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Objective: To evaluate time-dependent changes in hepatic extracellular volume (ECV) fraction using contrast-enhanced CT (CECT) and serological liver fibrosis markers, the fibrosis-4 (FIB-4) index and aspartate aminotransferase to platelet ratio index (APRI), before and after direct-acting antiviral therapy (DAA) for hepatitis C virus (HCV) infection. Methods: 41 HCV-infected patients who achieved sustained virological response (SVR) after DAA (SVR group) and 10 control patients (untreated or unresponsive to treatment) who underwent CECT and serum biochemical tests before or after the first examination/DAA (T1) and at intervals thereafter (T2:24 months) were evaluated. Results: In the control group, ECV fractions remained relatively unchanged through the study, and significant differences in FIB-4 index comparisons and APRI comparisons were only seen between the T2 and T4 values (p = 0.046 and p = 0.028, respectively). In the SVR group, ECV fractions were significantly different between T1 and T4 and T1 and T5 (p = 0.046 and 0.022, respectively), and both FIB-4 index and APRI were significantly different between T1 and all other time points (p = 0.017 to p < 0.001 and p = 0.001 to p < 0.001, respectively). Conclusion: After DAA, ECV fraction decreased slowly, suggesting an improvement in hepatic fibrosis, while serological liver fibrosis markers decreased immediately, probably due to improvement in hepatic inflammation. Advances in knowledge: ECV fraction has the potential to be a non-invasive biomarker for the assessment of liver fibrosis after direct-acting antiviral therapy.

COVID-19 together with variants have caused an unprecedented amount of mental and economic turmoil with ever increasing fatality and no proven therapies in sight. The healthcare industry is racing to find a cure with multitude of clinical trials underway to access the efficacy of repurposed antivirals, however the much needed insights into the dynamics of pathogenesis of SARS-CoV-2 and corresponding pharmacology of antivirals are lacking. This paper introduces systematic pathological model learning of COVID-19 dynamics followed by derivative free optimization based multi objective drug rescheduling. The pathological model learnt from clinical data of severe COVID-19 patients treated with Remdesivir could additionally predict immune T cells response and resulted in a dramatic reduction in Remdesivir dose and schedule leading to lower toxicities, however maintaining a high virological efficacy.

Background Ineffective linkage to care (LTC) is a known challenge for community HIV testing. To overcome this challenge, a robust linkage to care strategy was adopted by the 2018 Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS). The NAIIS linkage to care strategy was further adapted to improve Nigeria’s programmatic efforts to achieve the 1st 90 as part of the Nigeria Antiretroviral Therapy (ART) Surge initiative, which also included targeted community testing. In this paper we provide an overview of the NAIIS LTC strategy and describe the impact of this strategy on both the NAIIS and the Surge initiatives. Methods The NAIIS collaborated with community-based organizations (CBOs) and deployed mobile health (mHealth) technology with real-time dashboards to manage and optimize community LTC for people living with HIV (PLHIV) diagnosed during the survey. In NAIIS, CBOs’ role was to facilitate linkage of identified PLHIV in community to facility of their choice. For the ART Surge, we modified the NAIIS LTC strategy by empowering both CBOs and mobile community teams as responsible for not only active LTC but also for community testing, ART initiation, and retention in care. Results Of the 2,739 PLHIV 15 years and above identified in NAIIS, 1,975 (72.1%) were either unaware of their HIV-positive status (N = 1890) or were aware of their HIV-positive status but not receiving treatment (N = 85). Of these, 1,342 (67.9%) were linked to care, of which 952 (70.9%) were initiated on ART. Among 1,890 newly diagnosed PLHIV, 1,278 (67.6%) were linked to care, 33.7% self-linked and 66.3% were linked by CBOs. Among 85 known PLHIV not on treatment, 64 (75.3%) were linked; 32.8% self-linked and 67.2% were linked by a CBO. In the ART Surge, LTC and treatment initiation rates were 98% and 100%, respectively. Three-month retention for monthly treatment initiation cohorts improved from 76% to 90% over 6 months. Conclusions Active LTC strategies by local CBOs and mobile community teams improved LTC and ART initiation in the ART Surge initiative. The use of mHealth technology resulted in timely and accurate documentation of results in NAIIS. By deploying mHealth in addition to active LTC, CBOs and mobile community teams could effectively scale up ART with real-time documentation of client-level outcomes.