 pandemic.
By the use of these two approaches (registries and models), health authorities' reporting may lead to confusion. Typically, one can cite the excess number of deaths from seasonal influenza when arguing for the importance of public health measures against influenza, such as vaccination. This strategy may backfire if the public at another time is presented with the usually much lower number of registered deaths in the Cause of Death Registry, without a proper explanation of the methods.
The objective of this study was to compare the number of reported influenza-registered deaths with the results from two different models for estimating the excess mortality due to influenza during the 2009 pandemic in Norway. This was to try to understand the real impact of the pandemic on yearly mortality rates and allow for realistic planning for future pandemics. Using one of the models, we also wanted to compare the estimates for the pandemic season with previous regular influenza seasons.
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- Declaration of interest
From the designated surveillance at the NIPH of deaths due to pandemic influenza, a total of 32 fatalities (0·65 per 100 000 of the population) were registered between April 2009 and April 2010 (Table 1). Two further patients found in the Cause of Death Registry were not included as their influenza diagnosis was not laboratory confirmed. Questionnaires were received back for 28.
Table 1. Number of registered influenza deaths in Norway between April 2009 and April 2010, by gender and age group. Influenza deaths are deaths were laboratory-confirmed influenza A(H1N1)pdm09 was considered to have significantly contributed to death
Only one person was not found to have had a medical condition that put the person at higher risk from influenza complications. Ten people were found to have more than one condition that put them at higher risk. The most common condition was chronic pulmonary disease. No cases of vaccine failure were found.
The peak period of deaths from influenza A(H1N1) was earlier in Norway than that the average of countries in Europe (Figure 1); however, the mortality rate was consistent with that seen in other countries.
Figure 1. Mortality rates (per million) from influenza in the EU/EEA countries (from ECDC) and in Norway, by week during the first pandemic year, 2009-2010.
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The numbers of reported deaths by age group for the pandemic season compared with the season between 1997 and 2008 are presented in Figure 2. The figure indicates a significantly different age distribution for the deaths in the pandemic season, with cases spread out in all age groups, compared with the other seasons where almost all deaths are found among the elderly population.
Figure 2. Number of influenza deaths per million by age group reported to the Cause of Death Registry for the seasons 1997–2008 on average (light grey) and to the NIPH for the first pandemic year, April 2009–April 2010 (dark grey).
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With the Poisson regression model in Eq. (1), the estimated seasonal excess mortality using Eq. (3), from season 1998/1999 to season 2009/2010, varied from 56 deaths in the 2009/2010 pandemic season to 1520 deaths in the 1999/2000 season, when analysing all-cause mortality (Table 2). The mean estimated excess mortality for the entire period was 766 deaths per season (16·6 per 100 000 population). Results analysing P&I-certified deaths were considerably lower, ranging from 394 deaths in the 1999/2000 season to 72 deaths in the 2007/2008 season, with a mean estimate of 172 excess deaths per season (3·7 per 100 000 population). Note, however, that the P&I analysis does not cover season 1998/1999 and that the first and last seasons in both analysis do not cover a complete 52 weeks.
Table 2. Estimated excess mortality using the estimator in Eq. (3), analysing both all-cause and P&I deaths, mean level of reported ILI and dominant virus for all influenza seasons from 1998/1999 to 2010/2011
|Season||Estimated excess mortality using all-cause mortality (95% CI)||Estimated excess mortality using P&I deaths (95% CI)||Mean ILI per consultations 100 consultations||Dominant virus|
|1998/1999||1363 (1193–1559)||–||1·96||A/Sydney/5/97 (H3N2)|
|1999/2000||1520 (1326–1759)||394 (356–435)||1·42||A/Moscow/10/99 (H3N2)|
|2000/2001||339 (298–386)||80 (71–89)||0·67||A/New Caledonia/20/99 (H1N1)|
|2001/2002||761 (666–870)||203 (182–225)||0·98||A/Panama/2007/99 (H3N2)|
|2002/2003||629 (553–718)||132 (116–150)||0·89||No dominant virus|
|2003/2004||1083 (945–1242)||246 (219–275)||1·19||A/Fujian/411/2002 (H3N2)|
|2004/2005||784 (690–897)||151 (133–172)||1·03||A/California/6/2004 (H3N2)|
|2005/2006||631 (554–720)||125 (112–139)||0·92||B/Malaysia/2506/2004|
|2006/2007||818 (718–935)||190 (169–213)||1·03||A/Wisconsin/67/2005 (H3N2)|
|2007/2008||383 (337–437)||72 (64–80)||0·72||A/Solomon Island/3/2006 (H1N1) and B/Florida/4/2006|
|2008/2009||542 (476–621)||114 (102–126)||1·05||A/Brisbane/10/2007 (H3N2)|
|2009/2010||56 (−289–419)||96 (43–148)||2·16||A(H1N1)pdm09|
|2010/2011||607 (531–692)||118 (156–133)||0·97||B/Brisbane/60/08|
In Figure 3, the upper panel shows the observed mortality, predicted mortality and reported number of ILI cases per week for the entire period. We see that the predicted mortality is close to the observed, indicating a good model fit. The figure also shows how the mortality and ILI peaks coincided in most seasons, but not in the pandemic 2009/2010 season. The lower panel of Figure 3 shows the observed mortality together with the predicted mortality without the ILI contribution (with 95% confidence intervals for the latter). The estimated excess mortality is, by the definition in Eq. (3), found as the difference between these two solid lines.
Figure 3. Observed overall mortality, predicted mortality and reported number of influenza-like illness (ILI) cases per week (upper panel), together with observed mortality and predicted mortality without ILI contribution with 95% confidence intervals (lower panel), for all age groups in Norway 1999–2011, using the Poisson model in Eq. (1).
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Analyses were also carried out for age groups. Table 3 shows the effect of ILI on mortality (β3), the effect of the interaction between ILI and wave 1 and wave 2 of the pandemic season (β4), the overall mean estimated seasonal excess mortality and estimated excess mortality in the pandemic season using the estimator in Eq. (3), for all age groups and in total. The results are compared with an analysis using P&I deaths for all age groups. Note that numbers for all age groups do not equal the sum of the numbers for age groups alone, as they were estimated using separate models. We see that the largest effect of ILI on mortality is in the youngest and oldest age groups. For the 15–64 age group, there is no significant excess mortality. For the interaction terms, only wave 2 is significant in the 0–4, 5–14 or 15–64 groups, while in the 65+ group and for overall data, there is a significant interaction effect both during wave 1 and wave 2. A significant interaction term means that the ILI effect on mortality is significantly different during the specific pandemic wave than during the rest of the season. All the significant effects are negative, meaning that the impact of ILI during the pandemic was less than in regular seasons. Further, we see that the results from the pandemic season do not differ much from the seasonal average for the 0–4, 5–14 and 15–64 age groups, but are much lower than average for the 65+ group (and then naturally also the overall group). Note, however, that the uncertainty is very high for estimates during the pandemic period.
Table 3. Regression results using the model in Eq. (1) and estimated excess mortality for age groups and overall analyses using the estimator in Eq. (3)
|Age group||β3 ILI (P-value)||β4 interaction (P-value) for ILI × wave 1 and wave 2||Mean estimated excess mortality per season 1998/1999–2010/2011 (rate per 100 000 pop.) [95% CI] ||Estimated excess mortality pandemic season (rate per 100 000 pop.) [95% CI]|
|Analysing all-cause mortality|
|0–4||0·0376 (0·0575)|| ||6 (2·1) [1 (0·3)–11 (3·7)]||7 (2·4) [−15 (−4·8)–30 (9·9)]|
|5–14||0·0879 (0·0232)|| ||4 (0·7) [1 (0·2)–7 (1·1)]||3 (0·5) [−5 (−0·9)–13 (2·2)]|
|15–64||0·0055 (0·1787)|| ||22 (0·7) [−9 (−0·3)–54 (1·8)]||13 (0·4) [−96 (−3·0)–128 (4·0)]|
|65+||0·0339 (<0·0001)|| ||727 (104·3) [638 (91·5)–844 (121·1)]||30 (4·1) [−276 (−37·9)–338 (46·4)]|
|All||0·0300 (<0·0001)|| ||766 (16·6) [667 (14·4)–883 (19·1)]||56 (1·17) [−228 (−6·0)–380 (7·9)]|
|Analysing P&I-certified mortality|
|All||0·1322 (<0·0001)|| ||172 (3·7) [156 (3·4)–188 (4·0)]||96 (2·0) [43 (0·9)–148 (3·1)]|
Figure 4 shows the results from the modelling of the P&I data. Even though the analysis of P&I deaths generally gave lower estimates of excess mortality, the estimate for the pandemic season was somewhat higher than when analysing all-cause mortality, with an excess mortality estimate of 96 deaths per year (2·0 per 100 000 in the population) for all age groups. Due to what might be less noise in the P&I data, the model uncertainty is smaller than in the analysis of overall deaths, and we find a significant excess mortality during the pandemic period.
Figure 4. Observed P&I mortality, predicted mortality and reported number of influenza-like illness (ILI) cases per week (upper panel), together with observed mortality and predicted mortality without ILI contribution with 95% confidence intervals (lower panel), for all age groups in Norway 2000–2011, using the Poisson model in Eq. (1).
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Results from the EuroMOMO analysis are presented in Table 4. Note again that the overall numbers do not equal the sum of age-grouped numbers as they were estimated using separate models. The estimates from EuroMOMO are higher in the 15–64 and 65+ groups than the estimates using Eq. (3). The total number of excess mortality in the pandemic season was here estimated to be 252 deaths.
Table 4. Observed number of overall deaths, expected deaths and excess deaths, for age groups and overall, in Norway 2009–2010, using the EuroMOMO consensus method
|Weeks||Age group||Observed deaths||Expected deaths||Excess deaths (rate per 100 000 pop.)|
|29–52 (both waves)||0–4||103||98||5 (1·7)|
|65+||15 306||15 159||147 (20·1)|
|All||18 482||18 230||252 (5·2)|
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- Declaration of interest
We have compared the number of influenza-certified deaths during the 2009 influenza pandemic in Norway with the results from two models for estimating seasonal excess mortality due to influenza. The model based on Eq. (1) gives an estimated excess mortality of 56 deaths analysing all-cause mortality and an estimate of 96 deaths using P&I-certified deaths. Only the excess mortality found analysing P&I deaths is significant. The EuroMOMO model gives an estimate of 252 deaths, without stating uncertainty. The numbers from the ad hoc registry for pandemic deaths at NIPH are smaller than all of the above, with 32 deaths attributed to influenza.
Age-grouped analysis suggests some excess mortality in the lower age groups, although the estimates are far from significant, not noticeably different than in non-pandemic seasons. This finding may seem to contradict the actual reported deaths presented in Figure 2. An explanation can be that the enhanced death surveillance during the pandemic, including a more widespread use of laboratory tests for influenza, detected more of the actual deaths than during non-pandemic periods, especially among children and young adults.
Most of the estimated deaths occurred among the elderly. However, the excess mortality estimates for the 65+ group are lower during the 2009/2010 pandemic season than any other seasons. The model in Eq. (1) gives an estimated excess mortality of 30 deaths in the 65+ group in the pandemic season, versus an average mortality of 766 deaths for all seasons. The data on influenza-certified deaths also indicate a non-typical age distribution, with a much higher proportion of deaths taking place in the younger age groups. The major part of the mortality was among people below the age of 65, contrary to what we see during a typical seasonal winter influenza outbreak.
Our estimated excess mortality using P&I-certified deaths for all seasons was only about a fourth of the estimate using all-cause deaths, but during the pandemic, the P&I estimate was higher, and statistically significant, in contrast to the estimates based on all-cause data. However, even though P&I deaths have less noise than the all-cause mortality data, we believe that using P&I deaths underestimates the mortality burden of influenza, especially among the elderly. Several recent articles point to influenza as a trigger of acute myocardial infarction (AMI), which is a major cause of death in most countries, including Norway. For instance, Warren-Gash et al. found that 3·1–3·4% of AMI-associated deaths in England and Wales were attributable to influenza. The association was further supported by their self-controlled cases series study. Foster et al. found similar results in USA.
The Poisson regression model in Eq. (1) gave similar results as in Gran et al. for all overlapping seasons, even though the data covered twice the time span as in the original study. The results for the pandemic season were lower in comparison with the results using the EuroMOMO model, which partly can be explained by the use of the more moderate estimator in Eq. (3) compared with the more common estimator in Eq. (2). One should also note the large uncertainty present when analysing the pandemic season alone, especially when analysing all-cause mortality. It is likely that uncertainty in the EuroMOMO estimates, which are not reported, are of similar magnitude. Regarding other model choices, such as the different ways to model week-to-week and season-to-season variation, the results from the EuroMOMO model and the different variants of the model in Eq. (1) indicate that the excess mortality estimates are not very sensitive to these model choices.
It is important to note that the data from the extended pandemic death surveillance at NIPH and the Cause of Death Registry are not directly comparable with the excess mortality estimated from the model in Eq. (1) and the EuroMOMO method. As previously mentioned, it is often hard to discern between influenza and other contributing factors. And influenza is often seen as a contributing factor as it often aggravates other underlying illnesses such as serious heart and lung diseases. This is especially obvious in the elderly population, above 65 years, as they more often have several chronic underlying illnesses.
The mortality associated with the 2009 influenza pandemic has been a topic in many recent papers, some of which use excess mortality modelling. For example, Poisson models were used to estimate the influenza-related excess mortality in Hong Kong, before and during the pandemic season. Contrary to our analyses, they found that the mortality during the whole of 2009 was comparable with those in the preceding ten interpandemic years, with no real difference among age groups. A study in USA, on the other hand, estimated a higher excess mortality during the pandemic for people below 65 years of age and lower excess mortality for people in the 65+ group, compared with prior seasons. For people below 15 years of age, the excess mortality was higher than in any prior season between 1962/1963 and 2008/2009. Another US study found a mean age of deaths of 37 years during the pandemic, compared with an estimated mean age of 76 during seasonal influenza epidemics. A study estimating the excess mortality in England and Wales between 1999 and 2010 found the highest mortality burden among the 75+ age group, with the lowest mortality during the 2009/2010 pandemic season.
Excess mortality monitoring in England and Wales during the pandemic showed excess all-cause mortality in the 5–14 years age group, and in age groups >45 years ‘during a period of very cold weather’. Surveillance data from Finland and Denmark both showed high morbidity and high rates of hospital admissions in younger age groups compared with previous influenza seasons. A review of pandemic deaths in Alberta, Canada, showed that the mortality rate during the pandemic was the third highest in the period 1983 to 2010 and that the mean age of deaths was significantly younger by close to 30 years.
All the results suggest that the majority of the mortality took place during the main wave of the pandemic (October–December), which is in line with the general perception of the impact of the pandemic. It also appears that the mortality in Norway peaked earlier, but was not higher than other European countries. The fact that Norway had enhanced its mortality surveillance and the extremely high media attention probably ensured very rapid reporting of the fatalities.
The results from the two models considered in this study to different extent suggest an additional excess mortality during the 2009 pandemic beyond what is reported to the extended pandemic death surveillance at NIPH and the Cause of Death registry. The analysis of P&I deaths in particular finds an estimated excess mortality which is significantly higher than what was reported. Results as a whole indicates that this additional mortality is mainly found among people in the oldest age groups, and one might also expect that deaths among people in the older age groups in general are less likely to be detected in pandemic surveillance than deaths among younger age groups. However, it is important to note that this higher estimated excess mortality among the elderly is considerably lower during the 2009 pandemic than during regular influenza outbreaks. In other words, the results from the modelling suggest that the 2009 pandemic was less severe for people in the older age groups than during regular seasonal influenza. Reasons for this could be that many elderly people had acquired immunity to the pandemic virus through previous exposure to similar influenza viruses or through vaccination against the A(H1N1)pdm09 virus, which in Norway started at mid-October 2009 and eventually covered around 45% of the population, including the 65+ age group. The early and atypical time of onset of the epidemic may also have played a part.
From our results (Table 2), it is evident that there exists a great variation in mortality between seasonal influenza epidemics. This variation, perhaps partly mediated by variation in age distribution, probably results from a complex interplay between circulating influenza subtype virulence and transmissibility and population immunity to that virus. We note also that the pandemic seemed to be causing a lower excess mortality than recent seasonal epidemics. Thus, the dichotomy between seasonal influenza and pandemic influenza may not be so important for public health planning. Rather, it seems more important to assess the severity of every influenza epidemic, as suggested by the review of WHO's response to the pandemic and followed up by both WHO and Centers for Disease Control and Prevention (CDC).
Our findings may have several implications for public health practice. Surveillance of deaths during a pandemic may provide information for public health action. In communications with the public, authorities need to be absolutely clear about whether they are communicating actual registered deaths or estimated excess deaths. Norway should consider setting up a system, like the EuroMOMO system, for continuous monitoring of excess deaths due to influenza, other infectious diseases and extreme ambient temperatures.
Further research is necessary to understand the true mortality burden of influenza. This requires better criteria for when and how to attribute deaths to influenza.
Data on reported deaths due to influenza have its limitations, as influenza is often overseen as a contributing underlying cause of death among people with other underlying diseases. However, registries of reported causes of deaths serve an important purpose with a high information yield on those actually detected, for example, on co-morbidities, demography and virology. To give a good assessment of the total number of deaths, excess mortality modelling can be a better indicator.
Finally, it remains clear that deaths are only one part of the burden of influenza. In Norway, the 2009 pandemic led to far more cases of influenza, hospitalizations and intensive care admissions than regular influenza epidemics.[26-28] Estimates of influenza-associated excess mortality during the A(H1N1)pdm09 influenza pandemic suggest that the mortality might have been higher than reported, especially among the 65+ age group, but that these numbers were much lower than in regular seasonal influenza epidemics.