Differential Effects of Pandemic (H1N1) 2009 on Remote and Indigenous Groups, Northern Territory, Australia, 2009

TOC summary: Vaccination campaigns and public health responses should focus on high-risk groups.

U nderstanding the epidemiology of pandemic infl uenza is essential in directing public health responses, not only to the current pandemic, but also for recurrent waves of the same virus and future infl uenza pandemics. Knowledge of the distribution of protective immunity enables prediction of groups susceptible to reemergence of the virus and thus helps to improve effi cacy of vaccine programs. Infl uenza has uneven effects across demographic and geographic groups, which may contribute to the increases in illness and death sometimes seen with subsequent waves (1,2). There is an emerging understanding of the effects of the outbreak of pandemic (H1N1) 2009 on indigenous populations, but little is known of the virus's effect on remote and socioeconomically disadvantaged groups.
Direct serologic measures of population immunity are useful in assessing the effect of pandemic infl uenza, as case or surveillance-based measures of incidence of infection are dependent on recognition of symptoms, use of health services, and subsequent testing (3). In remote and ethnically diverse populations, the differential effect of these factors may be particularly marked.
The Northern Territory (NT) is a jurisdiction unique for its large area of 1.35 million km 2 (twice that of Texas) relative to its population of 225,000, of whom 30% are indigenous. The climate ranges from desert and semi-arid in central Australia to tropical in the northern "Top End" where the capital, Darwin, is located. There are also several smaller urban centers and many small, remote indigenous communities of 300-2,000 that may be >2 h fl ight from the nearest hospital. Indigenous Australians of the NT have considerably poorer health than the nonindigenous majority, with a life-expectancy gap of 15-20 years (4). Hemisphere winter (5). Despite enacting carefully prepared nationwide public health measures to delay viral entry and spread, widespread infection followed (6,7). Australia's fi rst case was reported on May 8, with the fi rst case in the NT reported on June 2 and the fi rst NT death occurring July 9 (8). Australia moved to the "protect" phase of its pandemic response on June 17 in an effort to limit illness and death from the virus (9), with notifi cations peaking nationwide and in the NT in July (10). We undertook serosurveys using opportunistically collected outpatient serum specimens from persons across the NT to estimate levels of pre-existing immunity and differential attack rates among demographic groups. Our study included a large proportion of remote-living persons, including Aboriginal and Torres Strait Islanders, enabling assessment of the differential effect of infl uenza upon these populations.

Specimens
Specimens were obtained from Western Diagnostic Pathology (Myaree, Western Australia, Australia), which provides outpatient pathology services covering most of the NT. Specimens were eligible for inclusion regardless of indication for testing, provided identifying information was complete and address was within the NT. We accepted only serum tubes with a residual volume >0.5 mL and obtained specimens before routine discarding. Baseline specimens were selected during January-May and all postpandemic specimens from September 2009.

Background Information
Data obtained for each specimen consisted of date of collection, patient's age in years at collection, gender, suburb/community of address, and a unique study identifi er. Identifying data (name and date of birth) were transferred directly from the laboratory to the Information Services Division of the NT Department of Health and Families for computer-matching to indigenous status. This was successful in 94.1% of cases, and the data were transferred to the investigators linked to the study identifi er. Of those cases with a successful match, 59.7% of patients were neither indigenous nor Torres Strait Islander, 39.7% were Aboriginal, 0.1% were Torres Strait Islander, and 0.6% were both Aboriginal and Torres Strait Islander. The suburb of patient's address for each specimen was linked to 2006 Statistical Local Area (SLA), the Australian Bureau of Statistics' general purpose base spatial unit, with 82 of 96 NT SLAs represented (11).
After testing, a small number of specimens were redistributed by region, following manual review of suburb of address linkage to SLA. The SLA code was also linked to the 11 statistical subdivisions and 7 health districts in the NT. Three study regions were defi ned, displayed in Figure 1, consisting of Urban Darwin; Rural Top End (Darwin Rural, East Arnhem, and Katherine districts); and Central Australia (Alice Springs Urban, Alice Springs Rural, and Barkly districts). SLA codes were then linked to the Australian Bureau of Statistics' Socio-Economic Indexes for Area (SEIFA) (12). These measures use information from census data relating to material and social resources and ability to participate in society to obtain a broad level of relative socioeconomic status for each SLA. For calculation of attack rates by quintile, the SEIFA index of relative disadvantage was used, while for regression analysis, the SEIFA index of relative advantage and disadvantage was preferred, as this index does not incorporate indigenous status.

Laboratory Methods
Antibody responses to pandemic (H1N1) 2009 infl uenza were assessed at the World Health Organization Collaborating Centre for Reference and Research on Infl uenza in North Melbourne, Victoria, Australia. Reactivity of serum against pandemic (H1N1) 2009 infl uenza was measured in 2140 serum samples by using hemagglutination inhibition (HI). Egg-grown A/ California/7/2009 virus was purifi ed by sucrose gradient, concentrated, and inactivated with β-propiolactone to create an infl uenza zonal pool preparation (a gift from CSL Ltd., Parkville, Victoria, Australia). Serum samples were pretreated with 1:4 vol/vol receptor-destroying enzyme II (Deka Seiken Co. Ltd., Tokyo, Japan) at 37°C for 16 h, then enzyme was inactivated by the addition of an equal volume of 54.4 mmol/L trisodium citrate (Ajax Chemicals, Taren Point, New South Wales, Australia) and incubated at 56°C for 30 min. A total of 25 μL (4 hemagglutinin units) infl uenza zonal pool preparation A/California/7/2009 virus or 25 μL phosphate-buffered saline ("no virus" control) was incubated at room temperature with an equal volume of receptor-destroying enzyme-treated serum. Serum specimens were titrated in 2-fold dilutions in phosphatebuffered saline from 1:10 to 1:1280. After a 1-h incubation, 25 μL of 1% vol/vol turkey erythrocytes was added to each well. HI was read after 30 min. Any samples that bound the erythrocytes in the absence of virus were adsorbed with erythrocytes for 1 hour and reassayed. Six samples bound erythrocytes in the absence of virus and were excluded from analysis. Titers were expressed as the reciprocal of the highest dilution of serum at which hemagglutination was prevented.
A panel of control and serum samples were run in addition to the test serum samples for all assays.

Study Population
We aimed to estimate the proportion of persons with serologic immunity in each of 12 groups in the postpandemic sample, consisting of 4 age groups (<14, 15-34, 35-54, and >55 y) within each of the 3 study regions described. In the postpandemic group, we calculated a required sample size of 195 specimens per group (for a total of 2,340 specimens) on the basis of an estimate of 15% immunity with a 95% confi dence interval (CI) of 10%-20%.
In the baseline group, we aimed to provide an agespecifi c, NT-wide estimate of preexisting immunity and calculated a single sample size for each of the same 4 age groups described. We did not stratify by region and assumed increasing prepandemic immunity with age (2% in those <14 y, 5% in those 15-54 y, and 15% in those >55 y).
Samples were chosen at random from each stratum and checked for representativeness of the NT population by gender and region before testing. Data on indigenous status were obtained from Information Services only after fi nal selection of specimens.

Analytic Methods
For all analyses, immunity was defi ned as an HI titer ≥40, consistent with published data (13) and the observation that titers of this order develop in 90% of persons <21 days of illness (14). Attack rates were calculated as the difference in proportion immune between the September category and the total baseline group, except for age-specifi c attack rates where the age-specifi c baseline proportion was used as the reference. All attack rate calculations were population standardized, with weights calculated separately for preand postpandemic samples, based on the demographic characteristics of the 2009 NT population by age-group, indigenous status, and study region. Regression models and proportions immune are displayed unweighted. Statistical analysis was performed with Stata version 11.0 (StataCorp LP, College Station, TX, USA).

Ethical Approval
We obtained ethical approval from the Menzies School of Health Research Human Research Ethics Committee and the Central Australia Human Research Ethics Committee. We continued to liaise with the Aboriginal and Torres Strait Islander subcommittees of both ethics committees throughout the study.

Baseline Immunity
A total of 445 specimens taken January 10-May 29 were selected from 10,575 available serum tubes (Table 1). Within each age group sampled, the baseline sample was representative of the 2009 NT population (15) by gender, indigenous status, and study region, except that higher proportions of indigenous Australians were seen in the 2 older age brackets. There was no tendency toward an increase in the proportion of specimens with protective immunity over the 5 months from which baseline specimens were taken (p = 0.79, by χ 2 test for trend).
A total of 34 of 445 baseline specimens (7.6%, 95% CI 5.2%-10.1%) had HI titers >40. Multivariate logistic regression revealed no difference in baseline immunity by gender, indigenous status, study region, or index of socioeconomic disadvantage (p>0.05), with increasing age in years the only signifi cant independent predictor of prepandemic immunity (p = 0.003). Although not statistically signifi cant on the regression model, the proportion of specimens with titers >40 appeared higher in Central Australia (14.0%) than Urban Darwin and Rural Top End (5.6%). Immunity was nevertheless evenly spread geographically within these regions.

Postpandemic Immunity
A total of 1,689 specimens collected September 3-30, 2009, were selected from 3,228 available. Because of insuffi cient numbers of specimens, the required sample size was not achieved in 5 of 12 postpandemic groups. The September samples were representative of the 2009 NT population by gender but again included higher proportions of specimens from indigenous Australians in the older age brackets. An HI titer >40 was seen in 329 specimens (19.5%, 95% CI 17.6%-21.4%), with proportions by study group shown in Table 2, geometric mean titers in Figure  2, and reverse cumulative distributions in Figure 3. There was a nonsignifi cant trend toward a decreasing proportion of specimens with protective immunity over the 5 weeks from which the September specimens were taken (p = 0.20, by χ 2 test for trend). Table 3 shows the results of multivariate logistic regression analysis for the 1,592 postpandemic specimens for which the indigenous status of patients was known. No association was detected between immunity and gender, socioeconomic status, or study region. However, younger age and indigenous status were independently associated with immunity. A measure of remoteness was examined as a possible exposure variable, but colinearity with region meant that it was not a useful predictor variable and therefore was not included in regression analysis (16).
The proportion immune in September was geographically heterogeneous across the 3 study regions (p<0.001, by χ 2 test). The same pattern was seen for Statistical Subdivisions (p<0.001, by χ 2 test), with proportionate immunity ranging from 7.5% to 42.9%, as illustrated in Figure 4. The picture of heterogeneity was also seen for the indigenous population considered separately. However, the prevalence of postpandemic immunity was more homogeneous for the nonindigenous population considered by either geographic classifi cation and for urban Darwin considered separately. Figure 5 demonstrates that while postpandemic levels of immunity were relatively homogeneous by SLA in less disadvantaged, generally urban areas, comparatively disadvantaged areas had more variable levels of immunity.

Attack Rates
As shown in Table 4, attack rates by age group were markedly higher in younger groups, reaching approximately 1 in 3 among children <14 years of age. Indigenous Australians were also disproportionately affected, with attack rates of ≈1 in 4, which were 1.85-fold higher than

Discussion
Our study is an outpatient-based serologic survey of the impact of pandemic infl uenza over a large geographic region. Because of our broad sampling base, we have been able to estimate attack rates across the NT population and to assess the differential impact of the virus on the indigenous population. We calculated a population attack rate of ≈15% but found marked differences in patterns of exposure by indigenous status, geographic location, and age. Younger age groups and indigenous Australians were disproportionately affected, with striking geographic variations seen.
Baseline immunity could be overestimated if undetected virus circulation was occurring during our prepandemic period. We believe this is unlikely, as there was no trend toward increasing immunity in samples taken at a later date, no child had a baseline titer >10, and the fi rst confi rmed case was not detected in the NT until May 29 (17). Similarly, our September sample could have underestimated true postpandemic immunity caused by ongoing infection during this month. However, emergency department presentations of infl uenza-like illness had returned to baseline by this time, and there were few laboratory-confi rmed cases during this period. Similarly, no increase in immunity was observed during September in our study. Because the national pandemic vaccination program in Australia commenced in NT on September 30, testing of specimens before this date would be unaffected by antibodies produced by vaccination (18).
Although we attempted to ensure that our sample was demographically representative of the NT population, the prevalence of risk factors for infl uenza infection may be different in our sample from that of the general population. In particular, chronic disease and pregnancy may have been overrepresented among patients presenting for outpatient pathologic analysis. However, because clinical data, including indication for testing, were not available, the strength of this possible effect cannot be assessed.
We found a prevalence of preexisting immunity of 3.6% in those born after 1980 and of 0% in children. In those born before 1950, the level of pre-existing immunity was 13.7%, which is lower than data from North America (19,20). This may refl ect regional differences or be the result of the 1976 mass-vaccination campaign against swineorigin H1N1 virus because seasonal infl uenza vaccination does not produce protective titers against the pandemic (H1N1) 2009 virus. Despite this fi nding, serologic data from a population in China with low seasonal vaccine coverage found lower levels of preexisting immunity (21), although comparable levels of preexisting immunity were seen in Singapore (22).
Our fi ndings of a postpandemic proportion immune rate of 19.5%, attack rate of 14.9%, and the association with younger age are consistent with other published data (14,22), although the difference in post-pandemic immunity in the Australian indigenous population has not been reported. Our overall attack rate was notably higher than the estimated clinical attack rate of 7.2% extrapolated from surveillance data (23). Moreover, the incidence rate ratio between indigenous and nonindigenous populations 1620 Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 17, No. 9, September 2011  based on the number of laboratory-confi rmed cases was 4.9, notably greater than our 2-fold ratio. However, the ratio in serologic attack rates between Central Australia and the Top End was ≈1.5 and consistent with the ratio from laboratory-confi rmed cases (23). Data from notifi cations and hospitalizations in the Top End indicate that the prevalence of risk factors in patients admitted with pandemic infl uenza was similar between indigenous and nonindigenous patients (24), suggesting that the increased frequency of admissions in indigenous persons was because of the greater prevalence of risk factors for severe disease. Australian indigenous populations have more respiratory infections than nonindigenous groups (25), and the higher pandemic attack rate in this group is also consistent with their overrepresentation in admissions to intensive care units (26). North American indigenous persons also have a greatly increased risk for hospitalization and death from pandemic (H1N1) 2009 infl uenza compared with their nonindigenous counterparts, particularly at extremes of age (27). However, Australia has among the greatest differences in rates of hospitalization and mortality between indigenous and nonindigenous populations in the Americas and Pacifi c regions (28). For this reason, the NT Centre for Disease Control has identifi ed this group as a particular focus of the univalent pandemic infl uenza vaccination program, achieving coverage of 24% overall and 41% in the indigenous population.
We used the Australian Bureau of Statistics SEIFA index as our measure of relative socioeconomic disadvantage (12). By this measure, the most disadvantaged quintile appeared to have higher rates of infection. However, this fi nding was not borne out by multivariate analysis, suggesting confounding by other variables, particularly indigenous status and remoteness, which are highly correlated in NT. Moreover, accurate estimates of socioeconomic disadvantage are notoriously diffi cult to attain (29) and, when measured by area, are at best at an average level of deprivation.
We observed marked differences in the postpandemic proportion immune between Statistical Subdivisions, with the degree of heterogeneity being particularly prominent among indigenous and remote populations. This variability in infl uenza infections has been noted from surveillance data (30) and serologic survey data (14). Although many Aboriginal communities in the NT are remote and isolated, a large proportion of persons from remote communities demonstrate intercommunity mobility (31). The Aboriginal population of the NT is known to have high rates of chronic diseases, including conditions identifi ed as increasing susceptibility to infl uenza (4,32), such as poor housing (33) and sanitation (34). These factors, in particular overcrowding, are likely to facilitate transmission of infl uenza once the disease is present within a community.  Our results suggest that although some communities were severely affected, others may have been less affected by the pandemic because of their isolation. These communities are likely to be particularly susceptible to subsequent waves of infection because East Arnhem communities were particularly hard hit by pandemic (H1N1) 2009 in 2010, and Central Australia communities were relatively spared. Moreover, the fi rst cluster of laboratory-confi rmed cases since the fi rst pandemic wave occurred in June and July 2010 in the SLA with the lowest postpandemic proportional immunity of any SLA represented by >20 specimens (2/38, 5.4%).
Our serosurvey indicates that the full effect of the infl uenza pandemic on the NT may have been underestimated and highlights the differential impact of the virus on vulnerable groups, including children and indigenous populations. Our fi ndings show similarities to other published data, but the results are more likely to be applicable to remote-living and ethnically diverse populations. Given that in all groups, the majority of the population is likely to remain susceptible to the virus following the pandemic, vaccination campaigns and public health responses are essential and should focus on highrisk groups, which requires respectful engagement with communities. 14.6 (7.5-26.8) 2 24.0 (14.6-33.5) 1 (most disadvantaged) 13.8 (6.9-20.6) *Australian Bureau of Statistics' Socio-Economic Indexes for Area index of relative socioeconomic advantage and disadvantage.