Dynamic transmission modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--5

Validating the Predictions of a Dynamic Transmission Model Using Real-World Data from a Universal Varicella Vaccination Program in Germany

Dynamic transmission models (DTMs) have been used to estimate various aspects of the public health impact of varicella vaccination programs. The aim of this study was to validate the predictions of a DTM-developed using the typical approach to varicella modeling-using real-world data from a country with a long-term universal varicella vaccination (UVV) program and to assess the sensitivity of the predictions to changes in model input parameters. A compartmental, age-stratified DTM was developed using the settings corresponding to the existing UVV program in Germany. The model-predicted total number of varicella cases followed the same trend as observed in the reported data. The agreement between the simulations' results and the data was the highest for the age group most exposed to varicella (0-5 years old), while for other age groups, a decline in accuracy was observed. Sensitivity analyses identified the input parameters having a crucial impact on the model's long-term predictions. The results supported the reliability of the DTM for assessing the impact of varicella vaccination programs over the first decades after their introduction and provided an insight into how certain parameters and assumptions influence the model output and thus require careful evaluation in the studies of future varicella vaccination programs.

Cost-Effectiveness Analysis of Testing Approaches for Diagnosis of Hepatitis C Among US Adults

BACKGROUND

Diagnosis of infection with hepatitis C virus (HCV) is the first step to accessing curative treatment, yet many infected adults in the United States are unaware of their infection. Viral-first HCV testing strategies may improve diagnosis. We assessed the cost-effectiveness of several hepatitis C testing strategies compared with the currently recommended testing algorithm.

METHODS

We used a decision tree framework with a Markov model of hepatitis C disease progression, to model a cohort representative of US adults at average risk. We modeled 4 strategies: anti-HCV test with automatic nucleic acid test (NAT) for HCV RNA when the anti-HCV result is reactive (comparator); anti-HCV test with automatic hepatitis C core antigen (HCVcAg) test when the anti-HCV result is reactive, followed by NAT for HCV RNA when the HCVcAg result is not reactive (intervention 1); concurrent anti-HCV and HCVcAg tests with automatic NAT for HCV RNA for discordant anti-HCV and HCVcAg results (intervention 2); and NAT for HCV RNA (intervention 3). We compared costs (in 2023 US dollars), quality-adjusted life-years (QALYs) and epidemiologic outcomes for the lifetime of the cohort.

RESULTS

Relative to the comparator, intervention 1 resulted in the same number of HCV diagnoses and subsequent health outcomes, with cost savings of $0.26 per person. Interventions 2 and 3 had increased costs per person ($8.60 2 and $21.48, respectively) and resulted in an increase in diagnosed infections, treated infections, and QALYs.

CONCLUSIONS

Compared with the current HCV testing approach, viral-first HCV testing approaches are potentially cost-effective strategies that resulted in gains in diagnoses and health outcomes.

Cost-effectiveness analysis of 21-valent pneumococcal conjugated vaccine among adults in Canada

BACKGROUND

A 21-valent pneumococcal conjugate vaccine (PCV21) was recently authorized in Canada to protect adults against invasive pneumococcal disease (IPD).

OBJECTIVE

To assess the cost-effectiveness of PCV21 compared to current Canadian vaccination recommendations for adults of different age and risk groups.

METHODS

We used a static cohort model to estimate lifetime incremental cost-effectiveness ratios (ICERs), in 2023 Canadian dollars per quality-adjusted life year (QALY), discounted at 1.5 %, in population cohorts aged 33 (midpoint of the 18-49 year age group), 50, and 65 years from the health system and societal perspectives. The primary analysis used 2022 serotype distributions for IPD cases. Additional analyses incorporated indirect effects from pediatric vaccination and used IPD serotype distributions from 2015 to 2019, to explore the impact of changes over time observed in some age groups.

RESULTS

For population groups currently recommended to receive PCV20 in Canada (65 years and older, 50-64 years with additional risk factors for IPD, or 18-49 years with immunocompromising conditions), PCV21 was cost-effective at a $50,000 per QALY threshold and dominated PCV20 in most scenarios when PCV21 serotypes were more prevalent. When PCV20 serotypes were equally or more prevalent than PCV21 serotypes, results were more sensitive to assumptions about indirect effects and serotype replacement. For groups not currently recommended a conjugate vaccine (50-64 years without additional IPD risk factors and 18-49 years with chronic medical conditions or unhoused populations), use of a higher-valency conjugate vaccine was a cost-effective intervention compared to no vaccination, with the optimal vaccine dependent on the proportion of IPD attributable to PCV20 and PCV21 serotypes in the population of interest. Results were sensitive to vaccine price in most scenarios.

INTERPRETATION

The use of PCV21 may be cost-effective in some populations, depending on the prevalence of IPD serotypes covered by PCV20 and PCV21.

Modelling the Epidemiological Impact of Different Adult Pneumococcal Vaccination Strategies in the United Kingdom

INTRODUCTION

Pneumococcal conjugate vaccines (PCVs) were first introduced in the paediatric United Kingdom (UK) immunisation programme in 2006 which led to significant declines in invasive pneumococcal disease (IPD) caused by targeted serotypes. Although paediatric PCVs provide some indirect protection to adults, a significant IPD burden remains in older adults. Here, we compared three adult (65+ years-old) and risk group (2-64-year-old) vaccination scenarios, namely a continuation of the status quo with PPSV23 vaccination, using the recently licensed-in-adults PCV20, or using the new adult-focused 21-valent PCV, V116.

METHODS

A population-level compartmental dynamic transmission model (DTM) was adapted to the UK setting. The model described Streptococcus pneumoniae carriage transmission dynamics and disease progression in the presence of age- and serotype-specific pneumococcal vaccines. We calibrated the DTM to age- and serotype-specific IPD data in the UK and used the model to make projections under the different adult vaccination scenarios while keeping PCV13 immunisation in children.

RESULTS

The calibrated model yielded reasonable parameter values and model fits that closely matched observed IPD dynamics. Among 65+ year-olds, 10-year model projections predicted that the routine use of V116 would reduce IPD incidence by 15.5%, while PCV20 would reduce IPD incidence by 8.9% and the continued use of PPSV23 would increase incidence by 3.83%. There was a notable decrease in IPD incidence in the serotypes unique to V116. In the serotypes included in PCV20 but not V116, the model did not predict a resurgence of IPD.

CONCLUSIONS

Projections revealed that in adults, V116 led to significantly greater reductions in IPD in the 65+ year-old population compared with PCV20 or PPSV23.

Modelling epidemiological and economics processes - the case of cervical cancer

Different types of mathematical models can be used to forecast the development of diseases as well as associated costs and analyse the cost-effectiveness of interventions. The set of models available to assess these parameters, reach from simple independent equations to highly complex agent-based simulations. For many diseases, it is simple to distinguish between infectious diseases and chronic-degenerative diseases. For infectious diseases, dynamic models are most appropriate because they allow for feedback from the number of infected to the number of new infections, while for the latter Markov models are more appropriate since this feedback is not required. However, for some diseases, the aforementioned distinction is not as clear. Cervical cancer, for instance, is caused by a sexually transmitted virus, and therefore falls under the definition of an infectious disease. However, once infected, the condition can progress to a chronic disease. Consequently, cervical cancer could be considered an infectious or a chronic-degenerative disease, depending on the stage of infection. In this paper, we will analyse the applicability of different mathematical models for epidemiological and economic processes focusing on cervical cancer. For this purpose, we will present the basic structure of different models. We will then conduct a literature analysis of the mathematical models used to predict the spread of cervical cancer. Based on these findings we will draw conclusions about which models can be used for which purpose and which disease. We conclude that each type of model has its advantages and disadvantages, but the choice of model type often seems arbitrary. In the case of cervical cancer, homogenous Markov models seem appropriate if a cohort of newly infected is followed for a shorter period, for instance, to assess the impact of screening programs. For long-term consequences, such as the impact of a vaccination program, a feedback loop from former infections to the future likelihood of infections is required. This can be done using system dynamics or inhomogeneous Markov models. Discrete event or agent-based simulations can be used in the case of cervical cancer when small cohorts or specific characteristics of individuals are required. However, these models require more effort than Markov or System Dynamics models.

Cost-Effectiveness of Introducing Nuvaxovid to COVID-19 Vaccination in the United Kingdom: A Dynamic Transmission Model

Background/Objectives: Vaccination against SARS-CoV-2 remains a key measure to control COVID-19. Nuvaxovid, a recombinant Matrix-M-adjuvanted protein-based vaccine, showed similar efficacy to mRNA vaccines in clinical trials and real-world studies, with lower rates of reactogenicity. Methods: To support decision making on UK vaccine selection, a population-based compartmental dynamic transmission model with a cost-utility component was developed to evaluate the cost-effectiveness of Nuvaxovid compared with mRNA vaccines from a UK National Health Service perspective. The model was calibrated to official epidemiology statistics for mortality, incidence, and hospitalisation. Scenario and sensitivity analyses were conducted. Results: In the probabilistic base case, a Nuvaxovid-only strategy provided total incremental cost savings of GBP 1,338,323 and 1558 additional quality-adjusted life years (QALYs) compared with an mRNA-only vaccination strategy. Cost savings were driven by reduced cold chain-related operational costs and vaccine wastage, while QALY gains were driven by potential differences in vaccine tolerability. Probabilistic sensitivity analysis indicated an approximately 70% probability of cost-effectiveness with Nuvaxovid-only versus mRNA-only vaccination across most cost-effectiveness thresholds (up to GBP 300,000/QALY gained). Conclusions: Nuvaxovid remained dominant over mRNA vaccines in scenario analyses assessing vaccine efficacy waning, Nuvaxovid market shares, and the vaccinated population.

Advances in HPV-Associated Cervical Cancer Dynamic Modelling for Prevention and Control Evaluation

Cervical cancer is a common malignancy in women, with persistent human papillomavirus (HPV) infection as its primary cause. Understanding the progression from HPV infection to cervical cancer is crucial. Mathematical models play a key role in converting clinical trial data into long-term health forecasts, helping decision-makers tackle challenges posed by limited data and uncertain outcomes. This paper reviews transmission dynamics models and advancements in simulating HPV transmission leading to cervical cancer. It evaluates preventive and control measures, focusing on the impact of HPV vaccination across different vaccine types, doses, age groups, and both genders. These model-based assessments aim to provide insights for developing effective strategies to prevent and control HPV-related cervical cancer.

Comparison of 13-, 15- and 20-valent pneumococcal conjugate vaccines in the paediatric Canadian population: A cost-utility analysis

Background

Two pneumococcal conjugate vaccines, covering 15 and 20 Streptococcus pneumoniae serotypes (Pneu-C-15 and Pneu-C-20, respectively), were recently approved for use in the Canadian paediatric population.

Objective

To assess the cost-effectiveness of Pneu-C-15 and Pneu-C-20 in unvaccinated infants initiating routine pneumococcal vaccination, compared to the currently used 13-valent conjugate vaccine (Pneu-C-13).

Methods

A static cohort model was used to estimate sequential incremental cost-effectiveness ratios (ICERs in 2022 Canadian dollars per quality-adjusted life year [QALY]) of Pneu-C-13, Pneu-C-15 and Pneu-C-20 in the paediatric population starting their primary series. Costs and outcomes were calculated over a 10-year time horizon at the program level and a lifetime time horizon at the individual level and discounted at a rate of 1.5% per year. We explored the impact of uncertainties in model parameters and assumptions in scenario and sensitivity analyses.

Results

Routine use of Pneu-C-20 and, to a lesser extent, Pneu-C-15 is projected to reduce pneumococcal disease burden, compared to Pneu-C-13. Based on product cost assumptions, sequential ICERs for Pneu-C-15 and Pneu-C-20 were $58,800 and $135,200 per QALY gained from the health system perspective and $18,272 and $93,416 per QALY gained from the societal perspective, excluding indirect effects. A reduction in serotype-attributable disease due to indirect vaccine effects of 5% or greater resulted in ICERs below $30,000 per QALY gained for Pneu-C-15 and Pneu-C-20, with the optimal strategy determined by the magnitude and time to reach a reduction in pneumococcal disease.

Conclusion

Both Pneu-C-15 and Pneu-C-20 are expected to increase QALYs in Canadian children compared to Pneu-C-13 and may be cost-effective interventions.

Cost effectiveness of a 21-valent pneumococcal conjugate vaccine in adults: A systematic review of economic evaluations

Background

In July 2024, Health Canada authorized a 21-valent pneumococcal conjugate vaccine (Pneu-C-21) for use in adults.

Objective

To conduct a systematic review of the cost-effectiveness of Pneu-C-21 for preventing pneumococcal disease in adults.

Methods

We conducted a systematic search of the literature and National Immunization Technical Advisory Groups' websites on July 3, 2024. We included economic evaluations that assessed Pneu-C-21 as a vaccination strategy among adults aged 18 years and older. Costs were adjusted to 2023 Canadian dollars.

Results

We identified 10 studies in our search, five of which were summarized in our review. No economic evaluations were conducted in Canada. All economic evaluations used static cohort models and incorporated indirect effects from paediatric pneumococcal conjugate vaccination in primary or sensitivity analyses. Although incremental cost-effectiveness ratios were heterogeneous across included economic evaluations, overall, they qualitatively identified the same vaccination strategies as optimal within the given age and risk groups. Pneu-C-21 is likely to be cost-effective in adults aged 65 years and older and adults under the age of 65 years with specific high risk conditions.

Conclusion

Pneu-C-21 is likely to be cost-effective in adults within specific age and risk groups. The applicability of the included economic evaluations to adults living in Canada is limited because the serotype-specific incidence of pneumococcal disease and the impact of indirect effects from pediatric vaccination varies by region and over time.

Good Practices for Health Technology Assessment Guideline Development: A Report of the Health Technology Assessment International, HTAsiaLink, and ISPOR Special Task Force

OBJECTIVES

Health technology assessment (HTA) guidelines are intended to support the successful implementation of HTA by enhancing consistency and transparency in concepts, methods, processes, and use, thereby enhancing the legitimacy of the decision-making process. This report lays out good practices and practical recommendations for developing or updating HTA guidelines to ensure successful implementation.

METHODS

The task force was established in 2022 and comprised experts and academics from various geographical regions, each with substantial experience in developing HTA guidelines for national health policy making. Literature reviews and key informant interviews were conducted to inform these good practices. Stakeholder consultations, open peer reviews, and expert opinions validated the recommendations. A series of teleconferences among task force members was held to iteratively refine the report.

RESULTS

The recommendations cover six key aspects throughout the guideline development cycle: (1) setting objectives, scope, and principles of the guideline, (2) building a team for a quality guideline, (3) defining a stakeholder engagement plan, (4) developing content and utilizing available resources, (5) putting in place appropriate institutional arrangements, and (6) monitoring and evaluating guideline success.

CONCLUSION

This report presents a set of resources and context-appropriate practices for developing or updating HTA guidelines. Across all contexts, the recommendations emphasize transparency, building trust among stakeholders, and fostering a culture of ongoing learning and improvement. The report recommends timing development and revision of guidelines according to the HTA landscape and pace of HTA institutionalization. Because HTA is increasingly used to inform different kinds of decision making in a variety of country contexts, it will be important to continue to monitor lessons learned to ensure the recommendations remain relevant and effective.

The economic rationale for cell-based influenza vaccines in children and adults: A review of cost-effectiveness analyses

Seasonal influenza significantly affects both health and economic costs in children and adults. This narrative review summarizes published cost-effectiveness analyses (CEAs) of cell-based influenza vaccines in children and adults <65 years of age, critically assesses the assumptions and approaches used in these analyses, and considers the role of cell-based influenza vaccines for children and adults. CEAs from multiple countries demonstrated the cost-effectiveness of cell-based quadrivalent influenza vaccines (QIVc) compared with egg-based trivalent/quadrivalent influenza vaccines (TIVe/QIVe). CEA findings were consistent across models relying on different relative vaccine effectiveness (rVE) estimate inputs, with the rVE of QIVc versus QIVe ranging from 8.1% to 36.2% in favor of QIVc. Across multiple scenarios and types of analyses, QIVc was consistently cost-effective compared with QIVe, including in children and adults across different regions of the world.

Projecting the Potential Clinical and Economic Impact of HIV Prevention Resource Reallocation in Tennessee

BACKGROUND

In 2023, Tennessee replaced $6.2 M in US Centers for Disease Control and Prevention (CDC) human immunodeficiency virus (HIV) prevention funding with state funds to redirect support away from men who have sex with men (MSM), transgender women (TGW), and heterosexual Black women (HSBW) and to prioritize instead first responders (FR), pregnant people (PP), and survivors of sex trafficking (SST).

METHODS

We used a simulation model of HIV disease to compare the clinical impact of Current, the present allocation of condoms, preexposure prophylaxis (PrEP), and HIV testing to CDC priority risk groups (MSM/TGW/HSBW); with Reallocation, funding instead increased HIV testing and linkage of Tennessee-determined priority populations (FR/PP/SST). Key model inputs included baseline condom use (45%-49%), PrEP provision (0.1%-8%), HIV testing frequency (every 2.5-4.8 years), and 30-day HIV care linkage (57%-65%). We assumed Reallocation would reduce condom use (-4%), PrEP provision (-26%), and HIV testing (-47%) in MSM/TGW/HSBW, whereas it would increase HIV testing among FR (+47%) and HIV care linkage (to 100%/90%) among PP/SST.

RESULTS

Reallocation would lead to 166 additional HIV transmissions, 190 additional deaths, and 843 life-years lost over 10 years. HIV testing reductions were most influential in sensitivity analysis; even a 24% reduction would result in 287 more deaths compared to Current. With pessimistic assumptions, we projected 1359 additional HIV transmissions, 712 additional deaths, and 2778 life-years lost over 10 years.

CONCLUSIONS

Redirecting HIV prevention funding in Tennessee would greatly harm CDC priority populations while conferring minimal benefits to new priority populations.

The cost-effectiveness of COVID-19 vaccination program among age-groups children, adults, and elderly in Europe: A systematic review

Objectives

To prepare for future epidemics, the experiences from the vaccination programs in the COVID-19 pandemic need to be collated. This systematic review synthesizes health economic evidence of COVID-19 vaccination programs in European countries comparing the target groups children, adults, and elderly, to study whether the Swedish vaccination strategy was justified on cost-effectiveness grounds.

Method

A literature search using the PICOS (Population, Intervention, Control, Outcomes, Study design) convention was conducted in the databases Medline, Embase, PsycInfo, CINAHL, and Tuft CEA Registry, Cochrane and INAHTA in February 2023. The inclusion criteria were economic evaluations (S) comparing COVID-19 vaccination (I) in age-groups children, adult, and elderly European residents (P) with non-vaccinated European residents (C) in terms of cost per QALY, cost differences, and net monetary benefit (O). Hand-search was done on selected websites and in reference lists of included reports. Title/abstract screening, full-text screening, and quality assessment with the Swedish HTA agency checklist were performed by two researchers. The reporting follows the PRISMA 2020 recommendations.

Results

The database search resulted in 5,720 reports, title/abstract screening yielded 162 reports and after full-text screening, four reports remained. Two studies comparing vaccination of adults and elderly with high and moderate study quality were included. No study was found on the children population. The economic evidence indicated that COVID-19 vaccination of the elderly is cost-effective when compared with vaccination of the adult group, but the transferability to Swedish circumstances was inconclusive due to differences in outcome and cost data between Sweden and the included studies' settings.

Conclusion

The common European COVID-19 vaccination policy that prioritized the elderly population was the cost-effective option in the reviewed studies. The lack of transferability to Sweden precludes a clear conclusion on the Swedish vaccination policy.

Reply to Volkman et al. Comment on "Fust et al. The Potential Economic Impact of the Updated COVID-19 mRNA Fall 2023 Vaccines in Japan. Vaccines 2024, 12, 434"

In their comment [...].

Incorporating Social Determinants of Health in Infectious Disease Models: A Systematic Review of Guidelines

BACKGROUND

Infectious disease (ID) models have been the backbone of policy decisions during the COVID-19 pandemic. However, models often overlook variation in disease risk, health burden, and policy impact across social groups. Nonetheless, social determinants are becoming increasingly recognized as fundamental to the success of control strategies overall and to the mitigation of disparities.

METHODS

To underscore the importance of considering social heterogeneity in epidemiological modeling, we systematically reviewed ID modeling guidelines to identify reasons and recommendations for incorporating social determinants of health into models in relation to the conceptualization, implementation, and interpretations of models.

RESULTS

After identifying 1,372 citations, we found 19 guidelines, of which 14 directly referenced at least 1 social determinant. Age (n = 11), sex and gender (n = 5), and socioeconomic status (n = 5) were the most commonly discussed social determinants. Specific recommendations were identified to consider social determinants to 1) improve the predictive accuracy of models, 2) understand heterogeneity of disease burden and policy impact, 3) contextualize decision making, 4) address inequalities, and 5) assess implementation challenges.

CONCLUSION

This study can support modelers and policy makers in taking into account social heterogeneity, to consider the distributional impact of infectious disease outbreaks across social groups as well as to tailor approaches to improve equitable access to prevention, diagnostics, and therapeutics.

HIGHLIGHTS

Infectious disease (ID) models often overlook the role of social determinants of health (SDH) in understanding variation in disease risk, health burden, and policy impact across social groups.In this study, we systematically review ID guidelines and identify key areas to consider SDH in relation to the conceptualization, implementation, and interpretations of models.We identify specific recommendations to consider SDH to improve model accuracy, understand heterogeneity, estimate policy impact, address inequalities, and assess implementation challenges.

From conceptualising to modelling structural determinants and interventions in HIV transmission dynamics models: a scoping review and methodological framework for evidence-based analyses

BACKGROUND

Including structural determinants (e.g. criminalisation, stigma, inequitable gender norms) in dynamic HIV transmission models is important to help quantify their population-level impacts and guide implementation of effective interventions that reduce the burden of HIV and inequalities thereof. However, evidence-based modelling of structural determinants is challenging partly due to a limited understanding of their causal pathways and few empirical estimates of their effects on HIV acquisition and transmission.

METHODS

We conducted a scoping review of dynamic HIV transmission modelling studies that evaluated the impacts of structural determinants, published up to August 28, 2023, using Ovid Embase and Medline online databases. We appraised studies on how models represented exposure to structural determinants and causal pathways. Building on this, we developed a new methodological framework and recommendations to support the incorporation of structural determinants in transmission dynamics models and their analyses. We discuss the data and analyses that could strengthen the evidence used to inform these models.

RESULTS

We identified 17 HIV modelling studies that represented structural determinants and/or interventions, including incarceration of people who inject drugs (number of studies [n] = 5), violence against women (n = 3), HIV stigma (n = 1), and housing instability (n = 1), among others (n = 7). Most studies (n = 10) modelled exposures dynamically. Almost half (8/17 studies) represented multiple exposure histories (e.g. current, recent, non-recent exposure). Structural determinants were often assumed to influence HIV indirectly by influencing mediators such as contact patterns, condom use, and antiretroviral therapy use. However, causal pathways' assumptions were sometimes simple, with few mediators explicitly represented in the model, and largely based on cross-sectional associations. Although most studies calibrated models using HIV epidemiological data, less than half (7/17) also fitted or cross-validated to data on the prevalence, frequency, or effects of exposure to structural determinants.

CONCLUSIONS

Mathematical models can play a crucial role in elucidating the population-level impacts of structural determinants and interventions on HIV. We recommend the next generation of models reflect exposure to structural determinants dynamically and mechanistically, and reproduce the key causal pathways, based on longitudinal evidence of links between structural determinants, mediators, and HIV. This would improve the validity and usefulness of predictions of the impacts of structural determinants and interventions.

Masks and respirators for prevention of respiratory infections: a state of the science review

SUMMARYThis narrative review and meta-analysis summarizes a broad evidence base on the benefits-and also the practicalities, disbenefits, harms and personal, sociocultural and environmental impacts-of masks and masking. Our synthesis of evidence from over 100 published reviews and selected primary studies, including re-analyzing contested meta-analyses of key clinical trials, produced seven key findings. First, there is strong and consistent evidence for airborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory pathogens. Second, masks are, if correctly and consistently worn, effective in reducing transmission of respiratory diseases and show a dose-response effect. Third, respirators are significantly more effective than medical or cloth masks. Fourth, mask mandates are, overall, effective in reducing community transmission of respiratory pathogens. Fifth, masks are important sociocultural symbols; non-adherence to masking is sometimes linked to political and ideological beliefs and to widely circulated mis- or disinformation. Sixth, while there is much evidence that masks are not generally harmful to the general population, masking may be relatively contraindicated in individuals with certain medical conditions, who may require exemption. Furthermore, certain groups (notably D/deaf people) are disadvantaged when others are masked. Finally, there are risks to the environment from single-use masks and respirators. We propose an agenda for future research, including improved characterization of the situations in which masking should be recommended or mandated; attention to comfort and acceptability; generalized and disability-focused communication support in settings where masks are worn; and development and testing of novel materials and designs for improved filtration, breathability, and environmental impact.

Use of Adjuvanted Quadrivalent Influenza Vaccine in Older-Age Adults: A Systematic Review of Economic Evidence

Influenza vaccination is an important public health measure that can reduce disease burden, especially among older persons (those aged 65 and over) who have weaker immune systems. Evidence suggests enhanced vaccines, including adjuvanted quadrivalent vaccines (aQIV), may be particularly effective in this group. This study reports the results of a systematic review of the cost-effectiveness of aQIV in this population. The review was undertaken and reported in accordance with good practice guidelines. Medline and EMBASE were searched from 2013 to the present. Pre-selected eligibility criteria were employed and quality assessment undertaken using the Consensus Health Economic Criteria (CHEC-extended) checklist and Consolidated Health Economic Evaluation Reporting Standard (CHEERS) 2022 checklists. A total of 124 records were returned, with 10 full text papers retained. All were modelling studies and exhibited heterogeneity in approach, perspective, and parameter estimation. Nine papers reported cost-effectiveness ranging from EUR 6694/QALY to EUR 20,000/QALY in evaluations employing a payer perspective and from EUR 3936/QALY to EUR 17,200/QALY in those using a societal perspective. Results remained robust to a range of sensitivity analyses. One paper that reported contrary findings adopted a distinct modelling approach. It is reasonable to conclude that there is a broad consensus as to the cost-effectiveness of aQIV in this population group.

Structured Literature Review to Identify Human Papillomavirus's Natural History Parameters for Dynamic Population Models of Vaccine Impacts

Human papillomavirus (HPV) is a common sexually transmitted virus that can cause cervical cancer and other diseases. Dynamic transmission models (DTMs) have been developed to evaluate the health and economic impacts of HPV vaccination. These models typically include many parameters, such as natural history of the disease, transmission, demographic, behavioral, and screening. To ensure the accuracy of DTM projections, it is important to parameterize them with the best available evidence. This study aimed to identify and synthesize data needed to parametrize DTMs on the natural history of HPV infection and related diseases. Parameters describing data of interest were grouped by their anatomical location (genital warts, recurrent respiratory papillomatosis, and cervical, anal, vaginal, vulvar, head and neck, and penile cancers), and natural history (progression, regression, death, cure, recurrence, detection), and were identified through a systematic literature review (SLR) and complementary targeted literature reviews (TLRs). The extracted data were then synthesized by pooling parameter values across publications, and summarized using the range of values across studies reporting each parameter and the median value from the most relevant study. Data were extracted and synthesized from 223 studies identified in the SLR and TLRs. Parameters frequently reported pertained to cervical cancer outcomes, while data for other anatomical locations were less available. The synthesis of the data provides a large volume of parameter values to inform HPV DTMs, such as annual progression rates from cervical intraepithelial neoplasia (CIN) 1 to CIN 2+ (median of highest quality estimate 0.0836), CIN 2 to CIN 3+ (0.0418), carcinoma in situ (CIS) 2 to local cancer+ (0.0396), and regional to distant cancer (0.0474). Our findings suggest that while there is a large body of evidence on cervical cancer, parameter values featured substantial heterogeneity across studies, and further studies are needed to better parametrize the non-cervical components of HPV DTMs.

A Practical Guide to Full Value of Vaccine Assessments

Articulating the wide range of health, social and economic benefits that vaccines offer may help to overcome obstacles in the vaccine development pipeline. A framework to guide the assessment and communication of the value of a vaccine-the Full Value of Vaccine Assessment (FVVA)-has been developed by the WHO. The FVVA framework offers a holistic assessment of the value of vaccines, providing a synthesis of evidence to inform the public health need of a vaccine, describing the supply and demand aspects, its market and its impact from a health, financial and economic perspective. This paper provides a practical guide to how FVVAs are developed and used to support investment in vaccines, ultimately leading to sustained implementation in countries. The FVVA includes a range of elements that can be broadly categorised as synthesis, vaccine development narrative and defining vaccine impact and value. Depending on the features of the disease/vaccine in question, different elements may be emphasised; however, a standardised set of elements is recommended for each FVVA. The FVVA should be developed by an expert group who represent a range of stakeholders, perspectives and geographies and ensure a fair, coherent and evidence-based assessment of vaccine value.

The economic burden of Ebola virus disease: a review and recommendations for analysis

BACKGROUND

Ebola virus disease (EVD) continues to be a major public health threat globally, particularly in the low-and-middle-income countries (LMICs) of Africa. The social and economic burdens of EVD are substantial and have triggered extensive research into prevention and control. We aim to highlight the impact and economic implications, identify research gaps, and offer recommendations for future economic studies pertaining to EVD.

METHOD

We conducted a comprehensive librarian-led search in PubMed/Medline, Embase, Google Scholar, EconLit and Scopus for economic evaluations of EVD. After study selection and data extraction, findings on the impact and economics of EVD were synthesized using a narrative approach, while identifying gaps, and recommending critical areas for future EVD economic studies.

RESULTS

The economic evaluations focused on the burden of illness, vaccine cost-effectiveness, willingness-to-pay for a vaccine, EVD funding, and preparedness costs. The estimated economic impact of the 2014 EVD outbreak in Guinea, Liberia, and Sierra Leone across studies ranged from $30 billion to $50 billion. Facility construction and modification emerged as significant cost drivers for preparedness. The EVD vaccine demonstrated cost-effectiveness in a dynamic transmission model; resulting in an incremental cost-effectiveness ratio of about $96 per additional disability adjusted life year averted. Individuals exhibited greater willingness to be vaccinated if it incurred no personal cost, with a minority willing to pay about $1 for the vaccine.

CONCLUSIONS

The severe impact of EVD puts pressure on governments and the international community for better resource utilization and re-allocation. Several technical and methodological issues related to economic evaluation of EVD remain to be addressed, especially for LMICs. We recommend conducting cost-of-sequelae and cost-of-distribution analyses in addition to adapting existing economic analytical methods to EVD. Characteristics of the affected regions should be considered to provide evidence-based economic plans and economic-evaluation of mitigations that enhance resource allocation for prevention and treatment.

Effective contact tracing for COVID-19: A systematic review

Contact tracing is commonly recommended to control outbreaks of COVID-19, but its effectiveness is unclear. Following PRISMA guidelines, we searched four databases using a range of terms related to contact tracing effectiveness for COVID-19. We found 343 papers; 32 were included. All were observational or modelling studies. Observational studies (n = 14) provided consistent, very-low certainty evidence that contact tracing (alone or in combination with other interventions) was associated with better control of COVID-19 (e.g. in Hong Kong, only 1084 cases and four deaths were recorded in the first 4.5 months of the pandemic). Modelling studies (n = 18) provided consistent, high-certainty evidence that under assumptions of prompt and thorough tracing with effective quarantines, contact tracing could stop the spread of COVID-19 (e.g. by reducing the reproduction number from 2.2 to 0.57). A cautious interpretation indicates that to stop the spread of COVID-19, public health practitioners have 2-3 days from the time a new case develops symptoms to isolate the case and quarantine at least 80% of its contacts.

Cost-effectiveness analysis of HIV pre-exposure prophylaxis in Japan

BACKGROUND

While global efforts have been made to prevent transmission of HIV, the epidemic persists. Men who have sex with men (MSM) are at high risk of infection. Despite evidence of its cost-effectiveness in other jurisdictions, pre-exposure prophylaxis (PrEP) for MSM is neither approved nor reimbursed in Japan.

METHOD

The cost-effectiveness analysis compared the use of once daily PrEP versus no PrEP among MSM over a 30-year time horizon from a national healthcare perspective. Epidemiological estimates for each of the 47 prefectures informed the model. Costs included HIV/AIDS treatment, HIV and testing for sexually transmitted infections, monitoring tests and consults, and hospitalization costs. Analyses included health and cost outcomes, as well as the incremental cost-effectiveness ratio (ICER) reported as the cost per quality-adjusted life year (QALY) for all of Japan and each prefecture. Sensitivity analyses were performed.

FINDINGS

The estimated proportion of HIV infections prevented with the use of PrEP ranged from 48% to 69% across Japan, over the time horizon. Cost savings due to lower monitoring costs and general medical costs were observed. Assuming 100% coverage, for Japan overall, daily use of PrEP costs less and was more effective; daily use of PrEP was cost-effective at a willingness to pay threshold of ¥5,000,000 per QALY in 32 of the 47 prefectures. Sensitivity analyses found that the ICER was most sensitive to the cost of PrEP.

INTERPRETATION

Compared to no PrEP use, once daily PrEP is a cost-effective strategy in Japanese MSM, reducing the clinical and economic burden associated with HIV.

Estimating the Cost-Effectiveness of Switching to Higher-Valency Pediatric Pneumococcal Conjugate Vaccines in the United Kingdom

Currently, the 13-valent pneumococcal conjugate vaccine (PCV13) is administered under a 1+1 (1 primary dose) pediatric schedule in the United Kingdom (UK). Higher-valency PCVs, 15-valent PCV (PCV15), or 20-valent PCV (PCV20) might be considered to expand serotype coverage. We evaluated the cost-effectiveness of PCV20 or PCV15 using either a 2+1 (2 primary doses) or 1+1 schedule for pediatric immunization in the UK. Using a dynamic transmission model, we simulated future disease incidence and costs under PCV13 1+1, PCV20 2+1, PCV20 1+1, PCV15 2+1, and PCV15 1+1 schedules from the UK National Health Service perspective. We prospectively estimated disease cases, direct costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio. Scenario analyses were performed to estimate the impact of model assumptions and parameter uncertainty. Over a five-year period, PCV20 2+1 averted the most disease cases and gained the most additional QALYs. PCV20 2+1 and 1+1 were dominant (cost-saving and more QALYs gained) compared with PCV15 (2+1 or 1+1) and PCV13 1+1. PCV20 2+1 was cost-effective (GBP 8110/QALY) compared with PCV20 1+1. PCV20 was found cost-saving compared with PCV13 1+1, and PCV20 2+1 was cost-effective compared with PCV20 1+1. Policymakers should consider the reduction in disease cases with PCV20, which may offset vaccination costs.

Infectious Disease Modelling of HIV Prevention Interventions: A Systematic Review and Narrative Synthesis of Compartmental Models

BACKGROUND

The HIV epidemic remains a major public health problem. Critical to transmission control are HIV prevention strategies with new interventions continuing to be developed. Mathematical models are important for understanding the potential impact of these interventions and supporting policy decisions. This systematic review aims to answer the following question: when a new HIV prevention intervention is being considered or designed, what information regarding it is necessary to include in a compartmental model to provide useful insights to policy makers? The primary objective of this review is therefore to assess suitability of current compartmental HIV prevention models for informing policy development.

METHODS

Articles published in EMBASE, Medline, Econlit, and Global Health were screened. Included studies were identified using permutations of (i) HIV, (ii) pre-exposure prophylaxis (PrEP), circumcision (both voluntary male circumcision [VMMC] and early-infant male circumcision [EIMC]), and vaccination, and (iii) modelling. Data extraction focused on study design, model structure, and intervention incorporation into models. Article quality was assessed using the TRACE (TRAnsparent and Comprehensive Ecological modelling documentation) criteria for mathematical models.

RESULTS

Of 837 articles screened, 48 articles were included in the review, with 32 unique mathematical models identified. The substantial majority of studies included PrEP (83%), whilst fewer modelled circumcision (54%), and only a few focussed on vaccination (10%). Data evaluation, implementation verification, and model output corroboration were identified as areas of poorer model quality. Parameters commonly included in the mathematical models were intervention uptake and effectiveness, with additional intervention-specific common parameters identified. We identified key modelling gaps; critically, models insufficiently incorporate multiple interventions acting simultaneously. Additionally, population subgroups were generally poorly represented-with future models requiring improved incorporation of ethnicity and sexual risk group stratification-and many models contained inappropriate data in parameterisation which will affect output accuracy.

CONCLUSIONS

This review identified gaps in compartmental models to date and suggests areas of improvement for models focusing on new prevention interventions. Resolution of such gaps within future models will ensure greater robustness and transparency, and enable more accurate assessment of the impact that new interventions may have, thereby providing more meaningful guidance to policy makers.

Estimated cost-effectiveness of point-of-care testing in community pharmacies vs. self-testing and standard laboratory testing for HIV

OBJECTIVE

Point-of-care-testing (POCT) for HIV at community pharmacies can enhance care linkage compared with self-tests and increase testing uptake relative to standard lab testing. While the higher test uptake may increase testing costs, timely diagnosis and treatment can reduce downstream HIV treatment costs and improve health outcomes. This study provides the first evidence on the cost-effectiveness of pharmacist-led POCT vs. HIV self-testing and standard lab testing.

DESIGN

Dynamic transmission model.

METHODS

We compared three HIV testing strategies: POCT at community pharmacies; self-testing using HIV self-test kits; and standard lab testing. Analyses were conducted from the Canadian health system perspective over a 30-year time horizon for all individuals aged 15-64 years in Canada. Costs were measured in 2021 Canadian dollars and effectiveness was captured using quality-adjusted life-years (QALYs).

RESULTS

Compared with standard lab testing, POCT at community pharmacies would save $885 million in testing costs over 30 years. Though antiretroviral treatment costs would increase by $190 million with POCT as more persons living with HIV are identified and treated, these additional costs would be partly offset by their lower downstream healthcare utilization (savings of $150 million). POCT at community pharmacies would also yield over 5000 additional QALYs. Compared with HIV self-testing, POCT at community pharmacies would generate both higher costs and higher QALYs and would be cost-effective with an incremental cost-effectiveness ratio of $47 475 per QALY gained.

CONCLUSIONS

Offering POCT at community pharmacies can generate substantial cost savings and improve health outcomes compared with standard lab testing. It would also be cost-effective vs. HIV self-testing.

Systematic review of applied mathematical models for the control of Schistosoma japonicum

BACKGROUND

Schistosoma japonicum remains endemic in China and the Philippines. Substantial progress has been made in the control of Japonicum in both China and the Philippines. China is reaching elimination thanks to a concerted effort of control strategies. Mathematical modelling has been a key tool in the design of control strategies, in place of expensive randomised-controlled trials. We conducted a systematic review to investigate mathematical models of Japonicum control strategies in China and the Philippines.

METHODS

We conducted a systematic review on July 5, 2020, in four electronic bibliographic databases - PubMed, Web of Science, SCOPUS and Embase. Articles were screened for relevance and for meeting the inclusion criteria. Data extracted included authors, year of publication, year of data collection, setting and ecological context, objectives, control strategies, main findings, the form and content of the model including its background, type, representation of population dynamics, heterogeneity of hosts, simulation period, source of parameters, model validation and sensitivity analysis. Results After screening, 19 eligible papers were included in the systematic review. Seventeen considered control strategies in China and two in the Philippines. Two frameworks were identified; the mean-worm burden framework and the prevalence-based framework, the latter of which increasingly common. Most models considered human and bovine definitive hosts. There were mixed additional elements included in the models, such as alternative definitive hosts and the role of seasonality and weather. Models generally agreed upon the need for an integrated control strategy rather than reliance on mass drug administration alone to sustain reductions in prevalence.

CONCLUSIONS

Mathematical modelling of Japonicum has converged from multiple approaches to modelling using the prevalence-based framework with human and bovine definitive hosts and find integrated control strategies to be most effective. Further research could investigate the role of other definitive hosts and model the effect of seasonal fluctuations in transmission.

Health economic analyses of latent tuberculosis infection screening and preventive treatment among people living with HIV in lower tuberculosis incidence settings: a systematic review

Introduction: In lower tuberculosis (TB) incidence countries (<100 cases/100,000/year), screening and preventive treatment (PT) for latent TB infection (LTBI) among people living with HIV (PLWH) is often recommended, yet guidelines advising which groups to prioritise for screening can be contradictory and implementation patchy. Evidence of LTBI screening cost-effectiveness may improve uptake and health outcomes at reasonable cost. Methods: Our systematic review assessed cost-effectiveness estimates of LTBI screening/PT strategies among PLWH in lower TB incidence countries to identify model-driving inputs and methodological differences. Databases were searched 1980-2020. Studies including health economic evaluation of LTBI screening of PLWH in lower TB incidence countries (<100 cases/100,000/year) were included. Results: Of 2,644 articles screened, nine studies were included. Cost-effectiveness estimates of LTBI screening/PT for PLWH varied widely, with universal screening/PT found highly cost-effective by some studies, while only targeting to high-risk groups (such as those from mid/high TB incidence countries) deemed cost-effective by others. Cost-effectiveness of strategies screening all PLWH from studies published in the past five years varied from US$2828 to US$144,929/quality-adjusted life-year gained (2018 prices). Study quality varied, with inconsistent reporting of methods and results limiting comparability of studies. Cost-effectiveness varied markedly by screening guideline, with British HIV Association guidelines more cost-effective than NICE guidelines in the UK. Discussion: Cost-effectiveness studies of LTBI screening/PT for PLWH in lower TB incidence settings are scarce, with large variations in methods and assumptions used, target populations and screening/PT strategies evaluated. The limited evidence suggests LTBI screening/PT may be cost-effective for some PLWH groups but further research is required, particularly on strategies targeting screening/PT to PLWH at higher risk. Standardisation of model descriptions and results reporting could facilitate reliable comparisons between studies, particularly to identify those factors driving the wide disparity between cost-effectiveness estimates. Registration: PROSPERO CRD42020166338 (18/03/2020).

Causal evidence in health decision making: methodological approaches of causal inference and health decision science

Objectives

Public health decision making is a complex process based on thorough and comprehensive health technology assessments involving the comparison of different strategies, values and tradeoffs under uncertainty. This process must be based on best available evidence and plausible assumptions. Causal inference and health decision science are two methodological approaches providing information to help guide decision making in health care. Both approaches are quantitative methods that use statistical and modeling techniques and simplifying assumptions to mimic the complexity of the real world. We intend to review and lay out both disciplines with their aims, strengths and limitations based on a combination of textbook knowledge and expert experience.

Methods

To help understanding and differentiating the methodological approaches of causal inference and health decision science, we reviewed both methods with the focus on aims, research questions, methods, assumptions, limitations and challenges, and software. For each methodological approach, we established a group of four experts from our own working group to carefully review and summarize each method, followed by structured discussion rounds and written reviews, in which the experts from all disciplines including HTA and medicine were involved. The entire expert group discussed objectives, strengths and limitations of both methodological areas, and potential synergies. Finally, we derived recommendations for further research and provide a brief outlook on future trends.

Results

Causal inference methods aim for drawing causal conclusions from empirical data on the relationship of pre-specified interventions on a specific target outcome and apply a counterfactual framework and statistical techniques to derive causal effects of exposures or interventions from these data. Causal inference is based on a causal diagram, more specifically, a directed acyclic graph (DAG), which encodes the assumptions regarding the causal relations between variables. Depending on the type of confounding and selection bias, traditional statistical methods or more complex g-methods are needed to derive valid causal effects. Besides the correct specification of the DAG and the statistical model, assumptions such as consistency, positivity, and exchangeability must be checked when aiming at causal inference. Health decision science aims for guiding policy decision making regarding health interventions considering and balancing multiple competing objectives of a decision based on data from multiple sources and studies, for example prevalence studies, clinical trials and long-term observational routine effectiveness studies, and studies on preferences and costs. It involves decision analysis, a systematic, explicit and quantitative framework to guide decisions under uncertainty. Decision analyses are based on decision-analytic models to mimic the course of disease as well as aspects and consequences of the intervention in order to quantitatively optimize the decision. Depending on the type of decision problem, decision trees, state-transition models, discrete event simulation models, dynamic transmission models, or other model types are applied. Models must be validated against observed data, and comprehensive sensitivity analyses must be performed to assess uncertainty. Besides the appropriate choice of the model type and the valid specification of the model structure, it must be checked if input parameters of effects can be interpreted as causal parameters in the model. Otherwise results will be biased.

Conclusions

Both causal inference and health decision science aim for providing best causal evidence for informed health decision making. The strengths and limitations of both methods differ and a good understanding of both methods is essential for correct application but also for correct interpretation of findings from the described methods. Importantly, decision-analytic modeling should be combined with causal inference when developing guidance and recommendations regarding decisions on health care interventions.

Cost-utility analysis of the universal pneumococcal vaccination programme for older adults in Norway

The aim of this study was to establish whether the universal pneumococcal vaccination for older adults in Norway is likely to be cost-effective from the perspective of the health care provider. A decision tree model developed by the Public Health Agency of Sweden was adapted to the Norwegian setting. Two cohorts, consisting of 65-year-olds and 75-year-olds grouped into vaccinated and unvaccinated, were followed over a 5-year time horizon. In the base case, the 23-valent polysaccharide vaccine (PPV23) was used while the 13-valent pneumococcal conjugate vaccine (PCV13) was included in scenario analyses only. The costs and health benefits (measured in quality adjusted life years (QALY) gained) were compared in the two cohorts between the vaccinated and unvaccinated groups. The impact of indirect effects of the vaccine, such as herd immunity and serotype replacement, were not investigated. The relative importance of change in price was assessed by performing one-way sensitivity analyses. Under base-case assumptions, the programme for the 75-year-old cohort is expected to be dominant (cost-effective) from the health care perspective at the current maximal pharmacy retail price and at 75% vaccination coverage. In comparison, for the 65-year-old cohort the cost per QALY gained is approximately NOK 601,784 (EUR 61,281) under the base-case assumptions. A reduction in the cost of the vaccine to one quarter of its current level also brings the cost per QALY gained within the acceptable ranges in a Norwegian context for both the 65- and 75-year-old cohorts. There is no exact cost-effectiveness threshold in Norway. However, introducing a vaccination programme against pneumococcal disease for 65-year-olds in Norway is likely to fall within the acceptable range while for the 75-year-old cohort the universal programme appears to be dominant (cost-effective).

Assessing the Cost-Utility of Universal Hepatitis B Vaccination Among Adults

BACKGROUND

Although effective against hepatitis B virus (HBV) infection, hepatitis B (HepB) vaccination is only recommended for infants, children, and adults at higher risk. We conducted an economic evaluation of universal HepB vaccination among US adults.

METHODS

Using a decision analytic model with Markov disease progression, we compared current vaccination recommendations (baseline) with either 3-dose or 2-dose universal HepB vaccination (intervention strategies). In simulated modeling of 1 million adults distributed by age and risk groups, we quantified health benefits (quality-adjusted life years, QALYs) and costs for each strategy. Multivariable probabilistic sensitivity analyses identified key inputs. All costs reported in 2019 US dollars.

RESULTS

With incremental base-case vaccination coverage up to 50% among persons at lower risk and 0% increment among persons at higher risk, each of 2 intervention strategies averted nearly one-quarter of acute HBV infections (3-dose strategy, 24.8%; 2-dose strategy, 24.6%). Societal incremental cost per QALY gained of $152 722 (interquartile range, $119 113-$235 086) and $155 429 (interquartile range, $120 302-$242 226) were estimated for 3-dose and 2-dose strategies, respectively. Risk of acute HBV infection showed the strongest influence.

CONCLUSIONS

Universal adult vaccination against HBV may be an appropriate strategy for reducing HBV incidence and improving resulting health outcomes.

Ku-gaa-gii pimitizi-win, the COVID-19 cohort study of people experiencing homelessness in Toronto, Canada: a study protocol

Introduction

Initial reports suggest people experiencing homelessness (PEH) are at high risk for SARS-CoV-2 infection and associated morbidity and mortality. However, there have been few longitudinal evaluations of the spread and impact of COVID-19 among PEH. This study will estimate the prevalence and incidence of COVID-19 infections in a cohort of PEH followed prospectively in Toronto, Canada. It will also examine associations between individual-level and shelter-level characteristics with COVID-19 infection, adverse health outcomes related to infection and vaccination. Finally, the data will be used to develop and parameterise a mathematical model to characterise SARS-CoV-2 transmission dynamics, and the transmission impact of interventions serving PEH.

Design, methods and analysis

Ku-gaa-gii pimitizi-win will follow a random sample of PEH from across Toronto (Canada) for 12 months. 736 participants were enrolled between June and September 2021, and will be followed up at 3-month intervals. At each interval, specimens (saliva, capillary blood) will be collected to determine active SARS-CoV-2 infection and serologic evidence of past infection and/or vaccination, and a detailed survey will gather self-reported information, including a detailed housing history. To examine the association between individual-level and shelter-level characteristics on COVID-19-related infection, adverse outcomes, and vaccination, shelter and healthcare administrative data will be linked to participant study data. Healthcare administrative data will also be used to examine long-term (up to 5 years) COVID-19-related outcomes among participants.

Ethics and dissemination

Ethical approval was obtained from the Unity Health Toronto and University of Toronto Health Sciences Research Ethics Boards (# 20-272). Ku-gaa-gii pimitizi-win was designed in collaboration with community and service provider partners and people having lived experience of homelessness. Findings will be reported to groups supporting Ku-gaa-gii pimitizi-win, Indigenous and other community partners and service providers, funding bodies, public health agencies and all levels of government to inform policy and public health programs.

Data-Related Challenges in Cost-Effectiveness Analyses of Vaccines

Cost-effectiveness analyses (CEAs) are often prepared to quantify the expected economic value of potential vaccination strategies. Estimated outcomes and costs of vaccination strategies depend on numerous data inputs or assumptions, including estimates of vaccine efficacy and disease incidence in the absence of vaccination. Limitations in epidemiologic data can meaningfully affect both CEA estimates and the interpretation of those results by groups involved in vaccination policy decisions. Developers of CEAs should be transparent with regard to the ambiguity and uncertainty associated with epidemiologic information that is incorporated into their models. We describe selected data-related challenges to conducting CEAs for vaccination strategies, including generalizability of estimates of vaccine effectiveness, duration and functional form of vaccine protection that can change over time, indirect (herd) protection, and serotype replacement. We illustrate how CEA estimates can be sensitive to variations in specific epidemiologic assumptions, with examples from CEAs conducted for the USA that assessed vaccinations against human papillomavirus and pneumococcal disease. These challenges are certainly not limited to these two case studies and may be relevant to other vaccines.

Finding and treating early-stage HIV infections: A cost-effectiveness analysis of the Sabes study in Lima, Peru

Background

Sabes, a treatment-as-prevention intervention among men who have sex with men and transgender women in Lima, Peru, was developed to identify HIV during early primary infection (<3 months from acquisition) through monthly serologic assays and HIV RNA tests. Newly diagnosed individuals were rapidly linked to care and offered to initiate ART. In this study we sought to study the cost-effectiveness of Sabes compared to the standard of care (SOC) for HIV testing and initiation of treatment.

Methods

We adapted a compartmental model of HIV transmission to evaluate the cost-effectiveness of the Sabes approach compared to the SOC using a government health care perspective, 20-year time horizon, and 3% annual discounting. We estimated the proportion of cases of HIV detected during early primary infection, reduction in HIV incidence and prevalence, incremental cost-effectiveness ratio (ICER), and net monetary benefit. We analyzed costs using data from the Sabes study, the Peruvian Ministry of Health, published literature, and expert consultation.

Findings

The Sabes intervention is projected to identify 9294 early primary HIV infections in Lima, Peru over 20 years. The intervention costs $6,896 per early primary infection diagnosed and by 2038 is expected to decrease the fraction of early infections among prevalent infections by 62%. Sabes is expected to improve health, resulting in greater total discounted QALYs per person than the SOC (16·7 vs 16·4, respectively). Sabes had an ICER of $1431 (22% per capita GDP in Peru) per QALY compared to SOC.

Interpretation

Our analysis suggests that in Lima, Peru the Sabes intervention could be a cost-effective approach to reduce the burden of HIV even under stringent cost-effectiveness criteria. This finding suggests that programs that use frequent HIV testing, rapid linkage to care and initiation of ART should be considered as part of a comprehensive HIV prevention strategy.

Funding

National Institutes of Health.

M2HepPrEP: study protocol for a multi-site multi-setting randomized controlled trial of integrated HIV prevention and HCV care for PWID

Background

Opioid use is escalating in North America and comes with a multitude of health consequences, including HIV and hepatitis C virus (HCV) outbreaks among persons who inject drugs (PWID). HIV pre-exposure prophylaxis (PrEP) and HCV treatment regimens have transformative potential to address these co-occurring epidemics. Evaluation of innovative multi-modal approaches, integrating harm reduction, opioid agonist therapy (OAT), PrEP, and HCV treatment is required. The aim of this study is to assess the effectiveness of an on-site integrated care model where delivery of PrEP and HCV treatment for PWID takes places at syringe service programs (SSP) and OAT programs compared with referring PWID to clinical services in the community through a patient navigation model and to examine how structural factors interact with HIV prevention adherence and HCV treatment outcomes.

Methods

The Miami-Montreal Hepatitis C and Pre-Exposure Prophylaxis trial (M²HepPrEP) is an open-label, multi-site, multi-center, randomized, controlled, superiority trial with two parallel treatment arms. A total of 500 persons who injected drugs in the prior 6 months and are eligible for PrEP will be recruited in OAT clinics and SSP in Miami, FL, and Montréal, Québec. Participants will be randomized to either on-site care, with adherence counseling, or referral to off-site clinics assisted by a patient navigator. PrEP will be offered to all participants and HCV treatment to those HCV-infected. Co-primary endpoints will be (1) adherence to pre-exposure prophylaxis medication at 6 months post-randomization and (2) HCV sustained virological response (SVR) 12 weeks post-treatment completion among participants who were randomized within the HCV stratum. Up to 100 participants will be invited to participate in a semi-structured interview regarding perceptions of adherence barriers and facilitators, after their 6-month assessment. A simulation model-based cost-effectiveness analysis will be performed to determine the comparative value of the strategies being evaluated.

Discussion

The results of this study have the potential to demonstrate the effectiveness and cost-effectiveness of offering PrEP and HCV treatment in healthcare venues frequently attended by PWID. Testing the intervention in two urban centers with high disease burden among PWID, but with different healthcare system dynamics, will increase generalizability of findings.

Trial registration

Clinicaltrials.gov NCT03981445. Trial registry name: Integrated HIV Prevention and HCV Care for PWID (M2HepPrEP). Registration date: June 10, 201.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06085-3.

Evaluating the cost-effectiveness of a pre-exposure prophylaxis program for HIV prevention for men who have sex with men in Japan

Men who have sex with men (MSM) have been disproportionally affected by the HIV epidemic in many countries, including Japan. Although pre-exposure prophylaxis (PrEP) is a strong prevention tool, it is not yet approved in Japan. A Markov model was developed to describe HIV infection and disease progression in an MSM cohort (N = 1000) in Japan receiving a PrEP program. The model was used to evaluate the cost-effectiveness of a PrEP program. HIV/AIDS treatment, screening, hospitalization due to AIDS, and PrEP were considered as costs and quality-adjusted life-years (QALYs) gained as utilities. Cost-effectiveness was assessed by comparing the incremental cost-effectiveness ratio (ICER) over a 30-year period against the willingness to pay (WTP) threshold. One-way sensitivity and probabilistic sensitivity analyses were performed. With 50% PrEP coverage, the PrEP program became dominant against the program without PrEP, using a threshold of 5.0 million JPY/QALY (45,455 USD). The probabilistic sensitivity analysis revealed that the PrEP program was dominant or at least cost-effective in most cases of 10,000 simulations. Therefore, preparing cheaper PrEP pills, which results in PrEP being dominant or ICER being lower than the WTP threshold, is important to make the program cost-effective. Introduction of PrEP to an MSM cohort in Japan would be cost-effective over a 30-year time horizon.

A review of epidemiological models of Clostridioides difficile transmission and control (2009-2021)

Clostridioides difficile is the leading cause of infectious diarrhea and one of the most common healthcare-acquired infections worldwide. We performed a systematic search and a bibliometric analysis of mathematical and computational models for Clostridioides difficile transmission. We identified 33 publications from 2009 to 2021. Models have underscored the importance of asymptomatic colonized patients in maintaining transmission in health-care settings. Infection control, antimicrobial stewardship, active testing, and vaccination have often been evaluated in models. Despite active testing and vaccination being not currently implemented, they are the most commonly evaluated interventions. Some aspects of C. difficile transmission, such community transmission and interventions in health-care settings other than in acute-care hospitals, remained less evaluated through modeling.

Preventing COVID-19 outbreaks through surveillance testing in healthcare facilities: a modelling study

BACKGROUND

Surveillance testing within healthcare facilities provides an opportunity to prevent severe outbreaks of coronavirus disease 2019 (COVID-19). However, the quantitative impact of different available surveillance strategies and their potential to decrease the frequency of outbreaks are not well-understood.

METHODS

We establish an individual-based model representative of a mental health hospital yielding generalizable results. Attributes and features of this facility were derived from a prototypical hospital, which provides psychiatric, psychosomatic and psychotherapeutic treatment. We estimate the relative reduction of outbreak probability for three test strategies (entry test, once-weekly test and twice-weekly test) relative to a symptom-based baseline strategy. Based on our findings, we propose determinants of successful surveillance measures.

RESULTS

Entry Testing reduced the outbreak probability by 26%, additionally testing once or twice weekly reduced the outbreak probability by 49% or 67% respectively. We found that fast diagnostic test results and adequate compliance of the clinic population are mandatory for conducting effective surveillance. The robustness of these results towards uncertainties is demonstrated via comprehensive sensitivity analyses.

CONCLUSIONS

We conclude that active testing in mental health hospitals and similar facilities considerably reduces the number of COVID-19 outbreaks compared to symptom-based surveillance only.

Sound Decision Making in Uncertain Times: Can Systems Modelling Be Useful for Informing Policy and Planning for Suicide Prevention?

The COVID-19 pandemic demonstrated the significant value of systems modelling in supporting proactive and effective public health decision making despite the complexities and uncertainties that characterise an evolving crisis. The same approach is possible in the field of mental health. However, a commonly levelled (but misguided) criticism prevents systems modelling from being more routinely adopted, namely, that the presence of uncertainty around key model input parameters renders a model useless. This study explored whether radically different simulated trajectories of suicide would result in different advice to decision makers regarding the optimal strategy to mitigate the impacts of the pandemic on mental health. Using an existing system dynamics model developed in August 2020 for a regional catchment of Western Australia, four scenarios were simulated to model the possible effect of the COVID-19 pandemic on levels of psychological distress. The scenarios produced a range of projected impacts on suicide deaths, ranging from a relatively small to a dramatic increase. Discordance in the sets of best-performing intervention scenarios across the divergent COVID-mental health trajectories was assessed by comparing differences in projected numbers of suicides between the baseline scenario and each of 286 possible intervention scenarios calculated for two time horizons; 2026 and 2041. The best performing intervention combinations over the period 2021–2041 (i.e., post-suicide attempt assertive aftercare, community support programs to increase community connectedness, and technology enabled care coordination) were highly consistent across all four COVID-19 mental health trajectories, reducing suicide deaths by between 23.9–24.6% against the baseline. However, the ranking of best performing intervention combinations does alter depending on the time horizon under consideration due to non-linear intervention impacts. These findings suggest that systems models can retain value in informing robust decision making despite uncertainty in the trajectories of population mental health outcomes. It is recommended that the time horizon under consideration be sufficiently long to capture the full effects of interventions, and efforts should be made to achieve more timely tracking and access to key population mental health indicators to inform model refinements over time and reduce uncertainty in mental health policy and planning decisions.

Development and application of a dynamic transmission model of health systems' preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries

The global impact of COVID-19 has challenged health systems across the world. This situation highlighted the need to develop policies based on scientific evidence to prepare the health systems and mitigate the pandemic. In this scenario, governments were urged to predict the impact of the measures they were implementing, how they related to the population's behavior, and the capacity of health systems to respond to the pandemic. The overarching aim of this research was to develop a customizable and open-source tool to predict the impact of the expansion of COVID-19 on the level of preparedness of the health systems of different Latin American and the Caribbean countries, with two main objectives. Firstly, to estimate the transmission dynamics of COVID-19 and the preparedness and response capacity of health systems in those countries, based on different scenarios and public policies implemented to control, mitigate, or suppress the spread of the epidemic. Secondly, to facilitate policy makers' decisions by allowing the model to adjust its parameters according to the specific pandemic trajectory and policy context. How many infections and deaths are estimated per day?; When are the peaks of cases and deaths expected, according to the different scenarios?; Which occupancy rate will ICU services have along the epidemiological curve?; When is the optimal time increase restrictions in order to prevent saturation of ICU beds?, are some of the key questions that the model can respond, and is publicly accessible through the following link: http://shinyapps.iecs.org.ar/modelo-covid19/. This open-access and open code tool is based on a SEIR model (Susceptible, Exposed, Infected and Recovered). Using a deterministic epidemiological model, it allows to frame potential scenarios for long periods, providing valuable information on the dynamics of transmission and how it could impact on health systems through multiple customized configurations adapted to specific characteristics of each country.

A Dynamic Approach to Economic Priority Setting to Invest in Youth Mental Health and Guide Local Implementation: Economic Protocol for Eight System Dynamics Policy Models

BACKGROUND

Mental illness costs the world economy over US2.5 Bn each year, including premature mortality, morbidity, and productivity losses. Multisector approaches are required to address the systemic drivers of mental health and ensure adequate service provision. There is an important role for economics to support priority setting, identify best value investments and inform optimal implementation. Mental health can be defined as a complex dynamic system where decision makers are challenged to prospectively manage the system over time. This protocol describes the approach to equip eight system dynamics (SD) models across Australia to support priority setting and guide portfolio investment decisions, tailored to local implementation context.

METHODS

As part of a multidisciplinary team, three interlinked protocols are developed; (i) the participatory process to codesign the models with local stakeholders and identify interventions for implementation, (ii) the technical protocol to develop the SD models to simulate the dynamics of the local population, drivers of mental health, the service system and clinical outcomes, and (iii) the economic protocol to detail how the SD models will be equipped to undertake a suite of economic analysis, incorporating health and societal perspectives. Models will estimate the cost of mental illness, inclusive of service costs (health and other sectors, where necessary), quality-adjusted life years (QALYs) lost, productivity costs and carer costs. To assess the value of investing (disinvesting) in interventions, economic analysis will include return-on-investment, cost-utility, cost benefit, and budget impact to inform affordability. Economic metrics are expected to be dynamic, conditional upon changing population demographics, service system capacities and the mix of interventions when synergetic or antagonistic interactions. To support priority setting, a portfolio approach will identify best value combinations of interventions, relative to a defined budget(s). User friendly dashboards will guide decision makers to use the SD models to inform resource allocation and generate business cases for funding.

DISCUSSION

Equipping SD models to undertake economic analysis is intended to support local priority setting and help optimise implementation regarding the best value mix of investments, timing and scale. The objectives are to improve allocative efficiency, increase mental health and economic productivity.

Inclusion of Additional Unintended Consequences in Economic Evaluation: A Systematic Review of Immunization and Tuberculosis Cost-Effectiveness Analyses

OBJECTIVE

Our objective was to review economic evaluations of immunization and tuberculosis to determine the extent to which additional unintended consequences were taken into account in the analysis and to describe the methodological approaches used to estimate these, where possible.

METHODS

We sourced the vaccine economic evaluations from a previous systematic review by Nymark et al. (2009-2015) and searched PubMed/MEDLINE and Embase from 2015 to 2019 using the same search strategy. For tuberculosis economic evaluations, we extracted studies from 2009 to 2019 that were published in a previous review by Siapka et al. We followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidance. Studies were classified according to the categories and subcategories (e.g., herd immunity, non-specific effects, and labor productivity) defined in a framework identifying additional unintended consequences by Nymark and Vassall. Where possible, methods for estimating the additional unintended consequences categories and subcategories were described. We evaluated the reporting quality of included studies according to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) extraction guideline.

RESULTS

We identified 177 vaccine cost-effectiveness analyses (CEAs) between 2009 and 2019 that met the inclusion criteria. Of these, 98 included unintended consequences. Of the total 98 CEAs, overall health consequence categories were included 73 times; biological categories: herd immunity 43 times; pathogen response: resistance 15 times; and cross-protection 15 times. For health consequences pertaining to the supply-side (health systems) categories, side effects were included five times. On the nonhealth demand side (intrahousehold), labor productivity was included 60 times. We identified 29 tuberculosis CEAs from 2009 to 2019 that met the inclusion criteria. Of these, six articles included labor productivity, four included indirect transmission effects, and one included resistance. Between 2009 and 2019, only 34% of tuberculosis CEAs included additional unintended consequences, compared with 55% of vaccine CEAs.

CONCLUSIONS

The inclusion of additional unintended consequences in economic evaluations of immunization and tuberculosis continues to be limited. Additional unintended consequences of economic benefits, such as those examined in this review and especially those that occur outside the health system, offer valuable information to analysts. Further work on appropriate ways to value these additional unintended consequences is still warranted.

Economic evaluation using dynamic transition modeling of ebola virus vaccination in lower-and-middle-income countries

BACKGROUND

With the increasing occurrence of infectious diseases in lower-and-middle-income countries (LMICs), emergency preparedness is essential for rapid response and mitigation. Economic evaluations of mitigation technologies and strategies have been recommended for inclusion in emergency preparedness plans. We aimed to perform an economic evaluation using dynamic transition modeling of ebola virus disease (EVD) vaccination in a hypothetical community of 1,000 persons in the Democratic Republic of Congo (DRC).

METHOD

Using a modified SEIR (Susceptible, Exposed, Infectious, Recovered, with Death added [SEIR-D]) model that accounted for death and epidemiological data from an EVD outbreak in the DRC, we modeled the transmission of EVD in a hypothetical population of 1,000. With our model, we estimated the cost-effectiveness of an EVD vaccine and an EVD vaccination intervention.

RESULTS

The results showed vaccinating 50% of the population at risk prevented 670 cases, 538 deaths, and 22,022 disability-adjusted life years (DALYs). The vaccine was found to be cost-effective with an incremental cost-effectiveness ratio (ICER) of $95.63 per DALY averted. We also determined the minimum required vaccination coverage for cost-effectiveness to be 40%. Sensitivity analysis showed our model to be fairly robust, assuring relatively consistent results even with variations in such input parameters as cost of screening, as well as transmission, infection, incubation, and case fatality rates.

CONCLUSION

EVD vaccination in our hypothetical population was found to be cost-effective from the payer perspective. Our model presents an efficient and reliable approach for conducting economic evaluations of infectious disease interventions as part of an emergency preparedness plan.

How to Prevent Vaccines Falling Victim to Their Own Success: Intertemporal Dependency of Incidence Levels on Indirect Effects in Economic Reevaluations

OBJECTIVES

Incremental cost-effectiveness analyses may inform the optimal choice of healthcare interventions. Nevertheless, for many vaccines, benefits fluctuate with incidence levels over time. Reevaluating a vaccine after it has successfully decreased incidences may eventually cause a disease resurgence if switching to a vaccine with lower indirect benefits. Decisions may successively alternate between vaccines alongside repeated rises and falls in incidence and when indirect effects from historic use are ignored. Our suggested proposal aims to prevent suboptimal decision making.

METHODS

We used a conceptual model of demand to illustrate alternating decisions between vaccines because of time-varying levels of indirect effects. Similar to the concept of subsidies, we propose internalizing the indirect effects achievable with vaccines. In a case study over 60 years, we simulated a hypothetical 10-year reevaluation of 2 oncogenic human papillomavirus vaccines, of which only 1 protects additionally against anogenital warts.

RESULTS

Our case study showed that the vaccine with additional warts protection is initially valued higher than the vaccine without additional warts protection. After 10 years, this differential decreases because of declines in warts incidence, which supports switching to the nonwarts vaccine that causes a warts resurgence eventually. Instead, pricing the indirect effects separately supports continuing with the warts vaccine.

CONCLUSIONS

Ignoring how the observed incidences depend on the indirect effects achieved with a particular vaccine may lead to repeated changes in vaccines at successive reevaluations, with unintended resurgences, economic inefficiencies, and eroding vaccine confidence. We propose internalizing indirect effects to prevent vaccines falling victim to their own success.

Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines

BACKGROUND

The importance of infectious disease epidemic forecasting and prediction research is underscored by decades of communicable disease outbreaks, including COVID-19. Unlike other fields of medical research, such as clinical trials and systematic reviews, no reporting guidelines exist for reporting epidemic forecasting and prediction research despite their utility. We therefore developed the EPIFORGE checklist, a guideline for standardized reporting of epidemic forecasting research.

METHODS AND FINDINGS

We developed this checklist using a best-practice process for development of reporting guidelines, involving a Delphi process and broad consultation with an international panel of infectious disease modelers and model end users. The objectives of these guidelines are to improve the consistency, reproducibility, comparability, and quality of epidemic forecasting reporting. The guidelines are not designed to advise scientists on how to perform epidemic forecasting and prediction research, but rather to serve as a standard for reporting critical methodological details of such studies.

CONCLUSIONS

These guidelines have been submitted to the EQUATOR network, in addition to hosting by other dedicated webpages to facilitate feedback and journal endorsement.

Protocol for the economic evaluation of COVID-19 pandemic response policies

INTRODUCTION

Several treatment options are available for COVID-19 to date. However, the use of a combination of non-pharmaceutical interventions (NPIs) is necessary for jurisdictions to contain its spread. Although the implementation cost of NPIs may be low from the healthcare system perspective, it can be costly when considering the indirect costs from the societal perspective. COVID-19 vaccination campaigns have begun in several countries worldwide. Nonetheless, the quantity of vaccines available remain limited over the next 1 to 2 years. A tool for informing vaccine prioritisation that considers both cost and effectiveness will be highly useful. This study aims to identify the most cost-effective combination of COVID-19 response policies, using Singapore as an example.

METHODS AND ANALYSIS

An age-stratified Susceptible-Exposed-Infectious-Recovered model will be used to generate the number of infections stratified by disease severity under different intervention scenarios. Polices of interest include test-trace-isolate, travel restriction, compulsory face mask and hygiene practices, social distancing, dexamethasone/remdesivir therapy and vaccination. The latest phase 3 trial results and the WHO Target Product Profiles for COVID-19 vaccines will be used to model vaccine characteristics. A cost (expected resource utilisation and productivity losses) and quality-adjusted life years (QALYs) will be attached to these outputs for a cost-utility analysis. The primary outcome measure will be the incremental cost-effectiveness ratio generated from the incremental cost of policy alternatives expressed as a ratio of the incremental benefits (QALYs gained). Efficacy of policy options will be gathered from literature review and from its observed impacts in Singapore. Cost data will be gathered from healthcare institutions, Ministry of Health and published data. Sensitivity analysis such as threshold analysis and scenario analysis will be conducted.

ETHICS AND DISSEMINATION

Ethics approval was not required for this study. The study findings will be disseminated through peer-reviewed journals.

Constructing public health evidence knowledge graph for decision-making support from COVID-19 literature of modelling study

The needs of mitigating COVID-19 epidemic prompt policymakers to make public health-related decision under the guidelines of science. Tremendous unstructured COVID-19 publications make it challenging for policymakers to obtain relevant evidence. Knowledge graphs (KGs) can formalize unstructured knowledge into structured form and have been used in supporting decision-making recently. Here, we introduce a novel framework that can extract the COVID-19 public health evidence knowledge graph (CPHE-KG) from papers relating to a modelling study. We screen out a corpus of 3096 COVID-19 modelling study papers by performing a literature assessment process. We define a novel annotation schema to construct the COVID-19 modelling study-related IE dataset (CPHIE). We also propose a novel multi-tasks document-level information extraction model SS-DYGIE++ based on the dataset. Leveraging the model on the new corpus, we construct CPHE-KG containing 60,967 entities and 51,140 relations. Finally, we seek to apply our KG to support evidence querying and evidence mapping visualization. Our SS-DYGIE++(SpanBERT) model has achieved a F1 score of 0.77 and 0.55 respectively in document-level entity recognition and coreference resolution tasks. It has also shown high performance in the relation identification task. With evidence querying, our KG can present the dynamic transmissions of COVID-19 pandemic in different countries and regions. The evidence mapping of our KG can show the impacts of variable non-pharmacological interventions to COVID-19 pandemic. Analysis demonstrates the quality of our KG and shows that it has the potential to support COVID-19 policy making in public health.

Advancing sustainable development goals through immunization: a literature review

BACKGROUND

Immunization directly impacts health (SDG3) and brings a contribution to 14 out of the 17 Sustainable Development Goals (SDGs), such as ending poverty, reducing hunger, and reducing inequalities. Therefore, immunization is recognized to play a central role in reaching the SDGs, especially in low- and middle-income countries (LMICs). Despite continuous interventions to strengthen immunization systems and to adequately respond to emergency immunization during epidemics, the immunization-related indicators for SDG3 lag behind in sub-Saharan Africa. Especially taking into account the current Covid19 pandemic, the current performance on the connected SDGs is both a cause and a result of this.

METHODS

We conduct a literature review through a keyword search strategy complemented with handpicking and snowballing from earlier reviews. After title and abstract screening, we conducted a qualitative analysis of key insights and categorized them according to showing the impact of immunization on SDGs, sustainability challenges, and model-based solutions to these challenges.

RESULTS

We reveal the leveraging mechanisms triggered by immunization and position them vis-à-vis the SDGs, within the framework of Public Health and Planetary Health. Several challenges for sustainable control of vaccine-preventable diseases are identified: access to immunization services, global vaccine availability to LMICs, context-dependent vaccine effectiveness, safe and affordable vaccines, local/regional vaccine production, public-private partnerships, and immunization capacity/capability building. Model-based approaches that support SDG-promoting interventions concerning immunization systems are analyzed in light of the strategic priorities of the Immunization Agenda 2030.

CONCLUSIONS

In general terms, it can be concluded that relevant future research requires (i) design for system resilience, (ii) transdisciplinary modeling, (iii) connecting interventions in immunization with SDG outcomes, (iv) designing interventions and their implementation simultaneously, (v) offering tailored solutions, and (vi) model coordination and integration of services and partnerships. The research and health community is called upon to join forces to activate existing knowledge, generate new insights and develop decision-supporting tools for Low-and Middle-Income Countries' health authorities and communities to leverage immunization in its transformational role toward successfully meeting the SDGs in 2030.