Hepatitis C virus notification rates in Australia are highest in socioeconomically disadvantaged areas

Abstract

Background: Poor access to health services is a significant barrier to achieving the World Health Organization's hepatitis C virus (HCV) elimination targets. We demonstrate how geospatial analysis can be performed with commonly available data to identify areas with the greatest unmet demand for HCV services.

Methods: We performed an Australia-wide cross-sectional analysis of 2015 HCV notification rates using local government areas (LGAs) as our unit of analysis. A zero-inflated negative binomial regression was used to determine associations between notification rates and socioeconomic/demographic factors, health service and geographic remoteness area (RA) classification variables. Additionally, component scores were extracted from a principal component analysis (PCA) of the healthcare service variables to provide rankings of relative service coverage and unmet demand across Australia.

Results: Among LGAs with non-zero notifications, higher rates were associated with areas that had increased socioeconomic disadvantage, more needle and syringe services (incidence rate ratio [IRR] 1.022; 95%CI 1.001, 1.044) and more alcohol and other drug services (IRR 1.019; 1.005, 1.034). The distribution of PCA component scores indicated that per-capita healthcare service coverage was lower in areas outside of major Australian cities. Areas outside of major cities also contained 94% of LGAs in the lowest two socioeconomic quintiles, as well as 35% of HCV notifications despite only representing 29% of the population.

Conclusions: As countries aim for HCV elimination, routinely collected data can be used to identify geographical areas for priority service delivery. In Australia, the unmet demand for HCV treatment services is greatest in socioeconomically disadvantaged and non-metropolitan areas.

Fig 1

Bivariate distribution of notification rate (per 100,000 population) and remoteness areas (top left), presence of a prison (top right), state (bottom left) and IRSD quintile (bottom right). The vertical axis has been cropped to 200 notifications per 100,000 population in each plot to improve readability.

Fig 2. Univariate distribution of annual notifications per 100,000 population.

A negative binomial curve is overlaid (red), with a mean of 43.1 (the empirical mean) and dispersion of 0.70.

Fig 3. Quintile rank of 2015 notification rates by Australian Local Government Area.

Quintile 1 indicates the 20% of LGAs with the lowest notifications per 100,000 population. LGAs removed from the analysis are indicated in grey. Adapted from [33] under a CC BY license, with permission from the Commonwealth of Australia, original copyright 2016.

Fig 4. Quintile rank of 2015 relative healthcare coverage index by Australian Local Government Area.

Quintile 1 indicates the 20% of LGAs with lowest healthcare service scores. LGAs removed from the analysis are indicated in grey. Adapted from [33] under a CC BY license, with permission from the Commonwealth of Australia, original copyright 2016.

Fig 5. Quintile rank of 2015 unmet demand index by Australian Local Government Area.

Quintile 1 indicates the 20% of LGAs with the least unmet demand. LGAs removed from the analysis are indicated in grey. Adapted from [33] under a CC BY license, with permission from the Commonwealth of Australia, original copyright 2016.