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Updated: Jan 31, 2026

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
Published on: December 27, 2010
Enumerating the population eligible for funded HIV pre-exposure prophylaxis (PrEP) in New Zealand
Peter J W Saxton1, Susan M McAllister2
1Gay Men's Sexual Health research group, Department of Social and Community Health, School of Population Health, University of Auckland, Private Bag 92109, Auckland 1142, New Zealand.
Abstract:
Background Pre-exposure prophylaxis (PrEP) became publicly funded in New Zealand (NZ) on 1 March 2018. PrEP could have a substantial population-level effect on HIV transmission if scaled up rapidly. An accurate estimate of the size of the PrEP-eligible population would guide implementation.
Methods:
We drew on nine sources to estimate the PrEP-eligible population, namely Statistics NZ data, Pharmaceutical Management Agency (PHARMAC) data on adults receiving funded antiretroviral treatment (ART), expert advice, estimates of the HIV care cascade, surveillance of undiagnosed HIV in a community sample of gay and bisexual men (GBM), surveillance of HIV diagnoses, NZ Health Survey data on sexual orientation among males, behavioural surveillance among GBM and behavioural data among people living with HIV (PLWH) from the HIV Futures NZ study. From these sources we derived three estimates relating to GBM, non-GBM and total eligible population. Sensitivity analyses examined different assumptions (GBM denominators, proportion PLWH diagnosed, proportion of diagnosed PLWH treated).
Results:
We estimated that 17.9% of sexually active HIV-negative GBM would be eligible for PrEP, equating to 5816 individuals. We estimated that 31 non-GBM individuals would be eligible for PrEP. Thus, in total, 5847 individuals would be eligible for PrEP, comprising 99.5% GBM and 0.5% non-GBM. Sensitivity analyses ranged from 3062 to 6718 individuals.
Conclusions:
Policy makers can use enumeration to monitor the speed and scale in coverage as implementation of publicly funded PrEP proceeds. Sexual health and primary care services can use enumeration to forecast PrEP demand and plan accordingly. Better quality data, especially on transgender adults in NZ, would improve the accuracy of estimates.
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