The Experts below are selected from a list of 46752 Experts worldwide ranked by ideXlab platform
Kosala Weerakoon - One of the best experts on this subject based on the ideXlab platform.
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droplet digital pcr diagnosis of human schistosomiasis parasite cell free dna detection in diverse clinical samples
The Journal of Infectious Diseases, 2017Co-Authors: Geoffrey N Gobert, Remigio M. Olveda, Gail M Williams, Kosala Weerakoon, Catherine A Gordon, Pengfei Cai, Allen G RossAbstract:Schistosomiasis japonica remains a major public health and socio-economic concern in Southeast-Asia. Sensitive and accurate diagnostics can play a pivotal role in achieving Disease Elimination goals. We previously reported a novel droplet digital-PCR (ddPCR) assay targeting the mitochondrial gene nad1 to diagnose schistosomiasis japonica. The tool identified both pre-patent and patent infections using Schistosoma japonicum DNA isolated from serum, urine, salivary glands and faeces in a murine model. The assay was validated here using clinical samples collected from 412 subjects resident in an area moderately endemic for schistosomiasis in the Philippines. S. japonicum DNA present in human stool, serum, urine and saliva was detected quantitatively with high sensitivity. The capability to diagnose cases of human schistosomiasis using non-invasively collected clinical samples, the higher level of sensitivity obtained compared with the microscopy-based Kato-Katz test, and the capacity to quantify infection intensity, have important public health implications for schistosomiasis control and programs targeting other neglected tropical Diseases. This verified ddPCR method represents a valuable new tool for the diagnosis and surveillance of schistosomiasis, particularly in low prevalence and low intensity areas approaching Elimination and in monitoring areas where Disease emergence or re-emergence is a concern.
Alessandro Vespignani - One of the best experts on this subject based on the ideXlab platform.
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spatiotemporal dynamics of the ebola epidemic in guinea and implications for vaccination and Disease Elimination a computational modeling analysis
BMC Medicine, 2016Co-Authors: Marco Ajelli, Natalie E Dean, Stefano Merler, Laura Fumanelli, Ana Pastore Y Piontti, Ira M Longini, Elizabeth M Halloran, Alessandro VespignaniAbstract:Background Among the three countries most affected by the Ebola virus Disease outbreak in 2014–2015, Guinea presents an unusual spatiotemporal epidemic pattern, with several waves and a long tail in the decay of the epidemic incidence.
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spatiotemporal dynamics of the ebola epidemic in guinea and implications for vaccination and Disease Elimination a computational modeling analysis
BMC Medicine, 2016Co-Authors: Marco Ajelli, Natalie E Dean, Stefano Merler, Laura Fumanelli, Ana Pastore Y Piontti, Ira M Longini, Elizabeth M Halloran, Alessandro VespignaniAbstract:Among the three countries most affected by the Ebola virus Disease outbreak in 2014–2015, Guinea presents an unusual spatiotemporal epidemic pattern, with several waves and a long tail in the decay of the epidemic incidence. Here, we develop a stochastic agent-based model at the level of a single household that integrates detailed data on Guinean demography, hospitals, Ebola treatment units, contact tracing, and safe burial interventions. The microsimulation-based model is used to assess the effect of each control strategy and the probability of Elimination of the epidemic according to different intervention scenarios, including ring vaccination with the recombinant vesicular stomatitis virus-vectored vaccine. The numerical results indicate that the dynamics of the Ebola epidemic in Guinea can be quantitatively explained by the timeline of the implemented interventions. In particular, the early availability of Ebola treatment units and the associated isolation of cases and safe burials helped to limit the number of Ebola cases experienced by Guinea. We provide quantitative evidence of a strong negative correlation between the time series of cases and the number of traced contacts. This result is confirmed by the computational model that suggests that contact tracing effort is a key determinant in the control and Elimination of the Disease. In data-driven microsimulations, we find that tracing at least 5–10 contacts per case is crucial in preventing epidemic resurgence during the epidemic Elimination phase. The computational model is used to provide an analysis of the ring vaccination trial highlighting its potential effect on Disease Elimination. We identify contact tracing as one of the key determinants of the epidemic’s behavior in Guinea, and we show that the early availability of Ebola treatment unit beds helped to limit the number of Ebola cases in Guinea.
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spatiotemporal dynamics of the ebola epidemic in guinea and implications for vaccination and Disease Elimination a computational modeling analysis
BMC Medicine, 2016Co-Authors: Marco Ajelli, Natalie E Dean, Stefano Merler, Laura Fumanelli, Ana Pastore Y Piontti, Ira M Longini, Elizabeth M Halloran, Alessandro VespignaniAbstract:Background Among the three countries most affected by the Ebola virus Disease outbreak in 2014–2015, Guinea presents an unusual spatiotemporal epidemic pattern, with several waves and a long tail in the decay of the epidemic incidence.
Alison L Hill - One of the best experts on this subject based on the ideXlab platform.
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dynamics of covid 19 under social distancing measures are driven by transmission network structure
PLOS Computational Biology, 2021Co-Authors: Anjalika Nande, Ben Adlam, Justin Sheen, Michael J Levy, Alison L HillAbstract:In the absence of pharmaceutical interventions, social distancing is being used worldwide to curb the spread of COVID-19. The impact of these measures has been inconsistent, with some regions rapidly nearing Disease Elimination and others seeing delayed peaks or nearly flat epidemic curves. Here we build a stochastic epidemic model to examine the effects of COVID-19 clinical progression and transmission network structure on the outcomes of social distancing interventions. Our simulations show that long delays between the adoption of control measures and observed declines in cases, hospitalizations, and deaths occur in many scenarios. We find that the strength of within-household transmission is a critical determinant of success, governing the timing and size of the epidemic peak, the rate of decline, individual risks of infection, and the success of partial relaxation measures. The structure of residual external connections, driven by workforce participation and essential businesses, interacts to determine outcomes. We suggest limited conditions under which the formation of household "bubbles" can be safe. These findings can improve future predictions of the timescale and efficacy of interventions needed to control second waves of COVID-19 as well as other similar outbreaks, and highlight the need for better quantification and control of household transmission.
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dynamics of covid 19 under social distancing measures are driven by transmission network structure
medRxiv, 2020Co-Authors: Anjalika Nande, Ben Adlam, Justin Sheen, Michael J Levy, Alison L HillAbstract:In the absence of pharmaceutical interventions, social distancing is being used worldwide to curb the spread of COVID-19. The impact of these measures has been inconsistent, with some regions rapidly nearing Disease Elimination and others seeing delayed peaks or nearly flat epidemic curves. Here we build a stochastic epidemic model to examine the effects of COVID-19 clinical progression and transmission network structure on the outcomes of social distancing interventions. We find that the strength of within-household transmission is a critical determinant of success, governing the timing and size of the epidemic peak, the rate of decline, individual risks of infection, and the success of partial relaxation measures. The structure of residual external connections, driven by workforce participation and essential businesses, interacts to determine outcomes. These findings can improve future predictions of the timescale and efficacy of interventions needed to control similar outbreaks, and highlight the need for better quantification and control of household transmission.
Allen G Ross - One of the best experts on this subject based on the ideXlab platform.
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droplet digital pcr diagnosis of human schistosomiasis parasite cell free dna detection in diverse clinical samples
The Journal of Infectious Diseases, 2017Co-Authors: Geoffrey N Gobert, Remigio M. Olveda, Gail M Williams, Kosala Weerakoon, Catherine A Gordon, Pengfei Cai, Allen G RossAbstract:Schistosomiasis japonica remains a major public health and socio-economic concern in Southeast-Asia. Sensitive and accurate diagnostics can play a pivotal role in achieving Disease Elimination goals. We previously reported a novel droplet digital-PCR (ddPCR) assay targeting the mitochondrial gene nad1 to diagnose schistosomiasis japonica. The tool identified both pre-patent and patent infections using Schistosoma japonicum DNA isolated from serum, urine, salivary glands and faeces in a murine model. The assay was validated here using clinical samples collected from 412 subjects resident in an area moderately endemic for schistosomiasis in the Philippines. S. japonicum DNA present in human stool, serum, urine and saliva was detected quantitatively with high sensitivity. The capability to diagnose cases of human schistosomiasis using non-invasively collected clinical samples, the higher level of sensitivity obtained compared with the microscopy-based Kato-Katz test, and the capacity to quantify infection intensity, have important public health implications for schistosomiasis control and programs targeting other neglected tropical Diseases. This verified ddPCR method represents a valuable new tool for the diagnosis and surveillance of schistosomiasis, particularly in low prevalence and low intensity areas approaching Elimination and in monitoring areas where Disease emergence or re-emergence is a concern.
Geoffrey N Gobert - One of the best experts on this subject based on the ideXlab platform.
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droplet digital pcr diagnosis of human schistosomiasis parasite cell free dna detection in diverse clinical samples
The Journal of Infectious Diseases, 2017Co-Authors: Geoffrey N Gobert, Remigio M. Olveda, Gail M Williams, Kosala Weerakoon, Catherine A Gordon, Pengfei Cai, Allen G RossAbstract:Schistosomiasis japonica remains a major public health and socio-economic concern in Southeast-Asia. Sensitive and accurate diagnostics can play a pivotal role in achieving Disease Elimination goals. We previously reported a novel droplet digital-PCR (ddPCR) assay targeting the mitochondrial gene nad1 to diagnose schistosomiasis japonica. The tool identified both pre-patent and patent infections using Schistosoma japonicum DNA isolated from serum, urine, salivary glands and faeces in a murine model. The assay was validated here using clinical samples collected from 412 subjects resident in an area moderately endemic for schistosomiasis in the Philippines. S. japonicum DNA present in human stool, serum, urine and saliva was detected quantitatively with high sensitivity. The capability to diagnose cases of human schistosomiasis using non-invasively collected clinical samples, the higher level of sensitivity obtained compared with the microscopy-based Kato-Katz test, and the capacity to quantify infection intensity, have important public health implications for schistosomiasis control and programs targeting other neglected tropical Diseases. This verified ddPCR method represents a valuable new tool for the diagnosis and surveillance of schistosomiasis, particularly in low prevalence and low intensity areas approaching Elimination and in monitoring areas where Disease emergence or re-emergence is a concern.