In March 2020 mathematics became a key part of the scientific advice to the UK government on the pandemic response to COVID-19. Mathematical and statistical modelling provided critical information on the spread of the virus and the potential impact of different interventions. The unprecedented scale of the challenge led the epidemiological modelling community in the UK to be pushed to its limits.
View Article and Find Full Text PDFIntroduction: This retrospective cohort study compares in-centre haemodialysis (ICHD) patients' outcomes between the 1st and 2nd waves of the COVID-19 pandemic in England, Wales, and Northern Ireland.
Methods: All people aged ≥18 years receiving ICHD at 31 December 2019, who were still alive and not in receipt of a kidney transplant at 1 March and who had a positive polymerase chain reaction test for SARS-CoV-2 between 1 March 2020 and 31 January 2021, were included. The COVID-19 infections were split into two "waves": wave 1 from March to August 2020 and wave 2 from September 2020 to January 2021.
Background: With the challenges that dengue fever (DF) presents to healthcare systems and societies, public health officials must determine where best to allocate scarce resources and restricted budgets. Constrained optimization (CO) helps to address some of the acknowledged limitations of conventional health economic analyses and has typically been used to identify the optimal allocation of resources across interventions subject to a variety of constraints.
Methods: A dynamic transmission model was developed to predict the number of dengue cases in Thailand at steady state.
Dengue fever is a vector-borne disease prevalent in tropical and subtropical regions. It is an important public health problem with a considerable and often under-valued disease burden in terms of frequency, cost and quality-of-life. Recent literature reviews have documented the development of mathematical models of dengue fever both to identify important characteristics for future model development as well as to assess the impact of dengue control interventions.
View Article and Find Full Text PDFWe analyse the tuberculosis (TB) epidemics of 211 countries with a view to proposing more efficient and targeted TB control strategies. Countries are classified by how their TB case notification rates have evolved over time and the age distribution of those suffering from active TB disease in 2008. Further analysis of key statistics associated with each of the countries shows the impact of different indicators.
View Article and Find Full Text PDFBackground: The HIV epidemic has caused a dramatic increase in tuberculosis (TB) in East and southern Africa. Several strategies have the potential to reduce the burden of TB in high HIV prevalence settings, and cost and cost-effectiveness analyses can help to prioritize them when budget constraints exist. However, published cost and cost-effectiveness studies are limited.
View Article and Find Full Text PDFObjective: To compare the benefits of tuberculosis (TB) treatment with TB and HIV prevention for the control of TB in regions with high HIV prevalence.
Design And Methods: A compartmental difference equation model of TB and HIV has been developed and fitted to time series and other published data using Bayesian methods. The model is used to compare the effectiveness of TB chemotherapy with three strategies for prevention: highly active antiretroviral therapy (HAART), the treatment of latent TB infection (TLTI) and the reduction of HIV transmission.