Using integrated modeling to support the global eradication of vaccine-preventable diseases

Health Economic Analysis of Antiviral Drugs in the Global Polio Eradication Endgame

BACKGROUND

Polio antiviral drugs (PAVDs) may provide a critical tool in the eradication endgame by stopping poliovirus infections in immunodeficient individuals who may not clear the virus without therapeutic intervention. Although prolonged/chronic poliovirus excreters are rare, they represent a source of poliovirus reintroduction into the general population. Prior studies that assumed the successful cessation of all oral poliovirus vaccine (OPV) use estimated the potential upper bound of the incremental net benefits (INBs) of resource investments in research and development of PAVDs. However, delays in polio eradication, OPV cessation, and the development of PAVDs necessitate an updated economic analysis to reevaluate the costs and benefits of further investments in PAVDs.

METHODS

Using a global integrated model of polio transmission, immunity, vaccine dynamics, risks, and economics, we explore the risks of reintroduction of polio transmission due to immunodeficiency-related vaccine-derived poliovirus (iVDPV) excreters and reevaluate the upper bound of the INBs of PAVDs.

RESULTS

Under the current conditions, for which the use of OPV will likely continue for the foreseeable future, even with successful eradication of type 1 wild poliovirus by the end of 2023 and continued use of Sabin OPV for outbreak response, we estimate an upper bound INB of 60 million US$2019. With >100 million US$2019 already invested in PAVD development and with the introduction of novel OPVs that are less likely to revert to neurovirulence, our analysis suggests the expected INBs of PAVDs would not offset their costs.

CONCLUSIONS

While PAVDs could play an important role in the polio endgame, their expected economic benefits drop with ongoing OPV use and poliovirus transmissions. However, stakeholders may pursue the development of PAVDs as a desired product regardless of their economic benefits.HighlightsWhile polio antiviral drugs could play an important role in the polio endgame, their expected economic benefits continue to drop with delays in polio eradication and the continued use of oral poliovirus vaccines.The incremental net benefits of investments in polio antiviral drug development and screening for immunodeficiency-related circulating polioviruses are small.Limited global resources are better spent on increasing global population immunity to polioviruses to stop and prevent poliovirus transmission.

Looking back at prospective modeling of outbreak response strategies for managing global type 2 oral poliovirus vaccine (OPV2) cessation

Introduction

Detection of poliovirus transmission and ongoing oral poliovirus vaccine (OPV) use continue to delay poliomyelitis eradication. In 2016, the Global Polio Eradication Initiative (GPEI) coordinated global cessation of type 2 OPV (OPV2) for preventive immunization and limited its use to emergency outbreak response. In 2019, GPEI partners requested restart of some Sabin OPV2 production and also accelerated the development of a genetically modified novel OPV2 vaccine (nOPV2) that promised greater genetic stability than monovalent Sabin OPV2 (mOPV2).

Methods

We reviewed integrated risk, economic, and global poliovirus transmission modeling performed before OPV2 cessation, which recommended multiple risk management strategies to increase the chances of successfully ending all transmission of type 2 live polioviruses. Following OPV2 cessation, strategies implemented by countries and the GPEI deviated from model recommended risk management strategies. Complementing other modeling that explores prospective outbreak response options for improving outcomes for the current polio endgame trajectory, in this study we roll back the clock to 2017 and explore counterfactual trajectories that the polio endgame could have followed if GPEI had: (1) managed risks differently after OPV2 cessation and/or (2) developed nOPV2 before and used it exclusively for outbreak response after OPV2 cessation.

Results

The implementation of the 2016 model-based recommended outbreak response strategies could have ended (and could still substantially improve the probability of ending) type 2 poliovirus transmission. Outbreak response performance observed since 2016 would not have been expected to achieve OPV2 cessation with high confidence, even with the availability of nOPV2 prior to the 2016 OPV2 cessation.

Discussion

As implemented, the 2016 OPV2 cessation failed to stop type 2 transmission. While nOPV2 offers benefits of lower risk of seeding additional outbreaks, its reduced secondary spread relative to mOPV2 may imply relatively higher coverage needed for nOPV2 than mOPV2 to stop outbreaks.

Collaboration-competition dilemma in flattening the COVID-19 curve

Testing for COVID-19 is a key intervention that supports tracking and isolation to prevent further infections. However, diagnostic tests are a scarce and finite resource, so abundance in one country can quickly lead to shortages in others, creating a competitive landscape. Countries experience peaks in infections at different times, meaning that the need for diagnostic tests also peaks at different moments. This phase lag implies opportunities for a more collaborative approach, although countries might also worry about the risks of future shortages if they help others by reallocating their excess inventory of diagnostic tests. This article features a simulation model that connects three subsystems: COVID-19 transmission, the diagnostic test supply chain, and public policy interventions aimed at flattening the infection curve. This integrated system approach clarifies that, for public policies, there is a time to be risk-averse and a time for risk-taking, reflecting the different phases of the pandemic (contagion vs. recovery) and the dominant dynamic behavior that occurs in these phases (reinforcing vs. balancing). In the contagion phase, policymakers cannot afford to reject extra diagnostic tests and should take what they can get, in line with a competitive mindset. In the recovery phase, policymakers can afford to give away excess inventory to other countries in need (one-sided collaboration). When a country switches between taking and giving, in a form of two-sided collaboration, it can flatten the curve, not only for itself but also for others.

Tools for Supporting the MCH Workforce in Addressing Complex Challenges: A Scoping Review of System Dynamics Modeling in Maternal and Child Health

Objectives

System Dynamics (SD) is a promising decision support modeling approach for growing shared understanding of complex maternal and child health (MCH) trends. We sought to inventory published applications of SD to MCH topics and introduce the MCH workforce to these approaches through examples to support further iteration and use.

Methods

We conducted a systematic search (1958–2018) for applications of SD to MCH topics and characterized identified articles, following PRISMA guidelines. Pairs of experts abstracted information on SD approach and MCH relevance.

Results

We identified 101 articles describing applications of SD to MCH topics. Approach: 27 articles present qualitative diagrams, 10 introduce concept models that begin to quantify dynamics, and 67 present more fully tested/analyzed models. Purpose: The most common purposes described were to increase understanding (n = 55) and support strategic planning (n = 26). While the majority of studies (n = 53) did not involve stakeholders, 40 included what we considered to be a high level of stakeholder engagement – a strength of SD for MCH. Topics: The two Healthy People 2020 topics addressed most frequently were early and middle childhood (n = 30) and access to health services (n = 26). The most commonly addressed SDG goals were “End disease epidemics” (n = 26) and “End preventable deaths” (n = 26).

Conclusions for Practice

While several excellent examples of the application of SD in MCH were found, SD is still underutilized in MCH. Because SD is particularly well-suited to studying and addressing complex challenges with stakeholders, its expanded use by the MCH workforce could inform an understanding of contemporary MCH challenges.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10995-022-03376-8.

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.

An evaluation of Hamiltonian Monte Carlo performance to calibrate age-structured compartmental SEIR models to incidence data

Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo method to estimate unknown quantities through sample generation from a target distribution for which an analytical solution is difficult. The strength of this method lies in its geometrical foundations, which render it efficient for traversing high-dimensional spaces. First, this paper analyses the performance of HMC in calibrating five variants of inputs to an age-structured SEIR model. Four of these variants are related to restriction assumptions that modellers devise to handle high-dimensional parameter spaces. The other one corresponds to the unrestricted symmetric variant. To provide a robust analysis, we compare HMC's performance to that of the Nelder-Mead algorithm (NMS), a common method for non-linear optimisation. Furthermore, the calibration is performed on synthetic data in order to avoid confounding effects from errors in model selection. Then, we explore the variation in the method's performance due to changes in the scale of the problem. Finally, we fit an SEIR model to real data. In all the experiments, the results show that HMC approximates both the synthetic and real data accurately, and provides reliable estimates for the basic reproduction number and the age-dependent transmission rates. HMC's performance is robust in the presence of underreported incidences and high-dimensional complexity. This study suggests that stringent assumptions on age-dependent transmission rates can be lifted in favour of more realistic representations. The supplementary section presents the full set of results.

Review of poliovirus modeling performed from 2000 to 2019 to support global polio eradication

INTRODUCTION

Over the last 20 years (2000-2019) the partners of the Global Polio Eradication Initiative (GPEI) invested in the development and application of mathematical models of poliovirus transmission as well as economics, policy, and risk analyses of polio endgame risk management options, including policies related to poliovirus vaccine use during the polio endgame.

AREAS COVERED

This review provides a historical record of the polio studies published by the three modeling groups that primarily performed the bulk of this work. This review also systematically evaluates the polio transmission and health economic modeling papers published in English in peer-reviewed journals from 2000 to 2019, highlights differences in approaches and methods, shows the geographic coverage of the transmission modeling performed, identified common themes, and discusses instances of similar or conflicting insights or recommendations.

EXPERT OPINION

Polio modeling performed during the last 20 years substantially impacted polio vaccine choices, immunization policies, and the polio eradication pathway. As the polio endgame continues, national preferences for polio vaccine formulations and immunization strategies will likely continue to change. Future modeling will likely provide important insights about their cost-effectiveness and their relative benefits with respect to controlling polio and potentially achieving and maintaining eradication.

Simulation-based estimation of the early spread of COVID-19 in Iran: actual versus confirmed cases

Understanding the state of the COVID-19 pandemic relies on infection and mortality data. Yet official data may underestimate the actual cases due to limited symptoms and testing capacity. We offer a simulation-based approach which combines various sources of data to estimate the magnitude of outbreak. Early in the epidemic we applied the method to Iran's case, an epicenter of the pandemic in winter 2020. Estimates using data up to March 20th, 2020, point to 916,000 (90% UI: 508 K, 1.5 M) cumulative cases and 15,485 (90% UI: 8.4 K, 25.8 K) total deaths, numbers an order of magnitude higher than official statistics. Our projections suggest that absent strong sustaining of contact reductions the epidemic may resurface. We also use data and studies from the succeeding months to reflect on the quality of original estimates. Our proposed approach can be used for similar cases elsewhere to provide a more accurate, early, estimate of outbreak state. © 2020 System Dynamics Society.

Identifying hotspots for antibiotic resistance emergence and selection, and elucidating pathways to human exposure: Application of a systems-thinking approach to aquaculture systems

Aquaculture systems are highly complex, dynamic and interconnected systems influenced by environmental, biological, cultural, socio-economic and human behavioural factors. Intensification of aquaculture production is likely to drive indiscriminate use of antibiotics to treat or prevent disease and increase productivity, often to compensate for management and husbandry deficiencies. Surveillance or monitoring of antibiotic usage (ABU) and antibiotic resistance (ABR) is often lacking or absent. Consequently, there are knowledge gaps for the risk of ABR emergence and human exposure to ABR in these systems and the wider environment. The aim of this study was to use a systems-thinking approach to map two aquaculture systems in Vietnam - striped catfish and white-leg shrimp - to identify hotspots for emergence and selection of resistance, and human exposure to antibiotics and antibiotic-resistant bacteria. System mapping was conducted by stakeholders at an interdisciplinary workshop in Hanoi, Vietnam during January 2018, and the maps generated were refined until consensus. Thereafter, literature was reviewed to complement and cross-reference information and to validate the final maps. The maps and component interactions with the environment revealed the grow-out phase, where juveniles are cultured to harvest size, to be a key hotspot for emergence of ABR in both systems due to direct and indirect ABU, exposure to water contaminated with antibiotics and antibiotic-resistant bacteria, and duration of this stage. The pathways for human exposure to antibiotics and ABR were characterised as: occupational (on-farm and at different handling points along the value chain), through consumption (bacterial contamination and residues) and by environmental routes. By using systems thinking and mapping by stakeholders to identify hotspots we demonstrate the applicability of an integrated, interdisciplinary approach to characterising ABU in aquaculture. This work provides a foundation to quantify risks at different points, understand interactions between components, and identify stakeholders who can lead and implement change.

Adoption of New Medical Technologies: The Case of Customized Individually Made Knee Implants

OBJECTIVES

To investigate the impact of insurance coverage on the adoption of customized individually made (CIM) knee implants and to compare patient outcomes and cost effectiveness of off-the-shelf and CIM implants.

METHODS

A system dynamics simulation model was developed to study adoption dynamics of CIM and meet the research objectives. The model reproduced the historical data on primary and revision knee replacement implants obtained from the literature and the Nationwide Inpatient Sample. Then the dynamics of adoption of CIM implants were simulated from 2018 to 2026. The rate of 90-day readmission, 3-year revision surgery, recovery period, time savings in operating rooms, and the associated cost within 3 years of primary knee replacement implants were used as performance metrics.

RESULTS

The simulation results indicate that by 2026, an adoption rate of 90% for CIM implants can reduce the number of readmissions and revision surgeries by 62% and 39%, respectively, and can save hospitals and surgeons 6% on procedure time and cut down cumulative healthcare costs by approximately $38 billion.

CONCLUSIONS

CIM implants have the potential to deliver high-quality care while decreasing overall healthcare costs, but their adoption requires the expansion of current insurance coverage. This work presents the first systematic study to understand the dynamics of adoption of CIM knee implants and instrumentation. More broadly, the current modeling approach and systems thinking perspective could be used to consider the adoption of any emerging customized therapies for personalized medicine.