Trichomonas vaginalis (TV) and bacterial vaginosis (BV) are highly prevalent vaginal infections. Both are associated with pelvic inflammatory disease and HIV acquisition and transmission, though the underlying mechanisms are incompletely understood. We characterized the effect of TV and BV infection on inflammatory markers in the vagina among reproductive-aged women in Atlanta, Georgia. Cervicovaginal lavage specimens were collected from HIV seronegative women at a baseline visit and again three months later. Eighteen individual cytokines, 17 T cell subsets, BV, and TV were measured at both timepoints. After natural log transformation, the median cytokine concentration and number of T cells were compared by infection status statistically using the Kruskal-Wallis test. A cytokine inflammation score and a T cell score were created using principal components analysis. The scores were then used as outcomes in separate linear mixed regression models with a random intercept. Sixty women had baseline data and 43 were seen for follow-up. The median age was 30 years, 78% self-reported Black race. TV and BV prevalence at the baseline visit was 15% and 37%, respectively. The concentration of 16 out of 18 cytokines differed by infection status. In multivariable modeling, neither TV nor BV were associated with cytokine score. Most CD4+ T cell subsets (7 out of 9) differed by infection status. In a multivariable model, TV infection was associated with a higher T cell score (1.54; 95%CI 0.00, 3.08). BV was not associated with a higher T cell score. Increased concentration of vaginal mucosal T cells may explain the observed association between TV infection and HIV risk.

UNAIDS estimates there were 160 000 incident | paediatric HIV infections globally in 2021. 1 HIV is | associated with high neonatal and infant morbidity | and mortality. More than half of untreated HIV-positive | children die before their second birthday.2 Early infant | diagnosis (EID) and prompt initiation of antiretroviral | therapy (ART) dramatically improves infant survival, | reducing mortality by 76%. 3,4 Consequently, WHO | recommends EID for HIV-exposed infants within the | first 6 weeks of life.5 | Current EID standard-of-care (SOC) models rely | on a complex cascade of steps that include clinical | presentation, sample collection, sample transport | (frequently to central laboratories) for the highly | sensitive and specific HIV nucleic acid tests (NAT), | notification of results, and coordination of patient and | caregivers to facilitate entry into HIV care. At each step | of this diagnostic cascade, there is substantial attrition, | which programme managers have tried to mitigate | through several interventions including improved | specimen handling and electronic return of results. 6 | Delays in time-to-result has led to increasing interest in | point-of-care NAT (POC-NAT) to decrease attrition in | linkage to paediatric HIV care.

BACKGROUND: Transportation of laboratory samples in low-income and middle-income countries is often constrained by poor road conditions, difficult geographical terrain, and insecurity. These constraints can lead to long turnaround times for laboratory diagnostic tests and hamper epidemic control or patient treatment efforts. Although uncrewed aircraft systems (UAS)-ie, drones-can mitigate some of these transportation constraints, their cost-effectiveness compared with land-based transportation systems is unclear. METHODS: We did a comparative economic study of the costs and cost-effectiveness of UAS versus motorcycles in Liberia (west Africa) for transportation of laboratory samples under simulated routine conditions and public health emergency conditions (based on the 2013-16 west African Ebola virus disease epidemic). We modelled three UAS with operational ranges of 30 km, 65 km, and 100 km (UAS30, UAS65, and UAS100) and lifespans of 1000 to 10 000 h, and compared the costs and number of samples transported with an established motorcycle transportation programme (most commonly used by the Liberian Ministry of Health and the charity Riders for Health). Data for UAS were obtained from Skyfire (a UAS consultancy), Vayu (a UAS manufacturer), and Sandia National Laboratories (a private company with UAS research experience). Motorcycle operational data were obtained from Riders for Health. In our model, we included costs for personnel, equipment, maintenance, and training, and did univariate and probabilistic sensitivity analyses for UAS lifespans, range, and accident or failures. FINDINGS: Under the routine scenario, the per sample transport costs were US$0.65 (95% CI 0.01-2.85) and $0.82 (0.56-5.05) for motorcycles and UAS65, respectively. Per-sample transport costs under the emergency scenario were $24.06 (95% CI 21.14-28.20) for motorcycles, $27.42 (95% CI 19.25-136.75) for an unadjusted UAS model with insufficient geographical coverage, and $34.09 (95% CI 26.70-127.40) for an adjusted UAS model with complementary motorcycles. Motorcycles were more cost-effective than short-range UAS (ie, UAS30). However, with increasing range and operational lifespans, UAS became increasingly more cost-effective. INTERPRETATION: Given the current level of technology, purchase prices, equipment lifespans, and operational flying ranges, UAS are not a viable option for routine transport of laboratory samples in west Africa. Field studies are required to generate evidence about UAS lifespan, failure rates, and performance under different weather conditions and payloads. FUNDING: None.