Health and economic effects of introducing single-dose or two-dose human papillomavirus vaccination in India.

BACKGROUND: Cervical cancer is a major public health problem in India, where access to prevention programmes is low. The WHO-Strategic Advisory Group of Experts recently updated their recommendation for human papillomavirus (HPV) vaccination to include a single-dose option in addition to the two-dose option, which could make HPV vaccination programmes easier to implement and more affordable. METHODS: We combined projections from a type-specific HPV transmission model and a cancer progression model to assess the health and economic effects of HPV vaccination at national and state level in India. The models used national and state-specific Indian demographic, epidemiological and cost data, and single-dose vaccine efficacy and immunogenicity data from the International Agency for Research on Cancer India vaccine trial with 10-year follow-up. We compared single-dose and two-dose HPV vaccination for a range of plausible scenarios regarding single-dose vaccine protection, coverage and catch-up. We used a healthcare sector payer perspective with a time horizon of 100 years. RESULTS: Under the base-case scenario of lifelong protection of single-dose vaccination in 10-year-old girls with 90% coverage, the discounted incremental cost-effectiveness ratio (ICER) of nationwide vaccination relative to no vaccination was US$406 (₹INR30 000) per DALY (disability-adjusted life-years) averted. This lay below an opportunity-cost-based threshold of 30% Indian gross domestic product per capita in each Indian state (state-specific ICER range: US$67-US$593 per DALY averted). The ICER of two-dose vaccination versus no vaccination vaccination was US$1404 (₹INR104 000). The ICER of two-dose vaccination versus single-dose vaccination, assuming lower initial efficacy and waning of single-dose vaccination, was at least US$2282 (₹INR169 000) per DALY averted. CONCLUSIONS: Nationwide introduction of single-dose HPV vaccination at age 10 in India is highly likely to be cost-effective whereas extending the number of doses from one to two would have a less favourable profile.

Reconstructing multi-strain pathogen interactions from cross-sectional survey data via statistical network inference.

Infectious diseases often involve multiple pathogen species or multiple strains of the same pathogen. As such, knowledge of how different pathogens interact is key to understand and predict the outcome of interventions targeting only a subset of species or strains involved in disease. Population-level data may be useful to infer pathogen strain interactions, but most previously used inference methods only consider uniform interactions between all strains or focus on marginal pairwise interactions. As such, these methods are prone to bias induced by indirect interactions through other strains. Here, we evaluated statistical network inference for reconstructing heterogeneous interactions from cross-sectional surveys detecting joint presence/absence patterns of pathogen strains within hosts. We applied various network models to simulated survey data, representing endemic infection states of multiple pathogen strains with potential interactions in acquisition or clearance of infection. Satisfactory performance was demonstrated by the estimators converging to the true interactions. Accurate reconstruction of interaction networks was achieved by regularization or penalization for sample size. Although performance deteriorated in the presence of host heterogeneity, this was overcome by correcting for individual-level risk factors. Our work demonstrates how statistical network inference could prove useful for detecting multi-strain pathogen interactions and may have applications beyond epidemiology.

Building resilient cervical cancer prevention through gender-neutral HPV vaccination.

The COVID-19 pandemic has disrupted HPV vaccination programmes worldwide. Using an agent-based model, EpiMetHeos, recently calibrated to Indian data, we illustrate how shifting from a girls-only (GO) to a gender-neutral (GN) vaccination strategy could improve the resilience of cervical cancer prevention against disruption of HPV vaccination. In the base case of 5-year disruption with no coverage, shifting from GO to GN strategy under 60% coverage (before disruption) would increase the resilience, in terms of cervical cancer cases still prevented in the disrupted birth cohorts per 100,000 girls born, by 2.8-fold from 107 to 302 cases, and by 2.2-fold from 209 to 464 cases under 90% coverage. Furthermore, shifting to GN vaccination helped in reaching the World Health Organization (WHO) elimination threshold. Under GO vaccination with 60% coverage, the age-standardised incidence rate of cervical cancer in India in the long term with vaccination decreased from 11.0 to 4.7 cases per 100,000 woman-years (above threshold), as compared to 2.8 cases (below threshold) under GN with 60% coverage and 2.4 cases (below threshold) under GN with 90% coverage. In conclusion, GN HPV vaccination is an effective strategy to improve the resilience to disruption of cancer prevention programmes and to enhance the progress towards cervical cancer elimination.

Approximating missing epidemiological data for cervical cancer through Footprinting: A case study in India.

Local cervical cancer epidemiological data essential to project the context-specific impact of cervical cancer preventive measures are often missing. We developed a framework, hereafter named Footprinting, to approximate missing data on sexual behaviour, human papillomavirus (HPV) prevalence, or cervical cancer incidence, and applied it to an Indian case study. With our framework, we (1) identified clusters of Indian states with similar cervical cancer incidence patterns, (2) classified states without incidence data to the identified clusters based on similarity in sexual behaviour, (3) approximated missing cervical cancer incidence and HPV prevalence data based on available data within each cluster. Two main patterns of cervical cancer incidence, characterized by high and low incidence, were identified. Based on the patterns in the sexual behaviour data, all Indian states with missing data on cervical cancer incidence were classified to the low-incidence cluster. Finally, missing data on cervical cancer incidence and HPV prevalence were approximated based on the mean of the available data within each cluster. With the Footprinting framework, we approximated missing cervical cancer epidemiological data and made context-specific impact projections for cervical cancer preventive measures, to assist public health decisions on cervical cancer prevention in India and other countries.

Evidence-based impact projections of single-dose human papillomavirus vaccination in India: a modelling study.

BACKGROUND: Despite the high burden of cervical cancer, access to preventive measures remains low in India. A single-dose immunisation schedule could facilitate the scale-up of human papillomavirus (HPV) vaccination, contributing to global elimination of cervical cancer. We projected the effect of single-dose quadrivalent HPV vaccination in India in comparison with no vaccination or to a two-dose schedule. METHODS: In this modelling study, we adapted an HPV transmission model (EpiMetHeos) to Indian data on sexual behaviour (from the Demographic and Health Survey and the Indian National AIDS Control Organisation), HPV prevalence data (from two local surveys, from the states of Tamil Nadu and West Bengal), and cervical cancer incidence data (from Cancer Incidence in Five Continents for the period 2008-12 [volume XI], and the Indian National Centre for Disease Informatics and Research for the period 2012-16). Using the model, we projected the nationwide and state-specific effect of HPV vaccination on HPV prevalence and cervical cancer incidence, and lifetime risk of cervical cancer, for 100 years after the introduction of vaccination or in the first 50 vaccinated birth cohorts. Projections were derived under a two-dose vaccination scenario assuming life-long protection and under a single-dose vaccination scenario with protection duration assumptions derived from International Agency for Research on Cancer (IARC) India vaccine trial data, in combination with different vaccination coverages and catch-up vaccination age ranges. We used two thresholds to define cervical cancer elimination: an age-standardised incidence rate of less than 4 cases per 100 000 woman-years, and standardised lifetime risk of less than 250 cases per 100 000 women born. FINDINGS: Assuming vaccination in girls aged 10 years, with 90% coverage, and life-long protection by two-dose or single-dose schedule, HPV vaccination could reduce the prevalence of HPV16 and HPV18 infection by 97% (80% UI 96-99) in 50 years, and the lifetime risk of cervical cancer by 71-78% from 1067 cases per 100 000 women born under a no vaccination scenario to 311 (80% UI 284-339) cases per 100 000 women born in the short term and 233 (219-252) cases per 100 000 women born in the long term in vaccinated cohorts. Under this scenario, we projected that the age-standardised incidence rate threshold for elimination could be met across India (range across Indian states: 1·6 cases [80% UI 1·5-1·7] to 4·0 cases [3·8-4·4] per 100 000 woman-years), while the complementary threshold based on standardised lifetime risk was attainable in 17 (68%) of 25 states, but not nationwide (range across Indian states: 207 cases [80% UI 194-223] to 477 cases [447-514] per 100 000 women born). Under the considered assumptions of waning vaccine protection, single-dose vaccination was projected to have a 21-100% higher per-dose efficiency than two-dose vaccination. Single-dose vaccination with catch-up for girls and women aged 11-20 years was more impactful than two-dose vaccination without catch-up, with reduction of 39-65% versus 38% in lifetime risk of cervical cancer across the ten catch-up birth cohorts and the first ten routine vaccination birth cohorts. INTERPRETATION: Our evidence-based projections suggest that scaling up cervical cancer prevention through single-dose HPV vaccination could substantially reduce cervical cancer burden in India. FUNDING: The Bill & Melinda Gates Foundation.

Approximate likelihood-based estimation method of multiple-type pathogen interactions: An application to longitudinal pneumococcal carriage data.

While the serotypes of Streptococcus pneumoniae are known to compete during colonization in human hosts, our knowledge of how competition occurs is still incomplete. New insights of pneumococcal between-type competition could be generated from carriage data obtained by molecular-based detection methods, which record more complete sets of serotypes involved in co-carriage than when detection is done by culture. Here, we develop a Bayesian estimation method for inferring between-type interactions from longitudinal data recording the presence/absence of the types at discrete observation times. It allows inference from data containing co-carriage of two or more serotypes, which is often the case when pneumococcal presence is determined by molecular-based methods. The computational burden posed by the increased number of types detected in co-carriage is addressed by approximating the likelihood under a multi-state model with the likelihood of only those trajectories with minimum number of acquisition and clearance events between observation times. The proposed method's performance was validated on simulated data. The estimates of the interaction parameters of acquisition and clearance were unbiased in settings with short sampling intervals between observation times. With less frequent sampling, the estimates of the interaction parameters became more biased, but their ratio, which summarizes the total interaction, remained unbiased. Confounding due to unobserved heterogeneity in exposure could be corrected by including individual-level random effects. In an application to empirical data about pneumococcal carriage in infants, we found new evidence for between-serotype competition in clearance, although the effect size was small.

Human Papillomavirus Genotype Replacement: Still Too Early to Tell?

BACKGROUND: Although human papillomavirus (HPV) vaccines are highly efficacious in protecting against HPV infections and related diseases, vaccination may trigger replacement by nontargeted genotypes if these compete with the vaccine-targeted types. HPV genotype replacement has been deemed unlikely, based on the lack of systematic increases in the prevalence of nonvaccine-type (NVT) infection in the first decade after vaccination, and on the presence of cross-protection for some NVTs. METHODS: To investigate whether type replacement can be inferred from early postvaccination surveillance, we constructed a transmission model in which a vaccine type and an NVT compete through infection-induced cross-immunity. We simulated scenarios of different levels of cross-immunity and vaccine-induced cross-protection to the NVT. We validated whether commonly used measures correctly indicate type replacement in the long run. RESULTS: Type replacement is a trade-off between cross-immunity and cross-protection; cross-immunity leads to type replacement unless cross-protection is strong enough. With weak cross-protection, NVT prevalence may initially decrease before rebounding into type replacement, exhibiting a honeymoon period. Importantly, vaccine effectiveness for NVTs is inadequate for indicating type replacement. CONCLUSIONS: Although postvaccination surveillance thus far is reassuring, it is still too early to preclude type replacement. Monitoring of NVTs remains pivotal in gauging population-level impacts of HPV vaccination.

Capturing multiple-type interactions into practical predictors of type replacement following human papillomavirus vaccination.

Current HPV vaccines target a subset of the oncogenic human papillomavirus (HPV) types. If HPV types compete during infection, vaccination may trigger replacement by the non-targeted types. Existing approaches to assess the risk of type replacement have focused on detecting competitive interactions between pairs of vaccine and non-vaccine types. However, methods to translate any inferred pairwise interactions into predictors of replacement have been lacking. In this paper, we develop practical predictors of type replacement in a multi-type setting, readily estimable from pre-vaccination longitudinal or cross-sectional prevalence data. The predictors we propose for replacement by individual non-targeted types take the form of weighted cross-hazard ratios of acquisition versus clearance, or aggregate odds ratios of coinfection with the vaccine types. We elucidate how the hazard-based predictors incorporate potentially heterogeneous direct and indirect type interactions by appropriately weighting type-specific hazards and show when they are equivalent to the odds-based predictors. Additionally, pooling type-specific predictors proves to be useful for predicting increase in the overall non-vaccine-type prevalence. Using simulations, we demonstrate good performance of the predictors under different interaction structures. We discuss potential applications and limitations of the proposed methodology in predicting type replacement, as compared to existing approaches. This article is part of the theme issue 'Silent cancer agents: multi-disciplinary modelling of human DNA oncoviruses'.

Occurrence of human papillomavirus (HPV) type replacement by sexual risk-taking behaviour group: Post-hoc analysis of a community randomized clinical trial up to 9 years after vaccination (IV).

Oncogenic non-vaccine human papillomavirus (HPV) types may conceivably fill the vacated ecological niche of the vaccine types. The likelihood of this may differ by the risk of acquiring HPV infections. We examined occurrence of HPV types among vaccinated and unvaccinated subgroups of 1992-1994 birth cohorts with differing acquisition risks up to 9 years post-implementation of HPV vaccination in 33 Finnish communities randomized to: Arm A (gender-neutral HPV16/18 vaccination), Arm B (girls-only HPV16/18 vaccination and hepatitis B-virus (HBV) vaccination of boys), and Arm C (gender-neutral HBV vaccination). Out of 1992-1994 born resident boys (31,117) and girls (30,139), 8,618 boys and 15,615 girls were vaccinated, respectively, with 20-30% and 50% coverage in 2007-2009. In 2010-2013, 8,868 HPV16/18 and non-HPV vaccinated females, and in 2014-2016, 5,574 originally or later (2010-2013) HPV16/18 vaccinated females attended two cervical sampling visits, aged 18.5 and 22-years. The samples were typed for HPV6/11/16/18/31/33/35/39/45/51/52/56/58/59/66/68 using PCR followed by MALDI-TOF MS. HPV prevalence ratios (PR) between Arms A/B vs. C were calculated for Chlamydia trachomatis positives (core-group), and negatives (general population minus core group). At both visits the vaccine-protected HPV type PRs did not significantly differ between the core-group and non-core group. Among the vaccinated 18-year-olds, HPV51 occurrence was overall somewhat increased (PRcore = 1.4, PRnon-core. = 1.4) whereas the HPV52 occurrence was increased in the core-group only (PRcore = 2.5, PRnon-core = 0.8). Among the non-HPV vaccinated 18-year-olds, the HPV51/52 PRs were higher in the core-group (PRcore = 3.8/1.8, PRnon-core = 1.2/1.1). The 22-year-olds yielded no corresponding observations. Monitoring of the sexual risk-taking core-group may detect early tendencies for HPV type replacement.

Inferring Pathogen Type Interactions Using Cross-sectional Prevalence Data: Opportunities and Pitfalls for Predicting Type Replacement.

BACKGROUND: Many multivalent vaccines target only a subset of all pathogenic types. If vaccine and nonvaccine types compete, vaccination may lead to type replacement. The plausibility of type replacement has been assessed using the odds ratio (OR) of co-infections in cross-sectional prevalence data, with OR > 1 being interpreted as low risk of type replacement. The usefulness of the OR as a predictor for type replacement is debated, as it lacks a theoretical justification, and there is no framework explaining under which assumptions the OR predicts type replacement. METHODS: We investigate the values that the OR can take based on deterministic S usceptible- I infected- S usceptible and S usceptible- Infected- Recovered- S usceptible multitype transmission models. We consider different mechanisms of type interactions and explore parameter values ranging from synergistic to competitive interactions. RESULTS: We find that OR > 1 might mask competition because of confounding due to unobserved common risk factors and cross-immunity, as indicated by earlier studies. We prove mathematically that unobserved common risk factors lead to an elevation of the OR, and present an intuitive explanation why cross-immunity increases the OR. We find that OR < 1 is predictive for type replacement in the absence of immunity. With immunity, OR < 1 remains predictive under biologically reasonable assumptions of unidirectional interactions during infection, and an absence of immunity-induced synergism. CONCLUSIONS: Using the OR in cross-sectional data to predict type replacement is justified, but is only unambiguous under strict assumptions. An accurate prediction of type replacement requires pathogen-specific knowledge on common risk factors and cross-immunity.

Photoinduced pompholyx: a report of 5 cases.

We describe 5 patients whose histories and investigation findings point toward a diagnosis of photo-induced hand pompholyx, a previously unreported condition. Several factors have been associated with the exacerbation of pompholyx, but no direct relationship with sunlight exposure has been reported.

An intraindividual study of the characteristics of erythema induced by bath and oral methoxsalen photochemotherapy and narrowband ultraviolet B.

We compared the characteristics of psoralen and ultraviolet A (PUVA) erythema in skin photosensitized by bath or oral methoxsalen in 20 subjects. Erythema was assessed visually and with a reflectance instrument at 24 h intervals for 7 days. In addition, narrowband ultraviolet B (TL-01 UVB) erythema was examined in 19 of these subjects at 4, 8, 12, 24, 48 and 72 h and in another nine subjects at 12, 15, 18, 21 and 24 h. Both bath and oral PUVA exhibited broad erythemal peaks beyond 72 h. For topical PUVA the lowest minimal phototoxic dose (MPD) occurred at 120 and 144 h (P = 0.01 and 0.03 compared with 72 h). Oral PUVA erythema peaked earlier at 96 h: the MPD was significantly lower at 96, 120 and 144 h compared with 72 h (P = 0.001, 0.01 and 0.02, respectively). At 120 h, bath PUVA had a significantly steeper slope compared with oral PUVA. The TL-01 UVB minimal erythema dose was significantly lower at 12 h compared with 24 h (P = 0.019). The majority of subjects were at maximal erythema at 12 h (22 of 28) and 15 h (eight of nine). Our results suggest that peak erythema for bath PUVA, oral PUVA and TL-01 UVB occurs at 120, 96 and 12-15 h, respectively.

An intraindividual comparative study of psoralen-UVA erythema induced by bath 8-methoxypsoralen and 4, 5', 8-trimethylpsoralen.

BACKGROUND: Limited work has been conducted on the characteristics of topical trimethylpsoralen (TMP) psoralen-UVA (PUVA) erythema. OBJECTIVE: We sought to determine the time-course and dose-response characteristics of erythema induced by topical TMP, and to compare these parameters with those for topical 8-methoxypsoralen (MOP) within patients. METHODS: After photosensitization of one forearm with topical TMP, test sites were exposed to a UVA dose series. The procedure was repeated on the other forearm using 8-MOP solution. Erythema was assessed visually and with a reflectance instrument every 24 hours for 7 days. RESULTS: TMP PUVA erythema followed a similar time course to 8-MOP PUVA erythema. The majority of patients were at maximal erythema at or beyond 96 hours. TMP PUVA had a significantly steeper dose-response curve at 48, 72, and 96 hours compared with 8-MOP PUVA. CONCLUSION: On the basis of these data, the optimal time to read the TMP minimal phototoxic dose is 96 hours. In view of the steeper dose-response curve for TMP PUVA, a lower UVA incremental regimen should be considered compared with that for 8-MOP PUVA.

The time course of topical PUVA erythema following 15- and 5-minute methoxsalen immersion.

BACKGROUND: Limited data exist in the literature concerning the characteristics of erythema following psoralen UV-A (PUVA) treatment using topical methoxsalen. To optimize the phototherapeutic regimen and reduce short- and long-term risks, knowledge of such basic information is essential. OBSERVATIONS: The characteristics of PUVA erythema following 15- and 5-minute immersion in methoxsalen was determined. The PUVA erythema after 15-minute methoxsalen immersion exhibited a broad peak, with the lowest median minimal phototoxic dose (MPD) at 96, 120, and 144 hours after UV-A irradiation. Seventy-three percent of subjects experienced peak erythema at 120 hours compared with only 45% at 72 hours. From the dose-response data, an increase in the erythema index of 0.025 (equivalent to the MPD) was significantly lower when determined at 120 hours after UV-A irradiation than at 72 hours (P =.03). The median maximum slope of the dose-response curve occurred at 144 hours. After 5-minute immersion, PUVA erythema displayed a broad peak from 72 hours. Erythema summation scores followed a trend similar to that of 15-minute immersion, but the intensity was significantly reduced. CONCLUSIONS: Methoxsalen-UV-A erythema exhibited a broad plateau between 96 and 144 hours, with most subjects at peak erythema at 120 hours. Reduction of methoxsalen immersion time significantly lowered the erythemal intensity. Minimum phototoxic dose reading at 72 hours underestimates the phototoxic effect of topical methoxsalen PUVA, and a change in the MPD assessment time should be considered.

UV-B phototherapy clears psoriasis through local effects.

OBJECTIVE: To determine if UV-B phototherapy clears psoriasis through systemic effects. DESIGN: Randomized, within-subject comparison of change in psoriasis in 3 plaques in patients attending for whole-body UV-B therapy. Change in patients' psoriasis plaques covered during UV-B treatment was compared with plaques in an untreated control group. SETTING: University hospital phototherapy unit. PATIENTS: The study population comprised 17 patients with chronic plaque psoriasis treated with UV-B and 24 psoriasis control patients awaiting UV-B phototherapy. INTERVENTIONS: Treatment with a standard 3-times weekly narrowband TL-01 UV-B regimen. Three similar plaques were randomly allocated to be covered every treatment, covered for 2 of 3 weekly treatments, and exposed to local UV-B every treatment. Similar plaques were selected in control patients (awaiting but not yet started UV-B therapy). Severity of psoriasis plaques was assessed using a scaling, erythema, and induration (SEI) scoring system. MAIN OUTCOME MEASURES: Change in SEI score of the selected plaques over the complete treatment course for UV-B-treated patients and change over 3 weeks in SEI score of plaques covered during UV-B treatment compared with that of plaques in controls. RESULTS: There was a significant (P<.001) difference in how much the SEI score changed in the 3 plaques in UV-B-treated patients. It fell by a mean of 7.6 for uncovered plaques compared with 3.2 for plaques covered during each UV-B exposure (95% confidence interval for difference, 3.0 to 5.8). In patients awaiting UV-B, SEI score of plaques fell by a mean of 0.4 over 3 weeks, compared with a mean fall of 1.4 for covered plaques in UV-B-treated patients (95% confidence interval for difference in means, 0.1 to 2.0). CONCLUSIONS: If UV-B therapy has any systemic effect capable of improving psoriasis, this effect is small and unlikely to be of clinical importance. It is insufficient to alter interpretation of findings of within-subject comparative phototherapy studies. UV-B phototherapy works for chronic plaque psoriasis through local effects.