Medicine (RMH) - Research Publications
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ItemNo Preview AvailableMathematical analysis of a two-strain disease model with amplification(PERGAMON-ELSEVIER SCIENCE LTD, 2021-02)
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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.
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ItemNo Preview AvailableModeling the Cost-Effectiveness of Latent Tuberculosis Screening and Treatment Strategies in Recent Migrants to a Low-Incidence Setting(OXFORD UNIV PRESS INC, 2022-01-24)Many tuberculosis (TB) cases in low-incidence settings are attributed to reactivation of latent TB infection (LTBI) acquired overseas. We assessed the cost-effectiveness of community-based LTBI screening and treatment strategies in recent migrants to a low-incidence setting (Australia). A decision-analytical Markov model was developed that cycled 1 migrant cohort (≥11-year-olds) annually over a lifetime from 2020. Postmigration/onshore and offshore (screening during visa application) strategies were compared with existing policy (chest x-ray during visa application). Outcomes included TB cases averted and discounted cost per quality-adjusted life-year (QALY) gained from a health-sector perspective. Most recent migrants are young adults and cost-effectiveness is limited by their relatively low LTBI prevalence, low TB mortality risks, and high emigration probability. Onshore strategies cost at least $203,188 (Australian) per QALY gained, preventing approximately 2.3%-7.0% of TB cases in the cohort. Offshore strategies (screening costs incurred by migrants) cost at least $13,907 per QALY gained, preventing 5.5%-16.9% of cases. Findings were most sensitive to the LTBI treatment quality-of-life decrement (further to severe adverse events); with a minimal decrement, all strategies caused more ill health than they prevented. Additional LTBI strategies in recent migrants could only marginally contribute to TB elimination and are unlikely to be cost-effective unless screening costs are borne by migrants and potential LTBI treatment quality-of-life decrements are ignored.
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ItemUnderstanding how Victoria, Australia gained control of its second COVID-19 wave(NATURE PORTFOLIO, 2021-11-01)During 2020, Victoria was the Australian state hardest hit by COVID-19, but was successful in controlling its second wave through aggressive policy interventions. We calibrated a detailed compartmental model of Victoria's second wave to multiple geographically-structured epidemic time-series indicators. We achieved a good fit overall and for individual health services through a combination of time-varying processes, including case detection, population mobility, school closures, physical distancing and face covering usage. Estimates of the risk of death in those aged ≥75 and of hospitalisation were higher than international estimates, reflecting concentration of cases in high-risk settings. We estimated significant effects for each of the calibrated time-varying processes, with estimates for the individual-level effect of physical distancing of 37.4% (95%CrI 7.2-56.4%) and of face coverings of 45.9% (95%CrI 32.9-55.6%). That the multi-faceted interventions led to the dramatic reversal in the epidemic trajectory is supported by our results, with face coverings likely particularly important.
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ItemAre We Better-Off? The Benefits and Costs of Australian COVID-19 Lockdown(FRONTIERS MEDIA SA, 2021-12-02)
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ItemTreatment outcomes in patients with multidrug-resistant tuberculosis in north-west Ethiopia(WILEY, 2017-03)OBJECTIVE: Multidrug-resistant tuberculosis (MDR-TB) is an emerging public health problem in Ethiopia. The aim of this study was to assess MDR-TB treatment outcomes and determine predictors of poor treatment outcomes in north-west Ethiopia. METHODS: A retrospective cohort study was conducted using all MDR-TB patients who were enrolled at Gondar University Hospital since the establishment of the MDR-TB programme in 2010. A Cox proportional hazard model was used to identify the predictors of time to poor treatment outcomes, which were defined as death or treatment failure. RESULTS: Of the 242 patients who had complete records, 131 (54%) were cured, 23 (9%) completed treatment, 31 (13%) died, four (2%) experienced treatment failure, 27 (11%) were lost to follow-up, six (2%) transferred out, and 20 (8%) were still on treatment at the time of analysis. The overall cumulative probability survival of the patients at the end of treatment (which was 24 months in duration) was 80% (95% CI: 70%, 87%). The proportion of patients with poor treatment outcomes increased over time from 6% per person-year (PY) during 2010-2012, to 12% per PY during 2013-2015. The independent predictors of time to poor treatment outcome were being anaemic [AHR = 4.2; 95% CI: 1.1, 15.9] and being a farmer [AHR = 2.2; 95% CI: 1.0, 4.9]. CONCLUSIONS: Overall, in north-west Ethiopia, the MDR-TB treatment success rate was high. However, poor treatment outcomes have gradually increased since 2012. Being a farmer and being anaemic were associated with poor treatment outcomes. It would be beneficial to assess other risk factors that might affect treatment outcomes such as co-infection with malaria, poverty and other socio-economic and biological risk factors.
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ItemNo Preview AvailableVaccines and variants: Modelling insights into emerging issues in COVID-19 epidemiology(ELSEVIER SCI LTD, 2021-09)Mathematical modelling has played a pivotal role in understanding the epidemiology of and guiding public health responses to the ongoing coronavirus disease of 2019 (COVID-19) pandemic. Here, we review the role of epidemiological models in understanding evolving epidemic characteristics, including the effects of vaccination and Variants of Concern (VoC). We highlight ways in which models continue to provide important insights, including (1) calculating the herd immunity threshold and evaluating its limitations; (2) verifying that nascent vaccines can prevent severe disease, infection, and transmission but may be less efficacious against VoC; (3) determining optimal vaccine allocation strategies under efficacy and supply constraints; and (4) determining that VoC are more transmissible and lethal than previously circulating strains, and that immune escape may jeopardize vaccine-induced herd immunity. Finally, we explore how models can help us anticipate and prepare for future stages of COVID-19 epidemiology (and that of other diseases) through forecasts and scenario projections, given current uncertainties and data limitations.
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ItemUnderstanding COVID-19 dynamics and the effects of interventions in the Philippines: A mathematical modelling study(ELSEVIER, 2021-09)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.
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ItemVaccination is Australia's most important COVID-19 public health action, even though herd immunity is unlikely( 2021)The Australian National Cabinet four-step plan to transition to post-pandemic re-opening begins with vaccination to achieve herd protection and protection of the health system against a surge in COVID-19 cases. Assuming a pre-vaccination reproduction number for the Delta variant of 5, we show that for the current Mixed program of vaccinating over 60s with AstraZeneca and 16-60s with Pfizer we would not achieve herd immunity. We would need to cover 85% of the population (including many 5-16 year-olds to achieve herd immunity). At lower reproduction number of 3 and our current Mixed strategy, we can achieve herd immunity without vaccinating 5-15 year olds. This will be achieved at a 60% coverage pursuing a strategy targetting high transmitters or 70% coverage using a strategy targetting the vulnerable first. A reproduction number of 7 precludes achieving herd immunity, however vaccination is able to prevent 75% of deaths compared with no vaccination. We also examine the impact of vaccination on death in the event that herd immunity is not achieved. Direct effects of vaccination on reducing death are very good for both Pfizer and AstraZeneca vaccines. However we estimate that the Mixed or Pfizer program performs better than the AstraZeneca program. Furthermore, vaccination levels below the herd immunity threshold can lead to substantial (albeit incomplete) indirect protection for both vaccinated and unvaccinated populations. Given the potential for not reaching herd immunity, we need to consider what level of severe disease and death is acceptable, balanced against the consequences of ongoing aggressive control strategies.
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ItemRisk factors for multidrug-resistant tuberculosis in northwest Ethiopia: A case-control study(WILEY-HINDAWI, 2019-07)Ethiopia is one of 30-high burden multidrug-resistant tuberculosis (MDR-TB) countries globally. The aim of this study was to describe the characteristics of patients with MDR-TB and to investigate risk factors for MDR-TB relative to having drug-susceptible tuberculosis (TB), in northwest Ethiopia. A hospital-based, unmatched case-control study was conducted. Cases were all MDR-TB patients (i.e., resistant to at least rifampicin and isoniazid) who were confirmed by culture and drug-susceptibility testing whilst enrolled on treatment at Gondar University Hospital. Controls were all drug-susceptible tuberculosis (DS-TB) patients who were confirmed by Gene Xpert MTB/RIF at Gondar University Hospital. Univariable and multivariable logistic regression models were used for comparisons, and odds ratios with 95% confidence intervals (CI) were computed to measure the strength of association between the dependent and independent variables. A total of 452 patients (242 MDR-TB and 210 DS-TB) were included in this study. The mean age of the study participants was 33 years (SD ± 14 years). Approximately one-fifth (78, 17%) of all study participants were human immunodeficiency virus (HIV) positive; 21% (51) of cases and 13% (27) of controls. Risk factors associated with MDR-TB were a history of previous TB treatment (Adjusted Odds Ratio (AOR): 83.8; 95% CI: 40.7, 172.5), low educational status (AOR: 5.32; 95% CI: 1.43, 19.81); and ages less than 20 years (AOR: 9.01; 95% CI: 2.30, 35.25) and 21-30 years (AOR: 2.61; 95% CI: 1.02, 6.64). HIV infection was also significantly associated with MDR-TB among new TB patients (AOR: 5.55; 95% CI: 1.17, 26.20). This study shows that clinical and demographic features can be used to indicate higher risks of drug resistance in this setting.