H Johnson

Inference of Type-Specific HPV Transmissibility, Progression and Clearance Rates: A Mathematical Modelling Approach.

Quantifying rates governing the clearance of Human Papillomavirus (HPV) and its progression to clinical disease, together with viral transmissibility and the duration of naturally-acquired immunity, is essential in estimating the impact of vaccination programmes and screening or testing regimes. However, the complex natural history of HPV makes this difficult. We infer the viral transmissibility, rate of waning natural immunity and rates of progression and clearance of infection of 13 high-risk and 2 non-oncogenic HPV types, making use of a number of rich datasets from Sweden. Estimates of viral transmissibility, clearance of initial infection and waning immunity were derived in a Bayesian framework by fitting a susceptible-infectious-recovered-susceptible (SIRS) transmission model to age- and type-specific HPV prevalence data from both a cross-sectional study and a randomised controlled trial (RCT) of primary HPV screening. The models fitted well, but over-estimated the prevalence of four high-risk types with respect to the data. Three of these types (HPV-33, -35 and -58) are among the most closely related phylogenetically to the most prevalent HPV-16. The fourth (HPV-45) is the most closely related to HPV-18; the second most prevalent type. We suggest that this may be an indicator of cross-immunity. Rates of progression and clearance of clinical lesions were additionally estimated from longitudinal data gathered as part of the same RCT. Our estimates of progression and clearance rates are consistent with the findings of survival analysis studies and we extend the literature by estimating progression and clearance rates for non-16 and non-18 high-risk types. We anticipate that such type-specific estimates will be useful in the parameterisation of further models and in developing our understanding of HPV natural history.

Quantifying Parameter and Structural Uncertainty of Dynamic Disease Transmission Models Using MCMC: An Application to Rotavirus Vaccination in England and Wales.

Background. Two vaccines (Rotarix and RotaTeq) are highly effective at preventing severe rotavirus disease. Rotavirus vaccination has been introduced in the United Kingdom and other countries partly based on modeling and cost-effectiveness results. However, most of these models fail to account for the uncertainty about several vaccine characteristics and the mechanism of vaccine action. Methods. A deterministic dynamic transmission model of rotavirus vaccination in the United Kingdom was developed. This improves on previous models by 1) allowing for 2 different mechanisms of action for Rotarix and RotaTeq, 2) using clinical trial data to understand these mechanisms, and 3) accounting for uncertainty by using Markov Chain Monte Carlo. Results. In the long run, Rotarix and RotaTeq are predicted to reduce the overall rotavirus incidence by 50% (39%−63%) and 44% (30%−62%), respectively but with an increase in incidence in primary school children and adults up to 25 y of age. The vaccines are estimated to give more protection than 1 or 2 natural infections. The duration of protection is highly uncertain but has only impact on the predicted reduction in rotavirus burden for values lower than 10 y. The 2 vaccine mechanism structures fit equally well with the clinical trial data. Long-term postvaccination dynamics cannot be predicted reliably with the data available. Conclusion. Accounting for the joint uncertainty of several vaccine characteristics resulted in more insight into which of these are crucial for determining the impact of rotavirus vaccination. Data for up to at least 10 y postvaccination and covering older children and adults are crucial to address remaining questions on the impact of widespread rotavirus vaccination.

Who mixes with whom among men who have sex with men? Implications for modelling the HIV epidemic in southern India

In India, the identity of men who have sex with men (MSM) is closely related to the role taken in anal sex (insertive, receptive or both), but little is known about sexual mixing between identity groups. Both role segregation (taking only the insertive or receptive role) and the extent of assortative (within-group) mixing are known to affect HIV epidemic size in other settings and populations. This study explores how different possible mixing scenarios, consistent with behavioural data collected in Bangalore, south India, affect both the HIV epidemic, and the impact of a targeted intervention. Deterministic models describing HIV transmission between three MSM identity groups (mostly insertive Panthis/Bisexuals, mostly receptive Kothis/Hijras and versatile Double Deckers), were parameterised with behavioural data from Bangalore. We extended previous models of MSM role segregation to allow each of the identity groups to have both insertive and receptive acts, in differing ratios, in line with field data. The models were used to explore four different mixing scenarios ranging from assortative (maximising within-group mixing) to disassortative (minimising within-group mixing). A simple model was used to obtain insights into the relationship between the degree of within-group mixing, R0 and equilibrium HIV prevalence under different mixing scenarios. A more complex, extended version of the model was used to compare the predicted HIV prevalence trends and impact of an HIV intervention when fitted to data from Bangalore. With the simple model, mixing scenarios with increased amounts of assortative (within-group) mixing tended to give rise to a higher R0 and increased the likelihood that an epidemic would occur. When the complex model was fit to HIV prevalence data, large differences in the level of assortative mixing were seen between the fits identified using different mixing scenarios, but little difference was projected in future HIV prevalence trends. An oral pre-exposure prophylaxis (PrEP) intervention was modelled, targeted at the different identity groups. For intervention strategies targeting the receptive or receptive and versatile MSM together, the overall impact was very similar for different mixing patterns. However, for PrEP scenarios targeting insertive or versatile MSM alone, the overall impact varied considerably for different mixing scenarios; more impact was achieved with greater levels of disassortative mixing.

Effect of HPV vaccination and cervical cancer screening in England by ethnicity: a modelling study

Summary Background Health equality is increasingly being considered alongside overall health gain when assessing public health interventions. However, the trade-off between the direct effects of vaccination and herd immunity could lead to unintuitive consequences for the distribution of disease burden within a population. We used a transmission dynamic model of human papillomavirus (HPV) to investigate the effect of ethnic disparities in vaccine and cervical screening uptake on inequality in disease incidence in England. Methods We developed an individual-based model of HPV transmission and disease, parameterising it with the latest data for sexual behaviour (from National Survey of Sexual Attitudes and Lifestyles [Natsal-3]) and vaccine and screening uptake by ethnicity (from Public Health England [PHE]) and fitting it to data for HPV prevalence (from ARTISTIC, PHE, Natsal-3) and HPV-related disease incidence (from National Cancer Registry [ONS]). The outcome of interest was the age-adjusted incidence of HPV-related cancer (both cervical and non-cervical) in all women in England in view of differences and changes in vaccination and screening uptake by ethnicity in England, over time. We also studied three potential public health interventions aimed at reducing inequality in HPV-related disease incidence: increasing uptake in black and Asian females to match that in whites for vaccination; cervical screening in women who turn 25 in 2018 or later; and cervical screening in all ages. Findings In the pre-vaccination era, before 2008, women from ethnic minorities in England reported a disproportionate share of cervical disease. Our model suggests that Asian women were 1·7 times (95% credibility interval [CI] 1·1–2·7) more likely to be diagnosed with cervical cancer than white women (22·8 vs 13·4 cases per 100 000 women). Because HPV vaccination uptake is lower in ethnic minorities, we predict an initial widening of this gap, with cervical cancer incidence in Asian women up to 2·5 times higher (95% CI 1·3–4·8) than in white women 20 years after vaccine introduction (corresponding to an additional 10·8 [95% CI 10·1–11·5] cases every year). In time, we predict that herd immunity benefits will diffuse from the larger white sub-population and the disparity will narrow. Increased cervical screening uptake in vaccinated women from ethnic minorities would lead to rapid improvement in equality with parity in incidence after 20 years of HPV vaccination. Interpretation Our study suggests that the introduction of HPV vaccination in England will initially widen a pre-existing disparity in the incidence of HPV-related cancer by ethnicity, partly due to herd immunity disproportionately benefiting subgroups with high vaccination rates. Although in time this induced disparity will narrow, increasing cervical screening uptake in girls from ethnic minorities should be encouraged to eliminate the inequality in cervical cancer incidence in the medium term. We recommend that dynamic effects should be considered when estimating the effect of public health programmes on equality. Funding Cancer Research UK.

P1-S4.21 Calibration of an individual-based model of STI transmission in Uganda: a novel ABC-Bayesian Emulation hybrid approach

Introduction The complexity of dynamic epidemic systems has led to the use of large-scale stochastic models for prediction purposes. However, methods for robustly calibrating and analysing these models can be prohibitively inefficient. We propose an algorithm for fitting complex models that incorporates elements of both Approximate Bayesian Computation (ABC) and Bayesian Emulation. ABC enables inference about model parameters without needing to calculate a likelihood function, by generating approximations from repeated model runs. However, each model run might take hours. Emulation methods are being developed in the fields of cosmology and meteorological modelling. The complex model function is summarised as an “emulator”: a stochastic function that represents global behaviour of the function as a linear regression model and local deviations from this behaviour as Gaussian processes. The emulator acts as a cheap proxy for the complex model, allowing both calibration and sensitivity analysis to be conducted in a fraction of the time. Methods We report the initial application of an emulation-based calibration algorithm to an individual-based stochastic model of STI transmission in Uganda. Starting with uninformative priors for 19 behavioural and biological input parameters, we “trained” an emulator with 200 sampled parameter sets and their corresponding model output (point estimates of HIV prevalence). Sampling a further 10 000 parameter sets from the priors, we used the emulator to make output predictions over a large area of input parameter space. Weighting each parameter set by goodness of fit to observed data, we identified promising areas of parameter space for complex model evaluation. A more accurate emulator was then trained, incorporating this additional complex model output. The process was repeated as in sequential ABC methods. Results The use of emulators allowed evaluation of large areas of parameter space due to increased computational efficiency. Processing time for one prevalence point estimate was reduced from over 15 min on an HPC cluster to less than 0.1 s on a PC. Even the first two waves of such an algorithm provided helpful insight into the most influential parameters. Conclusions The development of an ABC—Bayesian Emulation hybrid approach to complex model calibration is promising. Emulators offer large advantages in computational efficiency. However, further research is needed regarding weighting, tolerance levels and covariance.

P1-S4.24 Balancing the “supply and demand” of sex acts: implications for modelling the HIV epidemic among men who have sex with men in Southern India

Background In India, men who have sex with men (MSM) have distinct identities related to the role taken in anal sex (Panthi/Bisexual (PB): mostly insertive, Kothi/Hijra (KH): mostly receptive, Double Deckers: both). Wide discrepancies are found between the supply and demand for sex acts estimated for each group using data on reported frequency of anal sex, role taken and estimated group population sizes. Methods Two methods for balancing the number and type of sex acts between different groups were compared. They were used in a deterministic HIV transmission model to estimate mixing patterns and HIV prevalence over the first 20 years of the epidemic (including reported condom use trends) and a subsequent 10-year intervention (10% absolute increase in condom use). Data collected from Bangalore for the evaluation of Avahan (the India AIDS initiative) on the mean reported frequency of sex acts per individual, role taken in anal sex and population sizes for each group were used to construct a mixing matrix. In method A, the PB group size was set to balance the total number of insertive and receptive acts, and receptive acts for each group were distributed among the three groups in proportion to the number of insertive acts offered. In method B, the proportion of receptive acts KH had with other KH was an additional input parameter, with remaining receptive acts distributed as in method A. The number and type of contacts for all groups were adjusted to achieve balancing. The model was run using 300 000 randomly sampled parameter sets drawn from the data and multiple fits were found to group-specific HIV prevalence data. Results Model fits for method B had more assortative (like-with-like) mixing than method A, particularly for PB (median number of acts PB have with other PB: 48.5% (IQR 33.3–63.3%) in A, 63.3% (IQR 47.3–74.1%) in B), related to larger PB group sizes and PB taking the insertive role less often in B. Despite these differences, the fitted epidemic curves were very similar for all three groups across the two methods (Absrtact P1-S4.24 figure 1), as was the predicted intervention impact (relative reduction in MSM HIV prevalence after 10 years: A: 18.2% (95% CI 11.0 to 29.2%), B: 18.1% (10.6 to 29.7%)). Conclusions The choice of method used to balance insertive and receptive contacts in an HIV transmission model affected the estimates for the amount of like-with-like mixing within different MSM groups, but the estimated impact of an intervention was robust to the method used. Abstract P1-S4.24 Figure 1 MSM.