A systematic review of scabies transmission models and data to evaluate the cost-effectiveness of scabies interventions.

BACKGROUND: Scabies is a common dermatological condition, affecting more than 130 million people at any time. To evaluate and/or predict the effectiveness and cost-effectiveness of scabies interventions, disease transmission modelling can be used. OBJECTIVE: To review published scabies models and data to inform the design of a comprehensive scabies transmission modelling framework to evaluate the cost-effectiveness of scabies interventions. METHODS: Systematic literature search in PubMed, Medline, Embase, CINAHL, and the Cochrane Library identified scabies studies published since the year 2000. Selected papers included modelling studies and studies on the life cycle of scabies mites, patient quality of life and resource use. Reference lists of reviews were used to identify any papers missed through the search strategy. Strengths and limitations of identified scabies models were evaluated and used to design a modelling framework. Potential model inputs were identified and discussed. FINDINGS: Four scabies models were published: a Markov decision tree, two compartmental models, and an agent-based, network-dependent Monte Carlo model. None of the models specifically addressed crusted scabies, which is associated with high morbidity, mortality, and increased transmission. There is a lack of reliable, comprehensive information about scabies biology and the impact this disease has on patients and society. DISCUSSION: Clinicians and health economists working in the field of scabies are encouraged to use the current review to inform disease transmission modelling and economic evaluations on interventions against scabies.

Targeted human papillomavirus vaccination for young men who have sex with men in Australia yields significant population benefits and is cost-effective.

BACKGROUND: We investigated the effectiveness and cost-effectiveness of a targeted human papillomavirus (HPV) vaccination program for young (15-26) men who have sex with men (MSM). METHODS: We developed a compartmental model to project HPV epidemic trajectories in MSM for three vaccination scenarios: a boys program, a targeted program for young MSM only and the combination of the two over 2017-2036. We assessed the gain in quality-adjusted-life-years (QALY) in 190,000 Australian MSM. RESULTS: A targeted program for young MSM only that achieved 20% coverage per year, without a boys program, will prevent 49,283 (31,253-71,500) cases of anogenital warts, 191 (88-319) person-years living with anal cancer through 2017-2036 but will only stablise anal cancer incidence. In contrast, a boys program will prevent 82,056 (52,100-117,164) cases of anogenital warts, 447 (204-725) person-years living with anal cancers through 2017-2036 and see major declines in anal cancer. This can reduce 90% low- and high-risk HPV in young MSM by 2024 and 2032, respectively, but will require vaccinating ≥84% of boys. Adding a targeted program for young MSM to an existing boys program would prevent an additional 14,912 (8479-21,803) anogenital wart and 91 (42-152) person-years living with anal cancer. In combination with a boys' program, a catch-up program for young MSM will cost an additional $AUD 6788 ($4628-11,989) per QALY gained, but delaying its implementation reduced its cost-effectiveness. CONCLUSIONS: A boys program that achieved coverage of about 84% will result in a 90% reduction in HPV. A targeted program for young MSM is cost-effective if timely implemented.

A randomised trial of point-of-care tests for chlamydia and gonorrhoea infections in remote Aboriginal communities: Test, Treat ANd GO- the "TTANGO" trial protocol.

BACKGROUND: High prevalence rates of Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) have been reported in Aboriginal people in remote and regional areas of Australia for well over two decades, and repeat positivity rates are high. To interrupt disease transmission and reduce the risk of complications, early diagnosis and treatment is important. However in many remote and regional areas there are long delays between testing for these curable sexually transmissible infections and providing treatment, due to both physical distance from laboratories and difficulties when recalling patients for subsequent management once results are available. Point-of-care (POC) tests have the potential to provide more timely diagnosis, to increase treatment and contact tracing, and in turn reduce CT and NG infection rates. METHODS/DESIGN: TTANGO (Test, Treat, ANd GO) is a cross-over cluster randomised controlled trial in 12 regional or remote Australian health services, which predominantly provide clinical services to Aboriginal people. The overall aim of TTANGO is to measure the clinical effectiveness, cost-effectiveness and cultural and operational acceptability of molecular POC testing for CT and NG infection. The primary outcome is repeat positivity at three months after treatment of an initial CT or NG infection. Participating health services will undertake the clinical management of CT and NG under two different modalities for one year each. In the first year, six health services will be randomly assigned to manage these infections under current diagnostic guidelines. The other six will supplement current diagnostic guidelines with POC testing, whereby diagnosis is made and subsequent treatment for those with positive POC tests is offered at the initial consultation. In the second year, the health services will cross over to the opposite management modality. TTANGO will be conducted over four years; 1.5 years of trial initiation and community consultation, 2 years of trial conditions and evaluation, and 6 months of data analysis and feedback. DISCUSSION: TTANGO is the first cluster randomised trial of POC testing for CT and NG internationally. The results of this trial will provide crucial information to guide sexual health clinical practice in remote Aboriginal communities and other high prevalence settings. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTRN12613000808741.

Herd immunity effect of the HPV vaccination program in Australia under different assumptions regarding natural immunity against re-infection.

Deterministic dynamic compartmental transmission models (DDCTMs) of human papillomavirus (HPV) transmission have been used in a number of studies to estimate the potential impact of HPV vaccination programs. In most cases, the models were built under the assumption that an individual who cleared HPV infection develops (life-long) natural immunity against re-infection with the same HPV type (this is known as SIR scenario). This assumption was also made by two Australian modelling studies evaluating the impact of the National HPV Vaccination Program to assist in the health-economic assessment of male vaccination. An alternative view denying natural immunity after clearance (SIS scenario) was only presented in one study, although neither scenario has been supported by strong evidence. Some recent findings, however, provide arguments in favour of SIS. We developed HPV transmission models implementing life-time (SIR), limited, and non-existent (SIS) natural immunity. For each model we estimated the herd immunity effect of the ongoing Australian HPV vaccination program and its extension to cover males. Given the Australian setting, we aimed to clarify the extent to which the choice of model structure would influence estimation of this effect. A statistically robust and efficient calibration methodology was applied to ensure credibility of our results. We observed that for non-SIR models the herd immunity effect measured in relative reductions in HPV prevalence in the unvaccinated population was much more pronounced than for the SIR model. For example, with vaccine efficacy of 95% for females and 90% for males, the reductions for HPV-16 were 3% in females and 28% in males for the SIR model, and at least 30% (females) and 60% (males) for non-SIR models. The magnitude of these differences implies that evaluations of the impact of vaccination programs using DDCTMs should incorporate several model structures until our understanding of natural immunity is improved.

Adaptive Markov chain Monte Carlo forward projection for statistical analysis in epidemic modelling of human papillomavirus.

A Bayesian statistical model and estimation methodology based on forward projection adaptive Markov chain Monte Carlo is developed in order to perform the calibration of a high-dimensional nonlinear system of ordinary differential equations representing an epidemic model for human papillomavirus types 6 and 11 (HPV-6, HPV-11). The model is compartmental and involves stratification by age, gender and sexual-activity group. Developing this model and a means to calibrate it efficiently is relevant because HPV is a very multi-typed and common sexually transmitted infection with more than 100 types currently known. The two types studied in this paper, types 6 and 11, are causing about 90% of anogenital warts. We extend the development of a sexual mixing matrix on the basis of a formulation first suggested by Garnett and Anderson, frequently used to model sexually transmitted infections. In particular, we consider a stochastic mixing matrix framework that allows us to jointly estimate unknown attributes and parameters of the mixing matrix along with the parameters involved in the calibration of the HPV epidemic model. This matrix describes the sexual interactions between members of the population under study and relies on several quantities that are a priori unknown. The Bayesian model developed allows one to estimate jointly the HPV-6 and HPV-11 epidemic model parameters as well as unknown sexual mixing matrix parameters related to assortativity. Finally, we explore the ability of an extension to the class of adaptive Markov chain Monte Carlo algorithms to incorporate a forward projection strategy for the ordinary differential equation state trajectories. Efficient exploration of the Bayesian posterior distribution developed for the ordinary differential equation parameters provides a challenge for any Markov chain sampling methodology, hence the interest in adaptive Markov chain methods. We conclude with simulation studies on synthetic and recent actual data.

Geographical clustering of anal cancer incidence in Australia.

INTRODUCTION: Homosexual men are at an increased risk of anal cancer. We aimed to establish the burden of anal squamous cell carcinoma (SCC) in those parts of Australia where homosexual men are most likely to live. METHODS: Data on the proportion of homosexual male residents were obtained from published estimates. Men were categorised into three postcode groups by prevalence of men reporting homosexual identity. Male population data in age groups were extracted for each postcode group and analyses of cancer incidence were performed by postcode group. The analyses were restricted to 2000-2005. RESULTS: Eight postcodes had populations where more than 10% of males reported homosexual identity (high prevalence) and 4-10% of men reported homosexual activity in a further 19 postcodes (medium prevalence). From 2000 to 2005, the average annual age-standardised incidence rates of anal SCC in males was 7.61 per 100000 (95% confidence interval (CI): 4.68-10.55) and 2.21 per 100000 (95% CI: 1.05-3.37) in high and medium prevalence postcodes, respectively. The corresponding incidence rate ratios compared with low prevalence postcodes (less than 4% of males reported homosexual identity) were 9.6 (95% CI: 6.6-14.1) for the high prevalence and 2.4 (95% CI: 1.4-4.1) for the medium prevalence postcodes. CONCLUSION: A substantial concentration of the burden of anal cancer occurred among areas where large proportions of homosexual men reside. These results should guide the prioritisation of health service investment in anal cancer treatment and prevention to appropriate geographical areas.

Tracking type specific prevalence of human papillomavirus in cervical pre-cancer: a novel sampling strategy.

BACKGROUND: Surveillance designed to detect changes in the type-specific distribution of HPV in cervical intraepithelial neoplasia grade 3 (CIN-3) is necessary to evaluate the effectiveness of the Australian vaccination programme on cancer causing HPV types. This paper develops a protocol that eliminates the need to calculate required sample size; sample size is difficult to calculate in advance because HPV's true type-specific prevalence is imperfectly known. METHOD: A truncated sequential sampling plan that collects a variable sample size was designed to detect changes in the type-specific distribution of HPV in CIN-3. Computer simulation to evaluate the accuracy of the plan at classifying the prevalence of an HPV type as low (< 5%), moderate (5-15%), or high (> 15%) and the average sample size collected was conducted and used to assess its appropriateness as a surveillance tool. RESULTS: The plan classified the proportion of CIN-3 lesions positive for an HPV type very accurately, with >90% of simulations correctly classifying a simulated data-set with known prevalence. Misclassifying an HPV type of high prevalence as being of low prevalence, arguably the most serious kind of potential error, occurred < 0.05 times per 100 simulations. A much lower sample size (21-22 versus 40-48) was required to classify samples of high rather than low or moderate prevalence. CONCLUSIONS: Truncated sequential sampling enables the proportion of CIN-3 due to an HPV type to be accurately classified using small sample sizes. Truncated sequential sampling should be used for type-specific HPV surveillance in the vaccination era.

Modelling the population-level impact of vaccination on the transmission of human papillomavirus type 16 in Australia.

BACKGROUND: Vaccines are now available to prevent the development of cervical cancer from genital human papillomavirus (HPV) infection. The decision to vaccinate depends on a vaccine's cost-effectiveness. A rigorous cost-effectiveness model for vaccinated individuals is presented in a companion paper; this paper investigates the additional benefits the community might receive from herd immunity. METHODS: A mathematical model was developed to estimate the impact of a prophylactic vaccine on transmission of HPV type 16 in Australia. The model was used to estimate the expected reduction in HPV incidence and prevalence as a result of vaccination, the time required to achieve these reductions, and the coverage required for elimination. The modelled population was stratified according to age, gender, level of sexual activity and HPV infection status using a differential equation formulation. Clinical trials show that the vaccine is highly effective at preventing persistent infection and pre-cancerous lesions. These trials do not, however, provide conclusive evidence that infection is prevented altogether. The possible modes of vaccine action were investigated to see how vaccination might change the conclusions. RESULTS: The model predicts that vaccination of 80% of 12-year-old girls will eventually reduce HPV 16 prevalence by 60-100% in vaccinated and 7-31% in unvaccinated females. If 80% of boys are also vaccinated, reductions will be 74-100% in vaccinated and 86-96% in unvaccinated females. A campaign covering only 12-year-old girls would require 5-7 years to achieve 50% of the eventual reduction. With a catch-up campaign covering 13-26-year-olds, this delay would be reduced to only 2 years. Unrealistically high coverage in both sexes would be required to eliminate HPV 16 from the population. Under pessimistic assumptions about the duration of vaccine-conferred immunity, HPV 16 incidence is predicted to rise in some older age groups. CONCLUSIONS: Mass vaccination with a highly effective vaccine against HPV 16 has the potential to substantially reduce the incidence and prevalence of infection. Catch-up vaccination offers the potential to substantially reduce the delay before the benefits of vaccination are observed. A booster vaccination might be required to prevent an increase in incidence of infection in women over 25 years of age.

A cost-effectiveness analysis of adding a human papillomavirus vaccine to the Australian National Cervical Cancer Screening Program.

BACKGROUND: The cost-effectiveness of adding a human papillomavirus (HPV) vaccine to the Australian National Cervical Screening Program compared to screening alone was examined. METHODS: A Markov model of the natural history of HPV infection that incorporates screening and vaccination was developed. A vaccine that prevents 100% of HPV 16/18-associated disease, with a lifetime duration of efficacy and 80% coverage offered through a school program to girls aged 12 years, in conjunction with current screening was compared with screening alone using cost (in Australian dollars) per life-year (LY) saved and quality-adjusted life-year (QALY) saved. Sensitivity analyses included determining the cost-effectiveness of offering a catch-up vaccination program to 14-26-year-olds and accounting for the benefits of herd immunity. RESULTS: Vaccination with screening compared with screening alone was associated with an incremental cost-effectiveness ratio (ICER) of $51 103 per LY and $18 735 per QALY, assuming a cost per vaccine dose of $115. Results were sensitive to assumptions about the duration of vaccine efficacy, including the need for a booster ($68 158 per LY and $24 988 per QALY) to produce lifetime immunity. Accounting for herd immunity resulted in a more attractive ICER ($36 343 per LY and $13 316 per QALY) for girls only. The cost per LY of vaccinating boys and girls was $92 052 and the cost per QALY was $33 644. The cost per LY of implementing a catch-up vaccination program ranged from $45 652 ($16 727 per QALY) for extending vaccination to 14-year-olds to $78 702 ($34 536 per QALY) for 26-year-olds. CONCLUSIONS: These results suggest that adding an HPV vaccine to Australia's current screening regimen is a potentially cost-effective way to reduce cervical cancer and the clinical interventions that are currently associated with its prevention via screening alone.

Measurement of compartment size in q-space experiments: Fourier transform of the second derivative.

Restricted diffusion in compartmentalized systems can lead to spatial coherence phenomena being observed in q-space plots from pulsed field gradient spin-echo (PGSE) nuclear magnetic resonance (NMR) experiments. The underlying features observed in these plots contain information on the geometry of the compartments that is otherwise difficult to obtain. A numerical procedure is proposed that accentuates these coherence features: the data are weighted with a bell-shaped window function, interpolated with a shifting cubic spline, and then the second derivative is taken prior to Fourier transformation. The window function provides apodization of the noisy data at high q values, while it and the second derivative are equivalent to applying a high-pass filter to remove the zero- or low-frequency components in the echo-signal attenuation. Using a combination of theory, Monte Carlo simulations, and data from PGSE NMR experiments on human red blood cells, we demonstrate this to be a valuable processing tool for delineating the underlying coherence features. It should prove particularly useful where the coherence features are poorly defined or where more than one pattern is present in a q-space plot.

Simulations of NMR-detected diffusion in suspensions of red cells: the effects of variation in membrane permeability and observation time.

Monte Carlo random-walk simulations of diffusion in virtual lattices of cells have been used to study and characterize diffusion-coherence phenomena that arise when pulsed field-gradient spin-echo (PGSE) nuclear magnetic resonance (NMR) experiments are conducted on human red blood cell (RBC; erythrocytes) suspensions. These coherence effects are manifest as diffraction-like patterns when the normalized PGSE signal intensities are plotted as a function of the spatial wave vector q in so-called q-space plots. q-Space analysis is sensitive to small changes in cell morphology, cell size, membrane transport rates, hematocrit, and packing arrangement. In the present study we used simulations to predict the effect of varying the time over which diffusion is measured (the "observation time" or "diffusion time") and the permeability of the membrane on the form of q-space plots. Thus we predict that inhibiting water exchange across the human RBC membrane, such that the value of the permeability coefficient is reduced by approximately an order of magnitude below the normal physiological value, will effectively render the membrane impermeable on the timescale of the PGSE NMR experiment; further inhibition will therefore result in negligible reduction in the measured root-mean-square displacement (r.m.s.d.) of diffusing water as a function of the observation time. The work also underscores the importance of using an appropriate experimental observation time if q-space data are to be used to estimate compartment dimensions and interbarrier spacing, and illustrates an expeditious method for determining this value.

Simulations of molecular diffusion in lattices of cells: insights for NMR of red blood cells.

The pulsed field-gradient spin-echo (PGSE) nuclear magnetic resonance (NMR) experiment, conducted on a suspension of red blood cells (RBC) in a strong magnetic field yields a q-space plot consisting of a series of maxima and minima. This is mathematically analogous to a classical optical diffraction pattern. The method provides a noninvasive and novel means of characterizing cell suspensions that is sensitive to changes in cell shape and packing density. The positions of the features in a q-space plot characterize the rate of exchange across the membrane, cell dimensions, and packing density. A diffusion tensor, containing information regarding the diffusion anisotropy of the system, can also be derived from the PGSE NMR data. In this study, we carried out Monte Carlo simulations of diffusion in suspensions of "virtual" cells that had either biconcave disc (as in RBC) or oblate spheroid geometry. The simulations were performed in a PGSE NMR context thus enabling predictions of q-space and diffusion tensor data. The simulated data were compared with those from real PGSE NMR diffusion experiments on RBC suspensions that had a range of hematocrit values. Methods that facilitate the processing of q-space data were also developed.