38 research outputs found

    Sustaining effective COVID-19 control in Malaysia through large-scale vaccination

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    Introduction: As of 3rd June 2021, Malaysia is experiencing a resurgence of COVID-19 cases. In response, the federal government has implemented various non-pharmaceutical interventions (NPIs) under a series of Movement Control Orders and, more recently, a vaccination campaign to regain epidemic control. In this study, we assessed the potential for the vaccination campaign to control the epidemic in Malaysia and four high-burden regions of interest, under various public health response scenarios. Methods: A modified susceptible-exposed-infectious-recovered compartmental model was developed that included two sequential incubation and infectious periods, with stratification by clinical state. The model was further stratified by age and incorporated population mobility to capture NPIs and micro-distancing (behaviour changes not captured through population mobility). Emerging variants of concern (VoC) were included as an additional strain competing with the existing wild-type strain. Several scenarios that included different vaccination strategies (i.e. vaccines that reduce disease severity and/or prevent infection, vaccination coverage) and mobility restrictions were implemented. Results: The national model and the regional models all fit well to notification data but underestimated ICU occupancy and deaths in recent weeks, which may be attributable to increased severity of VoC or saturation of case detection. However, the true case detection proportion showed wide credible intervals, highlighting incomplete understanding of the true epidemic size. The scenario projections suggested that under current vaccination rates complete relaxation of all NPIs would trigger a major epidemic. The results emphasise the importance of micro-distancing, maintaining mobility restrictions during vaccination roll-out and accelerating the pace of vaccination for future control. Malaysia is particularly susceptible to a major COVID-19 resurgence resulting from its limited population immunity due to the country's historical success in maintaining control throughout much of 2020

    Understanding COVID-19 Dynamics and the Effects of Interventions in the Philippines: A Mathematical Modelling Study

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    Background COVID-19 initially caused less severe outbreaks in many low- and middle-income countries (LMIC) compared with many high-income countries; possibly because of differing demographics; socioeconomics; surveillance; and policy responses. Here; we investigate the role of multiple factors on COVID-19 dynamics in the Philippines; a LMIC that has had a relatively severe COVID-19 outbreak. Methods We applied an age-structured compartmental model that incorporated time-varying mobility; testing; and personal protective behaviors (through a “Minimum Health Standards” policy; MHS) to represent the first wave of the Philippines COVID-19 epidemic nationally and for three highly affected regions (Calabarzon; Central Visayas; and the National Capital Region). We estimated effects of control measures; key epidemiological parameters; and interventions. Findings Population age structure; contact rates; mobility; testing; and MHS were sufficient to explain the Philippines epidemic based on the good fit between modelled and reported cases; hospitalisations; and deaths. The model indicated that MHS reduced the probability of transmission per contact by 13-27%. The February 2021 case detection rate was estimated at ~8%; population recovered at ~9%; and scenario projections indicated high sensitivity to MHS adherence. Interpretation COVID-19 dynamics in the Philippines are driven by age; contact structure; mobility; and MHS adherence. Continued compliance with low-cost MHS should help the Philippines control the epidemic until vaccines are widely distributed; but disease resurgence may be occurring due to a combination of low population immunity and detection rates and new variants of concern

    A Chemical Strategy for Intracellular Arming of an Endogenous Broad-Spectrum Antiviral Nucleotide

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    The naturally occurring nucleotide 3′-deoxy-3′,4′-didehydro-cytidine-5′-triphosphate (ddhCTP) was recently found to exert potent and broad-spectrum antiviral activity. However, nucleoside 5′-triphosphates in general are not cell-permeable, which precludes the direct use of ddhCTP as a therapeutic. To harness the therapeutic potential of this endogenous antiviral nucleotide, we synthesized phosphoramidate prodrug HLB-0532247 (1) and found it to result in dramatically elevated levels of ddhCTP in cells. We compared 1 and 3′-deoxy-3′,4′-didehydro-cytidine (ddhC) and found that 1 more effectively reduces titers of Zika and West Nile viruses in cell culture with minimal nonspecific toxicity to host cells. We conclude that 1 is a promising antiviral agent based on a novel strategy of facilitating elevated levels of the endogenous ddhCTP antiviral nucleotide

    COVID-19 collaborative modelling for policy response in the Philippines, Malaysia and Vietnam

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    Mathematical models that capture COVID-19 dynamics have supported public health responses and policy development since the beginning of the pandemic, yet there is limited discourse to describe features of an optimal modelling platform to support policy decisions or how modellers and policy makers have engaged with each other. Here, we outline how we used a modelling software platform to support public health decision making for the COVID-19 response in the Western Pacific Region (WPR) countries of the Philippines, Malaysia and Viet Nam. This perspective describes an approach to support evidence-based public health decisions and policy, which may help inform other responses to similar outbreak events. The platform we describe formed the basis for one of the inaugural World Health Organization (WHO) Western Pacific (WPRO) Innovation Challenge awards, and was backed by collaboration between epidemiological modellers, those providing public health advice, and policy makers

    Automated Internet-based pain coping skills training to manage osteoarthritis pain: a randomized controlled trial

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    Osteoarthritis (OA) places a significant burden on worldwide public health because of the large and growing number of people affected by OA and its associated pain and disability. Pain coping skills training (PCST) is an evidence-based intervention targeting OA pain and disability. To reduce barriers that currently limit access to PCST, we developed an 8-week, automated, Internet-based PCST program called PainCOACH and evaluated its potential efficacy and acceptability in a small-scale, 2-arm randomized controlled feasibility trial. Participants were 113 men and women with clinically confirmed hip or knee OA and associated pain. They were randomized to a group completing PainCOACH or an assessment-only control group. Osteoarthritis pain, pain-related interference with functioning, pain-related anxiety, self-efficacy for pain management, and positive and negative affect were measured before intervention, midway through the intervention, and after intervention. Findings indicated high acceptability and adherence: 91% of participants randomized to complete PainCOACH finished all 8 modules over 8 to 10 weeks. Linear mixed models showed that, after treatment, women who received the PainCOACH intervention reported significantly lower pain than that in women in the control group (Cohen d = 0.33). Intervention effects could not be tested in men because of their low pain and small sample size. Additionally, both men and women demonstrated increases in self-efficacy from baseline to after intervention compared with the control group (d = 0.43). Smaller effects were observed for pain-related anxiety (d = 0.20), pain-related interference with functioning (d = 0.13), negative affect (d = 0.10), and positive affect (d = 0.24). Findings underscore the value of continuing to develop an automated Internet-based approach to disseminate this empirically supported intervention

    Thermal biology of mosquito-borne disease

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    Mosquito-borne diseases cause a major burden of disease worldwide. The vital rates of these ectothermic vectors and parasites respond strongly and nonlinearly to temperature and therefore to climate change. Here, we review how trait-based approaches can synthesise and mechanistically predict the temperature dependence of transmission across vectors, pathogens, and environments. We present 11 pathogens transmitted by 15 different mosquito species – including globally important diseases like malaria, dengue, and Zika – synthesised from previously published studies. Transmission varied strongly and unimodally with temperature, peaking at 23–29ºC and declining to zero below 9–23ºC and above 32–38ºC. Different traits restricted transmission at low versus high temperatures, and temperature effects on transmission varied by both mosquito and parasite species. Temperate pathogens exhibit broader thermal ranges and cooler thermal minima and optima than tropical pathogens. Among tropical pathogens, malaria and Ross River virus had lower thermal optima (25–26ºC) while dengue and Zika viruses had the highest (29ºC) thermal optima. We expect warming to increase transmission below thermal optima but decrease transmission above optima. Key directions for future work include linking mechanistic models to field transmission, combining temperature effects with control measures, incorporating trait variation and temperature variation, and investigating climate adaptation and migration

    The Cyclic AMP Cascade Is Altered in the Fragile X Nervous System

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    Fragile X syndrome (FX), the most common heritable cause of mental retardation and autism, is a developmental disorder characterized by physical, cognitive, and behavioral deficits. FX results from a trinucleotide expansion mutation in the fmr1 gene that reduces levels of fragile X mental retardation protein (FMRP). Although research efforts have focused on FMRP's impact on mGluR signaling, how the loss of FMRP leads to the individual symptoms of FX is not known. Previous studies on human FX blood cells revealed alterations in the cyclic adenosine 3′, 5′-monophosphate (cAMP) cascade. We tested the hypothesis that cAMP signaling is altered in the FX nervous system using three different model systems. Induced levels of cAMP in platelets and in brains of fmr1 knockout mice are substantially reduced. Cyclic AMP induction is also significantly reduced in human FX neural cells. Furthermore, cAMP production is decreased in the heads of FX Drosophila and this defect can be rescued by reintroduction of the dfmr gene. Our results indicate that a robust defect in cAMP production in FX is conserved across species and suggest that cAMP metabolism may serve as a useful biomarker in the human disease population. Reduced cAMP induction has implications for the underlying causes of FX and autism spectrum disorders. Pharmacological agents known to modulate the cAMP cascade may be therapeutic in FX patients and can be tested in these models, thus supplementing current efforts centered on mGluR signaling

    Crowdsourcing hypothesis tests: Making transparent how design choices shape research results

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    To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer fiveoriginal research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams renderedstatistically significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to +0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for two hypotheses, and a lack of support for three hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim.</div

    The steady state anaerobic digestion of Laminaria hyperborea : effect of hydraulic residence on biogas production and bacterial community composition

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    Methane production by anaerobic digestion (AD) of macroalgae (seaweed) is a promising algal bioenergy option. Work presented here is primarily based on the AD of Laminaria hyperborea using batch and continuously stirred tank reactors. Extrapolation of data from batch studies to long term continuous reactors was unreliable. A conservative organic loading rate (OLR) of 1 g L−1 d−1 was used due to difficulties experienced in achieving steady state performance at an OLR of 1.5 g L−1 d−1. Biogas composition and methane yields (60–70%) were near to values expected from terrestrial feedstocks. Biomass washout, as imposed by the dilution rate (i.e., hydraulic residence), had considerable bearing on the biogas generation profile, particularly at >3 hydraulic residences. Inhibition of methanogen growth was linked to nutrient deficiency and potentially antimicrobial compounds associated with the feedstock. Anaerobic digestion of L. hyperborea proved feasible over extended operational periods
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