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A mixed method evaluation of a novel targeted health messaging intervention to promote COVID-19 protective behaviours and vaccination among Black and South Asian communities living in the UK (The COBHAM study).
Clin Med (Lond)
January 2025
Professor of Hepatology, School of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Access and Medicine, Royal Surrey NHS FTInstitute of Liver Studies, Kings College Hospital NHS FT. Electronic address:
Aim: To evaluate an intervention (a film and electronic leaflet) disseminated via text message by general practices to promote COVID-19 preventative behaviours in Black and South Asian communities.
Methods: We carried out a before-and-after questionnaire study of attitudes to and implementation of COVID-19 preventative behaviours and qualitative interviews about the intervention with people registered with 26 general practices in England who identified as Black or South Asian.
Results: In the 108 people who completed both questionnaires, we found no significant change in attitudes to and implementation of COVID-19 preventative behaviours, although power was too low to detect significant effects.
Rift Valley fever (RVF) is a devastating zoonotic mosquito-borne viral hemorrhagic fever disease that threats human and animal health and biodiversity in Africa, including in Rwanda. RVF is increasingly outbreaking in Africa, leading to devastating impacts on health, socioeconomic stability and growth, and food insecurity in the region, particularly among livestock-dependent communi-ties. This systematic review synthesizes existing evidence on RVF's epidemiology, transmission dynamics, and the prevention and control measures implemented in Rwanda.
View Article and Find Full Text PDFApplication of Genomic Selection in Beef Cattle Disease Prevention.
Animals (Basel)
January 2025
Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Washington State University, Pullman, WA 99164-6610, USA.
Genomic applications in beef cattle disease prevention have gained traction in recent years, offering new strategies for improving herd health and reducing economic losses in the livestock industry. Advances in genomics, including identification of genetic markers linked to disease resistance, provide powerful tools for early detection, selection, and management of cattle resistant to infectious diseases. By incorporating genomic technologies such as whole-genome sequencing, genotyping, and transcriptomics, researchers can identify specific genetic variants associated with resistance to pathogens like bovine respiratory disease and Johne's disease.
View Article and Find Full Text PDFHarnessing the Power of AI to Improve Detection, Monitoring, and Public Health Interventions for Japanese Encephalitis.
Biomedicines
December 2024
School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.
Unlabelled: Japanese Encephalitis (JE) is the leading cause of viral encephalitis in regions with endemic Japanese Encephalitis Virus (JEV) infections.
Background/objectives: The aim of this review is to consider the potential role of artificial intelligence (AI) to improve detection, monitoring and public health interventions for JE.
Discussion: As climate change continues to impact mosquito population growth patterns, more regions will be affected by mosquito-borne diseases, including JE.
Analysis methods for covariate-constrained cluster randomized trials with time-to-event outcomes.
BMC Med Res Methodol
January 2025
Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia, USA.
Background: Cluster randomized trials, which often enroll a small number of clusters, can benefit from constrained randomization, selecting a final randomization scheme from a set of known, balanced randomizations. Previous literature has addressed the suitability of adjusting the analysis for the covariates that were balanced in the design phase when the outcome is continuous or binary. Here we extended this work to time-to-event outcomes by comparing two model-based tests and a newly derived permutation test.
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