The underlying factors of excess mortality in 2020: a cross-country analysis of pre-pandemic healthcare conditions and strategies to cope with Covid-19

BACKGROUND

Government responses to the pandemic varied in terms of timing, duration, and stringency, seeking to protect healthcare systems, whose pre-pandemic state varied significantly. Therefore, the severity of Covid-19 and, thus, excess mortality have been unequal across counties. This paper explores the geography of excess mortality and its underlying factors in 2020, highlighting the effects of health policies pre-pandemic and strategies devised by governments to cope with Covid-19.

METHODS

Excess mortality is estimated for 79 high, medium and low-income countries. The factors of excess mortality are examined employing median quantile regression analysis.

RESULTS

Health privatization, healthcare underfunding, and late implementation of containment and mitigation strategies were powerful drivers of excess mortality. By contrast, the results suggest a negative association of excess mortality with health expenditure, number of doctors and hospital beds, share of population covered by health insurance and test and trace capacity.

CONCLUSIONS

The evidence highlights the importance of sufficiently funded healthcare systems with universal access and strong primary healthcare in the battle against the pandemic. An early response to Covid-19, including borders' controls and a strong test and trace capacity, could improve epidemiological surveillance and minimize excess mortality, with stringent and lengthy lockdowns not providing a significant benefit.

Self-management of health care: multimethod study of using integrated health care and supportive housing to address systematic barriers for people experiencing homelessness

Objectives The aims of the present study were to examine tenants’ experiences of a model of integrated health care and supportive housing and to identify whether integrated health care and supportive housing improved self-reported health and healthcare access. Methods The present study used a mixed-method survey design (n = 75) and qualitative interviews (n = 20) performed between September 2015 and August 2016. Participants were tenants of permanent supportive housing in Brisbane (Qld, Australia). Qualitative data were analysed thematically. Results Integrated health care and supportive housing were resources for tenants to overcome systematic barriers to accessing mainstream health care experienced when homeless. When homeless, people did not have access to resources required to maintain their health. Homelessness meant not having a voice to influence the health care people received; healthcare practitioners treated symptoms of poverty rather than considering how homelessness makes people sick. Integrated healthcare and supportive housing enabled tenants to receive treatment for health problems that were compounded by the barriers to accessing mainstream healthcare that homelessness represented. Conclusions Extending the evidence about housing as a social determinant of health, the present study shows that integrated health care and supportive housing enabled tenants to take control to self-manage their health care. In addition to homelessness directly contributing to ill health, the present study provides evidence of how the experience of homelessness contributes to exclusions from mainstream healthcare. What is known about the topic? People who are homeless experience poor physical and mental health, have unmet health care needs and use disproportionate rates of emergency health services. What does the paper add? The experience of homelessness creates barriers to accessing adequate health care. The provision of onsite multidisciplinary integrated health care in permanent supportive housing enabled illness self-management and greater control over lifestyle, and was associated with self-reported improved health and life satisfaction in formerly homeless tenants. What are the implications for practitioners? Integrated health care and supportive housing for the formerly homeless can improve self-reported health outcomes, enable healthier lifestyle choices and facilitate pathways into more appropriate and effective health care.

Closing the Gaps: competing estimates of Indigenous Australian life expectancy in the scientific literature

Objective: Closing the gap in life expectancy between Indigenous and other Australians within a generation is central to national Indigenous reform policy (Closing the Gap). Over time, various methods of estimating Indigenous life expectancy and with that, the life expectancy gap, have been adopted with differing, albeit non-comparable results. We present data on the extent of the gap and elucidate the pattern of use and interpretations of the different estimates of the gap, between 2007 and 2012.

Methods: An extensive search was conducted for all peer-reviewed health publications citing estimates of and/or discussing the life expectancy of Indigenous Australians, for the period 2007–2012.

Results: Five predominant patterns of citation of the gap estimates were identified: 20 years, 17 years, 15–20 years, 13 years, and 11.5 years for males and 9.7 years for females. Some authors misinterpret the most recent estimates as reflecting improvement from the 17-year figure, rather than the result of different methods of estimation. Support for the direct methods used to calculate Indigenous life expectancy is indicated.

Conclusions and Implications: A specific estimate of the life expectancy gap has not been established among stakeholders in Indigenous health. Agreement on the magnitude of the gap is arguably needed in order to evaluate strategies aimed at improving health outcomes for Indigenous Australians. Moreover, measuring progress towards ‘closing the gap’ depends on the availability of comparable estimates, using the same techniques of measurement to assess changes over time.

A Multiple-Process Latent Transition Model of Poverty and Health

Health researchers often use the life-course perspective, exploring how long-range experiences in one life domain may influence, and be influenced by, those in another. We develop a multiple-process latent transition model (MPLTM) to estimate changes in health and poverty dynamics simultaneously, using repeated measures of self-rated health and income for working-aged adults from the British Household Panel Survey. We apply the model to quantify concurrent and longitudinal effects to assess whether changes in these two processes are related or independent. Model extensions add time-invariant (cohort, gender) and time-varying (weeks nonemployed in previous year) covariates. We find both concurrent and bidirectional longitudinal relationships between poverty and health, with nonemployment appearing to mediate longitudinal health-to-poverty effects and confound longitudinal poverty-to-health effects. The MPLTM can provide quantitative estimates of complex interlocking processes that are often difficult to measure and assess.

An ecological analysis of factors associated with food insecurity in South Australia, 2002–7

Objective

To estimate the extent of food insecurity in South Australia and its relationship with a variety of socio-economic variables.

Design

Data collected routinely from 2002 to 2007 by SA Health were analysed to explore food security in the State’s population. An ecological analysis of data collected by the South Australian Monitoring and Surveillance System (SAMSS) that collects data on key health indicators. Questions on food security are asked periodically from July 2002 to December 2007.

Setting

South Australia.

Subjects

Over 37 000 interviewees took part in SAMSS surveys. Questions about food security were asked of 19 037 subjects. The sample was weighted by area, age and gender so that the results were representative of the South Australian population.

Results

Seven per cent (1342/19 037) of subjects reported running out of food during the previous year and not having enough money to buy food (food insecurity). Logistic regression analysis found food insecurity to be highest in households with low levels of education, limited capacity to save money, Aboriginal households, and households with three or more children.

Conclusions

The study confirms that food insecurity is strongly linked to economic disadvantage. Increasing cost of food is likely to exacerbate food insecurity. This is of concern given that food insecurity is associated with poor health, especially obesity and chronic disease. Comprehensive action at all levels is required to address root causes of food insecurity. Regular surveillance is required to continue to monitor levels of food security, but more in-depth understandings, via qualitative research, would be useful.