Explore the vast range of titles available.

Estimating the value of global investment in immunization programs is critical to helping decision makers plan and mobilize immunization programs and allocate resources required to realize their full benefits. We estimated economic benefits using cost-of-illness and value-of-a-statistical-life approaches and combined this estimation with immunization program costs to derive the return on investment from immunization programs against ten pathogens for ninety-four low- and middle-income countries for the period 2011-30. Using the cost-of-illness approach, return on investment for one dollar invested in immunization against our ten pathogens was 26.1 for the ninety-four countries from 2011 to 2020 and 19.8 from 2021 to 2030. Using the value-of-a-statistical-life approach, return on investment was 51.0 from 2011 to 2020 and 52.2 from 2021 to 2030. The results demonstrate continued high return on investment from immunization programs. The return-on-investment estimates from this study will inform country policy makers and decision makers in funding agencies and will contribute to efforts to mobilize resources for immunization. Realization of the full benefits of immunization will depend on sustained investment in and commitment to immunization programs.

Background Given patient preferences, the choice of delivery modality for vaccines against SARS-CoV-2 has the potential to significantly impact both health and economic consequences of an outbreak of COVID-19. This study models the projected health and economic impact of an oral COVID-19 vaccine in the United States during an outbreak occurring between December 1, 2021 and February 16, 2022.  Methods A cost-of-illness economic decision analysis model is utilized to assess both the health and economic impact of an oral vaccine delivery platform compared with the status quo deployment of existing intramuscular vaccines against COVID-19. Health impact is assessed in terms of predicted cases, deaths, hospitalization days, intensive care unit admission days, and mechanical ventilation days averted. Health system economic impact is assessed based on the cost-of-illness averted derived from the average daily costs of medical care, stratified by severity. Productivity loss due to premature death is estimated based on regulatory analysis guidelines proposed by the U.S. Department of Health and Human Services.  Results Based upon preference data, we estimate that the availability of an oral COVID-19 vaccine would increase vaccine uptake from 214 million people to 232 million people. This higher vaccination rate was estimated to result in 2,497,087 fewer infections, 25,709 fewer deaths, 1,365,497 fewer hospitalization days, 186,714 fewer Intensive Care Unit (ICU) days, and 80,814 fewer patient days requiring mechanical ventilation (MV) compared with the status quo. From a health systems perspective, this translates into $3.3 billion in health sector costs averted. An additional $139-$450 billion could have been averted in productivity loss due to a reduction in premature deaths. Conclusions Vaccine delivery modalities that are aligned with patient preferences have the ability to increase vaccination uptake and reduce both the health and economic impact of an outbreak of COVID-19. We estimate that the total economic impact of productivity loss and health systems cost-of-illness averted from an oral vaccine could range from 0.6%-2.9% of 2021 U.S, Gross Domestic Product (GDP).

We estimated immunization program costs, financing, and funding gaps for sixteen vaccines among ninety-four low- and middle-income countries during the period 2011-30. Inputs were obtained from the Institute for Health Metrics and Evaluation, the 2020 Decade of Vaccine Economics costing analysis, the World Health Organization, Gavi, and the United Nations Children's Fund. We found a total funding gap of $38.4 billion between 2011 and 2030, with the cost of immunization delivery being the main driver (86 percent) of the funding gap. On average, government financing of vaccination programs steadily rises throughout the period. However, the decline in both Gavi and development assistance for health (DAH) financing anticipated between 2011 and 2030 outpaces the forecasted increases in domestic government immunization spending. Probabilistic sensitivity analysis was applied to both the costing and the scenario analyses to address uncertainty in the financing of vaccines and vaccine delivery. The results highlight a narrowing gap for vaccine acquisition but a growing gap for vaccine delivery, which emphasizes the critical need for resource mobilization and sustainable financial strategies for immunization programs at national and global levels, as well as a need to address the COVID-19 pandemic's potential effects on government financing for vaccines between 2021 and 2030.

Malaria is a leading global health problem that was responsible for an estimated 619,000 deaths worldwide in 2021. We modeled the return on investment (ROI) for the introduction and continuation of a four-dose malaria vaccine, RTS,S/AS01, from 2021 to 2030 in twenty sub-saharan African countries supported by Gavi, the Vaccine Alliance. We used the Decade of Vaccine Economics benefits and costing outputs to calculate an ROI using health impact data modeled by the Swiss Tropical and Public Health Institute (hereafter \"Swiss\") and Imperial College London (hereafter \"Imperial\"). The Swiss estimates with a base vaccine price of US$7.00 resulted in an ROI of 0.42, and the Imperial impact estimates with the same base vaccine price resulted in an ROI of 2.30. Inclusion of the fifth seasonal dose for ten countries exhibiting high seasonal disease burden increased the Swiss ROI by 143 percent, to 1.02, and the Imperial ROI by 23.5 percent, to 2.84. To improve ROI, decision makers should continue to improve delivery platforms, decrease vaccine delivery costs, deliver the malaria vaccine in fewer doses, and provide access to vaccine resources.

In 2021, an estimated 18 million children did not receive a single dose of routine vaccinations and constitute the population known as zero dose children. There is growing momentum and investment in reaching zero dose children and addressing the gross inequity in the reach of immunization services. To effectively do so, there is an urgent need to characterize more deeply the population of zero dose children and the barriers they face in accessing routine immunization services. We utilized the most recent DHS and MICS data spanning 2011 to 2020 from low, lower-middle, and upper-middle income countries. Zero dose status was defined as children aged 12-23 months who had not received any doses of BCG, DTP-containing, polio, and measles-containing vaccines. We estimated the prevalence of zero-dose children in the entire study sample, by country income level, and by region, and characterized the zero dose population by household-level factors. Multivariate logistic regressions were used to determine the household-level sociodemographic and health care access factors associated with zero dose immunization status. To pool multicountry data, we adjusted the original survey weights according to the country's population of children 12-23 months of age. To contextualize our findings, we utilized United Nations Population Division birth cohort data to estimate the study population as a proportion of the global and country income group populations. We included a total of 82 countries in our univariate analyses and 68 countries in our multivariate model. Overall, 7.5% of the study population were zero dose children. More than half (51.9%) of this population was concentrated in African countries. Zero dose children were predominantly situated in rural areas (75.8%) and in households in the lowest two wealth quintiles (62.7%) and were born to mothers who completed fewer than four antenatal care (ANC) visits (66.5%) and had home births (58.5%). Yet, surprisingly, a considerable proportion of zero dose children's mothers did receive appropriate care during pregnancy (33.5% of zero dose children have mothers who received at least 4 ANC visits). When controlled for other factors, children had three times the odds (OR = 3.00, 95% CI: 2.72, 3.30) of being zero dose if their mother had not received any tetanus injections, 2.46 times the odds (95% CI: 2.21, 2.74) of being zero dose if their mother had not received any ANC visits, and had nearly twice the odds (OR = 1.87, 95% CI: 1.70, 2.05) of being zero dose if their mother had a home delivery, compared to children of mothers who received at least 2 tetanus injections, received at least 4 ANC visits, and had a facility delivery, respectively. A lack of access to maternal health care was a strong risk factor of zero dose status and highlights important opportunities to improve the quality and integration of maternal and child health programs. Additionally, because a substantial proportion of zero dose children and their mothers do receive appropriate care, approaches to reach zero dose children should incorporate mitigating missed opportunities for vaccination.

Background Long-lasting insecticidal nets (LLINs) form a physical and chemical barrier against mosquitoes and have been shown to reduce malaria burden and mortality. Many countries, Uganda inclusive have distributed LLINs free of charge, drastically increasing LLIN ownership. However, ownership does not directly translate in to LLIN use. Methods Data from serial cross-sectional surveys were obtained from LLIN Evaluation in Uganda Project (LLINEUP); a cluster-randomized trial conducted in eastern and western Uganda. We apply the Vaccine Economics Research for Sustainability and Equity (VERSE) Toolkit to analyze LLIN usage and equity among household members before and after a nationwide mass distribution campaign in 48 districts. Results Overall, the proportion of household members who slept under a bed net a night prior to survey reduced from 85.4% (6 months), to 78.8% (12 months), and to 73.0% (at 18 months) following LLIN mass distribution campaign). The Wagstaff concentration indices were 0.131 at baseline and ranged between 0.023 to 0.051 between 6 and 18 months following the national LLIN campaign. This indicates that LLIN use is more prevalent amongst the more privileged people. At baseline, the Absolute Equity Gap (AEG) of 0.260 implied that the 20% most disadvantaged households would need to increase LLIN use by 26.0 percentage points to have similar levels as the top 20% most privileged households. Overall, inequity decomposition showed that relationship to household head was the major contributor to whether a household member slept under LLIN the previous night for their age in most timepoint with the exception at baseline. Conclusions LLIN use level significantly increased following a nationwide distribution campaign. It appears that respondent’s relationship with the household head explains most of the variation in LLIN use, while the least wealthy households seem to be dropping off at a faster rate in the use of LLINs following a nationwide distribution campaign. Strategies targeting LLIN use among the most disadvantaged households following a mass distribution campaigns are recommended.

Background India has made substantial progress in improving child health in recent years. However, the country continues to account for a large number of vaccine preventable child deaths. We estimated wealth-related full immunization inequalities in India. We also calculated the degree to which predisposing, reinforcing, and enabling factors contribute to these inequalities. Methods We used data from the two rounds of a large nationally representative survey done in all states in India in 2005–06 ( n  = 9582) and 2015–16 ( n  = 49,284). Full immunization status was defined as three doses of diphtheria-tetanus-pertussis vaccine, three doses of polio vaccine, one dose of Bacillus Calmette–Guérin vaccine, and one dose of measles vaccine in children 12–23 months. We compared full immunization coverage by wealth quintiles using descriptive statistics. We calculated concentration indices for full immunization coverage at the national and state levels. Using predisposing, reinforcing, and enabling factors associated with full immunization status identified from the literature, we applied a generalized linear model (GLM) framework with a binomial distribution and an identity link to decompose the concentration index. Results National full immunization coverage increased from 43.65% in 2005–06 to 62.46% in 2015–16. Overall, full immunization coverage in both 2005–06 and 2015–16 in all states was lowest in children from poorer households and improved with increasing socioeconomic status. The national concentration index decreased from 0.36 to 0.13 between the two study periods, indicating a reduction in poor-rich inequality. Similar reductions were observed for most states, except in states where inequalities were already minimal (i.e., Tamil Nadu) and in some northeastern states (i.e., Meghalaya and Manipur). In 2005–06, the contributors to wealth-related full immunization inequality were antenatal care, maternal education, and socioeconomic status. The same factors contributed to full immunization inequality in 2015–16 in addition to difficulty reaching a health facility. Conclusions Immunization coverage and wealth-related equality have improved nationally and in most states over the last decade in India. Targeted, context-specific interventions could help address overall wealth-related full immunization inequalities. Intensified government efforts could help in this regard, particularly in high-focus states where child mortality remains high.

Introduction: Following a call from the World Health Organization in 2017 for a methodology to monitor immunization coverage equity in line with the 2030 Agenda for Sustainable Development, this study applies the Vaccine Economics Research for Sustainability and Equity (VERSE) vaccination equity toolkit to measure national-level inequity in immunization coverage using a multidimensional ranking procedure and compares this with traditional wealth-quintile based ranking methods for assessing inequity. The analysis covers 56 countries with a most recent Demographic & Health Survey (DHS) between 2010 and 2022. The vaccines examined include Bacillus Calmette–Guerin (BCG), Diphtheria–Tetanus–Pertussis-containing vaccine doses 1 through 3 (DTP1–3), polio vaccine doses 1–3 (Polio1–3), the measles-containing vaccine first dose (MCV1), and an indicator for being fully immunized for age with each of these vaccines. Materials & Methods: The VERSE equity toolkit is applied to 56 DHS surveys to rank individuals by multiple disadvantages in vaccination coverage, incorporating place of residence (urban/rural), geographic region, maternal education, household wealth, sex of the child, and health insurance coverage. This rank is used to estimate a concentration index and absolute equity coverage gap (AEG) between the top and bottom quintiles, ranked by multiple disadvantages. The multivariate concentration index and AEG are then compared with traditional concentration index and AEG measures, which use household wealth as the sole criterion for ranking individuals and determining quintiles. Results: We find significant differences between the two sets of measures in almost all settings. For fully-immunized for age status, the inequities captured using the multivariate metric are between 32% and 324% larger than what would be captured examining inequities using traditional metrics. This results in a missed coverage gap of between 1.1 and 46.4 percentage points between the most and least advantaged. Conclusions: The VERSE equity toolkit demonstrated that wealth-based inequity measures systematically underestimate the gap between the most and least advantaged in fully-immunized for age coverage, correlated with maternal education, geography, and sex by 1.1–46.4 percentage points, globally. Closing the coverage gap between the bottom and top wealth quintiles is unlikely to eliminate persistent socio-demographic inequities in either coverage or access to vaccines. The results suggest that pro-poor interventions and programs utilizing needs-based targeting, which reflects poverty only, should expand their targeting criteria to include other dimensions to reduce systemic inequalities, holistically. Additionally, a multivariate metric should be considered when setting targets and measuring progress toward reducing inequities in healthcare coverage.

Vaccine confidence and coverage decreased following a death temporally but not causally related to measles vaccination in Ukraine in 2008. Large measles outbreaks including international exportations followed. Herein we characterize this experience including associated costs. Mixed-methods were used to characterize this vaccine safety incident and quantify health and economic costs. Qualitative interviews illuminate the incident, social climate, and corruption that influenced vaccine confidence in Ukraine. A literature review explored attitudes toward vaccines in the USSR and post-independence Ukraine. Infectious disease incidence was examined before and after the vaccine safety incident. An economic analysis estimated associated healthcare costs, including prevention and outbreak control measures, additional vaccination activities due to failure of the 2008 campaign, treatment costs for new cases domestically and foreign exportation, and productivity loss from treatment time and mortality for new cases. Vaccine hesitancy and distrust in government and public health programs due to corruption existed in Ukraine before the vaccine safety incident. The mishandling of the 2008 incident catalyzed the decline of vaccine confidence and prompted poor procurement decisions, leading to a drop in infant vaccination coverage, increased domestic measles cases, and exportation of measles. The estimated cost of this incident was approximately $140 million from 2008 to 2018. Absent a rapid and credible vaccine safety response, a coincidental death following immunization resulted in major outbreaks of measles with substantial economic costs. Adequate investments in a post-licensure safety system may help avoid similar future incidents.

Human behavior plays a crucial role in infectious disease transmission, yet traditional models often overlook or oversimplify this factor, limiting predictions of disease spread and the associated socioeconomic impacts. Here we introduce a feedback-informed epidemiological model that integrates human behavior with disease dynamics in a credible, tractable, and extendable manner. From economics, we incorporate a dynamic decision-making model where individuals assess the trade-off between disease risks and economic consequences, and then link this to a risk-stratified compartmental model of disease spread taken from epidemiology. In the unified framework, heterogeneous individuals make choices based on current and future payoffs, influencing their risk of infection and shaping population-level disease dynamics. As an example, we model disease-decision feedback during the early months of the COVID-19 pandemic, when the decision to participate in paid, in-person work was a major determinant of disease risk. Comparing the impacts of stylized policy options representing mandatory, incentivized/compensated, and voluntary work abstention, we find that accounting for disease-behavior feedback has a significant impact on the relative health and economic impacts of policies. Including two crucial dimensions of heterogeneity—health and economic vulnerability—the results highlight how inequities between risk groups can be exacerbated or alleviated by disease control measures. Importantly, we show that a policy of more stringent workplace testing can potentially slow virus spread and, surprisingly, increase labor supply since individuals otherwise inclined to remain at home to avoid infection perceive a safer workplace. In short, our framework permits the exploration of avenues whereby health and wealth need not always be at odds. This flexible and extendable modeling framework offers a powerful tool for understanding the interplay between human behavior and disease spread.