Estimating the HIV Effective Reproduction Number in the United States and Evaluating HIV Elimination Strategies

Rejection of Federal Guidance by Southern US States and Projected Consequences for Ending the HIV Epidemic

Evidence-based HIV programming focused on populations at risk of HIV is critical for sustainable disease prevention. In response to the Tennessee Department of Health decision to reject federal HIV guidance, the present study examines the potential impact of Southern US states adopting policies that direct HIV prevention and testing efforts away from populations "disproportionately affected" (DA) by HIV toward populations "non-disproportionately affected" (NDA). Descriptive and projection analyses with publicly available data explored the influence of policies emphasizing NDA populations on HIV cases. Across the Southern US, DA populations (cisgender women, men who have sex with men, transgender persons, and people who inject drugs) represent the absolute majority (90%) of diagnosed HIV cases, whereas NDA populations (pregnant women, infants, first responders, and human trafficking victims) represent only a small proportion (2%) of diagnosed HIV cases. Estimated projections show avoidable HIV cases among DA populations in the Southern US alone could aggregate to over 32,000 by 2030 if prevention efforts exclusively concentrate on NDA populations, which approximates the current national annual incidence of 36,000 HIV cases. Prevention efforts aimed at DA populations compared with NDA populations could reduce new infections across the Southern US by 47% versus 1%, respectively, by 2030. Policies disregarding epidemiological data may hinder efforts to end the HIV epidemic, both regionally and nationally.

The effects of HIV self-testing on HIV incidence and awareness of status among men who have sex with men in the United States: Insights from a novel compartmental model

BACKGROUND

The OraQuick In-Home HIV self-test represents a fast, inexpensive, and convenient method for users to assess their HIV status. If integrated thoughtfully into existing testing practices, accompanied by efficient pathways to formal diagnosis, self-testing could enhance both HIV awareness and reduce HIV incidence. However, currently available self-tests are less sensitive, particularly for recent infection, when compared to gold-standard laboratory tests. It is important to understand the impact if some portion of standard testing is replaced by self-tests. We used a compartmental model to evaluate the effects of self-testing in diverse scenarios among gay, bisexual and other men who have sex with men (MSM) in the United States for the period 2020-2030, and to understand which scenarios maximize the advantages of self-testing.

METHODS

We introduced a novel 4-compartment model for HIV self-testing. We employed the model under different screening rates, self-test proportions, and delays to diagnosis for those identified through self-tests to determine the potential effects of self-testing on HIV incidence and awareness of status when applied to the US MSM population. We studied scenarios in which self-tests supplement laboratory-based tests, with no replacement, and scenarios in which some replacement occurs. We also examined how future improvements in self-test sensitivity may affect our results.

RESULTS

When HIV self-tests are supplemental rather than substitutes for laboratory-based testing, self-testing can decrease HIV incidence among MSM in the US by up to 10 % and increase awareness of status among MSM from 85 % to 91 % over a 10-year period, provided linkage to care and formal diagnosis occur promptly following a positive self-test (90 days or less). As self-tests replace a higher percentage laboratory-based testing algorithms, increases in overall testing rates were necessary to ensure reductions in HIV incidence. However, such needed increases were relatively small (under 10 % for prompt engagement in care and moderate levels of replacement). Improvements in self-test sensitivity and/or decreases in the detection period may further reduce any necessary increases in overall testing by up to 40 %.

CONCLUSIONS

If properly utilized, self-testing can provide significant long-term reductions to HIV incidence and improve awareness of HIV status. Ensuring that self-testing increases overall testing and that formal diagnosis and engagement in care occur promptly following a positive self-test are necessary to maximize the benefits of self-testing. Future improvements in self-test sensitivity and reductions in the detection period would further reduce HIV incidence and the potential risks associated with replacing laboratory tests with self-tests.

Longitudinal evolution of the HIV effective reproduction number following sequential expansion of treatment as prevention and pre-exposure prophylaxis in British Columbia, Canada: a population-level programme evaluation

BACKGROUND

Treatment as prevention and pre-exposure prophylaxis (PrEP) are key strategies in the control of HIV/AIDS. We aimed to characterise the longitudinal effects of antiretroviral therapy (ART), followed by treatment as prevention and the addition of PrEP, on the HIV effective reproduction number (Re) in British Columbia, Canada.

METHODS

This population-level programme evaluation used data from the Drug Treatment Program of the British Columbia Centre for Excellence in HIV/AIDS (Vancouver, British Columbia, Canada). We also used estimates of HIV incidence and prevalence from the Public Health Agency of Canada, data on the number of new HIV diagnoses per year from the British Columbia Centre for Disease Control, and mortality data from the British Columbia Vital Statistics Agency. Data were obtained from 1985 until 2022, depending on the database source. Outcomes were the annual HIV prevalence, HIV incidence, number of new HIV diagnoses, number of people living with HIV on ART, HIV/AIDS-related and all-cause mortality rates, the HIV incidence-to-all-cause-mortality ratio, and Re. We calculated the modified effective reproduction number (Rme) using two thresholds of viral suppression and compared these values with Re.

FINDINGS

We found a 95% decline in HIV/AIDS-related mortality and a 91% decrease in HIV incidence over the study period. The Re progressively declined from 1996 to 2022; however, from 1996 to 2017, Rme remained stable (>1) when calculated for people living with HIV with unsuppressed viraemia, suggesting that treatment as prevention reduces HIV incidence by decreasing the pool of individuals who are potentially able to transmit the virus. From 2018 to 2022, a decline in the estimated Re and Rme (<1) was observed regardless of whether we considered all people living with HIV or only those who were virologically unsuppressed. This finding suggests that PrEP decreases HIV incidence by reducing the number of susceptible individuals in the community, independently of viral suppression.

INTERPRETATION

Our results show the synergy between generalised treatment as prevention and targeted PrEP in terms of decreasing HIV incidence. These findings support the incorporation of longitudinal monitoring of Re at a programmatic level to identify opportunities for the optimisation of treatment-as-prevention and PrEP programmes.

FUNDING

British Columbia Ministry of Health, Health Canada, Public Health Agency of Canada, Vancouver Coastal Health, Vancouver General Hospital Foundation, Genome British Columbia, and the Canadian Institutes of Health Research.

The numerical solution of a mathematical model of the Covid-19 pandemic utilizing a meshless local discrete Galerkin method

It was in early December 2019 that the terrible news of the outbreak of new coronavirus disease (Covid-19) was reported by the world media, which appeared in Wuhan, China, and is rapidly spreading to other parts of China and several overseas countries. In the field of infectious diseases, modeling, evaluating, and predicting the rate of disease transmission are very important for epidemic prevention and control. Several preliminary mathematical models for Covid-19 are formulated by various international study groups. In this article, the SEIHR(D) compartmental model is proposed to study this epidemic and the factors affecting it, including vaccination. The proposed model can be used to compute the trajectory of the spread of the disease in different countries. Most importantly, it can be used to predict the impact of different inhibition strategies on the development of Covid-19. A computational approach is applied to solve the offered model utilizing the Galerkin method based on the moving least squares approximation constructed on a set of scattered points as a locally weighted least square polynomial fitting. As the method does not need any background meshes, its algorithm can be easily implemented on computers. Finally, illustrative examples clearly show the reliability and efficiency of the new technique and the obtained results are in good agreement with the known facts about the Covid-19 pandemic.