Estimating age-specific mortality using calibrated splines.

Demographers have developed a number of methods for expanding abridged mortality data into a complete schedule; however, these can be usefully applied only under certain conditions, and the presence or absence of one or more additional sources of incompleteness can degrade their relative accuracy, lead to implausible profiles, or even cause the methods to fail. We develop a new method for expanding an abridged schedule based on calibrated splines; this method is accurate and robust in the presence of errors in mortality rates, missing values, and truncation. We compare its performance with the performance of existing methods for expanding abridged data and find that it is superior to current methods at producing accurate and plausible complete schedules over a broad range of data-quality conditions. The method when applied is a valuable addition to existing tools for estimating mortality, especially for small nations, countries with incomplete vital statistics, and subnational populations.

Reconstruction of age distributions from differentially private census data.

The age distribution of a population is important for understanding the demand and provision of labor and services, and as a denominator for calculating key age-specific rates such as fertility and mortality. In the US, the most important source of information on age distributions is the decennial census, but a new disclosure avoidance system (DAS) based on differential privacy will inject noise into the data, potentially compromising its utility for small areas and minority populations. In this paper, we explore the question whether there are statistical methods that can be applied to noisy age distributions to enhance the research uses of census data without compromising privacy. We apply a non-parametric method for smoothing with naive or informative priors to age distributions from the 2010 Census via demonstration data which have had the US Census Bureau's implementation of differential privacy applied. We find that smoothing age distributions can increase the fidelity of the demonstration data to previously published population counts by age. We discuss implications for uses of data from the 2020 US Census and potential consequences for the measurement of population dynamics, health, and disparities.

A spatial interpretation of Australia's COVID-vulnerability.

The school of social vulnerability in disaster sciences offers an alternative perspective on the current COVID-19 (coronavirus) pandemic crisis. Social vulnerability in general can be understood as a risk of exposure to hazard impacts, where vulnerability is embedded in the normal functioning of the society. The COVID-19 pandemic has exposed systemic (political and health care systems), demographic (aging, race) and,based on the results of our approach, spatial (spatial isolation and connectivity) yvulnerabilities as well. In this paper, we develop a risk prediction model based on two composite indicators of social vulnerability. These indicators reflect the two main contrasting risks associated with COVID-19, demographic vulnerability and, as consequences of the lockdowns, economic vulnerability. We conceptualise social vulnerability in the context of the extremely uneven spatial population distribution in Australia. Our approach helps extend understanding about the role of spatiality in the current pandemic disaster.