Medicine (RMH) - Research Publications
Permanent URI for this collection
Search Results
1 - 5 of 5
-
ItemNo Preview AvailableModelling the Economic Impacts of Epidemics in Developing Countries Under Alternative Intervention Strategies(Springer, 2020)Modern levels of global travel have intensified the risk of new infectious diseases becoming pandemics. Particularly at risk are developing countries whose health systems may be less well equipped to detect quickly and respond effectively to the importation of new infectious diseases. This chapter examines what might have been the economic consequences if the 2014 West African Ebola epidemic had been imported to a small Asia-Pacific country. Hypothetical outbreaks in two countries were modelled. The post-importation estimations were carried out with two linked models: a stochastic disease transmission (SEIR) model and a quarterly version of the multi-country GTAP model, GTAP-Q. The SEIR model provided daily estimates of the number of persons in various disease states. For each intervention strategy the stochastic disease model was run 500 times to obtain the probability distribution of disease outcomes. Typical daily country outcomes for both controlled and uncontrolled outbreaks under five alternative intervention strategies were converted to quarterly disease-state results, which in turn were used in the estimation of GTAP-Q shocks to country-specific health costs and labour productivity during the outbreak, and permanent reductions in each country’s population and labour force due to mortality. Estimated behavioural consequences (severe reductions in international tourism and crowd avoidance) formed further shocks. The GTAP-Q simulations revealed very large economic costs for each country if they experienced an uncontrolled Ebola outbreak, and considerable economic costs for controlled outbreaks in Fiji due to the importance of the tourism sector to its economy. A major finding was that purely reactive strategies had virtually no effect on preventing uncontrolled outbreaks, but pre-emptive strategies substantially reduced the proportion of uncontrolled outbreaks, and in turn the economic and social costs.
-
ItemProfiling Mycobacterium tuberculosis transmission and the resulting disease burden in the five highest tuberculosis burden countries(BMC, 2019-11-22)BACKGROUND: Tuberculosis (TB) control efforts are hampered by an imperfect understanding of TB epidemiology. The true age distribution of disease is unknown because a large proportion of individuals with active TB remain undetected. Understanding of transmission is limited by the asymptomatic nature of latent infection and the pathogen's capacity for late reactivation. A better understanding of TB epidemiology is critically needed to ensure effective use of existing and future control tools. METHODS: We use an agent-based model to simulate TB epidemiology in the five highest TB burden countries-India, Indonesia, China, the Philippines and Pakistan-providing unique insights into patterns of transmission and disease. Our model replicates demographically realistic populations, explicitly capturing social contacts between individuals based on local estimates of age-specific contact in household, school and workplace settings. Time-varying programmatic parameters are incorporated to account for the local history of TB control. RESULTS: We estimate that the 15-19-year-old age group is involved in more than 20% of transmission events in India, Indonesia, the Philippines and Pakistan, despite representing only 5% of the local TB incidence. According to our model, childhood TB represents around one fifth of the incident TB cases in these four countries. In China, three quarters of incident TB were estimated to occur in the ≥ 45-year-old population. The calibrated per-contact transmission risk was found to be similar in each of the five countries despite their very different TB burdens. CONCLUSIONS: Adolescents and young adults are a major driver of TB in high-incidence settings. Relying only on the observed distribution of disease to understand the age profile of transmission is potentially misleading.
-
ItemModel-Informed Risk Assessment and Decision Making for an Emerging Infectious Disease in the Asia-Pacific Region(PUBLIC LIBRARY SCIENCE, 2016-09-01)BACKGROUND: Effective response to emerging infectious disease (EID) threats relies on health care systems that can detect and contain localised outbreaks before they reach a national or international scale. The Asia-Pacific region contains low and middle income countries in which the risk of EID outbreaks is elevated and whose health care systems may require international support to effectively detect and respond to such events. The absence of comprehensive data on populations, health care systems and disease characteristics in this region makes risk assessment and decisions about the provision of such support challenging. METHODOLOGY/PRINCIPAL FINDINGS: We describe a mathematical modelling framework that can inform this process by integrating available data sources, systematically explore the effects of uncertainty, and provide estimates of outbreak risk under a range of intervention scenarios. We illustrate the use of this framework in the context of a potential importation of Ebola Virus Disease into the Asia-Pacific region. Results suggest that, across a wide range of plausible scenarios, preemptive interventions supporting the timely detection of early cases provide substantially greater reductions in the probability of large outbreaks than interventions that support health care system capacity after an outbreak has commenced. CONCLUSIONS/SIGNIFICANCE: Our study demonstrates how, in the presence of substantial uncertainty about health care system infrastructure and other relevant aspects of disease control, mathematical models can be used to assess the constraints that limited resources place upon the ability of local health care systems to detect and respond to EID outbreaks in a timely and effective fashion. Our framework can help evaluate the relative impact of these constraints to identify resourcing priorities for health care system support, in order to inform principled and quantifiable decision making.
-
ItemVaccination Programs for Endemic Infections: Modelling Real versus Apparent Impacts of Vaccine and Infection Characteristics(NATURE PUBLISHING GROUP, 2015-10-20)Vaccine effect, as measured in clinical trials, may not accurately reflect population-level impact. Furthermore, little is known about how sensitive apparent or real vaccine impacts are to factors such as the risk of re-infection or the mechanism of protection. We present a dynamic compartmental model to simulate vaccination for endemic infections. Several measures of effectiveness are calculated to compare the real and apparent impact of vaccination, and assess the effect of a range of infection and vaccine characteristics on these measures. Although broadly correlated, measures of real and apparent vaccine effectiveness can differ widely. Vaccine impact is markedly underestimated when primary infection provides partial natural immunity, when coverage is high and when post-vaccination infectiousness is reduced. Despite equivalent efficacy, 'all or nothing' vaccines are more effective than 'leaky' vaccines, particularly in settings with high risk of re-infection and transmissibility. Latent periods result in greater real impacts when risk of re-infection is high, but this effect diminishes if partial natural immunity is assumed. Assessments of population-level vaccine effects against endemic infections from clinical trials may be significantly biased, and vaccine and infection characteristics should be considered when modelling outcomes of vaccination programs, as their impact may be dramatic.
-
ItemThe effects of demographic change on disease transmission and vaccine impact in a household structured population(ELSEVIER, 2015-12-01)The demographic structure of populations in both more developed and less developed countries is changing: increases in life expectancy and declining fertility have led to older populations and smaller households. The implications of these demographic changes for the spread and control of infectious diseases are not fully understood. Here we use an individual based model with realistic and dynamic age and household structure to demonstrate the marked effect that demographic change has on disease transmission at the population and household level. The decline in fertility is associated with a decrease in disease incidence and an increase in the age of first infection, even in the absence of vaccination or other control measures. Although large households become rarer as fertility decreases, we show that there is a proportionate increase in incidence of disease in these households as the accumulation of susceptible clusters increases the potential for explosive outbreaks. By modelling vaccination, we provide a direct comparison of the relative importance of demographic change and vaccination on incidence of disease. We highlight the increased risks associated with unvaccinated households in a low fertility setting if vaccine behaviour is correlated with household membership. We suggest that models that do not account for future demographic change, and especially its effect on household structure, may potentially overestimate the impact of vaccination.