Evidence map›Paper›PMID 32790778›Full record

ArticlePloS one2020

The differential impacts of non-locally acquired infections and treatment interventions on heterosexual HIV transmission in Hong Kong.

Ngai Sze Wong, Man Po Lee, Ka Hing Wong, Owen T Y Tsang, Shui Shan Lee

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Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ngai Sze WongStanley Ho Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Shatin, Hong Kong, People's Republic of China.
Man Po LeeDepartment of Medicine, Queen Elizabeth Hospital, Kowloon, Hong Kong, People's Republic of China.
Ka Hing WongSpecial Preventive Programme, Department of Health, Hong Kong Special Administrative Region Government, Hong Kong, People's Republic of China.
Owen T Y TsangDepartment of Medicine and Geriatrics, Princess Margaret Hospital, Lai King, Kowloon, Hong Kong, People's Republic of China.
Shui Shan LeeStanley Ho Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Shatin, Hong Kong, People's Republic of China.ORCID 0000-0003-1448-765X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionHeterosexual infections have contributed to a high proportion of the HIV burden in Asia and Eastern Europe. Human mobility and non-local infections are important features in some cities/countries. An understanding of the determinants of the sustained growth of the heterosexual HIV epidemics would enable the potential impacts of treatment-based interventions to be assessed.

methodsWe developed a compartmental model for heterosexual HIV transmissions, parameterized by clinical and surveillance data (1984-2014) in Hong Kong. HIV sequence data were included for examining genetic linkages and clustering pattern. We performed sensitivity analyses to evaluate effects of high-risk sexual partnership and proportions of non-locally acquired infections. Four hypothetical interventions (a) immediate treatment, (b) enhancement of retention in care, (c) HIV testing campaigns, and (d) test-and-treat strategy, were examined.

resultsData of 2174 patients (723 female and 1451 male) diagnosed with HIV between 1984 and 2012 in Hong Kong were collected for model parameterization. Among 1229 sequences of non-MSM (men who have sex with men) patients, 70% were isolates and 17% were either dyads or triads. In base-case scenario, the total estimated number of new infections in 2012-2023 would be 672 for male and 452 for female. Following 100% retention in care intervention, the total proportion of averted new infections in 2012-2023 would be 7% for male and 10% for female. HIV testing campaign in 2012 and 2017 followed by 100% immediate treatment strategy would avert 5% and 9% of male and female new infections, respectively. In the epidemic model, an increase of high-risk sexual partnership from 6% to 9% would increase the epidemic growth (annual number of newly diagnosed and newly infected cases) by about 10%. If no non-locally acquired infection occurred as from 2012, the epidemic growth would slump. To control the heterosexual epidemic, periodic HIV testing at 5-year intervals with immediate treatment would avert 5-13% of annual new infections in 2013-2023.

conclusionsEnhanced HIV testing with immediate treatment is most effective in controlling the heterosexual epidemic, the impacts of which might however be attenuated by any increase of non-locally acquired infection, assuming little variations of high risk partnership over time.

Indexed as

HeterosexualityAdultAgedAnti-Retroviral AgentsEpidemicsFemaleHIV InfectionsHong KongHumansMaleMiddle AgedModels, TheoreticalAnti-Retroviral Agents

Identifiers

PMID32790778
PMCPMC7425942

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.