Medicine (RMH) - Research Publications
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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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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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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.
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ItemTreatment access is only the first step to hepatitis C elimination: experience of universal anti-viral treatment access in Australia(WILEY, 2019-05)BACKGROUND: Global targets to eliminate hepatitis C (HCV) might be met by sustained treatment uptake. AIM: To describe factors facilitating HCV treatment uptake and potential challenges to sustaining treatment levels after universal access to direct-acting anti-virals (DAA) across Australia. METHODS: We analysed national Pharmaceutical Benefits Scheme data to determine the number of DAA prescriptions commenced before and after universal access from March 2016 to June 2017. We inferred facilitators and barriers to treatment uptake, and challenges that will prevent local and global jurisdictions reaching elimination targets. RESULTS: In 2016, 32 877 individuals (14% of people living with HCV in Australia) commenced HCV DAA treatment, and 34 952 (15%) individuals commenced treatment in the first year of universal access. Treatment uptake peaked at 13 109 DAA commencements per quarter immediately after universal access, but more than halved (to 5320 in 2017 Q2) within 12 months. General practitioners have written 24% of all prescriptions but with a significantly increased proportion over time (9% in 2016 Q1 to 37% in 2017 Q2). In contrast, hepatology or infectious diseases specialists have written a declining share from 74% to 38% during the same period. General practitioners provided a greater proportion (47%) of care in regional/remote areas than major cities. CONCLUSIONS: Broad treatment access led to rapid initial increases in treatment uptake, but this uptake has not been sustained. Our results suggest achieving global elimination targets requires more than treatment availability: people with HCV need easy access to testing and linkage to care in community settings employing a diverse prescriber base.
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ItemSIRCLE: a randomised controlled cost comparison of self-administered short-course isoniazid and rifapentine for cost-effective latent tuberculosis eradication(WILEY, 2017-12)BACKGROUND: Currently, treatment of latent tuberculosis infection (LTBI) in Australia consists most commonly of a 9-month course of isoniazid (9H). A 3-month course of weekly isoniazid and rifapentine (3HP) has been shown to be as effective as 9 months of daily isoniazid, and associated with less hepatotoxicity; however, rifapentine is not currently available in Australia. Introduction of this regimen would have apparent advantages for people with LTBI in Victoria by safely shortening duration of LTBI therapy. However, the cost benefit of this new therapeutic approach is uncertain. AIM: Cost-analysis of standard and short-course therapy for LTBI in an Australian context. METHODS: Single-centre randomised controlled trial conducted between December 2013-March 2016. Participants underwent 1:1 randomisation to either a 9-month course of daily isoniazid or a 12-week course of weekly isoniazid and rifapentine. The primary outcome measure was total healthcare system costs (in Australian dollars; AUD) per completed course of LTBI therapy. Secondary cost analyses were performed to consider varying assumptions regarding commercial cost of rifapentine. RESULTS: Overall, 34 of 40 (85%) participants in the 9H group and 36/40 (90%) in the 3HR group completed therapy. One patient in the 3HP group was hospitalised for a febrile illness; no hospitalisations were recorded in the 9H group. The cost per completed course of 9H was 601 AUD, while that of 3HP was significantly lower at 511 AUD (P < 0.01). CONCLUSIONS: This study provides cost analysis evidence to support the use of 3HP for the treatment of LTBI in Australia.
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ItemThe epidemiology of tuberculosis in the rural Balimo region of Papua New Guinea(WILEY, 2018-09)OBJECTIVE: Papua New Guinea (PNG) has an emerging tuberculosis (TB) epidemic which has become a national public health priority. In Western Province, there are few data about TB outside Daru and the South Fly District. This study describes the epidemiology of TB diagnosed at Balimo District Hospital (BDH) in the Middle Fly District of Western Province, PNG. METHODS: All patients (n = 1614) diagnosed with TB at BDH from April 2013 to February 2017 were recorded. Incidence of reported new cases was calculated for the combined Balimo Urban and Gogodala Rural local level government areas. Analyses investigated patient demographic and clinical information, differences between pulmonary and extrapulmonary TB patients, and predictors of treatment failure. RESULTS: The average case notification rate (2014-2016) was 727 TB cases per 100 000 people per year. One-quarter of TB cases were in children, and 77.1% of all cases had an extrapulmonary TB diagnosis. There was a 1:1.1 ratio of female to male TB cases. When comparing pulmonary and extrapulmonary TB patients, extrapulmonary TB was more likely in those aged up to 14 years and over 54 years. Extrapulmonary TB was more likely in new patients, and pulmonary TB more likely in previously treated patients. Residence in rural regions was associated with treatment failure. CONCLUSION: There is a high burden of TB in the Balimo region, including a very high proportion of extrapulmonary TB. These factors emphasise the importance of BDH as the primary hospital for TB cases in the Balimo region and the Middle Fly District, and the need for resources and staff to manage both drug-susceptible and drug-resistant TB cases.
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ItemIs Nigeria really on top of COVID-19? Message from effective reproduction number( 2020)Following the importation of Covid-19 into Nigeria on the 27 February 2020 and then the outbreak, the question is: how do we anticipate the progression of the ongoing epidemics following all the intervention measures put in place? This kind of question is appropriate for public health responses and it will depend on the early estimates of the key epidemiological parameters of the virus in a defined population. In this study, we combined a likelihood-based method using a Bayesian framework and compartmental model of the epidemic of Covid-19 in Nigeria to estimate the effective reproduction number (R(t)) and basic reproduction number (R_0). This also enables us to estimate the daily transmission rate (β) that determines the effect of social distancing. We further estimate the reported fraction of symptomatic cases. The models are applied to the NCDC data on Covid-19 symptomatic and death cases from 27 February 2020 and 7 May 2020. In this period, the effective reproduction number is estimated with a minimum value of 0.18 and a maximum value of 1.78. Most importantly, the R(t) is strictly greater than one from April 13 till 7 May 2020. The R_0 is estimated to be 2.42 with credible interval: (2.37, 2.47). Comparing this with the R(t) shows that control measures are working but not effective enough to keep R(t) below one. Also, the estimated fractional reported symptomatic cases are between 10 to 50%. Our analysis has shown evidence that the existing control measures are not enough to end the epidemic and more stringent measures are needed.
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ItemFlattening the curve is not enough, we need to squash it: An explainer using a simple model( 2020)
Background
Around the world there are examples of both effective control (e.g., South Korea, Japan) and less successful control (e.g., Italy, Spain, United States) of COVID-19 with dramatic differences in the consequent epidemic curves. Models agree that flattening the curve without controlling the epidemic completely is insufficient and will lead to an overwhelmed health service. A recent model, calibrated for the UK and US, demonstrated this starkly.Methods
We used a simple compartmental deterministic model of COVID-19 transmission in Australia, to illustrate the dynamics resulting from shifting or flattening the curve versus completely squashing it.Results
We find that when the reproduction number is close to one, a small decrease in transmission leads to a large reduction in burden (i.e., cases, deaths and hospitalisations), but achieving this early in the epidemic through social distancing interventions also implies that the community will not reach herd immunity.Conclusions
Australia needs not just to shift and flatten the curve, but to squash it by getting the reproduction number below one. This will require Australia to achieve transmission rates at least two thirds lower than those seen in the most severely affected countries.The known
COVID-19 has been diagnosed in over 4,000 Australians. Up until mid-March, most were from international travel, but now we are seeing a rise in locally acquired cases.The new
This study uses a simple transmission dynamic model to demonstrate the difference between moderate changes to the reproduction number and forcing the reproduction number below one.The implications
Lowering local transmission is becoming important in reducing the transmission of COVID-19. To maintain control of the epidemic, the focus should be on those in the community who do not regard themselves as at risk. -
ItemMethods used in the spatial analysis of tuberculosis epidemiology: a systematic review(BMC, 2018-10-18)BACKGROUND: Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden. METHODS: We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO ( CRD42016036655 ). RESULTS: We identified 168 eligible studies with spatial methods used to describe the spatial distribution (n = 154), spatial clusters (n = 73), predictors of spatial patterns (n = 64), the role of congregate settings (n = 3) and the household (n = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff's spatial scan statistic followed by local Moran's I and Getis and Ord's local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined. CONCLUSIONS: A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control.
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ItemThe role of geospatial hotspots in the spatial spread of tuberculosis in rural Ethiopia: a mathematical model(ROYAL SOC, 2018-09)Geospatial tuberculosis (TB) hotspots are hubs of TB transmission both within and across community groups. We aimed to quantify the extent to which these hotspots account for the spatial spread of TB in a high-burden setting. We developed spatially coupled models to quantify the spread of TB from geographical hotspots to distant regions in rural Ethiopia. The population was divided into three 'patches' based on their proximity to transmission hotspots, namely hotspots, adjacent regions and remote regions. The models were fitted to 5-year notification data aggregated by the metapopulation structure. Model fitting was achieved with a Metropolis-Hastings algorithm using a Poisson likelihood to compare model-estimated notification rate with observed notification rates. A cross-coupled metapopulation model with assortative mixing by region closely fit to notification data as assessed by the deviance information criterion. We estimated 45 hotspot-to-adjacent regions transmission events and 2 hotspot-to-remote regions transmission events occurred for every 1000 hotspot-to-hotspot transmission events. Although the degree of spatial coupling was weak, the proportion of infections in the adjacent region that resulted from mixing with hotspots was high due to the high prevalence of TB cases in a hotspot region, with approximately 75% of infections attributable to hotspot contact. Our results suggest that the role of hotspots in the geospatial spread of TB in rural Ethiopia is limited, implying that TB transmission is primarily locally driven.