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Journal articlePaschoalotto MAC, Cima J, Costa E, et al., 2024,
Politics and confidence toward the COVID-19 vaccination: A Brazilian cross-sectional study.
, Hum Vaccin Immunother, Vol: 20This study has the aim of assessing the Brazilian perceptions, influencing factors and political positioning on the confidence concerning COVID-19 vaccination. To achieve the objective, the methods rely on a cross-sectional survey of Brazilian citizens, distributed through different social networks. The sample is composed of 1,670 valid responses, collected from almost all Brazilian states and state capitals. To analyze the data and give a clear view of the variables' relationship, the study used bivariate and comparative graphs. Results show a higher level of confidence in vaccines from Pfizer and AstraZeneca, while the lower level of confidence is associated with vaccines from Sinopharm and Sputinik5. Vaccine efficacy is the most significant influencing factor that helps in the decision to get vaccinated. Also, individuals are less willing to get vaccinated if their political preferences are related to the right-wing. The results led to three main health and social implications: i) the vaccination strategy campaigns should take in count vaccine efficacy and political aspects; ii) the vaccination process should be adapted to regions with different political positions; and iii) a reinforcement in the educational policies of the vaccine's importance to the public health, to avoid the politization of a health issue.
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Journal articleWangdi K, Unwin HJT, Penjor K, et al., 2024,
Estimating the impact of imported malaria on local transmission in a near elimination setting: a case study from Bhutan
, The Lancet Regional Health - Southeast Asia, Vol: 31Background: Bhutan has achieved a substantial reduction in both malaria morbidity and mortality over the last two decades and is aiming for malaria elimination certification in 2025. However, a significant percentage of malaria cases in Bhutan are imported (acquired in another country). The aim of the study was to understand how importation drives local malaria transmission in Bhutan. Methods: Information on geo-located individual-level laboratory-confirmed malaria cases between 2016 and 2020 was obtained from the Bhutan Vector-borne Disease Control Program. Records included the date of diagnosis and treatment, type of cases classified as indigenous or imported, and malaria species. Hawkes Processes were used to study the role of imported malaria in local transmission in Bhutan. We imposed 15 days delay for a mosquito to become infectious in the model. Findings: There were 285 cases during the study period and 58.6% (159) were imported malaria. 71.1% (113) of these imported cases were Plasmodium vivax and 73.6% (117) were from India. The model suggested that a person remains infectious for 8 days for Plasmodium falciparum malaria but over 19 days for P. vivax. The background intensity from imported malaria cases was much greater for P. vivax cases (maximum 0.17) resulting in more importations than P. falciparum cases (maximum 0.06). However, model fitting suggested that local P. falciparum transmission was mainly driven by importations but additional factors such as relapse played a role for P. vivax. Interpretation: Imported malaria cases are key drivers of transmission within Bhutan, with most cases since 2016 being P. vivax. Control programmes should be devised to target interventions towards the P. vivax strain and test those who are more likely to bring in imported malaria cases or acquire it from returning travellers. Funding: None.
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Journal articleAtsame J, Stapley JN, Ramani A, et al., 2024,
Comparison of diagnostic tools to assess the feasibility of programmatic use of rapid diagnostic tests for onchocerciasis: a dataset from Gabon
, Data in Brief, Vol: 57, ISSN: 2352-3409Due to the success of large-scale ivermectin mass drug administration (MDA), the aim of onchocerciasis intervention efforts have shifted from control of the disease to elimination of transmission. This has necessitated a greater understanding and comparison of the performance of diagnostic tools in hypoendemic (low prevalence) settings which had not been incorporated into large-scale MDA programmes before the goal switched from onchocerciasis elimination as a public health problem to elimination (interruption) of transmission (EOT). Data on age, sex and duration of residence were collected, prior to ivermectin treatment, across Gabon in 2015 from 5,829 participants in 67 communities from 14 districts. Skin-snip samples (for detection of Onchocerca volvulus microfilariae) were obtained from 4,350 (75 %) and blood samples (for detection of presence of IgG4 antibodies against the O. volvulus Ov16 antigen) from 4,257 of those skin-snip tested (98 %).Whole blood was tested in the field using the SD Ov16 Rapid Diagnostic Test Prototype (Ov16 RDT). Dried blood spots (DBS) were prepared for all blood-sampled individuals. After assessing DBS quality, 2,990 (70 %) samples underwent valid analysis in the lab using horseradish peroxidase (HRP) Ov16 enzyme-linked immunosorbent assay (Ov16 ELISA). The number of positive individuals varied between diagnostic tools with skin-snip microscopy, Ov16 RDT and Ov16 ELISA detecting 337/4,350 (8 %, 95 % CI =7 %–9 %), 383/4,257 (9 %, 8 %–10 %) and 348/2,990 (12 %, 10 %–13 %), respectively. Data were analysed to understand the age profiles of microfilarial and IgG4 antibody prevalence by diagnostic and mapped across Gabon.These data have reuse potential for policy makers, test manufacturers and country programmes when making determinations at community level of the suitability of using Ov16 RDT for conducting delineation mapping or evaluating the current stage of a community or, more generally, an evaluation unit along the
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Journal articleKwok KO, Huynh T, Wei WI, et al., 2024,
Utilizing large language models in infectious disease transmission modelling for public health preparedness.
, Comput Struct Biotechnol J, Vol: 23, Pages: 3254-3257, ISSN: 2001-0370INTRODUCTION: OpenAI's ChatGPT, a Large Language Model (LLM), is a powerful tool across domains, designed for text and code generation, fostering collaboration, especially in public health. Investigating the role of this advanced LLM chatbot in assisting public health practitioners in shaping disease transmission models to inform infection control strategies, marks a new era in infectious disease epidemiology research. This study used a case study to illustrate how ChatGPT collaborates with a public health practitioner in co-designing a mathematical transmission model. METHODS: Using natural conversation, the practitioner initiated a dialogue involving an iterative process of code generation, refinement, and debugging with ChatGPT to develop a model to fit 10 days of prevalence data to estimate two key epidemiological parameters: i) basic reproductive number (Ro) and ii) final epidemic size. Verification and validation processes are conducted to ensure the accuracy and functionality of the final model. RESULTS: ChatGPT developed a validated transmission model which replicated the epidemic curve and gave estimates of Ro of 4.19 (95 % CI: 4.13- 4.26) and a final epidemic size of 98.3 % of the population within 60 days. It highlighted the advantages of using maximum likelihood estimation with Poisson distribution over least squares method. CONCLUSION: Integration of LLM in medical research accelerates model development, reducing technical barriers for health practitioners, democratizing access to advanced modeling and potentially enhancing pandemic preparedness globally, particularly in resource-constrained populations.
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Journal articleHancock PA, North A, Leach AW, et al., 2024,
The potential of gene drives in malaria vector species to control malaria in African environments.
, Nat Commun, Vol: 15Gene drives are a promising means of malaria control with the potential to cause sustained reductions in transmission. In real environments, however, their impacts will depend on local ecological and epidemiological factors. We develop a data-driven model to investigate the impacts of gene drives that causes vector population suppression. We simulate gene drive releases in sixteen ~ 12,000 km2 areas of west Africa that span variation in vector ecology and malaria prevalence, and estimate reductions in vector abundance, malaria prevalence and clinical cases. Average reductions in vector abundance ranged from 71.6-98.4% across areas, while impacts on malaria depended strongly on which vector species were targeted. When other new interventions including RTS,S vaccination and pyrethroid-PBO bednets were in place, at least 60% more clinical cases were averted when gene drives were added, demonstrating the benefits of integrated interventions. Our results show that different strategies for gene drive implementation may be required across different African settings.
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Journal articlePickles M, Mountain E, Bhattacharjee P, et al., 2024,
Exploratory analysis of the potential impact of violence on HIV among female sex workers in Mombasa, Kenya: a mathematical modelling study
, BMC Medicine, Vol: 22, ISSN: 1741-7015BackgroundUnderstanding the frequency of violence experienced by female sex workers (FSWs) and how violence contributes to HIV transmission can help improve HIV programs.MethodsUsing recent recommendations for modelling structural factors and associated causal pathways, we developed a HIV transmission dynamic model for FSWs and their clients in Mombasa, Kenya, mechanistically representing three types of violence (sexual violence, SV; physical violence, PV; police assault and arrest, PAA). Each type of violence affects HIV transmission through key mediators (condom non-use, HIV testing). We parameterized the model using data from a cross-sectional study of FSWs aged 15–24 recruited from a systematic geographical mapping sampling frame in Mombasa, Kenya (Cheuk E et al., Frontiers in Reproductive Health 2(7), 2020). Using this model, calibrated (and cross-validated) to HIV epidemiological and violence outcomes, we estimated the incidence of violence episodes, the contribution of violence to the HIV epidemic measured by the transmission population-attributable fraction, and the potential impact of possible violence interventions.ResultsThe median estimated incidence of PAA in 2023 among FSWs who had not previously experienced that type of violence was 0.20 (95% credible interval: 0.17–0.22) per person-year (ppy), about double the incidence of SV and PV (0.10 (0.09–0.11), 0.11 (0.09–0.12), respectively). The incidence of violence was higher among FSWs who had previously experienced violence: the incidence of recurrent PV was 2.65 (1.82–3.37) ppy, while the incidence of recurrent SV and PAA were 1.26 (0.80–1.67) and 1.37 (0.94–1.74 ppy, respectively. In this setting, we estimated that a median of 35.3% (3.4–55.8%) infections in FSWs and clients combined over the next 10 years may be due to all types of violence (and mediators), mainly through reduced condom use in FSWs who have ever experienced SV (34.6% (2.4–55.5%)).
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Journal articleDerelle R, von Wachsmann J, Mäklin T, et al., 2024,
Seamless, rapid, and accurate analyses of outbreak genomic data using split k-mer analysis.
, Genome ResSequence variation observed in populations of pathogens can be used for important public health and evolutionary genomic analyses, especially outbreak analysis and transmission reconstruction. Identifying this variation is typically achieved by aligning sequence reads to a reference genome, but this approach is susceptible to reference biases and requires careful filtering of called genotypes. There is a need for tools that can process this growing volume of bacterial genome data, providing rapid results, but that remain simple so they can be used without highly trained bioinformaticians, expensive data analysis, and long-term storage and processing of large files. Here we describe split k-mer analysis (SKA2), a method that supports both reference-free and reference-based mapping to quickly and accurately genotype populations of bacteria using sequencing reads or genome assemblies. SKA2 is highly accurate for closely related samples, and in outbreak simulations, we show superior variant recall compared with reference-based methods, with no false positives. SKA2 can also accurately map variants to a reference and be used with recombination detection methods to rapidly reconstruct vertical evolutionary history. SKA2 is many times faster than comparable methods and can be used to add new genomes to an existing call set, allowing sequential use without the need to reanalyze entire collections. With an inherent absence of reference bias, high accuracy, and a robust implementation, SKA2 has the potential to become the tool of choice for genotyping bacteria. SKA2 is implemented in Rust and is freely available as open-source software.
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Journal articleBiggs J, Challenger J, Hellewell J, et al., 2024,
A systematic review of sample size estimation accuracy on power in malaria cluster randomised trials measuring epidemiological outcomes
, BMC Medical Research Methodology, Vol: 24, ISSN: 1471-2288IntroductionCluster randomised trials (CRTs) are the gold standard for measuring the community-wide impacts of malaria control tools. CRTs rely on well-defined sample size estimations to detect statistically significant effects of trialled interventions, however these are often predicted poorly by triallists. Here, we review the accuracy of predicted parameters used in sample size calculations for malaria CRTs with epidemiological outcomes.MethodsWe searched for published malaria CRTs using four online databases in March 2022. Eligible trials included those with malaria-specific epidemiological outcomes which randomised at least six geographical clusters to study arms. Predicted and observed sample size parameters were extracted by reviewers for each trial. Pair-wise Spearman’s correlation coefficients (rs) were calculated to assess the correlation between predicted and observed control-arm outcome measures and effect sizes (relative percentage reductions) between arms. Among trials which retrospectively calculated an estimate of heterogeneity in cluster outcomes, we recalculated study power according to observed trial estimates.ResultsOf the 1889 records identified and screened, 108 articles were eligible and comprised of 71 malaria CRTs. Among 91.5% (65/71) of trials that included sample size calculations, most estimated cluster heterogeneity using the coefficient of variation (k) (80%, 52/65) which were often predicted without using prior data (67.7%, 44/65). Predicted control-arm prevalence moderately correlated with observed control-arm prevalence (rs: 0.44, [95%CI: 0.12,0.68], p-value < 0.05], with 61.2% (19/31) of prevalence estimates overestimated. Among the minority of trials that retrospectively calculated cluster heterogeneity (20%, 13/65), empirical values contrasted with those used in sample size estimations and often compromised study power. Observed effect sizes were often smaller than had been predicted at the sample size stage
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Journal articleSangkaew S, Tumviriyakul H, Cheranakhorn C, et al., 2024,
Unveiling post-COVID-19 syndrome: incidence, biomarkers, and clinical phenotypes in a Thai population
, BMC Infectious Diseases, Vol: 24, ISSN: 1471-2334BackgroundPost-COVID- 19 syndrome (PCS) significantly impacts the quality of life of survivors. There is, however, a lack of a standardized approach to PCS diagnosis and management. Our bidirectional cohort study aimed to estimate PCS incidence, identify risk factors and biomarkers, and classify clinical phenotypes for enhanced management to improve patient outcomes.MethodsA bidirectional prospective cohort study was conducted at five medical sites in Hatyai district in Songkhla Province, Thailand. Participants were randomly selected from among the survivors of COVID-19 aged≥18 years between May 15, 2022, and January 31, 2023. The selected participants underwent a scheduled outpatient visit for symptom and health assessments 12 to 16 weeks after the acute onset of infection, during which PCS was diagnosed and blood samples were collected for hematological, inflammatory, and serological tests. PCS was defined according to the World Health Organization criteria. Univariate and multiple logistic regression analyses were used to identify biomarkers associated with PCS. Moreover, three clustering methods (agglomerative hierarchical, divisive hierarchical, and K-means clustering) were applied, and internal validation metrics were used to determine clustering and similarities in phenotypes.FindingsA total of 300 survivors were enrolled in the study, 47% of whom developed PCS according to the World Health Organization (WHO) definition. In the sampled cohort, 66.3% were females, and 79.4% of them developed PCS (as compared to 54.7% of males, p-value <0.001). Comorbidities were present in 19% (57/300) of all patients, with 11% (18/159) in the group without PCS and 27.7% (39/141) in the group with PCS. The incidence of PCS varied depending on the criteria used and reached 13% when a quality of life indicator was added to the WHO definition. Common PCS symptoms were hair loss (22%) and fatigue (21%), while mental health symptoms were less frequent (insomnia 3%, dep
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Journal articleMills C, Chadeau-Hyam M, Elliott P, et al., 2024,
The utility of wastewater surveillance for monitoring SARS-CoV-2 prevalence
, PNAS Nexus, ISSN: 2752-6542Public health authorities have increasingly used wastewater-based epidemiology (WBE) to monitor community transmission of SARS-CoV-2 and other agents. Here, we evaluate the utility of WBE during the COVID-19 pandemic in England for estimating SARS-CoV-2 prevalence. We use wastewater data from the Environmental Monitoring for Health Protection (EMHP) programme and prevalence data from the REal-time Assessment of Community Transmission-1 (REACT-1) study. Across the pandemic, we describe how wastewater-based modelling can achieve representative SARS-CoV-2 prevalence estimates in fine and coarse spatial resolutions for relatively short time horizons (of up to one month), and thus assist in filling temporal gaps in surveillance. We infer a temporally evolving relationship between wastewater and prevalence which may limit the utility of WBE for estimating SARS-CoV-2 prevalence over longer time horizons without a concurrent prevalence survey. Exploring further our finding of time-varying, population-level faecal shedding, we characterise WBE for SARS-CoV-2 prevalence as i) vaccination-coverage-dependent and ii) variant-specific. Our research suggests that these factors are important considerations in future uses of WBE by public health authorities in infectious disease outbreaks. We further demonstrate that WBE can improve both the cost efficiency and accuracy of community prevalence surveys which on their own may have incomplete geographic coverage and/or small sample sizes. Therefore, in England, for the objective of high spatial resolution prevalence monitoring, strategic use of SARS-CoV-2 wastewater concentration data nationally could have enhanced, but not replaced, community prevalence survey programmes.
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