Novel genetic markers for chronic kidney disease in a geographically isolated population of Indigenous Australians: Individual and multiple phenotype genome-wide association study.

BACKGROUND: Chronic kidney disease (CKD) is highly prevalent among Indigenous Australians, especially those in remote regions. The Tiwi population has been isolated from mainland Australia for millennia and exhibits unique genetic characteristics that distinguish them from other Indigenous and non-Indigenous populations. Notably, the rate of end-stage renal disease is up to 20 times greater in this population compared to non-Indigenous populations. Despite the identification of numerous genetic loci associated with kidney disease through GWAS, the Indigenous population such as Tiwi remains severely underrepresented and the increased prevalence of CKD in this population may be due to unique disease-causing alleles/genes. METHODS: We used albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) to estimate the prevalence of kidney disease in the Tiwi population (N = 492) in comparison to the UK Biobank (UKBB) (N = 134,724) database. We then performed an exploratory factor analysis to identify correlations among 10 CKD-related phenotypes and identify new multi-phenotype factors. We subsequently conducted a genome-wide association study (GWAS) on all single and multiple phenotype factors using mixed linear regression models, adjusted for age, sex, population stratification, and genetic relatedness between individuals. RESULTS: Based on ACR, 20.3% of the population was at severely increased risk of CKD progression and showed elevated levels of ACR compared to the UKBB population independent of HbA1c. A GWAS of ACR revealed novel association loci in the genes MEG3 (chr14:100812018:T:A), RAB36 (rs11704318), and TIAM2 (rs9689640). Additionally, multiple phenotypes GWAS of ACR, eGFR, urine albumin, and serum creatinine identified a novel variant that mapped to the gene MEIS2 (chr15:37218869:A:G). Most of the identified variants were found to be either absent or rare in the UKBB population. CONCLUSIONS: Our study highlights the Tiwi population's predisposition towards elevated ACR, and the collection of novel genetic variants associated with kidney function. These associations may prove valuable in the early diagnosis and treatment of renal disease in this underrepresented population. Additionally, further research is needed to comprehensively validate the functions of the identified variants/genes.

Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks.

BACKGROUND: The extent to which known and unknown factors explain how much people of the same age differ in disease risk is fundamental to epidemiology. Risk factors can be correlated in relatives, so familial aspects of risk (genetic and non-genetic) must be considered. DEVELOPMENT: We present a unifying model (VALID) for variance in risk, with risk defined as log(incidence) or logit(cumulative incidence). Consider a normally distributed risk score with incidence increasing exponentially as the risk increases. VALID's building block is variance in risk, Δ2, where Δ = log(OPERA) is the difference in mean between cases and controls and OPERA is the odds ratio per standard deviation. A risk score correlated r between a pair of relatives generates a familial odds ratio of exp(rΔ2). Familial risk ratios, therefore, can be converted into variance components of risk, extending Fisher's classic decomposition of familial variation to binary traits. Under VALID, there is a natural upper limit to variance in risk caused by genetic factors, determined by the familial odds ratio for genetically identical twin pairs, but not to variation caused by non-genetic factors. APPLICATION: For female breast cancer, VALID quantified how much variance in risk is explained-at different ages-by known and unknown major genes and polygenes, non-genomic risk factors correlated in relatives, and known individual-specific factors. CONCLUSION: VALID has shown that, while substantial genetic risk factors have been discovered, much is unknown about genetic and familial aspects of breast cancer risk especially for young women, and little is known about individual-specific variance in risk.

Computed tomography scan radiation and brain cancer incidence.

BACKGROUND: Computed tomography (CT) scans make substantial contributions to low-dose ionizing radiation exposures, raising concerns about excess cancers caused by diagnostic radiation. METHODS: Deidentified medicare records for all Australians aged 0-19 years between 1985-2005 were linked to national death and cancer registrations to 2012. The National Cancer Institute CT program was used to estimate radiation doses to the brain from CT exposures in 1985-2005, Poisson regression was used to model the dependence of brain cancer incidence on brain radiation dose, which lagged by 2 years to minimize reverse causation bias. RESULTS: Of 10 524 842 young Australians, 611 544 were CT-exposed before the age of 20 years, with a mean cumulative brain dose of 44 milligrays (mGy) at an average follow-up of 13.5 years after the 2-year lag period. 4472 were diagnosed with brain cancer, of whom only 237 had been CT-exposed. Brain cancer incidence increased with radiation dose to the brain, with an excess relative risk of 0.8 (95% CI 0.57-1.06) per 100 mGy. Approximately 6391 (95% CI 5255, 8155) persons would need to be exposed to cause 1 extra brain cancer. CONCLUSIONS: For brain tumors that follow CT exposures in childhood by more than 2 years, we estimate that 40% (95% CI 29%-50%) are attributable to CT Radiation and not due to reverse causation. However, because of relatively low rates of CT exposure in Australia, only 3.7% (95% CI 2.3%-5.4%) of all brain cancers are attributable to CT scans. The population-attributable fraction will be greater in countries with higher rates of pediatric scanning.

Cohort profile: The Australian Paediatric Exposure to Radiation Cohort (Aust-PERC).

Although the carcinogenic effects of high-dose radiation are well-established, the risks at low doses, such as from diagnostic X-rays, are less well understood. Children are susceptible to radiation induced cancers, and in the last decade, several cohort studies have reported increased cancer risks following computed tomography (CT) scans in childhood. However, cohort studies can be limited by insufficient follow-up, indication bias, reverse causation, or by lack of organ doses from CT scans or other exposures. Aust-PERC is a retrospective cohort designed to study the effects of low-dose medical radiation exposure, primarily from CT scans, in young Australians. The cohort was ascertained using deidentified billing records from patients who were aged 0-19 years while enrolled in Medicare (Australia's universal healthcare system) between 1985 and 2005. All procedures billed to Medicare in this age/time window that involved low-dose radiation were identified, and persons without such procedures were flagged as unexposed. The Aust-PERC cohort has been linked, using confidential personal identifiers, to the Australian Cancer Database and the National Death Index, on two occasions (to Dec. 2007 and Dec. 2012) by the responsible government agency (Australian Institute of Health and Welfare). Deidentified Medicare service records of all radiological procedures including CT scans, nuclear medicine (NM) scans and fluoroscopy and plain X-ray procedures have been available to derive estimated radiation doses in the cohort. Records of other medical and surgical procedures, together with demographic and socioeconomic variables are being used in analyses to assess biases arising from reverse causation and confounding. After excluding patients with errant records, 11 802 846 persons remained in the baseline cohort, with an average follow-up time of 22.3 years to December 2012. There were 275 489 patients exposed to diagnostic nuclear medicine scans and 688 363 patients exposed to CT scans before age 20 and before cancer diagnosis. Between 1 January 1985 and 31 December 2012, there were 105 124 deaths and 103 505 incident cancers. Dose-response analyses based on the relevant organ doses are underway for individual cancers, and we plan to extend the follow-up for another 8 years to Dec 2020. Analyses using this very large Aust-PERC cohort, with extended follow-up, will help to resolve international uncertainties about the causal role of diagnostic medical radiation as a cause of cancer.

Ct Dosimetry for The Australian Cohort Data Linkage Study.

Children undergoing computed tomography (CT) scans have an increased risk of cancer in subsequent years, but it is unclear how much of the excess risk is due to reverse causation bias or confounding, rather than to causal effects of ionising radiation. An examination of the relationship between excess cancer risk and organ dose can help to resolve these uncertainties. Accordingly, we have estimated doses to 33 different organs arising from over 900 000 CT scans between 1985 and 2005 in our previously described cohort of almost 12 million Australians aged 0-19 years. We used a multi-tiered approach, starting with Medicare billing details for government-funded scans. We reconstructed technical parameters from national surveys, clinical protocols, regulator databases and peer-reviewed literature to estimate almost 28 000 000 individual organ doses. Doses were age-dependent and tended to decrease over time due to technological improvements and optimisation.

CT scans in childhood predict subsequent brain cancer: Finite mixture modelling can help separate reverse causation scans from those that may be causal.

BACKGROUND: Excess brain cancers observed after computed tomography (CT) scans could be caused by ionizing radiation. However, as scans are often used to investigate symptoms of brain cancer, excess cancers could also be due to reverse causation bias. We used finite mixture models (FMM) to differentiate CT exposures that are plausibly causal from those due to reverse causation. METHODS: Persons with at least one CT scan exposure and a subsequent diagnosis of brain cancer were selected from a cohort of 11 million young Australians. We fitted FMMs and used the posterior probability to inform the choice of exclusion periods. We validated our findings using a separate clinical dataset describing the time between first symptoms and brain cancer diagnosis (pre-diagnostic symptomatic interval; PSI). RESULTS: The cohort included 1028 persons with a diagnosed brain tumor and exposed to a total of 1,450 CT scans. The best-fitting model was a generalized linear mixture model using the exponential distribution with three latent classes and two covariates (age at exposure and year of exposure). The 99th percentile classifier cutoff was 18.9 months. The sample-size weighted mean of the 99th percentile of the PSI, derived from clinical data, was 15.6 months. CONCLUSIONS: To minimize reverse causation bias in studies of CT scan and brain cancer, the optimal exclusion period is one to two years (depending on the choice of classifier). This information will inform the interpretation of current and future studies.

Analysis of the F2LR3 (PAR4) Single Nucleotide Polymorphism (rs773902) in an Indigenous Australian Population.

The F2RL3 gene encoding protease activated receptor 4 (PAR4) contains a single nucleotide variant, rs773902, that is functional. The resulting PAR4 variants, Thr120, and Ala120, are known to differently affect platelet reactivity to thrombin. Significant population differences in the frequency of the allele indicate it may be an important determinant in the ethnic differences that exist in thrombosis and hemostasis, and for patient outcomes to PAR antagonist anti-platelet therapies. Here we determined the frequency of rs773902 in an Indigenous Australian group comprising 467 individuals from the Tiwi Islands. These people experience high rates of renal disease that may be related to platelet and PAR4 function and are potential recipients of PAR-antagonist treatments. The rs773902 minor allele frequency (Thr120) in the Tiwi Islanders was 0.32, which is similar to European and Asian groups and substantially lower than Melanesians and some African groups. Logistic regression and allele distortion testing revealed no significant associations between the variant and several markers of renal function, as well as blood glucose and blood pressure. These findings suggest that rs773902 is not an important determinant for renal disease in this Indigenous Australian group. However, the relationships between rs773902 genotype and platelet and drug responsiveness in the Tiwi, and the allele frequency in other Indigenous Australian groups should be evaluated.

Diagnostic Nuclear Medicine for Paediatric Patients in Australia: Assessing the Individual's Dose Burden.

We report data for all Australians aged 0-19 y who underwent publicly funded nuclear medicine studies between 1985 and 2005, inclusive. Radiation doses were estimated for individual patients for 95 different types of studies. There were 374 848 occasions of service for 277 511 patients with a collective effective dose of 1123 Sievert (Sv). Most services were either bone scans (45%) or renal scans (29%), with renal scans predominating at younger ages and bone scans at older ages. This pattern persisted despite a 4-fold increase in the annual number of procedures. Younger children were more likely to experience multiple scans, with the third quartile of scans per patient dropping from two to one with patient age. The median effective dose per patient ranged from 1.3 mSv (4-7 y old) to 2.8 mSv (13-16 y old). This large data set provides valuable information on nuclear medicine services for young Australians in the period 1985-2005.

Exposure to ionizing radiation and brain cancer incidence: The Life Span Study cohort.

BACKGROUND: Ionizing radiation is a cause of cancer. This paper examines the effects of radiation dose and age at exposure on the incidence of brain cancer using data from the Life Span Study (LSS) of atomic bomb survivors. METHODS: The Radiation Effects Research Foundation website provides demographic details of the LSS population, estimated radiation doses at time of bomb in 1945, person years of follow-up and incident cancers from 1958 to 1998. We modelled brain cancer incidence using background-stratified Poisson regression, and compared the excess relative risk (ERR) per Gray (Gy) of brain dose with estimates from follow-up studies of children exposed to diagnostic CT scans. RESULTS: After exposure to atomic bomb radiation at 10 years of age the estimated ERR/Gy was 0.91 (90%CI 0.53, 1.40) compared with 0.07 (90%CI -0.27, 0.56) following exposure at age 40. Exposure at 10 years of age led to an estimated excess of 17 brain tumors per 100,000 person year (pyr) Gy by 60 years of age. These LSS estimates are substantially less than estimates based on follow-up of children exposed to CT scans. CONCLUSION: Estimates of ERR/Gy for brain cancers in the LSS and haemangioma cohorts seem much smaller than estimates of risk for young persons in the early years after exposure to CT-scans. This could be due to reverse causation bias in the CT cohorts, diagnostic error, measurement error with radiation doses, loss of early follow-up in the LSS, or non-linearity of the dose-response curve.

The changing use of pediatric CT in Australia.

BACKGROUND: Despite the medical benefits of CT, there are concerns about increased cancer risks following CT scans in childhood. OBJECTIVE: To assess Australian temporal trends in pediatric CT scans funded through Medicare over the period 1985 to 2005, as well as changes in the types of CT scanners used. MATERIALS AND METHODS: We studied de-identified electronic records of Medicare-funded services, including CT scans, that were available for children and adults younger than 20 years between 1985 and 2005. We assessed temporal trends using CT imaging rates by age, gender and anatomical region. Regulators provided CT scanner registration lists to identify new models installed in Australia and to date the introduction of new technologies. RESULTS: Between 1985 and 2005, 896,306 Medicare-funded CT services were performed on 688,260 individuals younger than 20 years. The imaging rate more than doubled during that time period. There were more than 1,000 CT scanners on registration lists during the study period. There were both a sharp increase in the availability of helical scanning capabilities from 1994 and significant growth in multi-detector CT scanners from 2000. CONCLUSION: Significant increases in the rate of pediatric CT scanning have occurred in Australia. This rate has stabilized since 2000, possibly a result of better understanding of cancer risks.

Chlamydia trachomatis from Australian Aboriginal people with trachoma are polyphyletic composed of multiple distinctive lineages.

Chlamydia trachomatis causes sexually transmitted infections and the blinding disease trachoma. Current data on C. trachomatis phylogeny show that there is only a single trachoma-causing clade, which is distinct from the lineages causing urogenital tract (UGT) and lymphogranuloma venerum diseases. Here we report the whole-genome sequences of ocular C. trachomatis isolates obtained from young children with clinical signs of trachoma in a trachoma endemic region of northern Australia. The isolates form two lineages that fall outside the classical trachoma lineage, instead being placed within UGT clades of the C. trachomatis phylogenetic tree. The Australian trachoma isolates appear to be recombinants with UGT C. trachomatis genome backbones, in which loci that encode immunodominant surface proteins (ompA and pmpEFGH) have been replaced by those characteristic of classical ocular isolates. This suggests that ocular tropism and association with trachoma are functionally associated with some sequence variants of ompA and pmpEFGH.

Short-term risk of colorectal cancer in individuals with lynch syndrome: a meta-analysis.

PURPOSE: For carriers of germline mutations in DNA mismatch repair genes, the most relevant statistic for cancer prevention is colorectal cancer (Lynch syndrome) risk, particularly in the short term. METHODS: We conducted a meta-analysis of all independent published Lynch syndrome studies reporting age- and sex-dependent colorectal cancer risks. We estimated 5-year colorectal cancer risk over different age groups, separately for male and female mutation carriers, and number needed to screen to prevent one death. RESULTS: We pooled estimates from analyses of 1,114 Lynch syndrome families (508 with MLH1 mutations and 606 with MSH2 mutations). On average, one in 71 male and one in 102 female MLH1 or MSH2 mutation carriers in their 20s will be diagnosed with colorectal cancer in the next 5 years. These colorectal cancer risks increase with age, peaking in the 50s (one in seven males and one in 12 females), and then decrease with age (one in 13 males and one in 19 females in their 70s). Annual colonoscopy in 16 males or 25 females in their 50s would prevent one death from colorectal cancer over 5 years while resulting in almost no serious complications. In comparison, annual colonoscopy in 155 males or 217 females in their 20s would prevent one death while resulting in approximately one serious complication. CONCLUSION: For MLH1 or MSH2 mutation carriers, current guidelines recommend colonoscopy every 1 to 2 years starting in their 20s. Our findings support this regimen from age 30 years; however, it might not be justifiable for carriers who are in their 20s.

Cancer risk in 680,000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 million Australians.

OBJECTIVE: To assess the cancer risk in children and adolescents following exposure to low dose ionising radiation from diagnostic computed tomography (CT) scans. DESIGN: Population based, cohort, data linkage study in Australia. COHORT MEMBERS: 10.9 million people identified from Australian Medicare records, aged 0-19 years on 1 January 1985 or born between 1 January 1985 and 31 December 2005; all exposures to CT scans funded by Medicare during 1985-2005 were identified for this cohort. Cancers diagnosed in cohort members up to 31 December 2007 were obtained through linkage to national cancer records. MAIN OUTCOME: Cancer incidence rates in individuals exposed to a CT scan more than one year before any cancer diagnosis, compared with cancer incidence rates in unexposed individuals. RESULTS: 60,674 cancers were recorded, including 3150 in 680,211 people exposed to a CT scan at least one year before any cancer diagnosis. The mean duration of follow-up after exposure was 9.5 years. Overall cancer incidence was 24% greater for exposed than for unexposed people, after accounting for age, sex, and year of birth (incidence rate ratio (IRR) 1.24 (95% confidence interval 1.20 to 1.29); P<0.001). We saw a dose-response relation, and the IRR increased by 0.16 (0.13 to 0.19) for each additional CT scan. The IRR was greater after exposure at younger ages (P<0.001 for trend). At 1-4, 5-9, 10-14, and 15 or more years since first exposure, IRRs were 1.35 (1.25 to 1.45), 1.25 (1.17 to 1.34), 1.14 (1.06 to 1.22), and 1.24 (1.14 to 1.34), respectively. The IRR increased significantly for many types of solid cancer (digestive organs, melanoma, soft tissue, female genital, urinary tract, brain, and thyroid); leukaemia, myelodysplasia, and some other lymphoid cancers. There was an excess of 608 cancers in people exposed to CT scans (147 brain, 356 other solid, 48 leukaemia or myelodysplasia, and 57 other lymphoid). The absolute excess incidence rate for all cancers combined was 9.38 per 100,000 person years at risk, as of 31 December 2007. The average effective radiation dose per scan was estimated as 4.5 mSv. CONCLUSIONS: The increased incidence of cancer after CT scan exposure in this cohort was mostly due to irradiation. Because the cancer excess was still continuing at the end of follow-up, the eventual lifetime risk from CT scans cannot yet be determined. Radiation doses from contemporary CT scans are likely to be lower than those in 1985-2005, but some increase in cancer risk is still likely from current scans. Future CT scans should be limited to situations where there is a definite clinical indication, with every scan optimised to provide a diagnostic CT image at the lowest possible radiation dose.

Post-streptococcal glomerulonephritis is a strong risk factor for chronic kidney disease in later life.

Although unusual in western countries and in Australia in general, post-streptococcal glomerulonephritis (PSGN) is still common in Australian Aboriginal children living in remote communities. Here, we evaluated whether episodes of acute PSGN increased the risk for chronic kidney disease in later life in 1519 residents of a remote Aboriginal community (85% of those age eligible), with high rates of renal and cardiovascular disease, who participated in a health screen over a 3-year period. Of these, 200 had had at least one episode of PSGN, with 27 having had multiple episodes, usually in childhood. High levels of albuminuria (albumin/creatinine ratio) with increasing age were confirmed. All PSGN episodes were associated with group A streptococcal skin infections, often related to scabies. In both genders, aged 10-39 years at screening, about one in five had such a history. Among them, PSGN (5 years or more earlier) was significantly associated with higher levels of albuminuria than those without. In women, aged 30-39 years, a history of PSGN was associated with a significantly higher frequency of estimated glomerular filtration rates <60 ml/min. The adjusted odds ratios for an albumin/creatinine ratio over 34 g/mol (overt albuminuria) in males and females with a history of PSGN were 4.6 and 3.1, respectively, compared with those without a history. Thus, PSGN contributes to the very serious burden of chronic kidney disease in this community. Rigorous strategies to prevent scabies and Group A streptococcal infections will reduce this burden.

Understanding mortality in the 1918-1919 influenza pandemic in England and Wales.

BACKGROUND: The causes of recurrent waves in the 1918-1919 influenza pandemic are not fully understood. OBJECTIVES: To identify the risk factors for influenza onset, spread and mortality in waves 1, 2 and 3 (summer, autumn and winter) in England and Wales in 1918-1919. METHODS: Influenza mortality rates for 333 population units and putative risk factors were analysed by correlation and by regressions weighted by population size and adjusted for spatial trends. RESULTS: For waves 1 and 3, influenza mortality was higher in younger, northerly and socially disadvantaged populations experiencing higher all-cause mortality in 1911-1914. Influenza mortality was greatest in wave 2, but less dependent on underlying population characteristics. Wave duration was shorter in areas with higher influenza mortality, typically associated with increasing population density. Regression analyses confirmed the importance of geographical factors and pre-pandemic mortality for all three waves. Age effects were complex, with the suggestion that younger populations with greater mortality in wave 1 had lesser mortality in wave 2. CONCLUSIONS: Our findings suggest that socially disadvantaged populations were more vulnerable, that older populations were partially protected by prior immunity in wave 1 and that exposure of (younger) populations in one wave could protect against mortality in the subsequent wave. An increase in viral virulence could explain the greater mortality in wave 2. Further modelling of causal processes will help to explain, in considerable detail, how social and geographical factors, season, pre-existing and acquired immunity and virulence affected viral transmission and pandemic mortality in 1918-1919.

Prior immunity helps to explain wave-like behaviour of pandemic influenza in 1918-9.

BACKGROUND: The ecology of influenza may be more complex than is usually assumed. For example, despite multiple waves in the influenza pandemic of 1918-19, many people in urban locations were apparently unaffected. Were they unexposed, or protected by pre-existing cross-immunity in the first wave, by acquired immunity in later waves, or were their infections asymptomatic? METHODS: We modelled all these possibilities to estimate parameters to best explain patterns of repeat attacks in 24,706 individuals potentially exposed to summer, autumn and winter waves in 12 English populations during the 1918-9 pandemic. RESULTS: Before the summer wave, we estimated that only 52% of persons (95% credibility estimates 41-66%) were susceptible, with the remainder protected by prior immunity. Most people were exposed, as virus transmissibility was high with R0 credibility estimates of 3.10-6.74. Because of prior immunity, estimates of effective R at the start of the summer wave were lower at 1.57-3.96. Only 25-66% of exposed and susceptible persons reported symptoms. After each wave, 33-65% of protected persons became susceptible again before the next wave through waning immunity or antigenic drift. Estimated rates of prior immunity were less in younger populations (19-59%) than in adult populations (38-66%), and tended to lapse more frequently in the young (49-92%) than in adults (34-76%). CONCLUSIONS: Our model for pandemic influenza in 1918-9 suggests that pre-existing immune protection, presumably induced by prior exposure to seasonal influenza, may have limited the pandemic attack-rate in urban populations, while the waning of that protection likely contributed to recurrence of pandemic waves in exposed cities. In contrast, in isolated populations, pandemic attack rates in 1918-9 were much higher than in cities, presumably because prior immunity was less in populations with infrequent prior exposure to seasonal influenza. Although these conclusions cannot be verified by direct measurements of historical immune mechanisms, our modelling inferences from 1918-9 suggest that the spread of the influenza A (H1N1) 2009 pandemic has also been limited by immunity from prior exposure to seasonal influenza. Components of that immunity, which are measurable, may be short-lived, and not necessarily correlated with levels of HI antibody.

Understanding influenza transmission, immunity and pandemic threats.

The current pandemic threat can be best understood within an ecological framework that takes account of the history of past pandemics caused by influenza A, the relationships between pandemic and seasonal spread of influenza viruses, and the importance of immunity and behavioural responses in human populations. Isolated populations without recent exposure to seasonal influenza seem more susceptible to new pandemic viruses, and much collateral evidence suggests that this is due to immunity directed against epitopes shared between pandemic and previously circulating strains of inter-pandemic influenza A virus. In the highly connected modern world, most populations are regularly exposed to non-pandemic viruses, which can even boost immunity without causing influenza symptoms. Such naturally-induced immunity helps to explain the low attack-rates of seasonal influenza, as well as the moderate attack-rates in many urbanized populations affected by 1918-1919 and later pandemics. The effectiveness of immunity, even against seasonal influenza, diminishes over time because of antigenic drift in circulating viruses and waning of post-exposure immune responses. Epidemiological evidence suggests that cross-protection against a new pandemic strain could fade even faster. Nevertheless, partial protection, even of short duration, induced by prior seasonal influenza or vaccination against it, could provide important protection in the early stages of a new pandemic.