Browsing by Author "Kitayimbwa, John M."

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    Estimation of the HIV-1 Backward Mutation Rate From Transmitted Drug-Resistant Strains
    (Theoretical Population Biology, 2016-12) Kitayimbwa, John M.; Mugisha, Joseph Y. T.; Saenz, Roberto A.
    One of the serious threats facing the administration of antiretroviral therapy to human immunodeficiency virus (HIV-1) infected patients is the reported increasing prevalence of transmitted drug resistance. However, given that HIV-1 drug-resistant strains are often less fit than the wild-type strains, it is expected that drug-resistant strains that are present during the primary phase of the HIV-1 infection are replaced by the fitter wild-type strains. This replacement of HIV-1 resistant mutations involves the emergence of wild-type strains by a process of backward mutation. How quickly the replacement happens is dependent on the class of HIV-1 mutation group. We estimate the backward mutation rates and relative fitness of various mutational groups known to confer HIV-1 drug resistance. We do this by fitting a stochastic model to data for individuals who were originally infected by an HIV-1 strain carrying any one of the known drug resistance-conferring mutations and observed over a period of time to see whether the resistant strain is replaced. To do this, we seek a distribution, generated from simulations of the stochastic model, that best describes the observed (clinical data) replacement times of a given mutation. We found that Lamivudine/Emtricitabine-associated mutations have a distinctly higher, backward mutation rate and low relative fitness compared to the other classes (as has been reported before) while protease inhibitors-associated mutations have a slower backward mutation rate and high relative fitness. For the other mutation classes, we found more uncertainty in their estimates.
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    Performance of an Open Source Facial Recognition System for Unique Patient Matching in a Resource-Limited Setting
    (International Journal of Medical Informatics, 2020) Kitayimbwa, John M.; Were, Martin C.; Ampamyaa, Sight
    Background: The lack of unique patient identifiers is a challenge to patient care in developing countries. Probabilistic and deterministic matching approaches remain sub-optimal. However, affordable and scalable biometric solutions have not been rigorously evaluated in these settings. Methods: We implemented and evaluated performance of an open-source facial recognition system, OpenFace, integrated within a nationally-endorsed electronic health record system in Western Kenya. Patients were first enrolled via facial images, and later matched via the system. Accuracy of facial recognition was evaluated using Sensitivity; False Acceptance Rate (FAR); False Rejection Rate (FRR); Failure to Capture Rate (FTC) and Failure to Enroll Rate (FTE). 103 patients (mean age 37.8, 49.5% female) were enrolled. Results: The system had a sensitivity of 99.0%, FAR<1%, FRR 0.00, FTC 0.00 and FTE 0.00. Wearing spectacles did not affect performance. Conclusion: An open source facial recognition system correctly and accurately identified almost all patients during the first match.
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    Pervasive and Non-random Recombination in Near Full-Length HIV Genomes From Uganda
    (Virus Evolution, 2020) Kitayimbwa, John M.; Grant, Heather E.; Hodcroft, Emma B.; Ssemwanga, Deogratius; Gonzalo, Yebra; Gomez, Luis Roger Esquivel; Frampton, Dan; Gall, Astrid; Kellam, Paul; Oliveira, Tulio de; Bbosa, Nicholas; Nsubuga, Rebecca N.; Kibengo, Freddie; Kwan, Tsz Ho; Lycett, Samantha; Kao, Rowland; Robertson, David L.; Ratmann, Oliver; Fraser, Christophe; Pillay, Deenan; Kaleebu, Pontiano; Brown, Andrew J. Leigh
    Recombination is an important feature of HIV evolution, occurring both within and between the major branches of diversity (subtypes). The Ugandan epidemic is primarily composed of two subtypes, A1 and D that have been co-circulating for 50 years frequently recombining in dually infected patients. Here, we investigate the frequency of recombinants in this population and the location of breakpoints along the genome. As part of the PANGEA-HIV consortium, 1,472 consensus genome sequences over 5 kb have been obtained from 1,857 samples collected by the MRC/UVRI & LSHTM Research unit in Uganda, 465 (31.6 per cent) of which were near full-length sequences (>8 kb). Using the subtyping tool SCUEAL, we find that of the near full-length dataset, 233 (50.1 per cent) genomes contained only one subtype, 30.8 per cent A1 (n¼143), 17.6 percent D (n¼82), and 1.7 per cent C (n¼8), while 49.9 per cent (n¼232) contained more than one subtype (including A1/D (n¼164), A1/C (n¼13), C/D (n¼9); A1/C/D (n¼13), and 33 complex types). K-means clustering of the recombinant A1/D genomes revealed a section of envelope (C2gp120-TMgp41) is often inherited intact, whilst a generalized linear model was used to demonstrate significantly fewer breakpoints in the gag–pol and envelope C2-TM regions compared with accessory gene regions. Despite similar recombination patterns in many recombinants, no clearly supported circulating recombinant form (CRF) was found, there was limited evidence of the transmission of breakpoints, and the vast majority (153/164; 93 percent) of the A1/D recombinants appear to be unique recombinant forms. Thus, recombination is pervasive with clear biases in breakpoint location, but CRFs are not a significant feature, characteristic of a complex, and diverse epidemic.
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    Phylogenetic Networks and Parameters Inferred from HIV Nucleotide Sequences of High-Risk and General Population Groups in Uganda: Implications for Epidemic Control
    (Viruses, 2021) Kitayimbwa, John M.; Bbosa, Nicholas; Ssemwanga, Deogratius; Nsubuga, Rebecca N.; Kiwanuka, Noah; Bagaya, Bernard S.; Ssekagiri, Alfred; Gonzalo, Yebra; Kaleebu, Pontiano; Leigh-Brown, Andrew
    Phylogenetic inference is useful in characterising HIV transmission networks and assessing where prevention is likely to have the greatest impact. However, estimating parameters that influence the network structure is still scarce, but important in evaluating determinants of HIV spread. We analyzed 2017 HIV pol sequences (728 Lake Victoria fisherfolk communities (FFCs), 592 female sex workers (FSWs) and 697 general population (GP)) to identify transmission networks on Maximum Likelihood (ML) phylogenetic trees and refined them using time-resolved phylogenies. Network generative models were fitted to the observed degree distributions and network parameters, and corrected Akaike Information Criteria and Bayesian Information Criteria values were estimated. 347 (17.2%) HIV sequences were linked on ML trees (maximum genetic distance _4.5%, _95% bootstrap support) and, of these, 303 (86.7%) that consisted of pure A1 (n = 168) and D (n = 135) subtypes were analyzed in BEAST v1.8.4. The majority of networks (at least 40%) were found at a time depth of _5 years. The waring and yule models fitted best networks of FFCs and FSWs respectively while the negative binomial model fitted best networks in the GP. The network structure in the HIV-hyperendemic FFCs is likely to be scale-free and shaped by preferential attachment, in contrast to the GP. The findings support the targeting of interventions for FFCs in a timely manner for effective epidemic control. Interventions ought to be tailored according to the dynamics of the HIV epidemic in the target population and understanding the network structure is critical in ensuring the success of HIV prevention programs.
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    The Role of Backward Mutations on the Within-Host Dynamics of HIV-1
    (Journal of Mathematical Biology, 2012-09-06) Kitayimbwa, John M.; Mugisha, Joseph Y. T.; Saenz, Roberto A.
    The quality of life for patients infected with human immunodeficiency virus (HIV-1) has been positively impacted by the use of antiretroviral therapy (ART). However, the benefits of ART are usually halted by the emergence of drug resistance. Drug-resistant strains arise from virus mutations, as HIV-1 reverse transcription is prone to errors, with mutations normally carrying fitness costs to the virus. When ART is interrupted, the wild-type drug-sensitive strain rapidly out-competes the resistant strain, as the former strain is fitter than the latter in the absence of ART. One mechanism for sustaining the sensitive strain during ART is given by the virus mutating from resistant to sensitive strains, which is referred to as backward mutation. This is important during periods of treatment interruptions as prior existence of the sensitive strain would lead to replacement of the resistant strain. In order to assess the role of backward mutations in the dynamics of HIV-1 within an infected host, we analyze a mathematical model of two interacting virus strains in either absence or presence of ART. We study the effect of backward mutations on the definition of the basic reproductive number, and the value and stability of equilibrium points. The analysis of the model shows that, thanks to both forward and backward mutations, sensitive and resistant strains co-exist. In addition, conditions for the dominance of a viral strain with or without ART are provided. For this model, backward mutations are shown to be necessary for the persistence of the sensitive strain during ART.