Gaining further insights into the COVID-19 pandemic in Australia: Evidence using capture-recapture methods.

Objective: We re-examined the reported number of COVID-19 cases in Australia and across its states during the first wave of the pandemic. We provided estimates of the total number of cases, adjusted for under-reporting. Methods: Publicly available data sourced from Australian governments at federal, state and territory levels included records on cumulative confirmed COVID-19 cases and cumulative deaths occurring in Australia and across its states on a daily basis. Lower bound and upper bound estimates of the total number of COVID-19 cases in Australia and across its states, that included the undetected cases that have not been recorded, were estimated. Results: On January 25, 2020, Australia recorded its first 4 cases of COVID-19 and the first death occurred on March 3, 2020. On April 1, 2020, 4864 cases had been reported with 21 deaths. Our estimation showed that on April 1, 2020, the minimum and maximum number of COVID-19 cases in Australia were in fact 10,160 (95 % CI: 9781-10,538) and 21,748 (95 % CI: 21,607-22,014) respectively. We estimated that the total number of cases were at least twice and at most four times the observed cases recorded. These differences were also found at the state level where in New South Wales there was a minimum and maximum of 207 and 447 cases in total for every 100 reported cases, while in Victoria these figures were much lower at 157 and 265 respectively for every 100 reported cases. Conclusion: Case ascertainment during the pandemic is known to have been underestimated due to difficulties in testing and contact tracing, amongst others. Capture-recapture methods provided a measure of the gap between the official number of cases recorded and the actual number during the first wave of the pandemic.

Sampling approaches and geographic coverage in Mayi Kuwayu: the national study of Aboriginal and Torres Strait Islander wellbeing.

OBJECTIVE: The objective of this paper is to investigate the geographic distribution of participants in Mayi Kuwayu, the National Study of Aboriginal and Torres Strait Islander Wellbeing. The Mayi Kuwayu Study is the largest national longitudinal study of the health and wellbeing of Aboriginal and Torres Strait Islander adults (aged 16 years and over) in Australia. It is an Aboriginal-led and governed Study with embedded community engagement. The Study collects data through self-report questionnaires, using multiple sampling approaches: (1) a large-scale mail-out based on stratified random sampling; (2) convenience sampling; (3) snowball sampling; (4) voluntary sampling. A comparison of the geographic distribution of Mayi Kuwayu Study participants to that of the total Aboriginal and Torres Strait Islander population was also conducted. RESULTS: A total of 9,843 people participated in the Mayi Kuwayu Study baseline survey from 2018 to 2022. Participants resided in all Australian States and Territories. The geographic distribution of participants broadly matched the total population distribution, with participants generally located on the east and south-east coast of Australia. Apparent differences in the geographic distribution were identified by sex and age group.

Data analysis of zoonoses notifications in Aboriginal and Torres Strait Islander populations in Australia 1996-2021: implications for One Health.

Introduction: Zoonoses are a health concern for Aboriginal and Torres Strait Islander peoples in Australia that face elevated risk of disease related to the environment and animals. Internationally, One Health is encouraged to effectively manage zoonoses by taking integrated approaches involving animal, human, and environmental health sectors to improve health outcomes. However, Australia's health systems manage zoonotic diseases in animals and people separately which does not support a One Health approach. For the effective management of zoonoses, a strong evidence base and database regarding the epidemiology of zoonotic pathogens is needed. However, we currently lack this evidence limiting our understanding of the impact of zoonoses on Aboriginal and Torres Strait Islander populations. Methods: As a first step towards building the evidence base, we undertook a descriptive analysis of Aboriginal and Torres Strait Islander zoonotic notifications in Australia from 1996 to 2021. We presented notifications as annual notification rates per 100,000 population, and percentages of notifications by state, remoteness, sex, and age group. Results: Salmonellosis and campylobacteriosis were the most notified zoonoses with the highest annual notification rates of 99.75 and 87.46 per 100,000 population, respectively. The north of Australia (Queensland, Northern Territory and Western Australia), remote and outer regional areas, and young children (0-4 years of age) had the highest percentages of notifications. Discussion: To our knowledge, these findings are the first national presentation of the epidemiology of zoonoses within Aboriginal and Torres Strait Islander populations. A greater understanding of transmission, prevalence and impact of zoonoses on Aboriginal and Torres Strait Islander peoples (including animal and environmental health factors) is required to inform their effective management through a One Health approach.

One Health and Australian Aboriginal and Torres Strait Islander Communities: A One Health Pilot Study.

Many Aboriginal and Torres Strait Islander communities face barriers in accessing animal healthcare and are exposed to disproportionate environmental health exposures leading to increased risk of disease. A One Health approach has been promoted to address public health risks and improve human, animal, and environmental health outcomes in communities. We undertook a pilot One Health study in Aboriginal and Torres Strait Islander communities in Queensland collecting animal, human, and environmental health data from 82 households. We performed a descriptive analysis and assessed the association between human and environmental health exposures and animal health outcomes. Most households were not crowded (82.9%) but did report a high level of environmental health concerns (86.6%). The majority of households owned cats and dogs (81.7%), with most animals assessed as healthy. There was no association between human and environmental health exposures and animal health outcomes. As most households experienced concerns regarding housing conditions, environmental health programs should prioritise improving household factors. There was also strong support for animal healthcare (including access to medicines and veterinarians, education programs and population management), indicating that a One Health approach is desired by communities.

Estimating population coverage of Tackling Indigenous Smoking teams, a placed-based health intervention in Australia.

OBJECTIVE: As part of the Tackling Indigenous Smoking (TIS) program, TIS teams provide Aboriginal and Torres Strait Islander-led tobacco control in their geographic area. We aimed to estimate the percentage and number of Aboriginal and Torres Strait Islander peoples living in an area serviced by a TIS team in 2018-19. METHODS: We analysed weighted, representative data from 8,048 Aboriginal and Torres Strait Islander people aged ≥10 years from the 2018-19 National Aboriginal and Torres Strait Islander Health Survey. TIS services mapping data were used to define areas served by TIS teams. Coverage was explored in relation to remoteness, program priority groups and sociodemographic characteristics. RESULTS: Around three-quarters (76.4%,95%CI:72.9-79.9) of the 2018-19 population aged ≥10 years lived in an area served by TIS teams (n=479,000). Coverage by TIS teams was generally similar across groups, with few exceptions. CONCLUSIONS: The recently announced expansion to national coverage would provide access to locally tailored tobacco control to a further 148,000 Aboriginal and Torres Strait Islander peoples aged ≥10 years, including 46,000 adults who currently smoke. IMPLICATIONS FOR PUBLIC HEALTH: Expansion to national TIS team coverage is a welcomed first step on the path to ensuring equitable access to tobacco control.

Population-level contribution of interpersonal discrimination to psychological distress among Australian Aboriginal and Torres Strait Islander adults, and to Indigenous-non-Indigenous inequities: cross-sectional analysis of a community-controlled First Nations cohort study.

BACKGROUND: International and population-specific evidence identifies elevated psychological distress prevalence among those experiencing interpersonal discrimination. We aim to quantify the potential whole-of-population contribution of interpersonal discrimination to psychological distress prevalence and Indigenous-non-Indigenous gaps in Australia. METHODS: We did a cross-sectional analysis of data from Mayi Kuwayu: the National Study of Aboriginal and Torres Strait Islander Wellbeing. Baseline surveys were completed between June 8, 2018, and Sept 28, 2022. We analysed responses from participants who were aged 18 years or older at survey completion, whose surveys were processed between Oct 1, 2018, and May 1, 2021. Sample weights were developed on the basis of national population benchmarks. We measured everyday discrimination using an eight-item measure modified from the Everyday Discrimination Scale and classified experiences as racial discrimination if participants attributed these experiences to their Indigeneity. Psychological distress was measured using a validated, modified Kessler-5 scale. Applying logistic regression, we calculated unadjusted odds ratios (ORs), to approximate incident rate ratios (IRRs), for high or very high psychological distress in relation to everyday discrimination and everyday racial discrimination across age-gender strata. Population attributable fractions (PAFs), under the hypothetical assumption that ORs represent causal relationships, were calculated using these ORs and population-level exposure prevalence. These PAFs were used to quantify the contribution of everyday racial discrimination to psychological distress gaps between Indigenous and non-Indigenous adults. FINDINGS: 9963 survey responses were eligible for inclusion in our study, of which we analysed 9951 (99·9%); 12 were excluded due to responders identifying as a gender other than man or woman (there were too few responses from this demographic to be included as a category in stratified tables or adjusted analyses). The overall prevalence of psychological distress was 48·3% (95% CI 47·0-49·6) in those experiencing everyday discrimination compared with 25·2% (23·8-26·6) in those experiencing no everyday discrimination (OR 2·77 [95% CI 2·52-3·04]) and psychological distress prevalence was 49·0% (95% CI 47·3-50·6) in those experiencing everyday racial discrimination and 31·8% (30·6-33·1) in those experiencing no everyday racial discrimination (OR 2·06 [95% CI 1·88-2·25]. Overall, 49·3% of the total psychological distress burden among Aboriginal and Torres Strait Islander adults could be attributable to everyday discrimination (39·4-58·8% across strata) and 27·1% to everyday racial discrimination. Everyday racial discrimination could explain 47·4% of the overall gap in psychological distress between Indigenous and non-Indigenous people (40·0-60·3% across strata). INTERPRETATION: Our findings show that interpersonal discrimination might contribute substantially to psychological distress among Aboriginal and Torres Strait Islander adults, and to inequities compared with non-Indigenous adults. Estimated PAFs include contributions from social and health disadvantage, reflecting contributions from structural racism. Although not providing strictly conclusive evidence of causality, this evidence is sufficient to indicate the psychological harm of interpersonal discrimination. Findings add weight to imperatives to combat discrimination and structural racism at its core. Urgent individual and policy action is required of non-Indigenous people and colonial structures, directed by Aboriginal and Torres Strait Islander peoples. FUNDING: National Health and Medical Research Council of Australia, Ian Potter Foundation, Australian Research Council, US National Institutes of Health, and Sierra Foundation.

Relationship of Aboriginal family wellbeing to social and cultural determinants, Central Australia: 'Waltja tjutangku nyakunytjaku'.

OBJECTIVE: The objective of this study was to apply a strength-based approach to examine the relation of cultural and social determinants to high family functioning for Aboriginal people in Central Australia. DESIGN: Cross-sectional study involving a quantitative analysis of survey data. Prevalence rate ratios (PRs) and 95% CIs were calculated from binomial regressions, adjusted for gender and age. Qualitative data from workshops with Aboriginal leaders in Central Australia supported the interpretation of the research findings. PARTICIPANTS: The study involved 639 Aboriginal people in Central Australia who participated in the Mayi Kuwayu Study. RESULT: Overall, 57.9% (370/639) of participants reported high/very high family functioning, 16.9% (108/639) reported moderate and 13.3% (85/639) reported low. The adjusted prevalence of family functioning was similar across gender, age groups and household sizes. Family functioning was associated with lower family financial status (aPR=0.74, 95% CI=0.60 to 0.91) and receiving welfare (0.88, 0.77 to 1.00). Family functioning was greater with high community cohesion (2.72, 1.68 to 4.39), high individual agency in community (2.15, 1.63 to 2.85); having an Aboriginal language as a first language (1.20, 1.04 to 1.37); speaking your Aboriginal language a lot (1.37, 1.12 to 1.68); high exposure to cultural practice and knowledge (1.45, 1.28 to 1.65); and multigenerational or extended family households (1.19, 1.02 to 1.38). CONCLUSION: High family functioning is a strength in Central Australia and is intrinsically connected with culture. Healthcare providers and programmes that build on the foundations of culture and family are an important approach to improving wellbeing.

Clearing the air: underestimation of youth smoking prevalence associated with proxy-reporting compared to youth self-report.

BACKGROUND: Smoking remains a leading cause of disease burden globally. Declining youth smoking prevalence is an essential feature of effective tobacco control; however, accurate data are required to assess progress. This study investigates bias in youth smoking prevalence estimates by respondent type (proxy-reported, self-report with parent present, or self-report independently) for Aboriginal and Torres Strait Islander and total populations of Australia. METHODS: Repeated cross-sectional analysis of representative Aboriginal and Torres Strait Islander Health and National Health Surveys, 2007-2019. Data were restricted to participants aged 15-17 years. Prevalence ratios (PR) and 95% Confidence Intervals (CI) for ever-smoking by respondent type were calculated using Poisson regression with robust standard errors. National youth current-smoking prevalence was estimated if all data were collected by youth self-report; estimates and trends were compared to observed estimates. RESULTS: Over 75% of all smoking status data were reported by proxy or with parent present. Ever-smoking prevalence among youth self-reporting independently versus proxy-reported was 1.29 (95% CI:0.96-1.73) to 1.99 (95% CI:1.39-2.85) times as high for Aboriginal and Torres Strait Islander youth, and 1.83 (95% CI:0.92-3.63) to 2.72 (95% CI:1.68-4.41) times as high for total population youth. Across surveys, predicted national current-smoking prevalence if all youth self-reported independently was generally higher than observed estimate. CONCLUSIONS: Estimates of youth smoking prevalence are likely inaccurate and underestimated if data are collected by proxy or with parent present. Increased reliance on data reported by youth independently is crucial to improve data accuracy, including to enable accurate assessment of national prevalence.

Reflection on modern methods: statistical, policy and ethical implications of using age-standardized health indicators to quantify inequities.

Methods for calculating health indicators profoundly influence understanding of and action on population health and inequities. Age-standardization can be useful and is commonly applied to account for differences in age structures when comparing health indicators across groups. Age-standardized rates have well-acknowledged limitations, including that they are relative indices for comparison, and not accurate measures of actual rates where the age structures of groups diverge. This paper explores these limitations, and demonstrates alternative approaches through a case study quantifying mortality rates within the Aboriginal and Torres Strait Islander (Indigenous) population of Australia and inequities compared with the non-Indigenous population, over 2001-16. Applying the Australian Standard Population, the Aboriginal and Torres Strait Islander age-standardized mortality rate was more than double the crude mortality rate in 2001 and 2016, inflated through high weighting of older age groups. Despite divergent population age structures, age-standardized mortality rates remain a key policy metric for measuring progress in reducing Indigenous-non-Indigenous inequities in Australia. Focusing on outcomes age-standardized to the total population can obscure inequities, and denies Aboriginal and Torres Strait Islander peoples and communities valid, actionable information about their health and well-being. Age-specific statistics convey the true magnitude of health risks and highlight high-risk subgroups. When requiring standardization, standardizing to a population-specific standard (here, an Indigenous standard) generates metrics centred around and reflective of reality for the population of focus, supporting communities' self-determination to identify priorities and informing resource allocation and service delivery. The principles outlined here apply across populations, including Indigenous and other populations internationally.

Workforce participation in relation to cancer diagnosis, type and stage: Australian population-based study of 163,556 middle-aged people.

PURPOSE: To quantify the relationship of cancer diagnosis to workforce participation in Australia, according to cancer type, clinical features and personal characteristics. METHODS: Questionnaire data (2006-2009) from participants aged 45-64 years (n=163,556) from the population-based 45 and Up Study (n=267,153) in New South Wales, Australia, were linked to cancer registrations to ascertain cancer diagnoses up to enrolment. Modified Poisson regression estimated age- and sex-adjusted prevalence ratios (PRs) for non-participation in the paid workforce-in participants with cancer (n=8,333) versus without (n=155,223), for 13 cancer types. RESULTS: Overall, 42% of cancer survivors and 29% of people without cancer were out of the workforce (PR=1.18; 95%CI=1.15-1.21). Workforce non-participation varied substantively by cancer type, being greatest for multiple myeloma (1.83; 1.53-2.18), oesophageal (1.70; 1.13-2.58) and lung cancer (1.68; 1.45-1.93) and moderate for colorectal (1.23; 1.15-1.33), breast (1.11; 1.06-1.16) and prostate cancer (1.06; 0.99-1.13). Long-term survivors, 5 or more years post-diagnosis, had 12% (7-16%) greater non-participation than people without cancer, and non-participation was greater with recent diagnosis, treatment or advanced stage. Physical disability contributed substantively to reduced workforce participation, regardless of cancer diagnosis. CONCLUSIONS: Cancer survivors aged 45-64 continue to participate in the workforce. However, participation is lower than in people without cancer, varying by cancer type, and is reduced particularly around the time of diagnosis and treatment and with advanced disease. IMPLICATIONS FOR CANCER SURVIVORS: While many cancer survivors continue with paid work, participation is reduced. Workforce retention support should be tailored to survivor preferences, cancer type and cancer journey stage.

One Health in Indigenous Communities: A Critical Review of the Evidence.

Indigenous populations around the world face disproportionately high rates of disease related to the environment and animals. One Health is a concept that has been used effectively to understand and address these health risks. One Health refers to the relationships and interdependencies between animal, human, and environmental health and is an emerging research field that aligns with indigenous views of health. To understand the applicability of One Health in indigenous communities, a critical review was undertaken to investigate evidence of One Health research in indigenous communities internationally, assess the strength of evidence, and understand what gaps are present. This review included the appraisal of twenty-four studies based in five regions: Canada, Africa, Australia, South America, and Central America. The review found that there is a need for studies of high strength, with rigorous methods, local leadership, and active involvement of indigenous viewpoints, to be undertaken in indigenous communities internationally that focus on One Health. It highlights the need to further consider indigenous viewpoints in research to reduce limitations, increase effectiveness of findings, consider appropriateness of recommendations, and benefit communities.

Markers of chronic disease risk in a cohort of Aboriginal children: findings from the Study of Environment on Aboriginal Resilience and Child Health (SEARCH).

OBJECTIVE: This study investigated chronic disease risk markers among a cohort of Aboriginal children in New South Wales. METHODS: Distributions of body mass index (BMI), blood lipids and haemoglobin A1c (HbA1c) among Aboriginal children aged 5-<19 years were investigated. Prevalence ratios (PR) were calculated for borderline/high total cholesterol, low-density lipoprotein (LDL) cholesterol and HbA1c, and low high-density lipoprotein (HDL) cholesterol, by age group, sex and BMI. RESULTS: Almost half (46.8%) of the cohort, had a normal BMI and 53.3% had overweight or obesity. Prevalence of chronic disease risk markers was low, with no individuals having high total cholesterol (0.0%) and few having high LDL (3.0%) or borderline/high HbA1c (2.6%); 85.5% of the cohort had normal HDL. There was no significant variation in the prevalence of chronic disease risk markers by age group or sex. The prevalence of borderline total cholesterol was 28% higher (PR 1.28, 95%CI 1.06-1.54), and the prevalence of low HDL was double (2.00, 1.19-3.35) for participants with obesity versus normal BMI. CONCLUSIONS: Dyslipidaemia and elevated HbA1c prevalence was low in the cohort, increasing with high BMI. Overweight and obesity were common, which increase the risk of developing chronic disease later in life. Implications for public health: Findings indicate few Aboriginal children have dyslipidaemia and hyperglycaemia, supporting screening for chronic disease risk factors from 18 years of age. Opportunities to reduce overweight and obesity among children should be considered to decrease the future risk of chronic disease.

Prevalence of Everyday Discrimination and Relation with Wellbeing among Aboriginal and Torres Strait Islander Adults in Australia.

Discrimination is a fundamental determinant of health and health inequities. However, despite the high prevalence of discrimination exposure, there is limited evidence specific to Indigenous populations on the link between discrimination and health. This study employs a validated measure to quantify experiences of everyday discrimination in a national sample of Aboriginal and Torres Strait Islander (Australia's Indigenous peoples) adults surveyed from 2018 to 2020 (≥16 years, n = 8108). It quantifies Prevalence Ratios (PRs) and 95% Confidence Intervals (CIs) for wellbeing outcomes by level of discrimination exposure, and tests if associations vary by attribution of discrimination to Indigeneity. Of the participants, 41.5% reported no discrimination, 47.5% low, and 11.0% moderate-high. Discrimination was more commonly reported by younger versus older participants, females versus males, and those living in remote versus urban or regional areas. Discrimination was significantly associated in a dose-response manner, with measures of social and emotional wellbeing, culture and identity, health behaviour, and health outcomes. The strength of the association varied across outcomes, from a 10-20% increased prevalence for some outcomes (e.g., disconnection from culture (PR = 1.08; 95% CI: 1.03, 1.14), and high blood pressure (1.20; 1.09, 1.32)), to a five-fold prevalence of alcohol dependence (4.96; 3.64, 6.76), for those with moderate-high versus no discrimination exposure. The association was of consistent strength and direction whether attributed to Indigeneity or not-with three exceptions. Discrimination is associated with a broad range of poor wellbeing outcomes in this large-scale, national, diverse cohort of Aboriginal and Torres Strait Islander adults. These findings support the vast potential to improve Aboriginal and Torres Strait Islander peoples' wellbeing, and to reduce Indigenous-non-Indigenous inequities, by reducing exposure to discrimination.

Disability, psychological distress and quality of life in relation to cancer diagnosis and cancer type: population-based Australian study of 22,505 cancer survivors and 244,000 people without cancer.

BACKGROUND: Improved survival means that cancer is increasingly becoming a chronic disease. Understanding and improving functional outcomes are critical to optimising survivorship. We quantified physical and mental health-related outcomes in people with versus without cancer, according to cancer type. METHODS: Questionnaire data from an Australian population-based cohort study (45 and Up Study (n = 267,153)) were linked to cancer registration data to ascertain cancer diagnoses up to enrolment. Modified Poisson regression estimated age- and sex-adjusted prevalence ratios (PRs) for adverse person-centred outcomes-severe physical functional limitations (disability), moderate/high psychological distress and fair/poor quality of life (QoL)-in participants with versus without cancer, for 13 cancer types. RESULTS: Compared to participants without cancer (n = 244,000), cancer survivors (n = 22,505) had greater disability (20.6% versus 12.6%, respectively, PR = 1.28, 95%CI = (1.25-1.32)), psychological (22.2% versus 23.5%, 1.05 (1.02-1.08)) and poor/fair QoL (15.2% versus 10.2%; 1.28 (1.24-1.32)). The outcomes varied by cancer type, being worse for multiple myeloma (PRs versus participants without cancer for disability 3.10, 2.56-3.77; distress 1.53, 1.20-1.96; poor/fair QoL 2.40, 1.87-3.07), lung cancer (disability 2.81, 2.50-3.15; distress 1.67, 1.46-1.92; poor/fair QoL 2.53, 2.21-2.91) and non-Hodgkin's lymphoma (disability 1.56, 1.37-1.78; distress 1.20, 1.05-1.36; poor/fair QoL 1.66, 1.44-1.92) and closer to those in people without cancer for breast cancer (disability 1.23, 1.16-1.32; distress 0.95, 0.90-1.01; poor/fair QoL 1.15, 1.05-1.25), prostate cancer (disability 1.11, 1.04-1.19; distress 1.09, 1.02-1.15; poor/fair QoL 1.15, 1.08-1.23) and melanoma (disability 1.02, 0.94-1.10; distress 0.96, 0.89-1.03; poor/fair QoL 0.92, 0.83-1.01). Outcomes were worse with recent diagnosis and treatment and advanced stage. Physical disability in cancer survivors was greater in all population subgroups examined and was a major contributor to adverse distress and QoL outcomes. CONCLUSIONS: Physical disability, distress and reduced QoL are common after cancer and vary according to cancer type suggesting priority areas for research, and care and support.

Evaluating Impacts of a One Health Approach to Companion Animal Health and Management in a Remote Aboriginal Community in the Northern Territory, Australia.

This study evaluated a community-driven animal health and management program in the remote community of Wadeye, Northern Territory. This evaluation used a pre-post design to assess changes in animal and human health outcomes over a 12-month period of program implementation, from June 2018 to June 2019. The evaluation assessed the program by comparing animal health outcomes before versus one year after program implementation and comparing human health outcomes before versus during the first 12 months of the program. Outcome measures included the desexing status of dogs and cats, body condition and hair score of dogs, and rates of people presenting to the health clinic for a dog bite. Animal health outcomes significantly improved after program implementation. From pre to post program, there was a 77% increase in the prevalence of good body condition score among dogs and a 9% increase in the prevalence of good hair score among dogs, and the prevalence of desexed dogs and cats more than doubled. There was no significant change in the number of people presenting to the health clinic for a dog bite. Consideration on how to further incorporate human and environmental health aspects into the program could be useful for future One Health programs.

Strengths-based approaches for quantitative data analysis: A case study using the australian Longitudinal Study of Indigenous Children.

In Australia and internationally, there are increasing calls for the use of strengths-based methodologies, to counter the dominant deficit discourse that pervades research, policy, and media relating to Indigenous health and wellbeing. However, there is an absence of literature on the practical application of strengths-based approaches to quantitative research. This paper describes and empirically evaluates a set of strategies to support strengths-based quantitative analysis. A case study about Aboriginal and Torres Strait Islander child wellbeing was used to demonstrate approaches to support strengths-based quantitative analysis, in comparison to the dominant deficit approach of identifying risk factors associated with a negative outcome. Data from Wave 8 (2015) of the Australian Longitudinal Study of Indigenous Children were analysed. The Protective Factors Approach is intended to enable identification of factors protective against a negative outcome, and the Positive Outcome Approach is intended to enable identification of factors associated with a positive health outcome. We compared exposure-outcome associations (prevalence ratios and 95% confidence intervals (CIs), calculated using Poisson regression with robust variance) between the strengths-based and deficit approaches. In this case study, application of the strengths-based approaches retains the identification of statistically significant exposure-outcome associations seen with the standard deficit approach. Strengths-based approaches can enable a more positive story to be told, without altering statistical rigour. For Indigenous research, a strengths-based approach better reflects community values and principles, and it is more likely to support positive change than standard pathogenic models. Further research is required to explore the generalisability of these findings.

Estimating Suicide Rates in Developing Nations: A Low-Cost Newspaper Capture-Recapture Approach in Cambodia.

This study tested a low-cost method for estimating suicide rates in developing nations that lack adequate statistics. Data comprised reported suicides from Cambodia's 2 largest newspapers. Capture-recapture modeling estimated a suicide rate of 3.8/100 000 (95% CI = 2.5-6.7) for 2012. That compares to World Health Organization estimates of 1.3 to 9.4/100 000 and a Cambodian government estimate of 3.5/100 000. Suicide rates of males were twice that of females, and rates of those <40 years were twice that of those ≥40 years. Capture-recapture modeling with newspaper reports proved a reasonable method for estimating suicide rates for countries with inadequate official data. These methods are low-cost and can be applied to regions with at least 2 newspapers with overlapping reports. Means to further improve this approach are discussed. These methods are applicable to both recent and historical data, which can benefit epidemiological work, and may also be applicable to homicides and other statistics.

Capture-recapture analysis with a latent class model allowing for local dependence and observed heterogeneity.

In epidemiology, capture-recapture models are commonly used to estimate the size of an unknown population based on several incomplete lists of individuals. The method operates under two main assumptions: independence between the lists (local independence) and homogeneity of capture probabilities of individuals. In practice, these assumptions are rarely satisfied. We introduce a multinomial latent class model that can account for both list dependence and heterogeneity. Parameter estimation is performed by maximizing the conditional likelihood function with the use of the EM algorithm. In addition, a new approach for evaluating the standard errors of the parameter estimates is discussed, which considerably reduces the computational burden associated with the evaluation of the variance of the population size estimate.