MotivationClinicians, health officials and researchers are interested in the epidemic spread of pathogens in both space and time to support the optimization of intervention measures and public health policies. Large sequence databases of virus sequences provide an interesting opportunity to study this spread through phylogenetic analysis. To infer knowledge from large phylogenetic trees, potentially encompassing tens of thousands of virus strains, an efficient method for data exploration is required. The clades that are visited during this exploration should be annotated with strain characteristics (e.g. transmission risk group, tropism, drug resistance profile) and their geographic context.ResultsPhyloGeoTool implements a visual method to explore large phylogenetic trees and to depict characteristics of strains and clades, including their geographic context, in an interactive way. PhyloGeoTool also provides the possibility to position new virus strains relative to the existing phylogenetic tree, allowing users to gain insight in the placement of such new strains without the need to perform a de novo reconstruction of the phylogeny.Availability and implementation https://github.com/rega-cev/phylogeotool (Freely available: open source software project).Supplementary information Supplementary data are available at Bioinformatics online.

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Background Although eHealth technology makes it possible to improve the management of complex health care systems and follow up on chronic patients, it is not without challenges, thus requiring the development of efficient programs and graphic user interface (GUI) features. Similar information technology tools are crucial, as health care populations are going to have to endure social distancing measures in the forthcoming months and years. Objective This study aims to provide adequate and personalized support to complex health care populations by developing a specific web-based mobile app. The app is designed around the patient and adapted to specific groups, for example, people with complex or rare diseases, autism, or disabilities (especially among children) as well as Alzheimer or senile dementia. The app’s core features include the collection, labeling, analysis, and sorting of clinical data. Furthermore, it authorizes a network of people around the patient to securely access the data contained in his or her electronic health record. Methods The application was designed according to the paradigms of patient-centered care and user-centered design (UCD). It considers the patient as the main empowered and motivating factor in the management of his or her well-being. Implementation was informed through a family needs and technology perception assessment. We used 3 interdisciplinary focus groups and 2 assessment surveys to study the contexts of app use, subpopulation management, and preferred functions. Finally, we developed an observational study involving 116 enrolled patients and 253 system users, followed by 2 feedback surveys to evaluate the performance and impact of the app. Results In the validated general GUI, we developed 10 user profiles with different privacy settings. We tested 81 functions and studied a modular structure based on disease or medical area. This allowed us to identify replicable methods to be applied to module design. The observational study not only showed good family and community engagement but also revealed some limitations that need to be addressed. In total, 42 of 51 (82%) patients described themselves as satisfied or very satisfied . Health care providers reported facilitated communication with colleagues and the need to support data quality. Conclusions The experimented solution addressed some of the health system challenges mentioned by the World Health Organization: usability appears to be significantly improved when the GUI is designed according to patients’ UCD mental models and when new media and medical literacy are promoted. This makes it possible to maximize the impact of eHealth products, thereby overcoming some crucial gaps reported in the literature. Two main features seemed to have potential benefit compared with other eHealth products: the modeling, within the app, of both the formal...

Long-acting (LA) formulations have been designed to improve the quality of life of people with HIV (PWH) by maintaining virologic suppression. However, clinical trials have shown that patient selection is crucial. In fact, the HIV-1 resistance genotype test and the Body Mass Index of individual patients assume a predominant role in guiding the choice. Our work aimed to estimate the patients eligible for the new LA therapy with cabotegravir (CAB) + rilpivirine (RPV). We selected, from the Antiviral Response Cohort Analysis (ARCA) database, all PWH who had at least one follow-up in the last 24 months. We excluded patients with HBsAg positivity, evidence of non-nucleoside reverse transcriptase inhibitor (except K103N) and integrase inhibitor mutations, and with a detectable HIV-RNA (>50 copies/mL). Overall, 4103 patients are currently on follow-up in the ARCA, but the eligible patients totaled 1641 (39.9%). Among them, 1163 (70.9%) were males and 1399 were Caucasian (85.3%), of which 1291 (92%) were Italian born. The median length of HIV infection was 10.2 years (IQR 6.3–16.3) with a median nadir of CD4 cells/count of 238 (106–366) cells/mm3 and a median last available CD4 cells/count of 706 (509–944) cells/mm3. The majority of PWH were treated with a three-drug regimen (n = 1116, 68%). Among the 525 (30.3%) patients treated with two-drug regimens, 325 (18.1%) were treated with lamivudine (3TC) and dolutegravir (DTG) and only 84 (5.1%) with RPV and DTG. In conclusion, according to our snapshot, roughly 39.9% of virologically suppressed patients may be suitable candidates for long-acting CAB+RPV therapy. Therefore, based on our findings, many different variables should be taken into consideration to tailor the antiretroviral treatment according to different individual characteristics.