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Preference: Public and Environmental Health

964

The quality of health research for young Indigenous Australians: systematic review

There are major incentives to invest in the health of Aboriginals and Torres Strait Islanders who are adolescent or young (used interchangeably throughout this article to refer to 10–24-year-olds).1 An estimated 31.7% of Indigenous Australians were aged 10–24 years in 2006, compared with 20.4% of the non-Indigenous population,2 and they experience an excess burden of preventable and treatable disease at a life stage when opportunities for education, employment, reproduction and independent living are at their peak.3 Births to Indigenous teenagers represent about one-fifth of all births to Australian Indigenous women;4 Indigenous young people have high rates of risk factors for the development of non-communicable diseases in adulthood (eg, obesity, tobacco-related disease);3 and the mortality gap between Indigenous and non-Indigenous Australians widens during adolescence and persists into adulthood.5–7 Indeed, improving young people’s health would appear to be critical to the success of the government’s National Indigenous Reform Agreement,8 particularly with regard to life expectancy, reading, writing and numeracy, secondary school completion and employment attainment.9

Indigenous young people’s health is a critical target for health system reform; however, the evidence base to inform health policy and the provision of programs to respond to specific needs remains poorly described.3,10 Measuring young people’s health is complicated by a lack of agreed indicators, and the problem is compounded by the publication of adolescent health data throughout the diverse paediatric and adult literature.11 Significant deficits of Indigenous health research have also been described.12–14 However, specific research policy reform by the National Health and Medical Research Council (NHMRC) has provided guidance for improved quality of Indigenous health research,15,16 and there was an increase in the quantity of Australian Indigenous health research during 1987–2003.17

The overarching aim of our project was to establish the health status of young Indigenous Australians and identify opportunities to improve their health outcomes. The starting point was to systematically document the existing good-quality literature and the limitations of this evidence base, which we describe here. A synthesis of health outcomes and effective interventions for young Indigenous Australians is forthcoming.

Methods

We systematically searched the literature from 1 Jan 1994 – 1 Jan 2011 for peer-reviewed studies reporting health data for Indigenous Australians aged 10–24 years, identifying both descriptive data and evaluations of health interventions.17 We included studies that exclusively reported data for Indigenous young people, as well as those reporting disaggregated data (ie, studies sampling Indigenous Australians and reporting data for young people, or studies sampling young people and reporting data for Indigenous Australians). Our review process is outlined in Box 1. Appendix 1a provides details of our search strategy and inclusion criteria.

Critical appraisal

We critically appraised the included studies, considering studies to be of good quality if they reliably ascertained Indigenous status, included samples that were representative of the target population and employed well defined measures of exposure and outcome (Appendix 1b). We identified whether descriptive studies reported determinants of health outcomes or health-risk exposures.

Demography: age and location

We defined three age subgroups (10–14 years, 15–19 years and 20–24 years) and described the source and location (eg, urban, rural) of the study sample as reported in the publication. Most studies did not report the geographical detail necessary for analysis by remoteness index8 as we had intended. Instead, we mapped the sample locations from each study manually on an Australian Bureau of Statistics map and compared it with the population distribution of Indigenous Australians,2,19 identifying locations using Google Maps Australia (Google Inc). We used the population distribution of all Indigenous Australians as our comparator, as the population distribution of young Indigenous Australians was not available.2,3

Study focus

We categorised the focus of each study as either health outcome or health-risk exposure. We further categorised health outcomes using the burden of disease framework as: Group Ia, Communicable diseases; Group Ib, Maternal, perinatal and nutritional conditions; Group II, Non-communicable diseases; and Group III, Injury6,20 (Appendix 2). Health-risk exposures were further categorised using an index of health risks which included the 11 main risk factors defined in the Australian Indigenous burden of disease report,6 risk factors as identified by the Global Burden of Disease Study expert group21 and risk factors identified for Australian Indigenous children (Appendix 2).22 We included teenage pregnancy as a health-risk exposure as it is a significant social-role transition with implications for individual and population health.23 While health outcomes could be categorised against a single burden of disease category, some studies of health risk measured multiple exposures (eg, alcohol and tobacco). We allowed multiple categorisation for studies measuring the 11 key risk factors. Studies measuring mortality rate (not cause-specific) and population-based studies measuring multiple indicators of health outcome and risk were considered separately.

Data handling and analyses

The review process was managed using an Excel (Microsoft Corporation) datasheet imported into Stata 10.0 (StataCorp) for analysis. Summary statistics were calculated using the χ2 test and linear and logistic regression. Hierarchical burden of disease groupings were reported using tree maps24 generated using the visualisation tool Many Eyes (IBM) and manually traced using Illustrator CS6 (Adobe). The level of statistical significance was set at P < 0.05.

Results

Our search strategy identified 3788 citations; 1509 full texts were reviewed, and we identified 360 peer-reviewed studies reporting data for young Indigenous Australians (Box 1). Ninety studies (25.0%) exclusively sampled Indigenous young people. Two-hundred and two studies (56.1%) were prospective in design. Studies were mostly descriptive (306 [85.0%]) and included 14 case series, 37 qualitative studies, 93 surveillance studies, 149 cross-sectional studies, 4 case–control studies and 9 cohort studies. Ninety-three of the 306 descriptive studies (30.4%) reported a determinant. Of the 54 evaluation studies, 34 (63.0%) were quantitative in design and there were no randomised trials. The number of studies published increased over time. The proportion focusing exclusively on Indigenous young people and the proportion with prospective study design increased significantly (P = 0.04 and P = 0.03, respectively) (Box 2). While the number of studies evaluating interventions also increased during 1994–2010, the proportion of all studies that were evaluative in design did not change (P = 0.56).

Critical appraisal

Two hundred and fifty studies (69.4%) were graded as good quality. Data quality improved significantly over time (P < 0.01) (Box 2). Quality was no different for descriptive compared with evaluative design (P = 0.42), or according to state or territory of the study sample (P = 0.46), urban compared with rural location (P = 0.37), study focus (P = 0.18) or for studies exclusively sampling Indigenous young people compared with those reporting disaggregated data (P = 0.36).

Demography: age and location

Most studies included young people aged 15–19 years (290 [80.6%]); 204 studies (56.7%) included 10–14-year-olds and 141 (39.2%) included 20–24-year-olds; 173 studies sampled two age subgroups and 51 sampled all three.

Overall, 61 studies (16.9%) reported data for young people from urban areas, 116 (32.2%) reported data for young people from rural areas, 139 (38.6%) presented mixed data and 44 (12.2%) studies were unclear. Forty-one of the 61 studies focusing on urban populations were published in 2005–2010 (P = 0.02). The community, town or city from which the young people were recruited was clearly identified in 144 studies (40.0%). Most studies included young people from the Northern Territory, Western Australia and Queensland (Box 3). Compared with studies including disaggregated data, studies that exclusively included Indigenous young people were more likely to have sampled urban populations (41% v 25%; P = 0.03); however, there was no difference by state or territory (P = 0.22). Indigenous young people were recruited or data were obtained from communities (113 [31.4%]), schools (58 [16.1%]), population datasets (50 [13.9%]), hospitals (48, 13.3%), clinics (47, 13.1%) and correctional facilities (27, 7.5%). Seventeen studies (4.7%) included data from mixed sources.

Study focus

Overall, 163 (45.3%) studies focused on health-risk exposures and 197 (54.7%) focused on outcomes: 65 of these (18.1%) on communicable diseases, 3 (0.8%) on maternal and nutritional conditions, 97 (26.9%) on non-communicable diseases, 16 (4.4%) on injury, and 16 (4.4%) on non-cause-specific mortality or population morbidity. The focus of research did not change during 1994–2010 (P = 0.6). Studies that exclusively included Indigenous young people did not focus on injury at all. Study focus did not differ by study quality (P = 0.59), and we restricted further analysis to good-quality studies.

Of the 250 good-quality studies, three reported multiple indicators of health for Indigenous young people25–27 and seven reported mortality (not cause-specific) for the NT, WA, South Australia and Queensland. The remaining 240 good-quality studies included 124 studies of health outcomes (Box 4) and 116 studies of exposure to health risks.

Health outcomes

The 124 good-quality studies of health outcomes comprised 109 descriptive studies and 15 that evaluated an intervention.

Group Ia: Communicable diseases: Thirty-seven descriptive and eight evaluative studies focused on communicable diseases. Descriptive studies mostly provided prevalence estimates from surveillance studies: 13 provided good-quality data for sexually transmitted infections and nine reported tuberculosis notifications. The eight evaluations focused on testing (4) and treatment (4) approaches.

Group Ib: Maternal, perinatal and nutritional conditions: There was a paucity of data on maternal diseases; one retrospective hospital-based study included some measures of obstetric risk among Indigenous teenage mothers and associated perinatal outcomes and was categorised under health-risk exposure.28

Group II: Non-communicable diseases: Fifty-seven descriptive studies and six evaluative studies focused on non-communicable diseases. Eighteen studies focused on mental disorders, nine of these on harmful substance use. Data on depression, anxiety and psychosis were limited. Fifteen descriptive studies focused on oral health; however, we did not identify any studies evaluating interventions. Four studies focused on cardiovascular disease (all on rheumatic heart disease), including a study on mortality.29 One study measured mortality related to cervical cancer.30

Group III: Injury: Thirteen descriptive studies focused on injury, and included three descriptive studies of suicide and one study of fatal unintentional injury.31–34 One study evaluated a community project to address both intentional and unintentional injury.35

Health-risk exposures

The 116 good-quality studies of health-risk exposures comprised 90 descriptive studies and 26 that evaluated an intervention. Eleven studies focused on nutrition and lifestyle, 11 on social–emotional wellbeing, eight on education and nine on justice. Twenty studies focused on sexual and reproductive health, including nine studies of adolescent pregnancy and 11 of related perinatal outcomes. Ten studies focused on health access and included four evaluations. A further eight studies focused on housing, community or parenting. Thirty-nine studies focused on the 11 key risk factors, with eight of these focused on more than one risk factor (Box 5). There were good data for substance use, and while data for unsafe sex were limited, two studies evaluated interventions.36,37

Discussion

Most health-outcome data for Indigenous young people published during 1994–2010 focused on communicable diseases, oral health and substance use. There were also some good-quality data for health-risk exposures related to adult non-communicable diseases (such as substance use, physical activity and diet) and for adolescent pregnancy, including some data on perinatal outcomes. These data illustrate how the health of today’s Indigenous young people will affect the health of Indigenous Australian adults and their children in the years to come. The quality of data improved over time, but there were still some important gaps. Data for urban locations were limited, as were data for mental disorders and injury. Data on the health of adolescent mothers were limited, despite fertility peaking in this age group.4 Mortality data were not available for all jurisdictions of Australia, and cause-specific estimates were limited. Overall, there was also a paucity of evaluation of programs and interventions. Identification of these gaps may assist in considering future research needs.

It is important not to interpret these findings as over-investment of research in some health areas. For example, sexually transmitted infection causes a disproportionate burden of poor health among Indigenous young people,38 and relevant good-quality data are likely to have informed the national strategy prioritising control of sexually transmitted infections among Indigenous Australians, particularly young people.39

We mapped the focus of studies using the burden of disease framework because using a predefined schedule of health outcome and risk allowed for objective assessment of any data gaps. It is not possible, however, to directly compare the scope of these publications to estimates of the burden of disease among Indigenous young people. Age-disaggregated data allowing calculation of disease burden for 10–24-year-olds were not available.6 Furthermore, estimates reported in the Australian Indigenous burden of disease study are dependent on quality input data, largely missing for Indigenous people living in urban settings13 and in areas such as mental health.40 With these limitations in mind, mental disorders and injury together account for 56% of the burden of disease among Indigenous people aged 15–34 years (calculated from annex tables).6 This proportion is similar for mental disorders and injury in young people aged 10–24 years globally.41 Burden of disease, however, is only one marker of research priority; priorities identified by Indigenous young people and their communities are a fundamental consideration. For example, a qualitative study of Indigenous adolescents in a remote area identified substance use, violence, boredom and racism as significant issues.25 Placing the findings of our study in this context, there appears to be a mismatch between estimates of the burden of disease, needs reported by young people, and the focus of research studies in Indigenous young people. The potential for implementing effective (and cost-effective) prevention and intervention is an additional consideration.42

The findings of our study are similar to a review of Canadian Indigenous health research that found research was primarily focused on health conditions amenable to “curative services”.43 One possible explanation is that competitive research funding and policy (such as Closing the Gap) encourages investment in health targets that are easily measured and amenable to simple intervention: this is a well recognised challenge of global health policy where there has been acceptable progress towards goals targeting individuals (ie, child survival), while goals such as gender equality and maternal health (shaped by socioeconomic and cultural determinants) have lagged.44,45 Despite social determinants playing a central role in Indigenous health inequality,8 we identified few studies that focused on social exclusion or socioeconomic inequality (justice, education, employment or housing). Less than a third of descriptive studies measured a determinant.

Three-quarters of all young Indigenous people live in urban and regional areas.3 Despite this, overall investment in research involving this population was limited, although it is improving. Challenges of conducting urban Indigenous health research are distinct from the cost and methodological challenges of rural research.46 There are no geographical boundaries or readily identifiable target populations that allow identification of Indigenous Australians living in urban settings.13 Appropriate consultation and collaboration (essential principles of Indigenous health research) in this context may involve a large number of communities and organisations and requires time, flexibility, and resourcing,47–50 which are increasingly at odds with research grants that focus on timely outputs. Developing a robust evidence base may also require non-standard approaches. While Indigenous health research is often conducted in collaboration with Aboriginal community-controlled health services or Aboriginal medical services,13 the Western Australian Aboriginal Child Health Survey showed that only 12% of Indigenous 12–17-year-olds had contact with an Aboriginal medical service in the preceding 6 months, with contact lowest among those living in the most urbanised settings.51 Data linkage may provide one mechanism to better understand patterns of health and social service access.

Health needs and opportunities for intervention vary significantly across the 10–24-years age band. We did not disaggregate our analysis by age subgroup because almost two-thirds of studies included multiple age subgroups. Additionally, we only included peer-reviewed literature; the grey literature may fill some of the identified gaps. The Western Australian Aboriginal Child Health Survey, for example, is published in four volumes and includes mental health data for 12–17-year-olds.52

The findings of our study serve two main purposes. First, we have identified some good-quality literature that can be used to inform health policy and programs to improve the health of young Indigenous Australians; a synthesis of this literature is forthcoming. Second, the findings provide a framework to allow Indigenous communities, researchers, funding bodies and the NHMRC to consider priorities for future research. Marriage of health research to need can only occur with consultation, engagement and the trust of Indigenous communities. This is essential for priority setting, dealing with sensitive health issues (such as mental health, injury and sexual and reproductive health) and appropriately and sustainably engaging young Indigenous Australians in understanding and addressing their health needs.53

1 Systematic review process

ERIC = Education Resources Information Center. CINAHL = Cumulative Index to Nursing and Allied Health Literature. ATSIhealth = Aboriginal and Torres Strait Islander Health Bibliography. * These were sorted by study design and include publications that did not sample Indigenous young people.

2 Frequency of publication and quality of data for young Indigenous Australians over time, 1994–2010

3 Sampling of young Indigenous Australians compared with the population distribution of all Indigenous Australians*

ACT = Australian Capital Territory. NSW = New South Wales. NT = Northern Territory.
QLD = Queensland. SA = South Australia. TAS = Tasmania. VIC = Victoria. WA = Western Australia.

* The graph shows the population distribution of Indigenous Australians, one dot representing 100 Indigenous Australians.2,19 Each red dot represents a single sampling site for a study (studies reporting sampling from five distinct sites are indicated by five individual dots; studies reporting sample location at a state or nation level are represented separately by a numeral).

4 Tree map plots* of 124 good-quality published studies on health outcomes among Australian Indigenous young people aged 10–24 years, colour-coded by Burden of Disease Framework category

M = musculoskeletal. Ca = malignancy. GIT = gastrointestinal. ME = meningoencephalitis. STI = sexually transmitted infection. TB = tuberculosis.

* Plots are drawn to scale to demonstrate the proportion of descriptive to evaluative studies.

5 Studies of health-risk exposure focusing on 11 key risk factors

Sharing Place, Learning Together: the birthplace of new ways?

Diversifying educational opportunities for remote Indigenous students is a key step to improving health outcomes

Young people and old people, Bininj, Yol and Balanda; we need to stand together for the future. The health and wellbeing of our people and our country depends upon us all.1

Djelk Rangers Victor Rostron, Wesley Campion and Ivan Namarnyilk. (Djelk Indigenous Protected Area, Arnhem Land.) The terms Bininj and Yol are used in Maningrida to refer to Aboriginal people. Balanda is used colloquially throughout the Maningrida region to describe non-Aboriginal people.

In the north, water chestnuts bring people and magpie geese together. Magpie geese migrate to the flood plains from elsewhere in Australasia as the chestnuts ripen after the wet season, and humans and magpie geese share the chestnuts. People can hunt for magpie geese only after the geese have eaten the chestnuts and fattened, slowing their flight. Hunting and preparing the goose is a particular process that must be taught, and learnt, in the right way. Magpie geese and water chestnuts each have songlines, dreamings and a moiety, and you have to follow the rules exactly, the old people’s way. Students at Maningrida College in Arnhem Land perform these life skills with their Indigenous teacher, Heleana Wauchope-Gulwa, around a traditional stringybark fire as part of the interagency government-funded Learning on Country (LoC) program. In the program, piloted at four remote Northern Territory schools, students are linked with their local Indigenous ranger group (in Maningrida, the Djelk Rangers) with whom part of their school program is spent “on country” (Box 1). As the students reflect later, magpie goose is “good for us, and good for our families”.2

International research reinforces that health outcomes for Indigenous populations are linked to a spectrum of social determinants that include education and access to culture.3,4 In this context, the LoC approach recognises that population health in remote Indigenous communities links to the health of “country”: the land to which a community belongs and is culturally and physically connected. This in turn relies on Indigenous culture remaining strong, since the health of people, country and culture go hand-in-hand.1,5 It is not just the nutritional properties of the magpie geese, but the way education can bring together two learning systems and link to the physical, social, emotional and spiritual health and wellbeing of the community that make it “good” for Maningrida students.

The Australian Venom Research Unit (AVRU), part of the Department of Pharmacology at the University of Melbourne, was invited to contribute to Maningrida College’s LoC program in 2010. The LoC students had discovered 45 new species of spiders during local fieldwork activities, and science teacher Mason Scholes was seeking to expand the program’s potential in respect to venom, venomous injury and biodiversity. Coincidentally, the AVRU had just completed a project with the Melbourne Graduate School of Education, developing science-based curriculum resources combining injury prevention with science and health literacy, and had received an anonymous donation toward Indigenous-related research and education. In consultation with the Murrup Barak, Melbourne Institute for Indigenous Development and Indigenous leaders at the University of Melbourne, and guided by research linking health and education with a spectrum of social determinants, the Sharing Place, Learning Together (SPLT) project evolved (Box 2).4

Since 2010, the SPLT project, led by an interdisciplinary team with backgrounds in curriculum, pedagogy, literacy, science and health, has connected with Maningrida College’s LoC program. Under the guidance of rangers and elders, the SPLT team has diversified the existing fieldwork program, partnering with outside institutions to link local biodiversity issues to a range of science and educational practices. The team has, additionally, worked to extend and strengthen the literacy focus of the LoC program, supporting the government’s priority to increase literacy and numeracy development in remote schools.6,7 Here, students, rangers and traditional owners are active participants in the development of their own curriculum resources. Explicit scaffolding and teaching of literacy skills has empowered students to draw on their knowledge of country and write the text for a series of pocket books produced in 2011: Bush tucker, First aid, Catch ‘n’ cook and Animal tracks. These books were based on students’ fieldwork experiences and familiarisation with tropical and remote first aid and injury prevention (Box 3). It was this experience of authorship that enabled the students to reflect, and document their knowledge, that hunting and cooking magpie geese was good for both them and their families.

The SPLT team is informed by the Australian National University’s Centre for Aboriginal Economic Policy Research, which supports the development of experiential learning in community-based contexts.5 Further, the Centre’s action research project People on country: vital landscapes, Indigenous futures has, over the past 5 years, explored the “links between Indigenous wellbeing, natural resource management and new resource-based development opportunities” in several Indigenous communities, including Maningrida.1 Its research shows that Indigenous-managed estates remain the most ecologically intact, but that Western science makes important contributions to present land management challenges.

Current policy focuses on “closing the gap” between Indigenous and non-Indigenous health, education and employment outcomes.7 However, there is concern that targets focused on closing statistical inequalities (from data on social and economic indicators) can risk directing remedies towards outcomes that, paradoxically, may widen the gap they seek to close.5,8 Data-based educational targets can prompt “teaching to the test” in disadvantaged schools where funding is linked to results of the National Assessment Program — Literacy and Numeracy (NAPLAN), leaving Indigenous students with a fragmented formal education.5 In addition, prioritising Western knowledge and world views in the classroom risks presenting a deficit-filled monocultural model of Indigenous Australia and subjugating the complexity and validity of Indigenous knowledge systems and cultures.9

If narrower, prescriptive pedagogies replace context-based educational approaches in remote settings, the impact is felt in communities like Maningrida where leaders worry that local knowledge and culture is not being transmitted to young people (Box 4). Linking literacy, health and science to community life and culture can strengthen the curriculum “both ways”, because “lots of kids won’t go to school, but . . . out bush they attend and listen.”1 The LoC approach involves community participation in the school’s programs, thereby encouraging school attendance and student engagement with learning. Community involvement and partnerships that are accountable “both ways” are recognised as being essential for successful educational outcomes.10

Health, wellbeing, resilience and cultural livelihoods for remote communities are contingent on effective land management, the synthesis of Western science and traditional knowledge, the maintenance of biodiversity, and the opportunity for Indigenous people to remain active users, custodians and inhabitants of their lands. Environmental threats are serious for remote communities. Maningrida’s surrounds contain sites —
of the very few still existing in Australia — where traditional land management practices remain unbroken, and biodiversity flourishes.11 Still, feral animals, weeds, illegal fishing and mining exploration threaten to disrupt traditional management practices and food sources (Box 5). For example, habitat damage from the buffalo and wild pig threatens the water chestnut’s availability to magpie geese and people. Traditional land management and science both have roles to play in redressing these imbalances.

The possibilities for this project are not isolated to
the Maningrida community. Education in Australia is undergoing change: the new national curriculum places emphasis on Indigenous history and culture, suggesting potential for resources developed by Indigenous students to find a place beyond the Maningrida classroom.12 The students’ spider discoveries have already contributed to Western science’s understanding of biodiversity in Australia, and the possibility of future developments in Australian toxinology, and public health relating to injury prevention and treatment are enhanced by the strength of such interdisciplinary and cross-cultural partnerships. Further, the possibilities
for enhanced biodiversity through traditional land management practices has Australia-wide relevance
for tertiary science and health programs as well as resonance with the broader health and societal value
of closer engagement with nature and place.

In turn, this project has become part of the University of Melbourne’s reconciliation agenda. Supported by the Melbourne Social Equity Institute, we are conducting research into the partnership formation between the Maningrida community and the SPLT team, particularly where this partnership seeks to promote and raise Indigenous students’ aspirations for engagement in further education.

Building this relationship with trust between stakeholders has taken time. Through it, the SPLT team have experienced “both ways” learning, showing that engaging communities to build capacity in health and education does not require closing in on diversity and heterogeneity, but rather, can move towards ways of being and knowing that embrace complexity and difference. This is potentially what could be lost in the mainstreaming of solutions to Indigenous disadvantage in both health and education. According to the elders and Djelk Rangers at Maningrida, being out on country is not just about the old ways, “it is the birthplace of the new ways for us”.1

1 Students, teachers and members of the Sharing Place, Learning Together team search for water chestnuts east of Maningrida

2 The Sharing Place, Learning Together (SPLT) program

Background

This program focuses on the research and development of innovative approaches to education and capacity building in remote Aboriginal communities. SPLT aims to increase educational opportunities for rural and remote students as a key step to improving health, access to higher education and employment outcomes, by supporting:

  • literacy, numeracy and science knowledge appropriate to remote community life

  • education curriculum development and research

  • Aboriginal health and resilience through capacity building

  • a program that is grounded to place

Key partners

  • Maningrida College (Maningrida, Northern Territory)

  • Djelk Rangers (Bawinanga Aboriginal Corporation, Maningrida, NT)

  • Australian Venom Research Unit (Department of Pharmacology) and the Melbourne Graduate School of Education, University of Melbourne (Victoria)

Specific activities

  • curriculum development: the concepts underpinning curriculum development within the program integrate Aboriginal biocultural knowledge with Western scientific knowledge, and foster shared learnings, methods and skills

  • field trips: students work with rangers and elders to map, interpret and share local biodiversity and cultural practices and to link these with school learning processes and outcomes

  • book development: these projects aim to develop leadership, literacy and presentation skills. Students create context to communicate significant biocultural knowledge within the integrated classroom program

  • Venom trail: this is a fieldwork program that connects rangers, scientists and students in local and wider contexts. It highlights the value of cross-cultural collaboration, higher education and capacity building

3 Pages from the First aid pocketbook created by Maningrida College students, describing first aid treatment for box jellyfish stings*

* Student Rickisha Redford-Bohme uses rainbow colours to represent the venom of the jellyfish.

4 Context-based educational approaches help to transmit local knowledge and culture to young people

When [students] come into Western society they learn things like writing and reading, working things like a laptop. And there is an information outcome, like PowerPoint. But at home it’s about talking to people, and you have to bring your grandmother and grandfather: ask them to tell stories.

Alistair James, traditional owner,
Ndjebbana Clan Group (interview 31 May 2013).

We don’t have pen and papers but we have what the men do on the walls [pointing to bark paintings], the traditional art and the stories, and the colours from the traditional art: from outside to inside, getting deeper. Sometimes the colour of the moiety, yellow, or red. The colours tell the country people came from, and those colours stay the same all the time. And their skin colours. In schools there are all sorts of colours but they should learn our two most important colours, which are Yirritja and Dhuwa.

Joseph Diddo, traditional owner,
Ndjebbana Clan Group (interview 31 May 2013).

5 Students identify the seeds of the “necklace plant”, an invasive European weed

Improving the health of First Nations children in Australia

Regular monitoring and supportive federal and state public policy are critical to closing the gap in child health

Health and wellbeing of children and young people are the keys to human capability of future generations. Human capability includes the capacity to participate in economic, social and civil activities and be a valued contributor to society;1 it means that not only can you usefully live, work and vote, but you can be a good parent to your children. Thus there is no better investment that the state can make than to influence factors that will enhance the health and wellbeing of children and youth.

There were an estimated 200 245 First Nations2 children aged 0–14 years in Australia in 2011, comprising 4.9% of the total child population and 35% of the total First Nations population.3 With such a high proportion of children compared with the non-Aboriginal population, the First Nations population is much younger, with fewer adults per child to care for them. An Australian Research Alliance for Children and Youth report adds to evidence from the most recent Australian Institute of Health and Welfare report on the health of Australia’s children to document the growing divide between the health of First Nations and other Australian children.3,4

Child health indicators include mortality rates (Box, A), prevalence of chronic conditions, indicators of early development (including rates of dental decay [Box, B]), promotion of early learning (eg, adults reading to children in preschool years) and school readiness assessed with the Australian Early Development Index (Box, C).3 Risk factors for poor child health include: teenage pregnancies; smoking and alcohol exposure during pregnancy; pregnancy outcomes such as stillbirths, low birthweight and preterm births; the proportion of children aged 5–14 years who are overweight or obese; and the proportion of children aged 12–15 years who are current smokers. In addition, indicators of the level of safety and security of children — including rates of accidental injury, substantiated reports of child abuse and neglect, evidence of children as victims of violence, and indicators of homelessness and crime — further highlight how poorly Aboriginal children fare during childhood.

Owing to significant gaps in available data, Australia is not included in UNICEF reports relevant to First Nations children, including The children left behind: a league table of inequality in child well-being in the world’s rich countries.5 This report is important for many First Nations children who experience conditions near the bottom because it focuses on closing the gap between the bottom and the middle:

We should focus on closing the gap between the bottom and the middle not because that is the easy thing to do, but because focusing on those who do not have the chance of a good life is the most important thing to do.5

While there has been progress, particularly in educational outcomes, the gap in healthy child development in safe and secure environments is disturbing. It has resulted from of a variety of complex social circumstances, due to colonisation, marginalisation and forced removals. To effectively and successfully interrupt and reverse these generational traumas on today’s children, careful and sensitive First Nations-led programs are required. Programs in Canada and Australia have shown that the major protective and healing effects of strong culture are immensely powerful, even in urban situations, which highlights the value of strong government support for such programs in Australia. For example, putting First Nations children and youth into cultural programs is more effective than incarceration for preventing recidivism, and increased recognition of Aboriginal cultures in school curricula increases rates of high school completion by First Nations students.6

Drawing on our own and overseas data,7 we believe that Australian services have failed to close the gap in child health because they have been developed without involving or engaging First Nations people. When participatory action research methods are used, as has been done with Inuit communities in Nunavut in Canada,8 the use and success of services are dramatic. Such strategies lead to higher levels of local employment, higher self-esteem, and reduced mental illness and substance misuse among First Nations people. British Columbian data on First Nations youth suicide rates have shown that the lowest rates in Canada were in communities with strong culture and Aboriginal control of services (eg, health, education and community safety).9 This means that a major rethink of services for First Nations people is needed, and that centralised policy applied to multiple diverse communities is unlikely to work. Although the policy content of what needs to be done can be developed centrally based on existing evidence (eg, alcohol in pregnancy causes brain damage, early childhood environments are vital to help children to be ready for school, complete immunisation prevents infections, and avoiding sweet drinks prevents obesity and dental decay), development and implementation of services need to be done locally and with community involvement. A great example of this is the strategy to overcome fetal alcohol spectrum disorders (FASD) that was developed by Aboriginal women June Oscar and Emily Carter and the First Nations people of Fitzroy Valley. This comprehensive and effective strategy has enabled the community to think and act beyond the stigma of FASD — community members drove the design and implementation of programs to prevent FASD, and they created opportunities and support mechanisms to enable the best possible treatment for children with FASD.10

Building on the Australian Research Alliance for Children and Youth report,4 we need a consistent national framework for monitoring health status and an understanding of the impact of federal and state policies on First Nations children. Recent policies with the potential to affect First Nations children include: the Northern Territory intervention, the loosening of alcohol restrictions in the Northern Territory, policies aimed at addressing overrepresentation of Aboriginal children in child protection reporting, housing policies (including evictions and the transfer of public housing properties to ownership and management by non-government organisations), policies that have changed financial support for single parents, education policies aimed at assessing school readiness and other policies aimed at closing the gap in health. The effects of these policies on First Nations children need to be considered in regular assessments of public policy, with the needs of children prioritised over competing interests.

The exciting thing is that we now have a growing number of Aboriginal health care providers and other university-trained professionals to employ to make services effective. We have equity in medical student intakes which augurs well for future progress in this critical area. The dream of having appropriate, culturally safe policies, programs and services for our First Nations children can become a reality if it is supported and promoted by all levels of government.

Child health indicators that show a divide between First Nations and other Australian children*

SES = socioeconomic status. LBOTE = language background other than English. * Adapted with permission from A picture of Australia’s children 2012.3 † Developmentally vulnerable on one or more Australian Early Development Index domains.

Sevenfold rise in likelihood of pertussis test requests in a stable set of Australian general practice encounters, 2000–2011

Pertussis, commonly known as whooping cough, is caused by the small, gram-negative coccobacillus Bordetella pertussis. Classic whooping cough illness is characterised by intense paroxysmal coughing followed by an inspiratory “whoop”, especially in young children or those without prior immunity, followed by a protracted cough.1,2 It is now more widely understood that these characteristic symptoms are not always present during B. pertussis infection, and that individuals may only have symptoms similar to those of the common cold or a non-specific upper respiratory tract infection.2

In recent years, rates of pertussis notifications have increased dramatically across Australia and in many other parts of the world.3–6 The rise has been seen in all Australian states and territories, with the highest notification rates in children aged under 15 years.7 Although increased notifications may be due to a true increase in circulating B. pertussis, it is possible that the magnitude of the increase has been amplified by better recognition of disease and more frequent testing.8

Historically, the diagnostic gold standard for pertussis laboratory testing was bacterial culture from nasopharyngeal secretions during the early phases of infection (Weeks 1 and 2), and serological testing was used as an alternative diagnostic method during later phases of infection.2 However, even with ideal specimen collection, transport and handling, culture has low sensitivity and does not provide timely results. Although serological testing is more sensitive, sensitivity and specificity may be lowered depending on the timing of specimen collection and the patient’s infection and vaccination history.9 Polymerase chain reaction (PCR) testing has emerged as a key diagnostic method, and respiratory specimens are now commonly tested for pertussis using PCR in Australia and other countries.2,4,10 PCR testing provides more sensitive and rapid results than culture and serological testing. Also, PCR allows less invasive specimen collection — especially useful in younger age groups, in whom infection rates are high and serum collection may be challenging.1

The key datasets used to monitor pertussis incidence and epidemiology in Australia — pertussis notifications, and pertussis-coded hospitalisations and deaths — are populated by positive test results from laboratories and, as such, are not independent of changes in testing practices. Without negative test results or other denominator data to assess changes in testing behaviour, it is difficult to distinguish changes in recorded disease incidence that are due to the effect of increased testing from any true increase in disease.

To better understand the role testing behaviour has on current pertussis epidemiology in Australia, we investigated pertussis testing trends in a stable set of general practice encounters. We hypothesised that the likelihood of pertussis testing, in a stable set of encounters that were most likely to result in a pertussis test request, has increased over time and that this may have led to amplification of laboratory-confirmed pertussis identification in Australia.

Methods

We analysed data from the Bettering the Evaluation and Care of Health (BEACH) program and the National Notifiable Diseases Surveillance System (NNDSS).

The BEACH program is a continuous cross-sectional national study that began collecting details of Australian general practice encounters in April 1998. Study methods for the BEACH program have been described elsewhere11 and are summarised in Appendix 1.

Initially, all encounters for which a pertussis test (ICPC-2 [International Classification of Primary Care, Version 2] PLUS code R33007 [ICPC-2 PLUS label: Test;pertussis]12) was ordered in the period April 2009 – March 2011 were identified and examined. During this period, 30 BEACH problems resulted in a pertussis test request at some time, and nine problems accounted for 90.9% of all pertussis test requests in the dataset. Four other problems, for which a pertussis test request was made at more than 1% of general practice management occasions of that problem, were added (Appendix 2). The 13 selected problems accounted for 92.3% of pertussis tests ordered between April 2009 and March 2011. These were labelled “pertussis-related problems” (PRPs) and data for these problems at encounters recorded between April 2000 and March 2011 were extracted.

BEACH data were grouped into two pre-epidemic periods (before the start of the national pertussis outbreak in 2008) and three epidemic years. During the pre-epidemic periods (April 2000 – March 2004 and April 2004 – March 2008), testing proportions were constant. For each pre-epidemic period and epidemic year, the proportion of PRPs with a pertussis test ordered and the proportion of BEACH problems that were PRPs were calculated. The proportions of PRPs with a pertussis test ordered were grouped into clinically meaningful age groups: 0–4 years, 5–9 years, 10–19 years, 20–39 years, 40–59 years, and ≥ 60 years.

The NNDSS collates notifications of confirmed and probable pertussis cases received in each state and territory of Australia under appropriate public health legislation.13 Notified cases meet a pertussis case definition, which requires: laboratory definitive evidence; or laboratory suggestive evidence and clinical evidence; or clinical evidence and epidemiological evidence (Appendix 3).

To match the BEACH years, all Australian pertussis notifications between April 2000 and March 2011 were extracted from the NNDSS database, including data on age and laboratory testing method. Pertussis notifications were aggregated by month and year, by age group, and by laboratory test method (serological, PCR, culture or unknown). Notifications that had more than one testing modality reported were classified into a single test category using the following hierarchy: culture, PCR, serological, unknown. A total of 1318 notifications were coded only as “antigen detection”, “histopathology”, “microscopy”, “not done” or “other” (epidemiologically linked cases); these were excluded from the analysis as they accounted for only 0.9% of notifications over the study period. The rates of pertussis notifications per 100 000 population were then calculated for each pre-epidemic period and epidemic year.

Temporal changes in the proportions of PRPs with a pertussis test ordered and the rates of pertussis notifications were assessed with a non-parametric test for trend over the whole study period and by calculating odds ratios with robust 95% confidence intervals. Correlation coefficients were calculated to determine the relationship between BEACH and NNDSS datasets. The BEACH analyses incorporated an adjustment for the cluster sample design. Initial BEACH analyses were performed using SAS version 9.1.3 (SAS Institute). Subsequent BEACH and NNDSS analyses were performed using Microsoft Excel and Stata version 11 (StataCorp).

During the study period, the BEACH program had ethics approval from the University of Sydney Human Research Ethics Committee and the Australian Institute of Health and Welfare Ethics Committee. This particular study was approved by the University of Queensland Medical Research Ethics Committee.

Results

The PRPs captured an average of 90.7% of all BEACH problems with a pertussis test ordered each year (range, 87.7%–92.7%) between April 2000 and March 2011 (Box 1). During the study period, PRPs as a proportion of all BEACH problems remained stable, with an annual average of 8.0% (range, 7.7%–8.7%).

When the BEACH data were grouped into pre-epidemic periods and epidemic years, the proportion of PRPs with a pertussis test ordered increased about sevenfold — from 0.25% to 1.71% — when comparing April 2000 – March 2004 and April 2010 – March 2011(Box 2, Box 3). This increase was highly correlated with NNDSS pertussis notification rates (correlation coefficient [r], 0.99), which increased about fivefold during the same period (Box 3). A highly significant trend was detected for changes in BEACH pertussis test requests (P < 0.001) and NNDSS notification rates (P < 0.001) from April 2000 to March 2011.

In the age-specific analysis, there were significant increases in laboratory-confirmed pertussis notifications and in the likelihood of pertussis test requests across all age groups during the study period (Box 3). When comparing April 2000 – March 2004 and April 2010 – March 2011 pertussis testing rates, the largest increase was in 5–9-year-olds (odds ratio, 11.6; 95% CI, 4.2–36.7), followed by 0–4-year-olds, 40–59-year-olds and ≥ 60-year-olds. With the exception of 5–9-year-olds, the increase in pertussis testing exceeded notification changes in all age groups.

Numbers of NNDSS pertussis notifications fluctuated over the study period (Box 4). From 2008 onwards, there was a clear increase in the numbers of PCR-confirmed notifications. Before April 2008, most NNDSS notifications were confirmed by serological testing (66.0%–80.7% of all notifications annually). The proportion of notifications confirmed by PCR increased from 16.3% in April 2000 – March 2004 to 65.3% in April 2010 – March 2011 (Box 1). The proportion of notifications confirmed by culture did not change, and accounted for an average of 2.0% of all notifications over the study period.

Discussion

Consistent with experience in other developed countries,4,14–16 we found that rates of pertussis notifications in Australia increased dramatically in recent years, from an average annual rate of 34 per 100 000 population between April 2000 and March 2004 to 158 per 100 000 population between April 2010 and March 2011. Our results cast some light on the potential role that the increasing likelihood of a pertussis test request may have on this change.

Using BEACH data, we found that individuals presenting to an Australian general practitioner between April 2010 and March 2011 were seven times more likely to have been tested for pertussis than 10 years earlier. This finding was within a set of general practice problems that remained stable as a proportion of all problems. This increased likelihood of pertussis testing, most evident in the epidemic years from April 2008 onwards, reached a maximum in the period April 2010 – March 2011, when pertussis tests were ordered in 1.71% of PRPs. A particular strength of our findings is that we used a data source that does not rely on laboratory testing, unlike most other datasets used to monitor pertussis in Australia and elsewhere.4,7,10,13

The increased likelihood of testing in general practice coincided with an increasing proportion of NNDSS pertussis notifications being confirmed by PCR, from 16.3% between April 2000 and March 2004 to 65.3% between April 2010 and March 2011. A review of pertussis cases in New South Wales during the period 2008–2009 also showed a shift away from serological testing (the predominant method before 2008) to PCR testing from 2008 onwards.10

Pertussis notification rates and the likelihood of testing varied considerably across age groups. There was a dramatic increase in notification rates in 0–4-year-olds and 5–9-year-olds from the 2004–2008 pre-epidemic period to the 2008–2009 epidemic year, compared with a moderate increase in testing, which indicates that there probably was a true increase in disease for these groups during this period. It is possible that a real increase in 0–4-year-olds and 5–9-year-olds early on prompted increased disease awareness among GPs, leading to widespread increases in testing across all ages. A positive feedback loop due to increased testing — leading to increased disease detection and awareness, leading to increased testing, and so on — may have been established. This interpretation is supported by the observation that although testing continued to increase from the epidemic year 2008–2009 to the epidemic year 2009–2010, there was little change in notifications, suggesting an increase in testing during that period rather than an increase in disease. In the other age groups, an increase in testing appeared to be responsible for magnified pertussis notifications. A study of pertussis resurgence in Toronto, Canada, also described this phenomenon and concluded that, although there had been true increase in local disease activity, the apparent size of the increase had been magnified by an increase in the use of pertussis testing and improvements in test sensitivity.4

In Australia, public funding for pathology laboratories to use PCR to test specimens for pertussis (and other pathogens) commenced under the Medicare Benefits Schedule (MBS) in November 2005.17 This specific reimbursement for PCR testing (MBS item 69494) — a Medicare fee of $28.65 compared with $22.00 for culture (MBS item 69303) and $15.65 for serological testing (MBS item 69384)17 — may have been an incentive for laboratories across Australia to implement PCR testing more routinely. In addition, during the 2009 H1N1 influenza pandemic, public funding was allocated for the purchase of laboratory equipment (notably PCR suites), but much of the funding was not received by laboratories until after the demand for pandemic influenza testing had subsided.18 New PCR capacity may have provided an increased opportunity for laboratories to conduct PCR testing for other pathogens, such as B. pertussis.

Several factors may have contributed to an increase in disease during the study period. Pertussis laboratory testing methods have been documented to vary between children and adults. While, historically, culture would have been preferred to serological tests for the very young,19 children now are more likely to be tested using PCR, and adults are predominantly tested using serological tests.10 The variation in testing and notification rates across age groups may be due to differences in susceptibility and immunity.20 Pertussis vaccination does not provide lifelong immunity against infection, with protection waning between booster doses.21 Waning immunity may partially explain differences in pertussis incidence between age groups, with older individuals having lower immunity due to longer periods since vaccination.20 Furthermore, there is evidence to suggest that whole-cell pertussis vaccine formulations used in Australia and overseas before the late 1990s were more protective against B. pertussis infection than currently used acellular pertussis vaccines,14,22–24 resulting in immunity levels waning faster in some age cohorts due to changes in vaccination schedules.25 In addition, a recent analysis of B. pertussis isolates collected in Australia between 2008 and 2010 indicates that there has been increasing circulation of vaccine-mismatched strains, hypothesised to be due to the selective pressure of vaccine-induced immunity.26

While these or other factors may have led to a true increase in disease during the study period, our data suggest that increased testing, most likely due to expanding use of PCR during the study period, has almost certainly amplified the magnitude of notified pertussis activity in Australia. This increase in testing might have led to identification of illness that would have otherwise gone undetected among age groups in which pertussis circulates widely or age groups in which pertussis had previously been largely left as a clinical diagnosis.

Our findings have global implications, particularly for countries with high or expanding PCR availability. They highlight the critical importance of analysing changes in infectious diseases using a range of surveillance systems. By monitoring changes in laboratory testing and using surveillance datasets that do not rely on laboratory test results, it is possible to determine whether increases in notifications for diseases such as pertussis are due to a true increase in disease, an increase in testing, or a combination of both.

1 PRPs as a proportion of all BEACH problems with a pertussis test ordered and as a proportion of all BEACH problems, and NNDSS PCR tests as a proportion of all NNDSS pertussis notifications, April 2000 to March 2011

Period
(April – March)

PRPs as a proportion of all BEACH problems with a pertussis test ordered
(total no. of pertussis tests)

PRPs as a proportion
of all BEACH problems
(total no. of PRPs)

NNDSS PCR tests as a proportion of all NNDSS pertussis notifications (total
no. of pertussis notifications)

2000–2004

89.4% (141)

8.7% (51 396)

16.3% (16 983)

2004–2008

92.1% (216)

7.9% (45 872)

11.3% (31 559)

2008–2009

87.7% (114)

7.9% (12 551)

55.4% (17 945)

2009–2010

92.7% (164)

7.8% (12 228)

55.8% (22 754)

2010–2011

91.7% (216)

7.7% (11 557)

65.3% (33 641)

PRP = pertussis-related problem. BEACH = Bettering the Evaluation and Care of Health. NNDSS = National Notifiable Diseases Surveillance System. PCR = polymerase chain reaction.

2 Proportions of BEACH PRPs with a pertussis test ordered, and NNDSS pertussis notification rates, April 2000 to March 2011

BEACH = Bettering the Evaluation and Care of Health. PRP = pertussis-related problem.
NNDSS = National Notifiable Diseases Surveillance System. * Data for 2000–2004 and 2004–2008 are averaged annual rates, and data for 2008–2009, 2009–2010 and 2010–2011 are annual rates.

3 Proportions of BEACH PRPs with a pertussis test ordered, and NNDSS pertussis notification rates per 100 000 population, by age group, April 2000 to March 2011

Period (April – March)

Odds ratio
(95% CI)‡

Correlation coefficient (r)§

Pre-epidemic period*

Epidemic year†

Age group

Dataset

2000–2004

2004–2008

2008–2009

2009–2010

2010–2011

0–4 years

BEACH

0.16%

0.12%

0.48%

0.89%

1.31%

8.0 (3.9–17.2)

0.89

NNDSS

44.97

35.78

244.23

225.60

299.17

4.7 (4.3–5.2)

5–9 years

BEACH

0.16%

0.22%

0.78%

2.61%

1.87%

11.6 (4.2–36.7)

0.75

NNDSS

29.68

17.55

202.17

260.06

507.62

14.2 (12.8–15.7)

10–19 years

BEACH

0.36%

0.36%

1.27%

1.95%

2.05%

5.7 (2.8–11.4)

0.88

NNDSS

82.29

38.24

126.87

134.15

226.45

2.2 (2.1–2.3)

20–39 years

BEACH

0.33%

0.54%

0.92%

1.10%

1.76%

5.4 (3.5–8.5)

0.98

NNDSS

22.58

34.51

64.41

84.42

105.60

2.8 (2.6–3.0)

40–59 years

BEACH

0.25%

0.65%

1.05%

1.50%

2.09%

8.5 (5.2–14.0)

0.99

NNDSS

29.17

54.60

82.12

113.33

153.61

3.2 (3.0–3.4)

≥ 60 years

BEACH

0.19%

0.41%

0.50%

0.54%

1.43%

7.6 (4.3–13.7)

0.90

NNDSS

16.12

50.15

76.57

103.49

142.84

5.6 (5.1–6.2)

All ages

BEACH

0.25%

0.43%

0.80%

1.24%

1.71%

7.0 (5.5–8.8)

0.99

NNDSS

33.73

42.31

88.86

108.56

158.42

3.2 (3.2–3.3)

BEACH = Bettering the Evaluation and Care of Health. PRP = pertussis-related problem. NNDSS = National Notifiable Diseases Surveillance System. * NNDSS data are average notifications per 100 000 population per year. † NNDSS data are notifications per 100 000 population per year. ‡ Comparison
of 2000–2004 and 2010–2011 data. § Correlation between BEACH and NNDSS data.

4 NNDSS pertussis notifications by laboratory test method, April 2000 to March 2011

NNDSS = National Notifiable Diseases Surveillance System. PCR = polymerase chain reaction.

The drama of zoonoses

MY CAREER choice was based on non-fiction reading as a teenager. Starting with American journalist Berton Roueché, who adapted material from the terse Morbidity and Mortality Weekly Report covering investigations by the US Centers for Disease Control, I have been reading popular accounts of epidemics for a while.

And epidemics fascinated the earliest writers: pestilence as one of the horsemen of the Apocalypse in the Bible; Daniel DeFoe’s experimental Journal of the plague year, mistaken for reality by 18th century readers; 20th century disease “biographies”, with Hans Zinsser’s Rats, lice and history (on typhus), and countless others since. Australia has contributed to this literature, of course; Frank Bowden’s Gone viral is a recent example.

For such books, short words are preferred in the title — certainly not “epidemiology”. There is Robin Cook’s Vector, or the current entry into this crowded field, David Quammen’s Spillover, which was nominated for a 2013 Pulitzer Prize.

For me, popular epidemiology in a bookshop is always worth perusing, but is only purchased when necessary. What moved me from perusal to purchase in this case? I had to find out if Quammen had done justice to the story and memory of Brisbane horse trainer Vic Rail. And, indeed, the second paragraph of the opening chapter started thus: “The emergence of Hendra virus didn’t seem very dire or newsworthy unless you happened to live in eastern Australia.” In 1994, the disease killed Rail and his horse, and captured the attention of the Australian press, and students of communicable disease. Linda Selvey, then working as an epidemiologist in Queensland, investigated bats as a host of this disease. Years later, Quammen reconstructed the story, with careful interviews, and presents the “spillover”, from bats, with amplification in horses, and then to humans.

Spillover focuses on the passage of pathogens from one species to another. It is a book about emergence of animal disease and human disease as “strands of one braided cord” (p 13). Here, Quammen is not afraid of technical detail, explaining, for example, the Anderson and May model of parasite-host interactions (p 305), how the evolutionary success of a bug is directly related to its lethality, the rate of recovery from it, and the normal death rate from all other causes.

Quammen’s survey results from years of travel and interviews, and extensive reading of the original literature, and in general seems to fairly consider many old papers; this book does not derive from the latest multi-author textbooks. But would you be in safer hands turning to those modern texts? With the availability of collaborative online resources now, how many books like this one, the result of so much individual effort, will appear in the future?

The book is in the style of National Geographic, to which the author has contributed for many years. Alongside moments of drama, Quammen also takes the time to examine competing theories. The book’s subtitle points to the Next Big One — after a detailed examination of SARS, and a bit less on influenza — but there is so much more here. Good for a holiday read, Spillover will also be a valuable companion to anyone with a professional interest in zoonoses. Students needing the salient facts in a concise summary will start elsewhere, however.

Gambling is always a big subject, and currently more prominent with betting on Australian sports, while the flu season has many of us reassessing our disease risk, with or without this year’s vaccine. In the United States, there has been extravagant praise for Spillover, but I lost my bet that it would win a Pulitzer Prize.

Immigration screening for latent tuberculosis infection

Epidemiologist Justin Denholm advocates universal screening of migrants from high-incidence countries

In Australia, 1222 cases of tuberculosis (TB) were notified in 2011, which represents an annual incidence of six cases per 100 000 population.1 Despite this relatively low incidence by global standards, TB disease continues to cause significant morbidity and mortality, and has a substantial impact on the health and wellbeing of affected individuals and communities.2 In addition to the direct clinical impact, effective management of TB imposes a substantial burden on health care systems and public health programs. Opportunities to reduce TB incidence further in Australia, therefore, would be welcome and should be actively pursued.

Over the past decade, 80%–90% of people who developed TB in Australia were born overseas, with by far the most common clinical pathway to presentation being reactivation of previously latent TB infection (LTBI).3 People migrating to Australia from countries with high TB incidence are at significant risk of developing TB disease, even decades after arrival.4 In 2012, the National Tuberculosis Advisory Committee highlighted the importance of migrants in their strategic plan for control of TB in Australia, identifying overseas-born people in general, and overseas-born students in particular, as priority populations in the plan to reduce TB risk.5 Effective therapy for preventing reactivation is available, but most people who have LTBI have not been diagnosed and are unaware of their risk of developing active TB disease. Practical approaches to diagnosing LTBI among groups who are at high risk of TB disease are required, particularly close to the time of arrival in Australia because this is when diagnosis of LTBI would be most effective in preventing subsequent disease. While a variety of different strategies might accomplish this aim, perhaps the most efficient would be incorporating a screening program for LTBI into the existing immigration process.

Currently, TB screening in immigrants consists of a chest x-ray and a clinical examination before entry, to identify those with active disease. This program, combined with postmigration follow-up (the TB Health Undertaking) is effective in identifying migrants who have active TB infection.6 However, no testing for LTBI — with tests such as the tuberculin skin test or the interferon-γ release assay (eg, the QuantiFERON-TB Gold In-Tube assay [Cellestis], which is in use in Australia) — is performed routinely, apart from the testing done in accordance with recommendations to screen refugees and asylum seekers. Thus, the opportunity to systematically identify those at highest risk of progression to active TB is missed, as is the chance to intervene and prevent TB disease.

Arguably, the most appropriate approach to identifying LTBI in immigrants would be a requirement for LTBI testing to be performed on those arriving from countries with a high incidence of tuberculosis, followed by provision of effective LTBI therapy after arrival. For such a strategy to be justifiable, it should screen immigrants with an appropriately large risk of LTBI, using a test with high specificity, and positive test results should not be used to restrict migration.7 Data from LTBI screening programs in the United Kingdom suggest that the use of an interferon-γ release assay for screening immigrants from high-incidence countries would have a high yield of positive results — a positive test result is seen in 20% and 28% of migrants from the Indian subcontinent and sub-Saharan Africa, respectively.8 These programs are cost-effective when used to screen those younger than 35 years from countries with TB incidence of more than 40 cases per 100 000 population per year, with optimal efficiency for country thresholds of about 150 cases per 100 000 population per year.8 While an optimal threshold for the Australian context remains to be established, it is likely to be broadly comparable with the UK experience, suggesting that an efficient and cost-effective immigration screening program is a realistic consideration.

TB rates in Australia are likely to continue to rise due to the ongoing arrival of migrants with LTBI. While international efforts to control TB disease in high-incidence countries are critical for reducing transmission, prevention of LTBI reactivation is very important in terms of eradicating TB as a global public health issue. An immigration screening program for LTBI would be an effective and practical way to improve the health of new Australians through prevention of TB, reduce TB incidence and risk of secondary transmission in the Australian community, and further strengthen TB control programs in the Asia–Pacific region.

Expanding the evidence on cancer screening: the value of scientific, social and ethical perspectives

Experts have called for more attention to the politics, communication and ethics of screening, but there has been limited guidance on how this should be done. In this article, we propose the need for an expanded evidence base for cancer screening policy and practice. This has significant implications for cancer screening research, and for the type of research that could then be considered in evidence reviews and summaries. This approach builds on two ideas previously raised but not yet fully explored in the medical literature.1,2 The first is that we need to better understand why screening happens the way it does, sometimes apparently at odds with evidence of benefits and harms. This requires thinking about screening as a social process involving interest groups, politics, markets, consumers and health professionals. The second is that we need to think more systematically about the ethics of screening. Decades of screening guidelines and research have involved implicit moral judgements, but these have rarely applied formal ethical theory or drawn on empirical ethics research. By applying ethical frameworks and theories to guide research on moral and ethical questions in cancer screening, we will be more able to make ethical judgements on cancer screening policies and practices. We argue that more explicit and systematic investigation of the social and ethical aspects of cancer screening can support better informed and more accountable policy and practice decisions.

The value of formal inquiry into social and ethical aspects of screening

While attention to the benefits, harms and costs of cancer screening is essential, it is often insufficient to guide cancer screening policy and practice; for example, on prostate-specific antigen (PSA) screening3 or mammography.4,5 An expanded approach will allow a more comprehensive understanding of the social and ethical implications of cancer screening that would rely on the generation and use of three kinds of evidence:

  • Scientific evidence of the benefits, harms or costs of screening. This type of evidence is generally available — albeit sometimes unclear, or conflicting and contested — and already used in the development of screening policy and practice.

  • Evidence about screening as a social activity, producing descriptions and explanations of how and why screening is done. This will require empirical research about social structures and processes, and consideration of screening provision in relation to evidence, societal values, and political and commercial interests. This type of evidence is currently limited and not generally used in the development of screening policy and practice.

  • Evidence from empirical ethics research that is guided by formal ethical concepts and reasoning, and normative ethical frameworks to answer ethical questions about screening options. This type of evidence is currently very limited and is not used in the development of screening policy and practice.

These three types of evidence, and the knowledge and understanding that they generate, would mutually influence each other, as illustrated in Box 1.

Investigating screening as a social issue

Cancer screening is a complex social process, involving different people, organisations and technologies. Social research is valued in medicine and public health for its ability to answer questions about the way that things happen and what things mean. It generates knowledge about people, their interactions, and the way their actions can be explained in the context of social structures and situations. It examines accounts of individuals’ experiences and perspectives on the world, and observes their actions, how they talk, and the way they use technologies and other material things. It can also examine and explain positions taken and the actions of groups such as social, professional or commercial entities. Interviews, focus groups, direct observations and existing documents (such as policies, websites or newspapers) can all provide data for research to determine how screening is currently occurring, why it is occurring in that way, and what is required to change how it occurs.

Research on how screening programs have developed would explain why implementation is variable, consistent or inconsistent with the evidence base, how screening providers make decisions in the context of uncertainty, and how conflicts have developed. Research on how screening programs are provided can also explain how and why consumers, providers, decisionmakers and commercial interests act in relation to screening. For example, why consumers overestimate screening benefits, how technologies can become entrenched in the absence of evidence, and how financial or institutional interests influence communication about screening. Fletcher has argued that population scientists need “to better communicate with the public if evidence-based recommendations [about screening] are to be heeded by clinicians, patients, and insurers”.2 This can only be achieved through understanding the actions, influences and motivations of all interest groups, and this can be empirically derived and described through systematic and rigorous social research.

Investigating screening as an ethical issue

Ethics is the branch of philosophy focused on moral reasoning and determining right actions; it aims to discover the right thing to do, and to determine why it is right. A number of writers have considered the ethics of screening, but screening research has not routinely considered ethical questions. Formal application of ethical theory in designing screening research could provide frameworks to examine and explain existing moral concerns in screening; expand the scope of what is investigated by introducing concepts and theories to drive new cancer screening research; and make explicit the plurality of values in screening decisions and offer criteria to evaluate whether and how well this plurality has been addressed.

Ethics can provide new tools to address moral concerns that have been troubling screening experts for many decades. For example, Fletcher’s analysis of breast cancer epidemiology,2 the proposal by Harris and colleagues that screening should be evaluated according to the umbrella concept of a “predictor of poor health”,1 or Eddy’s cost-effectiveness analysis decision tables6 all seek to answer a question with moral significance: how can we best maximise the benefits and minimise the harms of intervention? This question is central in utilitarianism, which considers the best actions to be those that generate the greatest utility for the greatest number of people — where utility might be defined as pleasure, happiness or health, or more generically, benefit. The literature about the strengths and weaknesses of utilitarianism can inform how we study the benefits and harms of screening. Traditional approaches to screening have been critiqued as “naively utilitarian”,7 for downplaying the moral significance of harming some to benefit others, and the consequences of service providers failing to disclose the possible harms of screening to recipients. Critiques of utilitarianism might also encourage further study of which benefits and harms count in a decision-making calculus, or the problems and implications of combining qualitatively different benefits and harms into a single metric.8

Other ethical theories emphasise different concerns, such as our moral duty to respect others, and how to balance concerns for individuals with concerns for communities. Such theories encourage explicit examination of the responsibilities of service providers towards screening candidates, empirical evaluation of the moral significance and impact of supporting (or not supporting) the autonomy of those screened, and whether there are any conditions under which mandatory screening might be considered acceptable.

Three-dimensional evidence: examining PSA screening as a scientific, social and ethical issue

We apply the proposed three-pronged approach to guide cancer screening research to the example of PSA testing (Box 2). This illustrates what types of scientific, social and ethical questions have been investigated to date, although social and ethics research is not often considered as evidence in reviews that guide cancer screening policy and practice. We also suggest questions that could be addressed if the expanded three-dimensional approach to evidence were to be applied to guide new PSA screening research.

The new health technology assessment (HTA) core model for screening technologies developed by the European network for HTA illustrates how an expanded assessment of cancer screening can be operationalised.25 This tool identifies questions for assessing the clinical, economic, ethical and social (which they distinguish from organisational and legal) implications of screening technologies. Although the HTA core model does not explore the interactions between the scientific, social and ethical domains identified in this article, the European approach is significantly broader than that adopted by the American Cancer Society, which focuses on scientific evidence.26 Unfortunately, there are significant gaps in the empirical work required to answer many of the questions posed in the European HTA model, and when appropriate social and ethics research is lacking, answers are sought from brief consultations and expert opinion.25 An expanded social and ethical agenda for cancer screening research would begin to address these gaps in the evidence. This would better support the commencement, provision or discontinuation of screening, inform public communication about screening, and assist citizens’ decisions about screening. As we move towards the second century of cancer screening, we need to ensure accountability to the citizens whose lives are changed, for better and for worse, by cancer screening programs. We believe the approach proposed is necessary to ensure such accountability.

1 A threefold approach for evaluating cancer screening

2 Scientific, social and ethics research on prostate-specific antigen (PSA) screening, and future research questions

Domain 1: benefits, harms and costs

Domain 2: social processes

Domain 3: ethics

Purpose of investigations

Measure benefits, harms and costs of PSA screening

Describe the way that PSA screening is provided and communicated about, and explain how it came to
be that way

Guide deliberation regarding the right policy and practice response, and formulate good reasons for those conclusions

Interactions with other domains

Ethics can identify new outcomes or distributions of outcomes to measure; social research can explain why PSA screening practice does not always align with evidence-based recommendations

Evidence of benefits, harms and costs can identify unanticipated effects that require social explanations; ethical frameworks can suggest research questions for social research

Ethical reasoning relies on evidence of benefits, harms and costs; ethical reasoning will be improved by understanding the social context, social structures and processes

Questions addressed in available research

Evidence reviews and recommendations for policy and practice:

  • What are the net benefits and harms of PSA screening, and what is the evidence-based recommendation for practice?3,9,10

  • What is the cost-effectiveness of PSA screening?11

Behaviour of physicians and patients:

  • Do trials and United States Preventive Services Task Force recommendations have some impact on PSA testing?12

  • Do physicians influence the likelihood of patients being tested, and what predicts the likelihood of physicians recommending PSA testing?13

  • What advice do physicians give patients about PSA testing?14

  • How do men respond to physician advice and why?15

Ethical evaluations of PSA screening:

  • What are important limitations and gaps in
    the traditional screening evaluation criteria?7

  • Under what circumstances it is ethical to provide individuals with screening tests that are not recommended at population level?19

  • How does consent apply to the sons of men with diagnosed prostate cancer with no clinical significance?20

Public understandings and communications:

  • How do consumers understand the benefits and harms of PSA screening, and what is the impact
    on screening?16

  • How do the media report on PSA testing?17

  • How do consumers respond to media reporting about PSA testing?18

Empirical findings with ethical implications for action: is it possible to produce better-informed decisions using community-based interventions21
or individual, online decision aids?22

Ethical implications of questions posed in domain 1: is cancer screening necessary and proportional to the problem, and what is the opportunity cost?1,2,23

Questions for further research

  • What are the broader social and ethical benefits and harms of PSA screening?

  • What is the social distribution of harms?

  • Are there any conditions under which benefits might outweigh harms?

  • Is PSA testing cost-effective?

How does PSA screening occur? Why does it occur
that way?

  • How has PSA screening come to be a solution
    for the problem of prostate cancer?

  • What drives testing in men? What are the supply-side and demand-side drivers for testing against the evidence?24

  • What is the experience of men who have different screening outcomes?1

  • How is PSA screening used in different jurisdictions? If this varies, how can we explain the variation?

  • What do clinicians consider their moral obligations to be in relation to PSA testing?

Can PSA screening be ethically justified? If so, how? If not, why not?

  • What do stakeholders value about PSA testing?

  • What harms and benefits, beyond morbidity and mortality, should be included in evaluation of PSA testing? Why?

  • Are men coerced into PSA testing?

  • Are the burdens of PSA testing inequitably distributed?

  • Is PSA policy accountable and transparent?

  • Can we justify being paternalistic (restricting access to PSA even when men want it)?

Human papillomavirus vaccine in boys: background rates of potential adverse events

Cervical cancer is the most common cancer affecting women in developing countries. It is caused by persistent infection with specific types of human papillomavirus (HPV).1 Quadrivalent human papillomavirus (4vHPV) vaccine is a recombinant vaccine administered as a three-dose course to provide protection against four types of HPV (6, 11, 16 and 18).2 The vaccine is highly efficacious for the four included types, of which 16 and 18 are reported to cause 70% of cervical cancers and 6 and 11 cause anogenital warts.1,3 4vHPV vaccination was introduced under the Australian National Immunisation Program (NIP) in April 2007 for adolescent girls, with an initial catch-up program including women up to 26 years of age. The current ongoing funded program is only for girls in the first year of high school (aged 12–13 years). Recent data suggest that the 4vHPV vaccination program has caused a rapid decline in genital wart presentations in females,4,5 and there are early indications of a reduction in high-grade cervical dysplasias.6

Following advice from the Australian Technical Advisory Group on Immunisation, vaccination of males was recommended as a cost-effective intervention by the Pharmaceutical Benefits Advisory Committee in November 2011.7 Accordingly, 4vHPV vaccination for boys has been added to the Australian NIP, commencing in 2013 and targeting boys aged 12–13 years in a school-based program, with a catch-up program over 2 years for boys aged 14–16 years.7,8 The program aims to reduce the incidence of HPV disease in males, such as anogenital warts and anal intraepithelial neoplasia,9 and reduce sexual pathways of virus transmission. Australia will be the first nation to implement HPV vaccination for boys in a national program.

Vaccines, as with any medicine, have potential adverse reactions varying from mild and expected to rare and/or serious events. Vaccination may cause such events — the nature of adverse events following immunisation (AEFI) and the timing of onset after vaccination are important factors when assessing causation. Adverse events may also coincide temporally with vaccine administration by chance. To interpret postlicensure surveillance data, it is useful to know the background rates of common and rare potential adverse events before introduction of the vaccine.10,11 With this understanding, increases above background rates can be rapidly identified, which can assist with the evaluation and reporting of potential vaccine-associated adverse event rates.

The mass school-based introduction of female 4vHPV vaccination raised a number of well publicised initial safety concerns, including “scares” regarding potential episodes of anaphylaxis and multiple sclerosis after vaccination.12–14 In addition, a mass psychogenic reaction was seen in a Melbourne school vaccination environment,15 with syncope and syncopal seizures occurring in response to the vaccination process.16 Such spurious events may arise from the psychological impact of the vaccination process, particularly when using mass vaccination strategies in a school-based teenaged population.

Release of the 4vHPV vaccine to boys has the advantage of adverse event information from prelicensure clinical trials and postlicensure surveillance of adverse events arising from administration to adolescent girls. However, additional information on the background rates of potential adverse events in teenaged boys is critical for assessing the safety of this vaccination program.

Our aim was to explore the use of routinely collected information for estimating potential adverse event rates. We used population-level health outcome administration data to describe the background rates of potential AEFI before the introduction of 4vHPV vaccination for boys into the NIP in Australia, and to estimate numbers of a range of neurological, allergic and other events that can be expected following vaccination, assuming temporal association with administration of vaccine but no other association.

Methods

Two statewide Victorian datasets were accessed — the Victorian Admitted Episodes Dataset (VAED; hospital discharge data) and the Victorian Emergency Minimum Dataset (VEMD; emergency department visit data) — both of which include International Classification of Diseases 10th revision Australian modification (ICD-10-AM) codes. The data included a unique identifier that enabled linking of individuals across the datasets, but were otherwise non-identifying, according to Victorian Department of Health data linkage protocols.17 Ethics approval for the study was provided by the VAED and VEMD data custodians.

Multiple records of the same event within a dataset or across datasets — for example, a person presenting at emergency who is subsequently admitted, or a person admitted to hospital who is then discharged to a different hospital or to home and who later returns with continuation of the same episode (with each presentation recorded as a separate event) — were linked via the unique identifier. All events occurring within 28 days of a previous event were combined into a single episode.

The data that we analysed comprised all episodes that occurred in boys aged 12 to < 16 years and were recorded in the VAED and/or VEMD with one of the ICD-10-AM codes listed in Box 1 and an admission or presentation date from 1 July 2004 to 30 June 2009.18 Conditions selected for inclusion are rare adverse events, conditions that patients are likely to present to hospitals with after vaccination, and conditions that have previously been raised as potential sources of concern in Australia and overseas.10,19

Age was taken to be the youngest age at which an episode occurred, and records were excluded from the analysis if sex was recorded inconsistently among records with the same unique identifier. Some records had more than one ICD-10-AM code, and these were preserved. Events with an interstate or overseas postcode were excluded, but those with “unknown” (8888 and 9988) and “of no fixed abode” (1000) postcodes were preserved under the assumption that these occurred in Victoria. Episodes that were ongoing from the 3 months before the study period, the washout period (31 March to 30 June 2004), were also excluded.

Events were described as the number of episodes and the number of first events. An episode was considered a discrete event if it occurred more than 28 days after a prior event in the same individual, as patients were deemed to still be “at risk” of the same event during their recovery from an acute condition. First events were defined as the first time a condition was diagnosed in each patient during the study period. First events are more relevant for chronic conditions and episodes are more relevant for acute conditions.

We calculated background annual incidence rates as the number of events during the 5-year study period divided by the population at risk during this period, using Australian Bureau of Statistics 2006 mid-year resident population data for males.20

The analysis was restricted to boys aged 12 to < 16 years — the target age range for vaccination. We used these background rates to estimate the number of events expected within 1 day, 1 week and 6 weeks of vaccination per 100 000 vaccinees. We then estimated the expected number of events for each condition 1 day, 1 week and 6 weeks after vaccination across Australia following the introduction of 4vHVP into the NIP, assuming there is no association (other than temporal) with the vaccine.

Seasonal variation was analysed by graphing the number of first events or episodes by month of presentation. As the numbers of chronic neurological presentations in the study group were small, they were combined and compared with numbers of all-age presentations in males for individual neurological conditions. For multiple sclerosis, data were also presented omitting presentations in the first 12 months of the study period to assess the effectiveness of the study’s 3-month washout period.

Results

The numbers of and incidence rates for potential AEFI in boys aged 12 to < 16 years are shown in Box 2, and the estimated numbers of cases of potential AEFI per 100 000 adolescent boys that would occur, even in the absence of vaccine, are shown in Box 3. Assuming an 80% vaccination rate with three doses per person — which equates to about 480 000 boys vaccinated and a total of 1 440 000 doses administered nationally per year in the first 2 years of the program — about 2.4 episodes of Guillain-Barré syndrome would be expected to occur within 6 weeks of vaccination. In addition, about 3.9 seizures and 6.5 acute allergy presentations would be expected to occur within 1 day of vaccination, including 0.3 episodes of anaphylaxis.

There was minimal seasonal variation in the occurrence of potential AEFI (Box 4, Box 5). However, repeating this analysis with a larger number of neurological presentations (using data for all age groups) revealed a notable peak in the number of multiple sclerosis presentations in July. This peak was reduced but not eliminated when the washout period was increased to 15 months (Box 4).

Discussion

Using statewide morbidity data, we estimated background rates of neurological and allergic events in adolescent boys in Victoria to be 252.9 and 175.2 per 100 000 person-years, respectively. Such adverse events may be mistakenly assumed to be caused by vaccination, owing to temporal association, when the 4vHPV vaccination program is expanded to include adolescent boys.10 Postlicensure safety assessments of 4vHPV vaccine programs in adolescent girls have shown little evidence of increased risk of neurological and allergic adverse events after vaccination.3,21,22

Expected rates of potential AEFI in recent studies vary widely, but direct comparisons are restricted because of differences in methods, health care systems and data collection and analyses.10,11,23 In particular, caution is required when using emergency presentation databases as these may record preliminary diagnoses, rather than final diagnoses. Studies limited to analysis of ICD-10 coded data, such as ours, lack the rigour of diagnosis verification and conformity to standardised case definitions, although coding standards are maintained. Our study identified higher reporting rates for anaphylaxis compared with similar studies.10,11 While data aberrations are possible, marked increases in anaphylaxis rates Australia and the United States over the past two decades may play a part.24,25

Background rates of potential AEFI and consequent thresholds for safety flags should not be informed merely using data on adolescent girls because sex-related differences could cause misinterpretation of potential signals.10,11 For example, the rate of adolescent boys presenting with a first multiple sclerosis event in the 6 weeks following vaccination would be expected to be one-third of the rate seen for adolescent girls assuming no relationship with vaccine other than temporal.26

In our study, we used a 3-month washout period to attempt to remove the risk of categorising events as incident cases when they were part of a pre-existing illness than was ongoing from before the study period. However, the 3-month washout period did not remove this issue for multiple sclerosis. While our study showed little seasonal variation in potential AEFI, school-based vaccination programs are conducted in blocks (as convenient to the vaccine schedule and the school year), which may give rise to false signal detection. Specific investigation of appropriate washout periods, as well as seasonal variation in the occurrence potential AEFI and implementation of the vaccine program, must therefore be explored before conducting in-depth analyses for specific conditions or extrapolating data to other jurisdictions.

In Victoria, first-dose 4vHPV vaccine coverage for adolescent girls has reached 80%,27 but challenges of uptake and course completion by males may be anticipated.28 If coverage for boys is less than 80%, the expected rates in our study should be recalculated to avoid erroneous alert thresholds.

The background rates of potential AEFI that we have estimated can be used to inform surveillance systems, health care providers and the community regarding health care events that may be temporally related to vaccination. In mass vaccination programs, where vaccine exposure is a common event in the target group, many incident acute health conditions will occur following vaccination, irrespective of causal association. While current passive surveillance system reporting is likely to underascertain postvaccination events, prior knowledge of expected numbers of events are valuable in helping determine whether reports or clusters of reports represent real safety flags that require urgent investigation.26

Our data highlight the value of statewide and nationwide health datasets in providing information that can improve public safety. In addition to establishing background rates of diseases, international systems such as those in Denmark and the US, have been used to link vaccination databases to health care event databases, enabling direct investigation of potential associations with adverse events.29–31 These methods, conducted in accordance with state and federal privacy protections, offer a promising future for further improving vaccine safety in Australia.32

Routinely collected state health outcome data can enable informed postlicensure safety surveillance of conditions that may be perceived as AEFI. When the 4vHPV vaccine program is expanded to adolescent boys, such data can be used for targeted active surveillance of potential vaccine safety flags.

1 Conditions included in the study

ICD-10-AM codes

Neurological

Guillain-Barré syndrome*

G61.0

Transverse myelitis*

G37.3

Multiple sclerosis*

G35

Optic neuritis*

H46, G36.0

ADEM

G04.0

Bell’s palsy

G51.0

Syncope

R55

Seizures

R56, R56.0, R56.8

Allergic

Anaphylaxis

T78.2, T88.6

Urticaria

L50.0, L50.1, L50.9

Serum sickness

T80.6

Adverse effect of drug or medication†

T88.7

Other

Adverse events

T78.8, T78.9, T88.1, T78.3

ICD-10-AM = International Classification of Diseases 10th revision Australian modification. ADEM = acute disseminated encephalomyelitis. * Conditions considered chronic. † Not otherwise specified.

2 Numbers of and incidence rates for potential AEFI in boys aged 12 to < 16 years (Victoria, July
2004 – June 2009)

First events

Episodes

No. of events

Incidence rate (95% CI) per 100 000 person-years

No. of events

Incidence rate (95% CI) per 100 000 person-years

Neurological

Guillain-Barré syndrome

10

1.46 (0.56 to 2.37)

11

1.61 (0.66 to 2.56)

Transverse myelitis

2

0.29 (− 0.11 to 0.70)

3

0.44 (− 0.06 to 0.94)

Multiple sclerosis

2

0.29 (− 0.11 to 0.70)

2

0.29 (− 0.11 to 0.70)

Optic neuritis

4

0.59 (0.01 to 1.16)

6

0.88 (0.18 to 1.58)

ADEM

8

0.17 (0.45 to 1.90)

11

1.61 (0.66 to 2.56)

Bell’s palsy

60

8.78 (6.56 to 11.00)

60

8.78 (6.56 to 11.00)

Syncope

807

118.0 (109.9 to 126.2)

831

121.5 (113.3 to 129.8)

Seizures

666

97.4 (90.0 to 104.8)

830

121.4 (113.1 to 129.7)

Total

1516

221.7 (210.6 to 232.9)

1729

252.9 (241.0 to 264.8)

Allergic

Anaphylaxis

49

7.17 (5.16 to 9.17)

51

7.46 (5.41 to 9.51)

Urticaria

620

90.7 (83.6 to 97.8)

647

94.6 (87.3 to 101.9)

Serum sickness

23

3.4 (2.0 to 4.7)

23

3.4 (2.0 to 4.7)

Allergic reaction

495

72.4 (66.0 to 78.8)

517

75.6 (69.1 to 82.1)

Total

1125

164.6 (154.9 to 174.2)

1198

175.2 (165.3 to 185.1)

Other

Total

7

1.02 (0.27 to 1.78)

7

1.02 (0.27 to 1.78)

AEFI = adverse events following immunisation. ADEM = acute disseminated encephalomyelitis.

3 Estimated numbers of cases of potential AEFI in vaccinated boys aged 12 to < 16 years, assuming no relationship with vaccine*

No. of first events per 100 000 population

No. of episodes per 100 000 population

1 day

1 week

6 weeks

1 day

1 week

6 weeks

Neurological

Guillain-Barré syndrome

0 (0.00–0.01)

0.03 (0.01–0.05)

0.17 (0.06–0.27)

0 (0.00–0.01)

0.03 (0.01–0.05)

0.19 (0.08–0.29)

Transverse myelitis

0 (0.00–0.00)

0.01 (0.00–0.01)

0.03 (0.00–0.08)

0 (0.00–0.00)

0.01 (0.00–0.02)

0.05 (0.00–0.11)

Multiple sclerosis

0 (0.00–0.00)

0.01 (0.00–0.01)

0.03 (0.00–0.08)

0 (0.00–0.00)

0.01 (0.00–0.01)

0.03 (0.00–0.08)

Optic neuritis

0 (0.00–0.00)

0.01 (0.00–0.02)

0.07 (0.00–0.13)

0 (0.00–0.00)

0.02 (0.00–0.03)

0.10 (0.02–0.18)

ADEM

0 (0.00–0.01)

0.02 (0.01–0.04)

0.15 (0.05–0.25)

0 (0.00–0.01)

0.03 (0.01–0.05)

0.19 (0.08–0.29)

Bell’s palsy

0.02 (0.02–0.03)

0.17 (0.13–0.21)

1.01 (0.75–1.26)

0.02 (0.02–0.03)

0.17 (0.13–0.21)

1.01 (0.75–1.26)

Syncope

0.32 (0.30–0.35)

2.26 (2.11–2.42)

13.57 (12.64–14.51)

0.33 (0.31–0.36)

2.33 (2.17–2.49)

13.98 (13.03–14.93)

Seizures

0.27 (0.25–0.29)

1.87 (1.73–2.01)

11.20 (10.35–12.05)

0.33 (0.31–0.35)

2.33 (2.17–2.48)

13.96 (13.01–14.91)

Total

0.61 (0.58–0.64)

4.25 (4.04–4.46)

25.50 (24.22–26.78)

0.69 (0.66–0.72)

4.85 (4.62–5.07)

29.08 (27.71–30.45)

Allergic

Anaphylaxis

0.02 (0.01–0.03)

0.14 (0.10–0.18)

0.82 (0.59–1.05)

0.02 (0.01–0.03)

0.14 (0.10–0.18)

0.86 (0.62–1.09)

Urticaria

0.25 (0.23–0.27)

1.74 (1.60–1.87)

10.43 (9.61–11.25)

0.26 (0.24–0.28)

1.81 (1.67–1.95)

10.88 (10.04–11.72)

Serum sickness

0.01 (0.01–0.01)

0.06 (0.04–0.09)

0.39 (0.23–0.54)

0.01 (0.01–0.01)

0.06 (0.04–0.09)

0.39 (0.23–0.54)

Allergic reaction

0.20 (0.18–0.22)

1.39 (1.27–1.51)

8.33 (7.59–9.06)

0.21 (0.19–0.22)

1.45 (1.32–1.57)

8.70 (7.95–9.44)

Total

0.45 (0.42–0.48)

3.15 (2.97–3.34)

18.92 (17.82–20.03)

0.48 (0.45–0.51)

3.36 (3.17–3.55)

20.15 (19.01–21.29)

Other

Total

0 (0.00–0.00)

0.02 (0.01–0.03)

0.12 (0.03–0.20)

0 (0.00–0.00)

0.02 (0.01–0.03)

0.12 (0.03–0.20)

AEFI = adverse events following immunisation. ADEM = acute disseminated encephalomyelitis. * Data are based on one dose of vaccine per vaccinee.

4 Numbers of first events of chronic conditions, by month (Victoria, July 2004 – June 2009)

* Data are numbers of first events for chronic neurological conditions analysed in boys aged 12 to
< 16 years and numbers of presentations for individual neurological conditions in males of all ages.
† Conditions included were Guillain-Barré syndrome, transverse myelitis, multiple sclerosis and
optic neuritis.

5 Number of episodes of acute conditions by month in boys aged 12 to < 16 years (Victoria, July 2004 – June 2009)

ADEM = acute disseminated encephalomyelitis.

Injuries to the head and face sustained while surfboard riding

To the Editor: Surfboard riding is an iconic pastime in Australia. Injuries to the head and face constitute a considerable proportion of surfing injuries;1–5 26% of acute surfing injuries are to the head and face, and these make up 42% of emergency department presentations by surfers.3

We conducted a retrospective review at our tertiary referral hospital of patients who underwent medical imaging for injuries sustained to the head and face while surfboard riding from January 2008 to January 2012. We searched the hospital radiology databases for patient records containing the terms “surfboard”, “surfer” or “surfing”. Patients were included if they were injured while surfboard riding and were excluded if they were injured during other water-based activities (eg, bodyboarding, kitesurfing, bodysurfing, paddleboarding). Twenty-nine patients were identified: 23 males and six females (mean age, 34 years; range, 10–73 years). Of the 26 who had acute injuries, 17 had imaging of the head only, seven had imaging of the head and cervical spine and two underwent a trauma protocol (computed tomography scans of the head, spine, chest and abdomen). Fifteen patients had been struck in the head by their own board, nine had other mechanisms of injury (primarily involving contact with the sea floor and associated neck pain), one collapsed while surfing and one was retrieved from the surf unconscious (mechanism of injury was unknown). The most common significant injuries were facial fractures (five of 26 patients, all of whom had been struck by their own board). One patient ruptured their left globe after being struck by their own board. No intracranial trauma (eg, intracranial haemorrhage, contusion) was identified.

Surfboard design and surfing accessories have evolved significantly over the past 20 years. Lighter, shorter boards are now commonly used and provide greater manoeuvrability in the water. Leg ropes are universally used to ensure that surfer and board do not become separated (Box). However, lighter boards and leg ropes might increase the risk of being struck and injured by one’s own board during a “wipe-out”. The pointed nose and fins on the undersurface of the board are also potentially injurious (Box).

Understanding injury mechanisms can drive surfboard and surfing accessory design to reduce the risk of injury and death. Protective devices — such as helmets, protective eyewear and nose guards that cover the tip of the surfboard — have been marketed, but there is no evidence of their effectiveness in injury reduction.

Innovations in surfboard design that are potentially injurious to the surfer

A: Leg rope. B: Pointed nose at the front of the board. C: Fins on the undersurface of the board (a three-fin design is the most common configuration on a modern shortboard).

Everett Koop — from pariah to paragon

Leading tobacco-control advocate Mike Daube pays his respects to an elder statesman of American public health

If former United States Surgeon General Everett Koop, who died on 25 February at the age of 96, had died in 1981, obituaries would have described him as a distinguished and innovative paediatric surgeon and teacher, widely known for his evangelical Christianity and his leadership in the antiabortion movement that endeared him to many conservatives in the US.

When Republican president Ronald Reagan — who earlier had featured as an actor in cigarette advertisements — nominated him as Surgeon General in 1981, the opposition from Democrats, media and many in the public health community was instant and ferocious. A New York Times editorial headed “Dr Unqualified” claimed that he lacked public health credentials, was too old and conservative, and his appointment would “be an affront both to the public health profession and the public”.1

By the end of his term in 1989, Koop was a public health hero. Surgeons General have little power: they depend for their impact on the role’s prestige, selection of issues, political savvy and communication skills. Koop looked, and spoke, like an Old Testament prophet. A superb and authoritative communicator, he used the standing of his office — and its vice-admiral’s uniform — to arguably greater effect than any Surgeon General before or since.

He is probably best known for his leadership in campaigning against smoking. He released a series of well publicised Surgeon General’s reports, highlighting the evidence on addiction, and declaring unequivocally that passive smoking is a cause of cancer and that children should be protected from it. He led moves to stronger health warnings and smoke-free environments and called for a smoke-free US by 2000. He not only attacked the “immoral” tobacco industry for “exporting death, disease and disability to the Third World”,2 but did so deep in the heart of US tobacco country. His powerful public statements, combining scientific rigour, evangelical rhetoric and a personality the media loved, constantly reminded the public of smoking’s hazards and encouraged tobacco control activists and action globally.

Although personally opposed to abortion, he believed that a Surgeon General must be informed by the evidence. President Reagan sought a report from him on the effects of abortion on women’s health, clearly expecting it to echo Koop’s previously expressed views. To the dismay of his former devotees, Koop decided after lengthy reviews of the evidence that an antiabortion report was not appropriate, because he had concluded that, in terms of harm, the evidence was insufficient to support “either the preconceived notions of those pro-life or those pro-choice”.3

Kept out of the AIDS debate for some years by the President’s office, he eventually found a rationale for his involvement and, again to the dismay of his earlier backers, became an unstoppable supporter for public health action and education. He bluntly advised all Americans about condom use, and promoted sex education for children “at the lowest grade possible”.4 He ensured the distribution of leaflets on AIDS to over 100 million households. His rationale was clear: “I am the Surgeon General of the heterosexuals and the homosexuals, of the young and the old, of the moral or the immoral, the married and the unmarried. I don’t have the luxury of deciding which side I want to be on”.5

Following from his professional experience as a paediatric surgeon, he championed the cause of babies born with disabilities, leading to the passing by Congress of the “Baby Doe” law that protected their interests.6

Koop saw the role of Surgeon General as one from which he could change the world; but beyond his public personality, he based his work, advice and campaigns on the best available science. Consequently, his views were sought, and respected, on many issues. He feared no one, whether tobacco companies or powerful conservative southern senators, and picked his issues carefully, focusing on areas where it was possible to make a significant impact on public health and the rights of the vulnerable.

Those of us who knew him from his work on tobacco learned that behind the formidable exterior lay a kind personality and a willingness to help and support younger campaigners around the world, as well as in the US.

Helped by Koop’s work and advocacy, action on smoking in Australia moved to new levels in the 1980s, with pioneering Quit campaigns and moves to ban cigarette advertising and strengthen health warnings and protection from passive smoking. Similarly, his humane stance on AIDS provided encouragement to Australians promoting evidence-based responses to challenging public health problems.

Everett Koop showed American health leadership at its best: with fearlessness, a strong public health focus, wonderful communication skills and a belief that “in science, you can’t hide from the data”.7