Risk factors and burden of acute Q fever in older adults in New South Wales: a prospective cohort study

Q fever is a highly infectious zoonotic disease caused by the bacterium Coxiella burnetii.1–3 The main reservoirs for this bacterium are domestic and wild animals, and it can be excreted in their urine, faeces, milk and products of conception, and can survive in harsh environmental conditions.1 Transmission to humans occurs mainly through direct contact with infected animal products or by inhalation of contaminated dust or aerosols.4 In humans, Q fever manifests as an acute flu-like illness or, less frequently, with pneumonia or hepatitis; infection is often asymptomatic.1 Chronic Q fever, most frequently presenting as endocarditis, occurs in about 5% of symptomatic cases.1 Q fever fatigue syndrome is the most frequently reported sequela of acute infection (10%–20% of cases).5

A Q fever vaccine is available in Australia and is recommended for those at high occupational risk of infection.6,7 During 2001–2006, the federal government funded the National Q Fever Management Program (NQFMP) in various states, including New South Wales; under this program, people at high risk were screened and vaccinated, including abattoir workers, sheep shearers, and sheep, dairy and beef cattle farmers and their farm workers. Uptake of the vaccine was almost 100% among abattoir workers and about 43% among farmers; the program significantly reduced the number of notified cases of Q fever in abattoir workers.7 National notification rates suggest there was some decline in the incidence of Q fever during 2006–2009 — from 2.0 to 1.4 notified cases per 100 000 population — but this was followed by a gradual return to 2.0 cases per 100 000 population by 2014; the highest reported rates were among adults aged 45–69 years.8

Most epidemiological studies have been retrospective and focused on specific occupational groups,9,10 and there are only limited data on factors associated with Q fever risk outside these populations. We therefore examined the risk and acute burden of Q fever in a population-based prospective study of Australian adults aged 45 years and over living in NSW.

Methods

Participants

We used data for participants recruited in NSW during 2006–2009 for a prospective study of adults aged 45 years and over (the Sax Institute’s 45 and Up Study); the recruitment procedures have been published elsewhere.11 In brief, NSW residents aged 45 years or over were randomly selected from the Australian Medicare database and invited to participate. The 45 and Up Study oversampled residents in rural and remote areas, and those aged 80 years and over. At recruitment, participants completed a baseline questionnaire that provided information on their sociodemographic factors, behaviour and health.12

Participants consented to long-term follow-up and linkage of their data.11 For the study described in this article, participants were linked to the NSW Notifiable Conditions Information Management System (NCIMS), the NSW Admitted Patient Data Collection (APDC) and the NSW Registry of Births, Deaths and Marriages (RBDM). The NSW Centre for Health Record Linkage (CHeReL) performed the linkage independently of the study investigators, using probabilistic matching.

The NCIMS database records all notifications of Q fever in NSW residents; it includes information on the date of onset and details of laboratory confirmation, including the type of specimen used. Notifications of Q fever require laboratory definitive evidence or laboratory suggestive evidence together with clinically compatible disease (Box 1).13 The APDC records information about all admissions to hospitals in NSW, including the date of admission and discharge, the primary diagnosis, and up to 49 secondary diagnoses affecting treatment or length of stay, coded according to the International Classification of Diseases, 10th revision, Australian modification (ICD-10-AM). The RBDM records the date of death of NSW residents.14 For this study, the data from the NCIMS and RBDM were complete to 31 December 2012, and the APDC data were complete to 30 June 2012.

All participants provided written informed consent. This study was approved by the NSW Population Health Research Ethics Committee (approval number, 2010/12/292) and the University of New South Wales Human Research Ethics Committee.

Outcome definitions

The study outcomes were incident Q fever diagnoses (cases) and the proportion of these patients who were admitted to hospital. We defined participants as having an incident Q fever diagnosis if they had a linked record of notified Q fever in the NCIMS database after recruitment. Cases of Q fever with linked hospital records between 6 weeks before and after the Q fever notification date were examined, and classified as follows:

primary Q fever: at least one hospitalisation for which the ICD-10-AM code A78 was recorded as the primary diagnosis
secondary Q fever: at least one record including A78 as a secondary diagnosis
Q fever-related: no A78 codes but one of the following primary diagnoses recorded: A49.9 (bacterial infection, unspecified), B17.9 (acute viral hepatitis, unspecified), B34.9 (viral infection, unspecified), J18.9 (pneumonia, unspecified organism), or R50.9 (fever, unspecified);15,16 and
presumed unrelated: none of the above recorded.

The 6-week window was chosen because most cases of acute illness resolve within 6 weeks of onset.17 The number of deaths among notified Q fever patients within 6 weeks of the recorded onset of disease were determined.

Statistical analyses

Analyses excluded those with a record of Q fever notification before study recruitment. Person-years at risk were calculated from the date of study recruitment to the date of Q fever onset or death, or 31 December 2012, whichever occurred first. Hospitalisation analyses were restricted to cases with a diagnosis date on or before 20 May 2012; ie, 6 weeks before the last date for which we had complete hospital records. This restriction was imposed to ensure that all hospitalisation events within 6 weeks of the onset of Q fever were captured.

The incidence of notified Q fever cases was estimated according to age (stratified as 45–54 years, 55–64 years and 65 years or older); sex; area and type of residence (a composite variable that includes both area of residence — major city, inner regional or outer regional/remote/very remote, according to the Accessibility/Remoteness Index of Australia [ARIA+] — and accommodation type — living on a farm or not); smoking history (never or ever smoked); and number of hours spent outdoors each day (less than 4, 4 to less than 8, 8 hours or more).

We used Cox proportional hazard models to estimate unadjusted (univariate) hazard ratios (HR) for Q fever according to these characteristics. Variables associated with Q fever (P < 0.1) were included in a multivariable model, with the final model determined using a backward elimination method. Variables for which P < 0.05 were retained in the final model. Missing categories were only included in the multivariable model and reported if the proportion of missing cases was greater than 5%.

We also examined the proportion of notified patients who were hospitalised, their concurrent diagnoses on admission, and, for those with a Q fever-coded hospitalisation, the median length of stay. Kruskal–Wallis tests were used to compare the median number of hours spent outdoors each day according to area and type of residence. P < 0.05 was defined as statistically significant. All analyses were performed with Stata 12 (StataCorp).

Results

After excluding 202 participants with notified Q fever before recruitment, our analysis included 266 906 participants who were followed up for 1 254 650 person-years (mean follow-up time, 4.7 ± 1.0 years per person). The mean recruitment age was 62.7 ± 11.2 years, and 53.6% were women. There were 45 participants with a linked Q fever notification during follow-up (for 44 there was positive serological evidence; for one, the diagnosis method was unknown).

In our study population, the incidence of notified Q fever was 3.6 (95% CI, 2.7–4.8) per 100 000 person-years. The relationship of incidence with various sociodemographic characteristics is shown in Box 2. In unadjusted models, age (P = 0.01), sex (P = 0.03), area and type of residence (P < 0.001 for trend), and time spent outdoors each day (P < 0.001 for trend) were significantly associated with Q fever notification, while smoking was not (P = 0.8). Only age (P = 0.03), sex (P = 0.02), and area and type of residence (P < 0.001 for trend) remained significant in the multivariable model. There was a gradient of increasing risk according to geographic area and residence on a farm. Those living on a farm in outer regional/remote areas were at greatest risk, followed by those living on a farm in inner regional areas, with those not living on farms least at risk (Box 2). The relative risk of Q fever for those aged 65 years or over was significantly lower than for younger participants, and was also lower for women than men (Box 2). The amount of time spent outdoors each day was related to the area and type of residence, ranging from 2.6 hours for living in a major city to 4.6 hours for those living on a farm in outer regional/remote areas (Kruskal–Wallis test, P < 0.001). However, differences in time outdoors did not remain significant (P = 0.4 for trend) after adjustment for area and type of residence in the multivariable model.

Of 45 incident notifications, we had complete follow-up of hospital records for 39 patients. Of these, 17 (44%) were hospitalised at least once (for any cause) within 6 weeks of the recorded disease onset date (before or after onset). The hospitalisation was coded as being for Q fever in 15 cases (seven patients with primary Q fever or secondary Q fever, eight as Q fever-related). The median length of stay for patients with these diagnoses was 4 days (interquartile range, 3–9 days). There were no deaths or intensive care unit stays recorded for the notified cases.

According to the APDC database, 11 participants had been hospitalised with primary Q fever or secondary Q fever, but four of these were not recorded as Q fever cases in the NCIMS database.

Discussion

This is the first population-based prospective study of the risk and burden of acute Q fever in a general adult population in Australia. We found that a clear increase in the risk of notified Q fever in adults was associated with living on a farm and with geographic remoteness. Those living on farms in outer regional and remote areas were at highest risk, and the hazard was lowest for those living in major cities. Risks were also greater for those under 65 years of age and for men, but risk was not increased for smokers or associated with greater time spent outdoors. Fifteen of 39 notified Q fever cases (38%) were hospitalised with a diagnosis consistent with Q fever.

In this study, we observed an incidence of notified Q fever of 3.6 per 100 000 person-years, with the highest rate among those aged 55–64 years (5.4 per 100 000 person-years). This is broadly consistent with Q fever notification rates for the total NSW population aged 45 years or over reported during 2009–2012 (2.9 per 100 000 persons, with the highest average annual rates for those aged 55–64 years: 4.1 per 100 000 persons).7,8,18 The slightly higher disease burden in our study is not surprising, as the 45 and Up Study oversampled the residents of rural and remote NSW, where Q fever notification rates are much higher than in urban centres.

We estimated that the notified Q fever risk was about five times higher for adults living on a farm in inner regional areas and about 12 times higher for those living on a farm in outer regional and remote areas than for those in inner regional areas not living on a farm. This finding is consistent with other reports that found farmers to be at greater risk of Q fever,18,19 and suggests that immunisation coverage in this group is inadequate. Even though the NQFMP provided free vaccination to farmers, uptake was estimated to be only about 43%, and in NSW the vaccination program ended in 2004.7 After allowing for workforce turnover, it is likely that an even lower proportion of current farmers have been vaccinated. An alternative explanation would be that vaccine-induced immunity has waned, but there is good evidence that the vaccine is highly effective, with immunity lasting for at least 5 years and probably for life.20

Massey and colleagues19 have suggested that demographic factors other than occupation should be identified to better define risk groups, as a fifth of notified Q fever cases from rural areas did not report occupational exposure to Q fever. Similarly, the recent major Q fever outbreak in the Netherlands found that people living near farms, but not specifically working on one, were also at increased risk of disease.21–23 We did not have information on the occupations of participants in our study, but our finding of increased Q fever risk for those living in more remote areas but not living on a farm are consistent with the results of these other studies. Taken together, they support calls for medical practitioners in regional and remote Australia to routinely consider Q fever in their differential diagnosis of acute flu-like illnesses, even for patients not living on farms.24

We also examined other factors potentially relevant to Q fever risk. Time spent outdoors was not significant in our multivariable model, as any effect was almost completely explained by the area and type of residence variable. There was no indication of an increased risk for smokers. A significant fraction (44%) of notified Q fever cases had been hospitalised. This is within the higher range of hospitalisation estimates reported by an extensive review.1 Studies suggest that up to 20% of those with Q fever will develop chronic conditions, such as endocarditis or chronic fatigue syndrome, that also require health care outside of hospitals, and which also entail losses of productivity and quality of life.14,25–27 This lends further weight to calls for improving disease prevention efforts.

We identified 15 cases of Q fever for which a hospitalisation code consistent with Q fever was recorded, but only seven were specifically coded as Q fever (ICD-10-AM, A78). This suggests that limiting analysis to hospital admissions specifically coded as primary or secondary Q fever diagnoses is likely to substantially underestimate the true burden of Q fever-related morbidity. We also identified four participants linked to hospitalisations coded as Q fever, but for which there was no record of Q fever in the NCIMS database. It is possible that these were clinically compatible cases that did not meet the case definition of confirmed Q fever because of negative diagnostic test results, and were therefore not notified, or it may indicate under-reporting of genuine cases.

To our knowledge, our study is the first using prospectively ascertained events to examine the risk and burden of Q fever in older adults in a general population of Australian residents. Our study encompassed a time period during which no major Q fever outbreaks were reported, and thus more accurately assesses the risk and burden of endemic Q fever. Potential limitations include the fact that we used notification data to identify Q fever cases, and such data usually underestimate the number of infections; they may also depend on the propensity of physicians to consider the diagnosis, which may differ according to the characteristics of their patients. In addition, we had no data on the occupations or the vaccination status of participants. The numbers of Q fever cases were relatively small, leading to wide confidence intervals for the risk estimates. Similarly, the small numbers meant that we could not stratify the “ever smoked” category into current and past smokers. Finally, the study cohort was probably healthier than the overall NSW population of the same age range, as indicated by a lower rate of smoking.11

In conclusion, our results support current recommendations for Q fever vaccination of farmers and add to the existing body of evidence that suggests targeting a broader, geographically based population in regional and remote regions is required to reduce the burden of Q fever in Australia.

Box 1 –
Australian national notifiable diseases case definitions — Q fever13

Confirmed case

A confirmed case requires either:

1. Laboratory definitive evidence

2. Laboratory suggestive evidence AND clinical evidence.

Laboratory definitive evidence

1. Detection of Coxiella burnetii by nucleic acid testing

2. Seroconversion or significant increase in antibody level to Phase II antigen in paired sera tested in parallel in absence of recent Q fever vaccination

3. Detection of C. burnetii by culture (note this practice should be strongly discouraged except where appropriate facilities and training exist.)

Laboratory suggestive evidence

Detection of specific IgM in the absence of recent Q fever vaccination.

Clinical evidence

A clinically compatible disease

Box 2 –
Incidence of and hazard ratios for notified Q fever in NSW according to various sociodemographic characteristics, 2006–2012

	Cases	Population	Person-years	Incidence per 100 000 person-years (95% CI)	HR* (95% CI)	Adjusted HR^† (95% CI)

All participants	45	266 906	1 254 650	3.6 (2.7–4.8)
Age group
45–54 years	16	78 756	377 770	4.2 (2.6–6.9)	1.00	1.00
55–64 years	22	85 654	408 515	5.4 (3.5–8.2)	1.27 (0.67–2.42)	1.20 (0.63–2.29)
≥ 65 years	7	102 496	468 365	1.5 (0.7–3.1)	0.35 (0.14–0.85)	0.39 (0.16–0.96)
Sex
Men	28	123 766	579 608	4.8 (3.3–7.0)	1.00	1.00
Women	17	143 140	675 042	2.5 (1.6–4.0)	0.52 (0.28–0.95)	0.48 (0.26–0.88)
Smoking
Never	27	152 427	718 838	3.7 (2.6–5.5)	1.00	na
Ever	18	113 052	529 243	3.4 (2.1–5.4)	0.90 (0.50–1.64)	na
Area and type of residence
Major city	^‡	120 267	562 377	0.2 (0.1–1.3)	0.07 (0.01–0.55)	0.07 (0.01–0.54)
Inner region; not on farm	10	84 699	398 756	2.5 (1.3–4.7)	1.00	1.00
Outer region/remote; not on farm	11	42 006	198 012	5.5 (3.1–10.0)	2.21 (0.94–5.21)	2.21 (0.94–5.21)
Inner region; on farm	6	9 082	43 511	13.8 (6.2–30.6)	5.51 (2.00–15.15)	4.95 (1.79–13.65)
Outer region/remote; on farm	17	10 657	51 090	33.3 (20.7–53.5)	13.28 (6.08–29.01)	11.98 (5.47–26.21)
Time spent outdoors^§
< 4 hours/day	19	172 874	814 719	2.3 (1.5–3.6)	1.00	1.00
4–7 hours/day	14	57 363	269 247	5.2 (3.1–8.8)	2.23 (1.12–4.45)	1.21 (0.58–2.51)
≥ 8 hours/day	6	16 432	76 995	7.8 (3.5–17.3)	3.35 (1.34–8.38)	1.20 (0.45–3.19)
Missing data	6	20 237	93 689	6.40 (2.9–14.2)	2.74 (1.09–6.86)	1.93 (0.75–4.93)

HR = hazard ratio; na = not applicable. *Unadjusted results. †Variables in final model: age group, sex, area and type of residence. ‡Number of cases not displayed due to small numbers. §Adjusted for age group, sex, and area and type of residence.

[Articles] Changes in health in England, with analysis by English regions and areas of deprivation, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Health in England is improving although substantial opportunities exist for further reductions in the burden of preventable disease. The gap in mortality rates between men and women has reduced, but marked health inequalities between the least deprived and most deprived areas remain. Declines in mortality have not been matched by similar declines in morbidity, resulting in people living longer with diseases. Health policies must therefore address the causes of ill health as well as those of premature mortality.

[Editorial] Primary care is a team sport

Physicians are often called the gatekeepers of primary care, describing the providers at the front lines who orchestrate the steps in the cascade of care. Primary care is the first stop to connect patients—especially those with complex health needs, such as multiple chronic illnesses—with other necessary services, including specialists, after hours or home care, and social services. But a rising number of patients at risk for chronic diseases, an ageing population, and life-prolonging medical interventions have added new financial and capacity stresses on primary care systems, with primary care physicians making decisions from an increasingly challenging position.

[Correspondence] Tackling preventable diseases in Yemen

The health-care system in Yemen has deteriorated since the start of the war in March, 2015. Impairment exists at all levels of health services; from improper function of health-care facilities to a shortage of basic and life-saving needs, such as drugs, water, and fuel. This continuous, unresolved crisis has led to a rise in preventable diseases and other health problems, such as infectious diseases, malnutrition, diarrhoea, and unnecessary organ loss.1,2

[Perspectives] Salmaan Keshavjee: tackling tuberculosis (without rocket science)

Salmaan Keshavjee’s CV is a puzzling document. A first degree in biochemistry from Queen’s University in Ontario, Canada, is followed by a move to the USA and a master’s in immunology and infectious diseases from the then Harvard School of Public Health. The next 5 years find him still at Harvard, but now doing a course in Middle Eastern Studies, and then writing a doctoral thesis in anthropology. 3 years on he’s graduating from Stanford University, this time with a medical degree. Is this a man who can’t make up his mind?

[Health Policy] Will Ebola change the game? Ten essential reforms before the next pandemic. The report of the Harvard-LSHTM Independent Panel on the Global Response to Ebola

The west African Ebola epidemic that began in 2013 exposed deep inadequacies in the national and international institutions responsible for protecting the public from the far-reaching human, social, economic, and political consequences of infectious disease outbreaks. The Ebola epidemic raised a crucial question: what reforms are needed to mend the fragile global system for outbreak prevention and response, rebuild confidence, and prevent future disasters? To address this question, the Harvard Global Health Institute and the London School of Hygiene & Tropical Medicine jointly launched the Independent Panel on the Global Response to Ebola.

[Comment] Opening the GATE to inclusion for people with disabilities

For more than an estimated billion people with disabilities,1 assistive technologies are crucial mediators for realising people’s rights, and for promoting access and empowerment—the theme of the International Day of Persons with Disability for this year (Dec 3, 2015). By 2050, the number of older (aged over 60 years) people will have increased, worldwide, from about 840 million in 2013 to more than 2 billion, many of whom will also need assistive technology to remain independent.2 Some older people will need several assistive products, as will the increased proportion of people living with chronic diseases.

Why we can trust scientists with the power of new gene-editing technology

A summit of experts from around the world is meeting in Washington to consider the scientific, ethical and governance issues linked to research into gene editing. Convened in response to recent advances in the field, the summit includes experts from the US National Academy of Science, the UK’s Royal Society and the Chinese Academy of Science.

Gene editing is a new technique that allows one to change chosen genes at will. It has been applied to many organisms but a recent report from China showing the modification of human embryos using a technology known as CRISPR/Cas9 mediated editing set alarm bells ringing.

Here’s the main fear: if you modify an embryo (and therefore also its germline), you change not only the person that embryo will become but also its future sons, daughters, grandsons and granddaughters.

Since we don’t know much about this technology, it’s right to stop and think about it. But personally I’m not overly concerned: we’ve been here – or somewhere quite like it – before.

Learning from history

In 1975, scientists met at Asilomar on the Californian coast to discuss a moratorium on recombinant DNA (that’s DNA formed from combining constituents from different organisms).

Alarm bells had started ringing when scientists realised they could combine the DNA from a monkey virus with a circle of DNA called a plasmid, carrying an antibiotic resistance gene purified from the human gut bacteria, Escherichia coli (E. coli).

This cocktail sounded dangerous and scientists discussed a voluntary moratorium on certain experiments, as well as sensible guidelines for containing recombinant material within laboratories.

Why we can trust scientists with the power of new gene-editing technology - Featured Image

Horizontal gene transfer occurs in nature when DNA is carried between species by viruses and related carriers.
Jer Thorp/Flickr, CC BY

Regulations and guidelines are still in place and after 40 years few, if anyone, has been harmed by recombinant DNA. And there have been no reported outbreaks of recombinant material that have significantly affected human health or the environment.

All technologies, including different agricultural practices, have upsides and downsides, and most medicines and treatments have side effects. But recombinant DNA would now have to be classed among the least dangerous of scientific developments.

Understanding science

One reason the technology has proven so safe may be that genetic recombination has been going on for millions of years. In most cases, genes are simply passed on from parent to child. But horizontal gene transfer also occurs in nature when DNA is carried between organisms or even species by viruses.

Over time, DNA is naturally swapped around and moved. Though you may have eaten transgenic plant products, I very much doubt you’ve noticed.

There was a fear “mad scientists” would invent dangerous new superbugs and killer viruses. Perhaps this could have happened, but sadly there are enough pre-existing dangerous substances and naturally occurring diseases, which have been perfected by evolution, out there already. So germ warfare scientists are more likely to just use them.

Another fear was that researchers would modify humans. Most countries quickly outlawed the modification of human germ cells and, to my knowledge, it has never occurred. In general, scientists seem to have obeyed the regulations.

But another reason is that it has proved difficult to introduce new genes into mammalian cells. It’s legal to modify human cells, such as blood stem cells, to cure genetic diseases. But human cells are among the hardest to modify. Human “anti-viral” software seems so powerful that it inhibits the stable insertion and expression of new DNA.

The promise of gene editing

I’m sure you’ve met people who’ve had their teeth straightened or undergone cosmetic surgery. But you’ve probably never met anyone who’s had gene therapy or ever seen a transgenic animal.

Could that change with gene editing? Gene editing is so precise that one doesn’t just lob in a new gene and hope it works; what one does is edit the existing gene to eliminate any misspellings, introduce beneficial natural variants, or perhaps cut out or insert new genes into chosen locations.

Our anti-viral software may not even detect what’s happened. And provided there aren’t any “off-target’” effects, where we hit the wrong gene, there may be no or minimal side effects.

Now that it’s so easy to meddle in human genes, why shouldn’t we worry?

The new technology is a game-changer – but it’s not a runaway phenomenon, like releasing cane toads, blackberries or rabbits into Australia. After 40 years, there have been few, if any problems, with genetically modified organisms. And the experiments – though much easier now – are still so elaborate and expensive that the technology will spread slowly.

We’ll likely remain cautious about modifying human embryos and about any modification that may be passed on to the next generation. To date, consent is required for all treatments. And while patients may opt for experimental cancer therapy or surgery, we always try to think carefully when others, who cannot consent, will be affected.

Some people will even ask why it’s wrong to correct a defect that could haunt future generations. Or, if we could introduce a gene variant that protects people from cancer – such as creating a duplication of the tumour suppressor gene p53 – why wouldn’t we want that for our children?

Genetics is a branch of science that’s ripe for discussions, and conversations on recombinant DNA, gene therapy, cloning and stem cells have all gone well. Guidelines have been sensible and researchers have largely complied with them.

The very fact that people from across the world are gathering to discuss the issues surrounding the latest breakthroughs in gene technology is a very strong sign that the science will be used responsibly. One hopes that the concurrent meeting on climate change in Paris is also a victory for science.

Merlin Crossley, Dean of Science and Professor of Molecular Biology, UNSW Australia. This article was originally published on The Conversation. Read the original article. Main photo: Libertas Academica/Flickr

Other doctorportal blogs

Govts doing little to tackle climate health threat

Picture: paintings%20/%20Shutterstock.com“>paintings / Shutterstock.com

More than half of governments around the world are yet to develop national plans to protect their citizens from the health effects of climate change despite increasing warnings it will cause more extreme weather, spread disease and put pressure on food and water supplies.

As leaders from around the world meet in Paris for UN climate talks, an international survey of 35 countries, including Australia, has found a general lack of focus and urgency around the looming threat of climate change to health, with most governments doing little work on likely effects and how to mitigate them.

The survey results underline calls from the AMA, the World Medical Association and other national medical organisations for the health effects of climate change to be made a priority at the climate talks.

AMA President Professor Brian Owler said that while much of the Paris talks will be about carbon emission targets, there should be equal emphasis on equipping health systems to cope with the extra burden of problems created by climate change.

“Climate change will dramatically alter the patterns and rate of spread of diseases, rainfall distribution, availability of drinking water and drought,” Professor Owler said. “The incidence of conditions such as malaria, diarrhoea and cardio-respiratory problems is likely to rise.”

He said the Paris Conference was “the perfect place” to develop and implement plans to deal with these effects.

The AMA President’s comments came as a survey coordinated by the World Federation of Public Health Associations (WFPHA) found almost 80 per cent of governments are yet to comprehensively assess the threat climate change poses to the health of their citizens, two-thirds had done little to identify vulnerable populations and infrastructure or examine their capacity to cope, and less than half had developed a national plan.

The result underlines the importance of repeated AMA calls for the Federal Government to do much more to prepare for the effects of climate change, which Professor Owler said were “inevitable”.

Earlier this year the AMA released an updated Position Statement on Climate Change and Human Health that warned of multiple risks including increasingly frequent and severe extreme weather events, deleterious effects on food production, increased pressure on scarce water resources, the displacement of people and an increase in health threats such as vector-borne diseases and climate-related illnesses.

“There are already significant health and social effects of climate change and extreme weather events, and these effects will worsen over time if we do not take action now,” Professor Owler said.

“Nations must start now to plan and prepare. If we do not get policies in place now, we will be doing the next generation a great disservice.

“It would be intergenerational theft of the worst kind — we would be robbing our kids of their future.”

In May, the AMA and the Australian Academy of Science jointly launched the Climate change challenges to health: Risks and opportunities report that detailed the likely health effects of climate change and called for the establishment of a National Centre of Disease Control to provide a national and coordinated approach to threat.

The WFPHA said the results of its survey, released little more than two weeks before the United Nations Climate Change Conference in Paris, should serve as a wake-up call for governments to do much more.

“The specifics of these responses provide insight into the lack of focus of national governments around the world on climate and health,” the Federation said.

Disturbingly, the survey found that Australia was one of the laggards in addressing the health effects of climate change, having done little to assess vulnerabilities and long-term impacts, develop an early warning system or adaptation responses, and yet to establish a health surveillance plan.

On many of these measures, the nation was lagging behind countries like the United States, Sweden, Taiwan, New Zealand and even Russia and China.

Climate and Health Alliance Executive Director Fiona Armstrong, who helped coordinate the survey, said the results showed the Federal Government needed to place far greater emphasis on human health in its approach to climate change.

“As a wealthy country…whose population is particularly vulnerable to the health impacts of climate change, it is very disappointing to see this lack of leadership from policymakers in Australia,” Ms Armstrong said.

Public Health Association of Australia Chief Executive Officer Mike Moore said the increasing number and ferocity of bushfires and storms underlined the urgent need for action.

“It is time to ensure that health-related climate issues are part of our national planning and budgeting if we are to pre-empt many avoidable illnesses and injuries,” Mr Moore said.

The AMA’s Position Statement on Climate Change and Human Health can be viewed at: position-statement/ama-position-statement-climate-change-and-human-health-2004-revised-2015

Adrian Rollins

[Comment] Primary health care and the Sustainable Development Goals

After the eight Millennium Development Goals that have shaped progress in the past 15 years, 17 Sustainable Development Goals (SDGs) were adopted by governments at the UN General Assembly in September, 2015. SDG3 explicitly relates to health—to “Ensure healthy lives and promote well-being for all at all ages”. This goal is translated into 13 targets: three relate to reproductive and child health; three to communicable diseases, non-communicable diseases, and addiction; two to environmental health; and one to achieving universal health coverage (UHC).