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Artikel ; Online: Simulation of Full HIV Cluster Networks in a Nationally Representative Model Indicates Intervention Opportunities.

France, Anne Marie / Panneer, Nivedha / Farnham, Paul G / Oster, Alexandra M / Viguerie, Alex / Gopalappa, Chaitra

Journal of acquired immune deficiency syndromes (1999)

2024 Band 95, Heft 4, Seite(n) 355–361

Abstract: Background: Clusters of rapid HIV transmission in the United States are increasingly recognized through analysis of HIV molecular sequence data reported to the National HIV Surveillance System. Understanding the full extent of cluster networks is ... ...

Abstract	Background: Clusters of rapid HIV transmission in the United States are increasingly recognized through analysis of HIV molecular sequence data reported to the National HIV Surveillance System. Understanding the full extent of cluster networks is important to assess intervention opportunities. However, full cluster networks include undiagnosed and other infections that cannot be systematically observed in real life. Methods: We replicated HIV molecular cluster networks during 2015-2017 in the United States using a stochastic dynamic network simulation model of sexual transmission of HIV. Clusters were defined at the 0.5% genetic distance threshold. Ongoing priority clusters had growth of ≥3 diagnoses/year in multiple years; new priority clusters first had ≥3 diagnoses/year in 2017. We assessed the full extent, composition, and transmission rates of new and ongoing priority clusters. Results: Full clusters were 3-9 times larger than detected clusters, with median detected cluster sizes in new and ongoing priority clusters of 4 (range 3-9) and 11 (range 3-33), respectively, corresponding to full cluster sizes with a median of 14 (3-74) and 94 (7-318), respectively. A median of 36.3% (range 11.1%-72.6%) of infections in the full new priority clusters were undiagnosed. HIV transmission rates in these clusters were >4 times the overall rate observed in the entire simulation. Conclusions: Priority clusters reflect networks with rapid HIV transmission. The substantially larger full extent of these clusters, high proportion of undiagnosed infections, and high transmission rates indicate opportunities for public health intervention and impact.
Mesh-Begriff(e)	Humans ; United States/epidemiology ; HIV-1/genetics ; HIV Infections/diagnosis ; HIV Infections/epidemiology ; Cluster Analysis ; Computer Simulation ; Phylogeny
Sprache	Englisch
Erscheinungsdatum	2024-02-27
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	645053-2
ISSN	1944-7884 ; 1077-9450 ; 0897-5965 ; 0894-9255 ; 1525-4135
ISSN (online)	1944-7884 ; 1077-9450
ISSN	0897-5965 ; 0894-9255 ; 1525-4135
DOI	10.1097/QAI.0000000000003367
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: COVID-19-related excess missed HIV diagnoses in the United States in 2021.

Viguerie, Alex / Song, Ruiguang / Johnson, Anna Satcher / Lyles, Cynthia M / Hernandez, Angela / Farnham, Paul G

AIDS (London, England)

2024 Band 38, Heft 6, Seite(n) 907–911

Abstract: Objective: Coronavirus disease 2019 (COVID-19) and related disruptions led to a significant decline in HIV diagnoses in the United States in 2020. A previous analysis estimated 18% fewer diagnoses than expected among persons with HIV (PWH) acquiring ... ...

Abstract	Objective: Coronavirus disease 2019 (COVID-19) and related disruptions led to a significant decline in HIV diagnoses in the United States in 2020. A previous analysis estimated 18% fewer diagnoses than expected among persons with HIV (PWH) acquiring infection in 2019 or earlier, suggesting that the decline in overall diagnoses cannot be attributed solely to decreased transmission. This analysis evaluates the progress made towards closing the 2020 diagnosis deficit in 2021. Methods: We apply previously developed methods analyzing 2021 diagnosis data from the National HIV Surveillance System to determine whether 2021 diagnosis levels of PWH infected pre-2020 are above or below the expected pre-COVID trends. Results are stratified by assigned sex at birth, transmission group, geographic region, and race/ethnicity. Results: In 2021, HIV diagnoses returned to pre-COVID levels among all PWH acquiring infection 2011-2019. Among Hispanic/Latino PWH and male individuals, diagnoses returned to pre-COVID levels. White PWH, MSM, and PWH living in the south and northeast showed higher-than-expected levels of diagnosis in 2021. For the remaining populations, there were fewer HIV diagnoses in 2021 than expected. Conclusion: Although overall diagnoses among persons acquiring HIV pre-2020 returned to pre-COVID levels, the diagnosis gap observed in 2020 remained unclosed at the end of 2021. Fewer than expected diagnoses among certain populations indicate that COVID-19-related disruptions to HIV diagnosis trends remained in 2021. Although some groups showed higher-than-expected levels of diagnoses, such increases were smaller than corresponding 2020 decreases. Expanded testing programs designed to close these gaps are essential.
Mesh-Begriff(e)	Infant, Newborn ; Humans ; Male ; United States/epidemiology ; HIV Infections/complications ; HIV Infections/diagnosis ; HIV Infections/epidemiology ; Homosexuality, Male ; COVID-19/diagnosis ; COVID-19/epidemiology ; Sexual and Gender Minorities ; Ethnicity
Sprache	Englisch
Erscheinungsdatum	2024-01-04
Erscheinungsland	England
Dokumenttyp	Journal Article
ZDB-ID	639076-6
ISSN	1473-5571 ; 0269-9370 ; 1350-2840
ISSN (online)	1473-5571
ISSN	0269-9370 ; 1350-2840
DOI	10.1097/QAD.0000000000003829
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Delay differential equations for the spatially resolved simulation of epidemics with specific application to COVID-19.

Guglielmi, Nicola / Iacomini, Elisa / Viguerie, Alex

Mathematical methods in the applied sciences

2022 Band 45, Heft 8, Seite(n) 4752–4771

Abstract: In the wake of the 2020 COVID-19 epidemic, much work has been performed on the development of mathematical models for the simulation of the epidemic and of disease models generally. Most works follow ... ...

Abstract	In the wake of the 2020 COVID-19 epidemic, much work has been performed on the development of mathematical models for the simulation of the epidemic and of disease models generally. Most works follow the
Sprache	Englisch
Erscheinungsdatum	2022-01-18
Erscheinungsland	Germany
Dokumenttyp	Journal Article
ZDB-ID	1478610-2
ISSN	1099-1476 ; 0170-4214
ISSN (online)	1099-1476
ISSN	0170-4214
DOI	10.1002/mma.8068
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Assessing the Impact of COVID-19 on HIV Outcomes in the United States: A Modeling Study.

Viguerie, Alex / Jacobson, Evin U / Hicks, Katherine A / Bates, Laurel / Carrico, Justin / Honeycutt, Amanda / Lyles, Cindy / Farnham, Paul G

Sexually transmitted diseases

2024 Band 51, Heft 4, Seite(n) 299–304

Abstract: Background: The COVID-19 pandemic impacted sexual behaviors and the HIV continuum of care in the United States, reducing HIV testing and diagnosis, and use of preexposure prophylaxis and antiretroviral therapy. We aimed to understand the future ... ...

Abstract	Background: The COVID-19 pandemic impacted sexual behaviors and the HIV continuum of care in the United States, reducing HIV testing and diagnosis, and use of preexposure prophylaxis and antiretroviral therapy. We aimed to understand the future implications of these effects through a modeling study. Methods: We first ran our compartmental model of HIV transmission in the United States accounting for pandemic-related short-term changes in transmission behavior and HIV prevention and care provision in 2020 to 2021 only. We then ran a comparison scenario that did not apply pandemic effects but assumed a continuation of past HIV prevention and care trends. We compared results from the 2 scenarios through 2024. Results: HIV incidence was 4·4% lower in 2020 to 2021 for the pandemic scenario compared with the no-pandemic scenario because of reduced levels of transmission behavior, despite reductions in HIV prevention and care caused by the pandemic. However, reduced care led to less viral load suppression among people with HIV in 2020, and in turn, our model resulted in a slightly greater incidence of 2·0% from 2022 to 2024 in the COVID-19 scenario, as compared with the non-COVID scenario. Discussion: Disruptions in HIV prevention and care services during COVID-19 may lead to somewhat higher postpandemic HIV incidence than assuming prepandemic trends in HIV care and prevention continued. These results underscore the importance of continuing to increase HIV prevention and care efforts in the coming years.
Mesh-Begriff(e)	Humans ; United States ; COVID-19/epidemiology ; Pandemics ; HIV Infections/epidemiology ; Acquired Immunodeficiency Syndrome ; Sexual Behavior
Sprache	Englisch
Erscheinungsdatum	2024-01-23
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	435191-5
ISSN	1537-4521 ; 0148-5717
ISSN (online)	1537-4521
ISSN	0148-5717
DOI	10.1097/OLQ.0000000000001935
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Mortality Among Persons With HIV in the United States During the COVID-19 Pandemic: A Population-Level Analysis.

Viguerie, Alex / Song, Ruiguang / Bosh, Karin / Lyles, Cynthia M / Farnham, Paul G

Journal of acquired immune deficiency syndromes (1999)

2023 Band 95, Heft 2, Seite(n) 126–132

Abstract: Background: Whether the COVID-19 pandemic has had a disproportionate impact on mortality among persons with diagnosed HIV (PWDH) in the United States is unclear. Through our macroscale analysis, we seek to better understand how the COVID-19 pandemic ... ...

Abstract	Background: Whether the COVID-19 pandemic has had a disproportionate impact on mortality among persons with diagnosed HIV (PWDH) in the United States is unclear. Through our macroscale analysis, we seek to better understand how the COVID-19 pandemic affected mortality among PWDH. Methods: We obtained mortality and population data for the years 2018-2020 from the National HIV Surveillance System for the US PWDH population and from publicly available data for the general population. We computed mortality rates and excess mortality for both the general and PWDH populations. Stratifications by age, race/ethnicity, and sex were considered. For each group, we determined whether the 2020 mortality rates and mortality risk ratio showed a statistically significant change from 2018 to 2019. Results: Approximately 1550 excess deaths occurred among PWDH in 2020, with Black, Hispanic/Latino, and PWDH aged 55 years and older comprising the majority of excess deaths. Mortality rates increased in 2020 from 2018-2019 across the general population in all groups. Among PWDH, mortality rates either increased or showed no statistically significant change. These increases were similar to, or smaller than, those observed in the general population, resulting in a 7.7% decrease in the mortality risk ratio between PWDH and the general population. Conclusions: While mortality rates among PWDH increased in 2020 relative to 2018-2019, the increases were smaller, or of similar magnitude, to those observed in the general population. We thus do not find evidence of elevated mortality risk from the COVID-19 pandemic among PWDH. These findings held across subpopulations stratified by age, sex, and racial/ethnic group.
Mesh-Begriff(e)	Humans ; United States/epidemiology ; COVID-19 ; HIV ; Pandemics ; HIV Infections ; Ethnicity
Sprache	Englisch
Erscheinungsdatum	2023-11-21
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	645053-2
ISSN	1944-7884 ; 1077-9450 ; 0897-5965 ; 0894-9255 ; 1525-4135
ISSN (online)	1944-7884 ; 1077-9450
ISSN	0897-5965 ; 0894-9255 ; 1525-4135
DOI	10.1097/QAI.0000000000003347
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: A multi-domain shear-stress dependent diffusive model of cell transport-aided dialysis: analysis and simulation.

Viguerie, Alex / Swapnasrita, Sangita / Veneziani, Alessandro / Carlier, Aurélie

Mathematical biosciences and engineering : MBE

2021 Band 18, Heft 6, Seite(n) 8188–8200

Abstract: Kidney dialysis is the most widespread treatment method for end-stage renal disease, a debilitating health condition common in industrialized societies. While ubiquitous, kidney dialysis suffers from an inability to remove larger toxins, resulting in a ... ...

Abstract	Kidney dialysis is the most widespread treatment method for end-stage renal disease, a debilitating health condition common in industrialized societies. While ubiquitous, kidney dialysis suffers from an inability to remove larger toxins, resulting in a gradual buildup of these toxins in dialysis patients, ultimately leading to further health complications. To improve dialysis, hollow fibers incorporating a cell-monolayer with cultured kidney cells have been proposed; however, the design of such a fiber is nontrivial. In particular, the effects of fluid wall-shear stress have an important influence on the ability of the cell layer to transport toxins. In the present work, we introduce a model for cell-transport aided dialysis, incorporating the effects of the shear stress. We analyze the model mathematically and establish its well-posedness. We then present a series of numerical results, which suggest that a hollow-fiber design with a wavy profile may increase the efficiency of the dialysis treatment. We investigate numerically the shape of the wavy channel to maximize the toxin clearance. These results demonstrate the potential for the use of computational models in the study and advancement of renal therapies.
Mesh-Begriff(e)	Computer Simulation ; Diffusion ; Humans ; Renal Dialysis ; Stress, Mechanical ; Toxins, Biological
Chemische Substanzen	Toxins, Biological
Sprache	Englisch
Erscheinungsdatum	2021-12-09
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2265126-3
ISSN	1551-0018 ; 1551-0018
ISSN (online)	1551-0018
ISSN	1551-0018
DOI	10.3934/mbe.2021406
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Buch ; Online: Modeling of Asymptotically Periodic Outbreaks

Viguerie, Alex / Carletti, Margherita / Veneziani, Alessandro / Silvestri, Guido

a long-term SIRW2 description of COVID-19?

2022

Abstract: As the outbreak of COVID-19 enters its third year, we have now enough data to analyse the behavior of the pandemic with mathematical models over a long period of time. The pandemic alternates periods of high and low infections, in a way that sheds a ... ...

Abstract	As the outbreak of COVID-19 enters its third year, we have now enough data to analyse the behavior of the pandemic with mathematical models over a long period of time. The pandemic alternates periods of high and low infections, in a way that sheds a light on the nature of mathematical model that can be used for reliable predictions. The main hypothesis of the model presented here is that the oscillatory behavior is a structural feature of the outbreak, even without postulating a time-dependence of the coefficients. As such, it should be reflected by the presence of limit cycles as asymptotic solutions. This stems from the introduction of (i) a non-linear waning immunity based on the concept of immunity booster (already used for other pathologies); (ii) a fine description of the compartments with a discrimination between individuals infected/vaccinated for the first time, and individuals already infected/vaccinated, undergoing to new infections/doses. We provide a proof-of-concept that our novel model is capable of reproducing long-term oscillatory behavior of many infectious diseases, and, in particular, the periodic nature of the waves of infection. Periodic solutions are inherent to the model, and achieved without changing parameter values in time. This may represent an important step in the long-term modeling of COVID-19 and similar diseases, as the natural, unforced behavior of the solution shows the qualitative characteristics observed during the COVID-19 pandemic.
Schlagwörter	Quantitative Biology - Populations and Evolution ; Mathematics - Dynamical Systems
Thema/Rubrik (Code)	330
Erscheinungsdatum	2022-03-15
Erscheinungsland	us
Dokumenttyp	Buch ; Online
Datenquelle	BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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Artikel ; Online: Isolating the Effect of COVID-19-Related Disruptions on HIV Diagnoses in the United States in 2020.

Viguerie, Alex / Song, Ruiguang / Johnson, Anna Satcher / Lyles, Cynthia M / Hernandez, Angela / Farnham, Paul G

Journal of acquired immune deficiency syndromes (1999)

2022 Band 92, Heft 4, Seite(n) 293–299

Abstract: Background: Diagnoses of HIV in the United States decreased by 17% in 2020 due to COVID-related disruptions. The extent to which this decrease is attributable to changes in HIV testing versus HIV transmission is unclear. We seek to better understand ... ...

Abstract	Background: Diagnoses of HIV in the United States decreased by 17% in 2020 due to COVID-related disruptions. The extent to which this decrease is attributable to changes in HIV testing versus HIV transmission is unclear. We seek to better understand this issue by analyzing the discrepancy in expected versus observed HIV diagnoses in 2020 among persons who acquired HIV between 2010 and 2019 because changes in diagnosis patterns in this cohort cannot be attributed to changes in transmission. Methods: We developed 3 methods based on the CD4-depletion model to estimate excess missed diagnoses in 2020 among persons with HIV (PWH) infected from 2010 to 2019. We stratified the results by transmission group, sex assigned at birth, race/ethnicity, and region to examine differences by group and confirm the reliability of our estimates. We performed similar analyses projecting diagnoses in 2019 among PWH infected from 2010 to 2018 to evaluate the accuracy of our methods against surveillance data. Results: There were approximately 3100-3300 (approximately 18%) fewer diagnoses than expected in 2020 among PWH infected from 2010 to 2019. Females (at birth), heterosexuals, persons who inject drugs, and Hispanic/Latino PWH missed diagnoses at higher levels than the overall population. Validation and stratification analyses confirmed the accuracy and reliability of our estimates. Conclusions: The substantial drop in number of previously infected PWH diagnosed in 2020 suggests that changes in testing played a substantial role in the observed decrease. Levels of missed diagnoses differed substantially across population subgroups. Increasing testing efforts and innovative strategies to reach undiagnosed PWH are needed to offset this diagnosis gap. These analyses may be used to inform future estimates of HIV transmission during the COVID-19 pandemic.
Mesh-Begriff(e)	Female ; Infant, Newborn ; Humans ; United States ; HIV Infections/epidemiology ; Drug Users ; Pandemics ; Reproducibility of Results ; Substance Abuse, Intravenous/epidemiology ; COVID-19/epidemiology
Sprache	Englisch
Erscheinungsdatum	2022-12-09
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	645053-2
ISSN	1944-7884 ; 1077-9450 ; 0897-5965 ; 0894-9255 ; 1525-4135
ISSN (online)	1944-7884 ; 1077-9450
ISSN	0897-5965 ; 0894-9255 ; 1525-4135
DOI	10.1097/QAI.0000000000003140
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Data-Driven Simulation of Fisher-Kolmogorov Tumor Growth Models Using Dynamic Mode Decomposition.

Viguerie, Alex / Grave, Malú / Barros, Gabriel F / Lorenzo, Guillermo / Reali, Alessandro / Coutinho, Alvaro L G A

Journal of biomechanical engineering

2022 Band 144, Heft 12

Abstract: The computer simulation of organ-scale biomechanistic models of cancer personalized via routinely collected clinical and imaging data enables to obtain patient-specific predictions of tumor growth and treatment response over the anatomy of the patient's ... ...

Abstract	The computer simulation of organ-scale biomechanistic models of cancer personalized via routinely collected clinical and imaging data enables to obtain patient-specific predictions of tumor growth and treatment response over the anatomy of the patient's affected organ. These patient-specific computational forecasts have been regarded as a promising approach to personalize the clinical management of cancer and derive optimal treatment plans for individual patients, which constitute timely and critical needs in clinical oncology. However, the computer simulation of the underlying spatiotemporal models can entail a prohibitive computational cost, which constitutes a barrier to the successful development of clinically-actionable computational technologies for personalized tumor forecasting. To address this issue, here we propose to utilize dynamic-mode decomposition (DMD) to construct a low-dimensional representation of cancer models and accelerate their simulation. DMD is an unsupervised machine learning method based on the singular value decomposition that has proven useful in many applications as both a predictive and a diagnostic tool. We show that DMD may be applied to Fisher-Kolmogorov models, which constitute an established formulation to represent untreated solid tumor growth that can further accommodate other relevant cancer phenomena (e.g., therapeutic effects, mechanical deformation). Our results show that a DMD implementation of this model over a clinically relevant parameter space can yield promising predictions, with short to medium-term errors remaining under 1% and long-term errors remaining under 20%, despite very short training periods. In particular, we have found that, for moderate to high tumor cell diffusivity and low to moderate tumor cell proliferation rate, DMD reconstructions provide accurate, bounded-error reconstructions for all tested training periods. Additionally, we also show that the three-dimensional DMD reconstruction of the tumor field can be leveraged to accurately reconstruct the displacement fields of the tumor-induced deformation of the host tissue. Thus, we posit the proposed data-driven approach has the potential to greatly reduce the computational overhead of personalized simulations of cancer models, thereby facilitating tumor forecasting, parameter identification, uncertainty quantification, and treatment optimization.
Mesh-Begriff(e)	Computer Simulation ; Humans ; Neoplasms
Sprache	Englisch
Erscheinungsdatum	2022-06-30
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	243094-0
ISSN	1528-8951 ; 0148-0731
ISSN (online)	1528-8951
ISSN	0148-0731
DOI	10.1115/1.4054925
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: COVID-related Excess Missed HIV Diagnoses in the United States in 2021: Follow-up to 2020

Viguerie, Alex / Song, Ruiguang / Johnson, Anna Satcher / Lyles, Cynthia M. / Hernandez, Angela / Farnham, Paul G.

medRxiv

Abstract: Objective: COVID-19 and related disruptions led to a significant drop in HIV diagnoses in the US in 2020. Recent analyses found 18% fewer diagnoses than expected among persons with HIV (PWH) acquiring infection in 2019 or earlier, suggesting that the ... ...

Abstract	Objective: COVID-19 and related disruptions led to a significant drop in HIV diagnoses in the US in 2020. Recent analyses found 18% fewer diagnoses than expected among persons with HIV (PWH) acquiring infection in 2019 or earlier, suggesting that the drop in diagnoses cannot be attributed solely to decreased transmission. This analysis evaluates the progress made towards closing the 2020 diagnosis deficit in 2021. Methods: We apply modified versions of previously developed methods analyzing 2021 diagnosis data from the National HIV Surveillance System to determine whether the 2021 diagnosis levels of PWH infected pre-2020 are above or below the projected pre-COVID trends. We apply these analyses on stratifications based on assigned sex at birth, transmission group, geographic region, and race/ethnicity. Results: In 2021, HIV diagnoses returned to pre-COVID levels among all PWH acquiring infection 2011-19. Among Hispanic/Latino PWH and males, diagnoses returned to pre-COVID levels. White PWH, men who have sex with men, and PWH living in the south and northeast showed higher-than-expected levels of diagnosis in 2021. For the remaining populations, there were fewer HIV diagnoses in 2021 than expected. Conclusions: While overall diagnoses returned to pre-COVID levels, the large diagnosis gap observed in 2020 remained unclosed at the end of 2021. Lower than expected diagnosis levels among certain populations indicates that COVID-19 related disruptions to HIV diagnosis trends were present in 2021. Although some groups showed higher-than-projected levels of diagnoses, such increases were smaller than the corresponding 2020 decreases. Expanded testing programs designed to close these gaps are essential.
Schlagwörter	covid19
Sprache	Englisch
Erscheinungsdatum	2023-09-29
Verlag	Cold Spring Harbor Laboratory Press
Dokumenttyp	Artikel ; Online
DOI	10.1101/2023.09.28.23296285
Datenquelle	COVID19

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