Browsing by Author "Ocom, Felix"

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    COVID-19 immune signatures in Uganda persist in HIV co-infection and diverge by pandemic phase
    (Nature Publishing Group, 2024-02) Cummings, Matthew J; Bakamutumaho, Barnabas; Lutwama, Julius J; Owor, Nicholas; Che, Xiaoyu; Astorkia, Maider; Postler, Thomas S; Kayiwa, John; Kiconco, Jocelyn; Muwanga, Moses; Nsereko, Christopher; wamutwe, Emmanuel; Nayiga, Irene; Kyebambe, Stephen; Haumba, Mercy; Bosa, Henry Kyobe; Ocom, Felix; Watyaba, Benjamin; TKikaire, Bernard; Tomoiaga, Alin S; Kisaka, Stevens; Kiwanuka, Noah; Lipkin, W Ian; O'Donnell, Max R
    Little is known about the pathobiology of SARS-CoV-2 infection in sub-Saharan Africa, where severe COVID-19 fatality rates are among the highest in the world and the immunological landscape is unique. In a prospective cohort study of 306 adults encompassing the entire clinical spectrum of SARS-CoV-2 infection in Uganda, we profile the peripheral blood proteome and transcriptome to characterize the immunopathology of COVID-19 across multiple phases of the pandemic. Beyond the prognostic importance of myeloid cell-driven immune activation and lymphopenia, we show that multifaceted impairment of host protein synthesis and redox imbalance define core biological signatures of severe COVID-19, with central roles for IL-7, IL-15, and lymphotoxin-α in COVID-19 respiratory failure. While prognostic signatures are generally consistent in SARS-CoV-2/HIV-coinfection, type I interferon responses uniquely scale with COVID-19 severity in persons living with HIV. Throughout the pandemic, COVID-19 severity peaked during phases dominated by A.23/A.23.1 and Delta B.1.617.2/AY variants. Independent of clinical severity, Delta phase COVID-19 is distinguished by exaggerated pro-inflammatory myeloid cell and inflammasome activation, NK and CD8+ T cell depletion, and impaired host protein synthesis. Combining these analyses with a contemporary Ugandan cohort of adults hospitalized with influenza and other severe acute respiratory infections, we show that activation of epidermal and platelet-derived growth factor pathways are distinct features of COVID-19, deepening translational understanding of mechanisms potentially underlying SARS-CoV-2-associated pulmonary fibrosis. Collectively, our findings provide biological rationale for use of broad and targeted immunotherapies for severe COVID-19 in sub-Saharan Africa, illustrate the relevance of local viral and host factors to SARS-CoV-2 immunopathology, and highlight underemphasized yet therapeutically exploitable immune pathways driving COVID-19 severity. Less is known about SARS-CoV-2 infection in unstudied geographical areas such as sub-Saharan Africa. Here the authors use multi-omics to characterize the immune response to SARS-CoV-2 in Uganda and consider how people living with HIV immunologically differentially respond to the virus.
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    Risk assessment of Ebola virus disease spreading in Uganda using a multilayer temporal network
    (bioRxiv, 2019) Riad, Mahbubul H.; Sekamatte, Musa; Ocom, Felix; Makumbi, Issa; Scoglio, Caterina M
    Network-based modelling of infectious diseases apply compartmental models on a contact network, which makes the epidemic process crucially dependent on the network structure. For highly contagious diseases such as Ebola virus disease (EVD), the inter-personal contact plays the most vital role in the human to human transmission. Therefore, for accurate representation of the EVD spreading, the contact network needs to resemble the reality. Prior research work has mainly focused on static networks (only permanent contacts) or activity driven networks (only temporal contacts) for Ebola spreading. A comprehensive network for EVD spreading should include both these network structures, as there are always some permanent contacts together with temporal contacts. Therefore, we propose a multilayer temporal network for Uganda, which is at risk of Ebola outbreak from the neighboring Democratic Republic of Congo (DRC) epidemic. The network has a permanent layer representing permanent contacts among individuals within family level, and a data driven temporal network for human movements motivated by cattle trade, fish trade, or general communications. We propose a Gillespie algorithm with the susceptible-infected-recovered (SIR) compartmental model to simulate the evolution of the EVD spreading as well as to evaluate the risk throughout our network. As an example, we applied our method to a multilayer network consisting of 23 districts along different movement routes in Uganda starting from bordering districts of DRC to Kampala. Simulation results shows that some regions are at higher risk of infection, suggesting some focal points for Ebola preparedness and providing direction to inform interventions in the field. Simulation results also shows that decreasing physical contacts as well as increasing preventive measures result in a reduction of chances to develop an outbreak. Overall, the main contribution of this paper lies in the novel method for risk assessment, the accuracy of which can be increased by increasing the amount and the accuracy of the data used to build the network and the model.
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    Risk assessment of Ebola virus disease spreading in Uganda using a two-layer temporal network
    (Scientific reports, 2019) Riad, Mahbubul H.; Sekamatte, Musa; Ocom, Felix; Makumbi, Issa; Scoglio, Caterina M.
    Network-based modelling of infectious diseases apply compartmental models on a contact network, which makes the epidemic process crucially dependent on the network structure. For highly contagious diseases such as Ebola virus disease (EVD), interpersonal contact plays the most vital role in humanto- human transmission. Therefore, for accurate representation of EVD spreading, the contact network needs to resemble the reality. Prior research has mainly focused on static networks (only permanent contacts) or activity-driven networks (only temporal contacts) for Ebola spreading. A comprehensive network for EVD spreading should include both these network structures, as there are always some permanent contacts together with temporal contacts. Therefore, we propose a two-layer temporal network for Uganda, which is at risk of an Ebola outbreak from the neighboring Democratic Republic of Congo (DRC) epidemic. The network has a permanent layer representing permanent contacts among individuals within the family level, and a data-driven temporal network for human movements motivated by cattle trade, fish trade, or general communications. We propose a Gillespie algorithm with the susceptible-infected-recovered (SIR) compartmental model to simulate the evolution of EVD spreading as well as to evaluate the risk throughout our network. As an example, we applied our method to a network consisting of 23 districts along different movement routes in Uganda starting from bordering districts of the DRC to Kampala. Simulation results show that some regions are at higher risk of infection, suggesting some focal points for Ebola preparedness and providing direction to inform interventions in the field. Simulation results also show that decreasing physical contact as well as increasing preventive measures result in a reduction of chances to develop an outbreak. Overall, the main contribution of this paper lies in the novel method for risk assessment, which can be more precise with an increasing volume of accurate data for creating the network model.
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    Severe COVID-19 in Uganda across Two Epidemic Phases: A Prospective Cohort Study
    (The American journal of tropical medicine and hygiene, 2021) Bakamutumaho, Barnabas; Cummings, Matthew J.; Owor, Nicholas; Kayiwa, John; Namulondo, Joyce; Byaruhanga, Timothy; Muwanga, Moses; Nsereko, Christopher; Mutonyi, Roselyn; Achan, Josephine; wanyenze, Lucy; Ndazarwe, Alice; Nakanjako, Ruth; Natuhwera, Richard; Nsangi, Annet; Bosa, Henry Kyobe; Ocom, Felix; Kikaire, Bernard; Lutwama, Julius J.
    Among a prospective cohort of children and adults admitted to a national COVID-19 treatment unit in Uganda from March to December 2020, we characterized the epidemiology of and risk factors for severe illness. Across two epidemic phases differentiated by varying levels of community transmission, the proportion of patients admitted with WHO-defined severe COVID-19 ranged from 5% (7/146; 95% CI: 2–10) to 33% (41/124; 95% CI: 25–42); 21% (26/124; 95% CI: 14–29%) of patients admitted during the peak phase received oxygen therapy. Severe COVID-19 was associated with older age, male sex, and longer duration of illness before admission. Coinfection with HIV was not associated with illness severity; malaria or tuberculosis coinfection was rare. No patients died during admission. Despite low mortality, hospital incidence of severe COVID-19 during the first epidemic peak in Uganda was substantial. Improvements in vaccine deployment and acute care capacity, including oxygen delivery, are urgently needed to prevent and manage severe COVID-19 in sub-Saharan Africa.