Current Challenges With the Use of Test-Negative Designs for Modeling COVID-19 Vaccination and Outcomes

The widespread testing for severe acute respiratory syndrome coronavirus 2 infection has facilitated the use of test-negative designs (TNDs) for modeling coronavirus disease 2019 (COVID-19) vaccination and outcomes. Despite the comprehensive literature on TND, the use of TND in COVID-19 studies is relatively new and calls for robust design and analysis to adapt to a rapidly changing and dynamically evolving pandemic and to account for changes in testing and reporting practices. In this commentary, we aim to draw the attention of researchers to COVID-specific challenges in using TND as we are analyzing data amassed over more than two years of the pandemic. We first review when and why TND works and general challenges in TND studies presented in the literature. We then discuss COVID-specific challenges which have not received adequate acknowledgment but may add to the risk of invalid conclusions in TND studies of COVID-19.

Modeling the Impact of HIV-1 Nucleic Acid Testing Among Symptomatic Adult Outpatients in Kenya

BACKGROUND

Up to 69% of adults who acquire HIV in Kenya seek care before seroconversion, providing an important opportunity for early diagnosis and treatment. The Tambua Mapema Plus (TMP) trial tested a combined HIV-1 nucleic acid testing, linkage, treatment, and partner notification intervention for adults aged 18-39 years with symptoms of acute HIV infection presenting to health facilities in coastal Kenya. We estimated the potential impact of TMP on the Kenyan HIV epidemic.

METHODS

We developed an agent-based network model of HIV-1 transmission using TMP data and Kenyan statistics to estimate potential population-level impact of targeted facility-based testing over 10 years. Three scenarios were modeled: standard care [current use of provider-initiated testing and counseling (PITC)], standard HIV rapid testing scaled to higher coverage obtained in TMP (scaled-up PITC), and the TMP intervention.

RESULTS

Standard care resulted in 90.7% of persons living with HIV (PLWH) knowing their status, with 67.5% of those diagnosed on treatment. Scaled-up PITC resulted in 94.4% of PLWH knowing their status and 70.4% of those diagnosed on treatment. The TMP intervention achieved 97.5% of PLWH knowing their status and 80.6% of those diagnosed on treatment. The percentage of infections averted was 1.0% (95% simulation intervals: -19.2% to 19.9%) for scaled-up PITC and 9.4% (95% simulation intervals: -8.1% to 24.5%) for TMP.

CONCLUSION

Our study suggests that leveraging new technologies to identify acute HIV infection among symptomatic outpatients is superior to scaled-up PITC in this population, resulting in >95% knowledge of HIV status, and would reduce new HIV infections in Kenya.