Background
Implementation of the Affordable Care Act motivates assessment of health insurance and supplementary programs, such as the AIDS Drug Assistance Program (ADAP) on health outcomes of HIV-infected people in the United States. We assessed the effects of health insurance, ADAP, and income on HIV viral load suppression.
Methods
We utilized existing cohort data from the HIV-infected participants of the Women’s Interagency HIV Study (WIHS). Cox proportional hazards models were used to estimate the time from 2006 to unsuppressed HIV viral load (>200 copies/mL) among those with Medicaid, private, Medicare or other public insurance, and no insurance, stratified by use of ADAP.
Results
In 2006, 65% of women had Medicaid, 18% had private insurance, 3% had Medicare or other public insurance, and 14% reported no health insurance. ADAP coverage was reported by 284 women (20%); 56% of uninsured participants reported ADAP coverage. After accounting for study site, age, race, lowest observed CD4, and prior health insurance, the hazard ratio (HR) for unsuppressed viral load among those privately insured without ADAP, compared to those on Medicaid without ADAP (referent group), was 0.61 (95% CI: 0.48–0.77). Among the uninsured, those with ADAP had a lower relative hazard of unsuppressed viral load compared to the referent group (HR, 95% CI: 0.49, 0.28–0.85) than those without ADAP (HR, 95% CI: 1.00, 0.63–1.57).
Conclusions
While women with private insurance are most likely to be virally suppressed, ADAP also contributes to viral load suppression. Continued support of this program may be especially critical for states that have not expanded Medicaid.
BackgroundHPV typing using formalin fixed paraffin embedded (FFPE) cervical tissue is used to evaluate HPV vaccine impact, but DNA yield and quality in FFPE specimens can negatively affect test results. This study aimed to evaluate 2 commercial assays for HPV detection and typing using FFPE cervical specimens.MethodsFour large North Carolina pathology laboratories provided FFPE specimens from 299 women ages18 and older diagnosed with cervical disease from 2001 to 2006. For each woman, one diagnostic block was selected and unstained serial sections were prepared for DNA typing. Extracts from samples with residual lesion were used to detect and type HPV using parallel and serial testing algorithms with the Linear Array and LiPA HPV genotyping assays.FindingsLA and LiPA concordance was 0.61 for detecting any high-risk (HR) and 0.20 for detecting any low-risk (LR) types, with significant differences in marginal proportions for HPV16, 51, 52, and any HR types. Discordant results were most often LiPA-positive, LA-negative. The parallel algorithm yielded the highest prevalence of any HPV type (95.7%). HR type prevalence was similar using parallel (93.1%) and serial (92.1%) approaches. HPV16, 33, and 52 prevalence was slightly lower using the serial algorithm, but the median number of HR types per woman (1) did not differ by algorithm. Using the serial algorithm, HPV DNA was detected in >85% of invasive and >95% of pre-invasive lesions. The most common type was HPV16, followed by 52, 18, 31, 33, and 35; HPV16/18 was detected in 56.5% of specimens. Multiple HPV types were more common in lower grade lesions.ConclusionsWe developed an efficient algorithm for testing and reporting results of two commercial assays for HPV detection and typing in FFPE specimens, and describe HPV type distribution in pre-invasive and invasive cervical lesions in a state-based sample prior to HPV vaccine introduction.
The incubation period, or the time from infection to symptom onset of COVID-19 has been usually estimated using data collected through interviews with cases and their contacts. However, this estimation is influenced by uncertainty in recalling effort of exposure time. We propose a novel method that uses viral load data collected over time since hospitalization, hindcasting the timing of infection with a mathematical model for viral dynamics. As an example, we used the reported viral load data from multiple countries (Singapore, China, Germany, France, and Korea) and estimated the incubation period. The median, 2.5, and 97.5 percentiles of the incubation period were 5.23 days (95% CI: 5.17, 5.25), 3.29 days (3.25, 3.37), and 8.22 days (8.02, 8.46), respectively, which are comparable to the values estimated in previous studies. Using viral load to estimate the incubation period might be a useful approach especially when impractical to directly observe the infection event.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.