ORCID Profile
0000-0003-4274-4158
Current Organisation
University of Oxford
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Publisher: Cold Spring Harbor Laboratory
Date: 02-2023
DOI: 10.1101/2023.01.30.526303
Abstract: In humans, the nocturnal secretion of melatonin by the pineal gland is suppressed by ocular exposure to light. In the laboratory, melatonin suppression is a convenient biomarker for this neural pathway. Recent work has found that in iduals differ substantially in their melatonin-suppressive response to light, with the most sensitive in iduals being up to 60 times more sensitive than the least sensitive in iduals. Planning experiments with melatonin suppression as an outcome needs to incorporate these in idual differences, particularly in common resource-limited scenarios where running within-subjects studies at multiple light levels is expensive and not feasible with respect to participant compliance. Here, we present a novel framework for virtual laboratory melatonin suppression experiments, incorporating a Bayesian statistical model. We provide a Shiny web app for power analyses that allows users to modify various experimental parameters (s le size, in idual-level heterogeneity, statistical significance threshold, light levels), and simulate a systematic shift in sensitivity (e.g., due to a pharmacological or other intervention). Our framework helps experimenters to design compelling and robust studies, offering novel insights into the underlying biological variability relevant for practical applications.
Publisher: Cold Spring Harbor Laboratory
Date: 12-07-2023
DOI: 10.1101/2023.07.10.23292424
Abstract: Recent Marburg virus disease (MVD) outbreaks in Equatorial Guinea and Tanzania highlighted the importance of better understanding this highly lethal infectious pathogen. Past epidemics of Ebola, COVID-19, and other pathogens have re-emphasised the usefulness of mathematical models in guiding public health responses during outbreaks. We conducted a systematic review, registered with PROSPERO (CRD42023393345) and reported according to PRISMA guidelines, of peer-reviewed papers reporting historical out-breaks, modelling studies and epidemiological parameters focused on MVD, including contextual information. We searched PubMed and Web of Science until 31st March 2023. Two reviewers evaluated all titles and abstracts, with consensus-based decision-making. To ensure agreement, 31% (13/42) of studies were double-extracted and a custom-designed quality assessment questionnaire was used to assess the risk of bias. We present detailed outbreak, model and parameter information on 970 reported cases and 818 deaths from MVD until 31 March 2023. Analysis of historical outbreaks and sero-prevalence estimates suggests the possibility of undetected MVD outbreaks, asymptomatic transmission and/or cross-reactivity with other pathogens. Only one study presented a mathematical model of MVD transmission. We estimate an unadjusted, pooled total random effect case fatality ratio for MVD of 61.9% (95% CI: 38.8-80.6%, I 2 =93%). We identify key epidemiological parameters relating to transmission and natural history for which there are few estimates. This review provides a comprehensive overview of the epidemiology of MVD, identifying key knowledge gaps about this pathogen. The extensive collection of knowledge gathered here will be crucial in developing mathematical models for use in the early stages of future outbreaks of MVD. All data are published alongside this article with functionality to easily update the database as new data become available. MRC Centre for Global Infectious Disease Analysis Evidence before this study We searched Web of Science and PubMed up to 31 March 2023 using the search terms Marburg virus, epidemiology, outbreaks, models, transmissibility, severity, delays, risk factors, mutation rates and seroprevalence. We found five systematic reviews, all of which considered MVD alongside Ebola virus disease (EVD). One modelling study of Marburg virus disease (MVD) focused on animals, and not on computational models to understand past or project future disease transmission. One systematic review collated risk factors for transmission based on four MVD studies, but did not report attack rates due to missing underlying MVD estimates another systematic review pooled estimates of MVD case fatality ratios (CFR): 53.8% (95% CI: 26.5–80.0%) and seroprevalence: 1.2% (95% CI: 0.5–2.0%). No systematic review covered transmission models of MVD, and the impact of public health and social measures is unknown. Added value of this study We provide a comprehensive summary of the available, peer-reviewed literature of historical outbreaks, transmission models and parameters for MVD. Meta-analysis of existing estimates of CFRs, and our original estimates based on historical outbreak information, illustrate the severity of MVD with our pooled random effect estimated CFR of 61.9% (95% CI: 38.8-80.6%, I 2 =93%). We demonstrate the sparsity of evidence on MVD transmission and disease dynamics, particularly on transmissibility and natural history, which are key input parameters for computational models supporting outbreak response. Our work highlights key areas where further disease characterization is necessary. Implications of all the available evidence Previous outbreaks of infectious pathogens emphasized the usefulness of computational modelling in assessing epidemic trajectories and the impact of mitigation strategies. Our study provides necessary information for using mathematical models in future outbreaks of MVD, identifies uncertainties and knowledge gaps in MVD transmission and natural history, and highlights the severity of MVD.
Publisher: Springer Science and Business Media LLC
Date: 27-03-2018
DOI: 10.1038/S41598-018-22712-Z
Abstract: Mosquito control with bednets, residual sprays or fumigation remains the most effective tool for preventing vector-borne diseases such as malaria, dengue and Zika, though there are no widely used entomological methods for directly assessing its efficacy. Mosquito age is the most informative metric for evaluating interventions that kill adult mosquitoes but there is no simple or reliable way of measuring it in the field. Near-Infrared Spectroscopy (NIRS) has been shown to be a promising, high-throughput method that can estimate the age of mosquitoes. Currently the ability of NIRS to measure mosquito age is biased, and has relatively high in idual mosquito measurement error, though its capacity to rigorously monitor mosquito populations in the field has never been assessed. In this study, we use machine learning methods from the chemometric literature to generate more accurate, unbiased estimates of in idual mosquito age. These unbiased estimates produce precise population-level measurements, which are relatively insensitive to further increases in NIRS accuracy when feasible numbers of mosquitoes are s led. The utility of NIRS to directly measure the impact of pyrethroid resistance on mosquito control is illustrated, showing how the technology has potential as a highly valuable tool for directly assessing the efficacy of mosquito control interventions.
Publisher: Springer Science and Business Media LLC
Date: 02-2018
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Ben Lambert.