Modelling the first dose of measles vaccination: the role of maternal immunity, demographic factors, and delivery systems

Trends of measles in Tanzania: A 5-year review of case-based surveillance data, 2018-2022

OBJECTIVES

Tanzania observed a gradual increase in the number of measles cases since 2019 with a large outbreak recorded during 2022. This study describes the trend of measles in Tanzania over a 5-year period from 2018-2022.

METHODS

This was a descriptive study conducted using routine measles case-based surveillance system including 195 councils of the United Republic of Tanzania.

RESULTS

Between 2018 and 2022 there were 12,253 measles cases reported. Out of 10,691 (87.25%) samples tested by enzyme-linked immunosorbent assay, 903 (8.4%) were measles immunoglobulin M positive. The highest number of laboratory-confirmed measles cases was in 2022 (64.8%), followed by 2020 (13.8%), and 2019 (13.5%). Out of 1279 unvaccinated cases, 213 (16.7%) were laboratory-confirmed measles cases compared to 77/723 (10.6%) who were partially vaccinated and 71/1121 (6.3%) who were fully vaccinated (P < 0.001). Children aged between 1-4 years constituted the most confirmed measles cases after laboratory testing, followed by those aged 5-9 years. There was a notable increase in the number of laboratory-confirmed measles cases in children <1 year and 10-14 years during 2022 compared to previous years. The vaccination coverage of the first dose of measles-containing vaccine (MCV1) was maintained >90% since 2013 while MCV2 increased gradually reaching 88% in 2022.

CONCLUSIONS

Accumulation of susceptible children to measles due to suboptimal measles vaccination coverage over the years has resulted in an increase in the number of laboratory-confirmed measles cases in Tanzania with more cases recorded during the COVID-19 pandemic. Strengthening surveillance, routine immunization, and targeted strategies are key to achieving the immunity levels required to interrupt measles outbreaks.

Determination Factors Associated with Immune Responses Towards First Dose Edmonston-Zagreb (EZ) Measles Vaccine in Indonesian Infants

Background:

Measles outbreaks under high coverage of measles vaccination in Indonesia is gaining a necessary evaluation of factors associated with measles-vaccine immune responses.

Objctive:

The purposes of recent study were to evaluate the association of sociodemographic and anthropometric parameters and specific immune responses towards first dose Edmonston-Zagreb (EZ) measles vaccine in Indonesian infants.

Methods:

A total of 35 infants were enrolled in this cohort study. Measles immune responses were followed up at one and six months after vaccination then analyzed for its association with sociodemographic, anthropometric, and nutritional parameters. The plaque-reduction microneutralization assay was conducted to measure the titer of measles specific IgG antibody. The level of CD4⁺ and CD8⁺ T-cells that exhibiting gamma interferon (IFN-γ) secretion were analyzed by flow cytometry. The association between variable was analyzed by linear regression. The difference immune response among variable were analyzed with Mann-Whitney test.

Results:

Vitamin A supplementation and breastfeeding were predicted as associated factor for humoral and cellular immune response after one month and six months measles vaccination among Indonesia Infants.

Conclusion:

Nutritional factor is associated with measles vaccination immune response in Indonesian infants.

Impact of health system strengthening on delivery strategies to improve child immunisation coverage and inequalities in rural Madagascar

Background

To reach global immunisation goals, national programmes need to balance routine immunisation at health facilities with vaccination campaigns and other outreach activities (eg, vaccination weeks), which boost coverage at particular times and help reduce geographical inequalities. However, where routine immunisation is weak, an over-reliance on vaccination campaigns may lead to heterogeneous coverage. Here, we assessed the impact of a health system strengthening (HSS) intervention on the relative contribution of routine immunisation and outreach activities to reach immunisation goals in rural Madagascar.

Methods

We obtained data from health centres in Ifanadiana district on the monthly number of recommended vaccines (BCG, measles, diphtheria, tetanus and pertussis (DTP) and polio) delivered to children, during 2014–2018. We also analysed data from a district-representative cohort carried out every 2 years in over 1500 households in 2014–2018. We compared changes inside and outside the HSS catchment in the delivery of recommended vaccines, population-level vaccination coverage, geographical and economic inequalities in coverage, and timeliness of vaccination. The impact of HSS was quantified via mixed-effects logistic regressions.

Results

The HSS intervention was associated with a significant increase in immunisation rates (OR between 1.22 for measles and 1.49 for DTP), which diminished over time. Outreach activities were associated with a doubling in immunisation rates, but their effect was smaller in the HSS catchment. Analysis of cohort data revealed that HSS was associated with higher vaccination coverage (OR between 1.18 per year of HSS for measles and 1.43 for BCG), a reduction in economic inequality, and a higher proportion of timely vaccinations. Yet, the lower contribution of outreach activities in the HSS catchment was associated with persistent inequalities in geographical coverage, which prevented achieving international coverage targets.

Conclusion

Investment in stronger primary care systems can improve vaccination coverage, reduce inequalities and improve the timeliness of vaccination via increases in routine immunisations.

Effect of evidence updates on key determinants of measles vaccination impact: a DynaMICE modelling study in ten high-burden countries

BACKGROUND

Model-based estimates of measles burden and the impact of measles-containing vaccine (MCV) are crucial for global health priority setting. Recently, evidence from systematic reviews and database analyses have improved our understanding of key determinants of MCV impact. We explore how representations of these determinants affect model-based estimation of vaccination impact in ten countries with the highest measles burden.

METHODS

Using Dynamic Measles Immunisation Calculation Engine (DynaMICE), we modelled the effect of evidence updates for five determinants of MCV impact: case-fatality risk, contact patterns, age-dependent vaccine efficacy, the delivery of supplementary immunisation activities (SIAs) to zero-dose children, and the basic reproduction number. We assessed the incremental vaccination impact of the first (MCV1) and second (MCV2) doses of routine immunisation and SIAs, using metrics of total vaccine-averted cases, deaths, and disability-adjusted life years (DALYs) over 2000-2050. We also conducted a scenario capturing the effect of COVID-19 related disruptions on measles burden and vaccination impact.

RESULTS

Incorporated with the updated data sources, DynaMICE projected 253 million measles cases, 3.8 million deaths and 233 million DALYs incurred over 2000-2050 in the ten high-burden countries when MCV1, MCV2, and SIA doses were implemented. Compared to no vaccination, MCV1 contributed to 66% reduction in cumulative measles cases, while MCV2 and SIAs reduced this further to 90%. Among the updated determinants, shifting from fixed to linearly-varying vaccine efficacy by age and from static to time-varying case-fatality risks had the biggest effect on MCV impact. While varying the basic reproduction number showed a limited effect, updates on the other four determinants together resulted in an overall reduction of vaccination impact by 0.58%, 26.2%, and 26.7% for cases, deaths, and DALYs averted, respectively. COVID-19 related disruptions to measles vaccination are not likely to change the influence of these determinants on MCV impact, but may lead to a 3% increase in cases over 2000-2050.

CONCLUSIONS

Incorporating updated evidence particularly on vaccine efficacy and case-fatality risk reduces estimates of vaccination impact moderately, but its overall impact remains considerable. High MCV coverage through both routine immunisation and SIAs remains essential for achieving and maintaining low incidence in high measles burden settings.

The Role of Sex, Ethnicity, Age, and Nutritional Status in the Seropositivity of the Measles Vaccine

AIM: This study investigates the relationship between sex, ethnicity, age, nutritional status with the seropositivity of the Edmonston-Zagreb vaccine in children. METHODS: A cross sectional, observational study was conducted. A total of 45 children were differentiated based on sex, ethnicity, age, and nutritional status when they received the Edmonston-Zagreb measle vaccine for the first time. Flow cytometry was used to look at differences in antibody status as well as populations of CD-4 and CD-8 cells that release IFN- γ. RESULTS: We found no significant differences in antibody levels or CD-4 and CD-8 cell populations that secrete IFN- γ between boys and girls (p > 0.05). Besides, similar results were also confirmed in comparisons between Javanese and Sundanese ethnic groups, 9 months versus more than 9 months of age, or normal versus low body mass index (p > 0.05). CONCLUSIONS: We conclude that sex, race, age, and nutritional status had no effect on immune response to vaccination. As a result, there was no barrier to seroconversion and optimal immunological performance in the children in this trial who received the Edmonston-Zagreb measles vaccination.

Pathogen Dynamics across the Diversity of Aging

AbstractReproduction, mortality, and immune function often change with age but do not invariably deteriorate. Across the tree of life, there is extensive variation in age-specific performance and changes to key life-history traits. These changes occur on a spectrum from classic senescence, where performance declines with age, to juvenescence, where performance improves with age. Reproduction, mortality, and immune function are also important factors influencing the spread of infectious disease, yet there exists no comprehensive investigation into how the aging spectrum of these traits impacts epidemics. We used a model laboratory infection system to compile an aging profile of a single organism, including traits directly linked to pathogen susceptibility and those that should indirectly alter pathogen transmission by influencing demography. We then developed generalizable epidemiological models demonstrating that different patterns of aging produce dramatically different transmission landscapes: in many cases, aging can reduce the probability of epidemics, but it can also promote severity. This work provides context and tools for use across taxa by empiricists, demographers, and epidemiologists, advancing our ability to accurately predict factors contributing to epidemics or the potential repercussions of senescence manipulation.

The Importance of Prioritizing Pre and Posttransplant Immunizations in an Era of Vaccine Refusal and Epidemic Outbreaks

Vaccine-preventable infections are occurring at epidemic rates both nationally and internationally. At the same time, rates of vaccine hesitancy and refusal are increasing across the country leading to decreased herd immunity. For immunosuppressed transplant recipients, this situation poses great risk. Currently, 1 in 6 pediatric solid organ transplant recipients is hospitalized with a vaccine-preventable infection in the first 5 years posttransplant. For many recipients, these infections result in significant morbidity, mortality, and increased hospitalization costs. Surprisingly, despite this risk many transplant recipients are not up-to-date on age appropriate immunizations at the time of transplant and thereafter. As a transplant community, we must prioritize immunizations in both pre and posttransplant care. Research is needed to understand how to monitor immune response to vaccines in immunosuppressed patients and when to optimally immunize patients posttransplant. Finally, recommendations about administration of live vaccines posttransplant may need to be reevaluated in the setting of measles outbreaks and decreased herd immunity.

Using models to shape measles control and elimination strategies in low- and middle-income countries: A review of recent applications

After many decades of vaccination, measles epidemiology varies greatly between and within countries. National immunization programs are therefore encouraged to conduct regular situation analyses and to leverage models to adapt interventions to local needs. Here, we review applications of models to develop locally tailored interventions to support control and elimination efforts. In general, statistical and semi-mechanistic transmission models can be used to synthesize information from vaccination coverage, measles incidence, demographic, and/or serological data, offering a means to estimate the spatial and age-specific distribution of measles susceptibility. These estimates complete the picture provided by vaccination coverage alone, by accounting for natural immunity. Dynamic transmission models can then be used to evaluate the relative impact of candidate interventions for measles control and elimination and the expected future epidemiology. In most countries, models predict substantial numbers of susceptible individuals outside the age range of routine vaccination, which affects outbreak risk and necessitates additional intervention to achieve elimination. More effective use of models to inform both vaccination program planning and evaluation requires the development of training to enhance broader understanding of models and where feasible, building capacity for modelling in-country, pipelines for rapid evaluation of model predictions using surveillance data, and clear protocols for incorporating model results into decision-making.

Characteristics of measles epidemics in China (1951-2004) and implications for elimination: A case study of three key locations

Measles is a highly infectious, severe viral disease. The disease is targeted for global eradication; however, this result has proven challenging. In China, where countrywide vaccination coverage for the last decade has been above 95% (the threshold for measles elimination), measles continues to cause large epidemics. To diagnose factors contributing to the persistency of measles, here we develop a model-inference system to infer measles transmission dynamics in China. The model-inference system uses demographic and vaccination data for each year as model inputs to directly account for changing population dynamics (including births, deaths, migrations, and vaccination). In addition, it simultaneously estimates unobserved model variables and parameters based on incidence data. When fitted to yearly incidence data for the entire population, it is able to accurately estimate independent, out-of-sample age-specific incidence. Using this validated model-inference system, we are thus able to estimate epidemiological and demographical characteristics key to measles transmission during 1951-2004 for three key locations in China, including its capital Beijing. These characteristics include age-specific population susceptibility and incidence rates, the basic reproductive number (R0), reporting rate, population mixing intensity, and amplitude of seasonality. Key differences among the three sites reveal population and epidemiological characteristics crucial for understanding the current persistence of measles epidemics in China. We also discuss the implications our findings have for future elimination strategies.

Benefits and Challenges in Using Seroprevalence Data to Inform Models for Measles and Rubella Elimination

Background

Control efforts for measles and rubella are intensifying globally. It becomes increasingly important to identify and reach remaining susceptible populations as elimination is approached.

Methods

Serological surveys for measles and rubella can potentially measure susceptibility directly, but their use remains rare. In this study, using simulations, we outline key subtleties in interpretation associated with the dynamic context of age-specific immunity, highlighting how the patterns of immunity predicted from disease surveillance and vaccination coverage data may be misleading.

Results

High-quality representative serosurveys could provide a more accurate assessment of immunity if challenges of conducting, analyzing, and interpreting them are overcome. We frame the core disease control and elimination questions that could be addressed by improved serological tools, discussing challenges and suggesting approaches to increase the feasibility and sustainability of the tool.

Conclusions

Accounting for the dynamical context, serosurveys could play a key role in efforts to achieve and sustain elimination.

Assessing the transmission dynamics of measles in Japan, 2016

OBJECTIVES

Despite the verification of measles elimination, Japan experienced multiple generations of measles transmission following importation events in 2016. The purpose of the present study was to analyze the transmission dynamics of measles in Japan, 2016, estimating the transmission potential in the partially vaccinated population.

METHODS

All diagnosed measles cases were notified to the government, and the present study analyzed two pieces of datasets independently, i.e., the transmission tree of the largest outbreak in Osaka (n=49) and the final size distribution of all importation events (n=23 events). Branching process model was employed to estimate the effective reproduction number R_v, and the analysis of transmission tree in Osaka enabled us to account for the timing of introducing contact tracing and case isolation.

RESULTS

Employing a negative binomial distribution for the offspring distribution, the model with time-dependent decline in R_v due to interventions appeared to best fit to the transmission tree data with R_v of 9.20 (95% CI (confidence interval): 2.08, 150.68) and the dispersion parameter 0.32 (95% CI: 0.07, 1.17) before interventions were introduced. The relative transmissibility in the presence of interventions from week 34 was estimated at 0.005. Analyzing the final size distribution, models for subcritical and supercritical processes fitted equally well to the observed data, and the estimated reproduction number from both models did not exclude the possibility that R_v>1.

CONCLUSIONS

Our results likely reflect the highly contagious nature of measles, indicating that Japan is at risk of observing multiple generations of measles transmission given imported cases. Considering that importation events may continue in the future, supplementary vaccination of adults needs to be considered.

Evolution and Use of Dynamic Transmission Models for Measles and Rubella Risk and Policy Analysis

The devastation caused by periodic measles outbreaks motivated efforts over more than a century to mathematically model measles disease and transmission. Following the identification of rubella, which similarly presents with fever and rash and causes congenital rubella syndrome (CRS) in infants born to women first infected with rubella early in pregnancy, modelers also began to characterize rubella disease and transmission. Despite the relatively large literature, no comprehensive review to date provides an overview of dynamic transmission models for measles and rubella developed to support risk and policy analysis. This systematic review of the literature identifies quantitative measles and/or rubella dynamic transmission models and characterizes key insights relevant for prospective modeling efforts. Overall, measles and rubella represent some of the relatively simplest viruses to model due to their ability to impact only humans and the apparent life-long immunity that follows survival of infection and/or protection by vaccination, although complexities arise due to maternal antibodies and heterogeneity in mixing and some models considered potential waning immunity and reinfection. This review finds significant underreporting of measles and rubella infections and widespread recognition of the importance of achieving and maintaining high population immunity to stop and prevent measles and rubella transmission. The significantly lower transmissibility of rubella compared to measles implies that all countries could eliminate rubella and CRS by using combination of measles- and rubella-containing vaccines (MRCVs) as they strive to meet regional measles elimination goals, which leads to the recommendation of changing the formulation of national measles-containing vaccines from measles only to MRCV as the standard of care.

Modeling the Impact of Alternative Immunization Strategies: Using Matrices as Memory Lanes

Existing modeling approaches are divided between a focus on the constitutive (micro) elements of systems or on higher (macro) organization levels. Micro-level models enable consideration of individual histories and interactions, but can be unstable and subject to cumulative errors. Macro-level models focus on average population properties, but may hide relevant heterogeneity at the micro-scale. We present a framework that integrates both approaches through the use of temporally structured matrices that can take large numbers of variables into account. Matrices are composed of several bidimensional (time×age) grids, each representing a state (e.g. physiological, immunological, socio-demographic). Time and age are primary indices linking grids. These matrices preserve the entire history of all population strata and enable the use of historical events, parameters and states dynamically in the modeling process. This framework is applicable across fields, but particularly suitable to simulate the impact of alternative immunization policies. We demonstrate the framework by examining alternative strategies to accelerate measles elimination in 15 developing countries. The model recaptured long-endorsed policies in measles control, showing that where a single routine measles-containing vaccine is employed with low coverage, any improvement in coverage is more effective than a second dose. It also identified an opportunity to save thousands of lives in India at attractively low costs through the implementation of supplementary immunization campaigns. The flexibility of the approach presented enables estimating the effectiveness of different immunization policies in highly complex contexts involving multiple and historical influences from different hierarchical levels.

The effects of demographic change on disease transmission and vaccine impact in a household structured population

The demographic structure of populations in both more developed and less developed countries is changing: increases in life expectancy and declining fertility have led to older populations and smaller households. The implications of these demographic changes for the spread and control of infectious diseases are not fully understood. Here we use an individual based model with realistic and dynamic age and household structure to demonstrate the marked effect that demographic change has on disease transmission at the population and household level. The decline in fertility is associated with a decrease in disease incidence and an increase in the age of first infection, even in the absence of vaccination or other control measures. Although large households become rarer as fertility decreases, we show that there is a proportionate increase in incidence of disease in these households as the accumulation of susceptible clusters increases the potential for explosive outbreaks. By modelling vaccination, we provide a direct comparison of the relative importance of demographic change and vaccination on incidence of disease. We highlight the increased risks associated with unvaccinated households in a low fertility setting if vaccine behaviour is correlated with household membership. We suggest that models that do not account for future demographic change, and especially its effect on household structure, may potentially overestimate the impact of vaccination.

The evolutionary dynamics of timing of maternal immunity: evaluating the role of age-specific mortality

If a female survives an infection, she can transfer antibodies against that particular pathogen to any future offspring she produces. The resulting protection of offspring for a period after their birth is termed maternal immunity. Because infection in newborns is associated with high mortality, the duration of this protection is expected to be under strong selection. Evolutionary modelling structured around a trade-off between fertility and duration of maternal immunity has indicated selection for longer duration of maternal immunity for hosts with longer lifespans. Here, we use a new modelling framework to extend this analysis to consider characteristics of pathogens (and hosts) in further detail. Importantly, given the challenges in characterizing trade-offs linked to immune function empirically, our model makes no assumptions about costs of longer lasting maternal immunity. Rather, a key component of this analysis is variation in mortality over age. We found that the optimal duration of maternal immunity is shaped by the shifting balance of the burden of infection between young and old individuals. As age of infection depends on characteristics of both the host and the pathogen, both affect the evolution of duration of maternal immunity. Our analysis provides additional support for selection for longer duration of maternal immunity in long-lived hosts, even in the absence of explicit costs linked to duration of maternal immunity. Further, the scope of our results provides explanations for exceptions to the general correlation between duration of maternal immunity and lifespan, as we found that both pathogen characteristics and trans-generational effects can lead to important shifts in fitness linked to maternal immunity. Finally, our analysis points to new directions for quantifying the trade-offs that drive the development of the immune system.

Adaptive management and the value of information: learning via intervention in epidemiology

This Research Article explores the benefits of applying Adaptive Management approaches to disease outbreaks, finding that formally integrating science and policy allows one to reduce uncertainty and improve disease management outcomes.

Optimal intervention for disease outbreaks is often impeded by severe scientific uncertainty. Adaptive management (AM), long-used in natural resource management, is a structured decision-making approach to solving dynamic problems that accounts for the value of resolving uncertainty via real-time evaluation of alternative models. We propose an AM approach to design and evaluate intervention strategies in epidemiology, using real-time surveillance to resolve model uncertainty as management proceeds, with foot-and-mouth disease (FMD) culling and measles vaccination as case studies. We use simulations of alternative intervention strategies under competing models to quantify the effect of model uncertainty on decision making, in terms of the value of information, and quantify the benefit of adaptive versus static intervention strategies. Culling decisions during the 2001 UK FMD outbreak were contentious due to uncertainty about the spatial scale of transmission. The expected benefit of resolving this uncertainty prior to a new outbreak on a UK-like landscape would be £45–£60 million relative to the strategy that minimizes livestock losses averaged over alternate transmission models. AM during the outbreak would be expected to recover up to £20.1 million of this expected benefit. AM would also recommend a more conservative initial approach (culling of infected premises and dangerous contact farms) than would a fixed strategy (which would additionally require culling of contiguous premises). For optimal targeting of measles vaccination, based on an outbreak in Malawi in 2010, AM allows better distribution of resources across the affected region; its utility depends on uncertainty about both the at-risk population and logistical capacity. When daily vaccination rates are highly constrained, the optimal initial strategy is to conduct a small, quick campaign; a reduction in expected burden of approximately 10,000 cases could result if campaign targets can be updated on the basis of the true susceptible population. Formal incorporation of a policy to update future management actions in response to information gained in the course of an outbreak can change the optimal initial response and result in significant cost savings. AM provides a framework for using multiple models to facilitate public-health decision making and an objective basis for updating management actions in response to improved scientific understanding.

If the response to a disease outbreak is poorly managed, lives may be lost and money wasted unnecessarily. Lack of knowledge about the disease dynamics, and about the effects of our control strategies on those dynamics, means that it is difficult to do the best job possible managing such epidemiological problems. Here, we present an adaptive management approach that allows researchers to use knowledge gained during an outbreak to update ongoing interventions, thereby translating scientific discovery into improved policy. We explore the implications of adaptive management for foot-and-mouth disease outbreaks in livestock and for measles vaccination strategies in humans. In these two particular cases, planning to update management actions leads to the recommendation of a less aggressive initial approach than if changes in management are not anticipated. We demonstrate expected savings of up to £20 million in terms of lower livestock losses to culling in a foot-and-mouth outbreak based on the dynamics observed in the UK in 2001. Similarly, up to 10,000 cases could have been averted in a measles outbreak like the one observed in Malawi in 2010. Adaptive management allows real-time improvement of our understanding, and hence of management efforts, with potentially significant positive financial and health benefits.

Length of intervals between epidemics: evaluating the influence of maternal transfer of immunity

The length of intervals between epidemic outbreaks of infectious diseases is critical in epidemiology. In several species of marine mammals and birds, it is pivotal to also consider the life history of the species of concern, as the contact rate between individuals can have a seasonal flux, for example, due to aggregations during the breeding season. Recently, particular interest has been given to the role of the dynamics of immunity in determining the intervals between epidemics in wild animal populations. One potentially powerful, but often neglected, process in this context is the maternal transfer of immunity. Here, we explore theoretically how the transfer of maternal antibodies can delay the recurrence of epidemics using Phocine Distemper in harbor seals as an example of a system in which epidemic outbreaks are followed by pathogen extinction. We show that the presence of temporarily protected newborns can significantly increase the predicted interval between epidemics, and this effect is strongly dependent on the degree of synchrony in the breeding season. Furthermore, we found that stochasticity in the onset of epidemics in combination with maternally acquired immunity increases the predicted intervals between epidemics even more. These effects arise because newborns with maternal antibodies temporarily boost population level immunity above the threshold of herd immunity, particularly when breeding is synchronous. Overall, our results show that maternal antibodies can have a profound influence on the dynamics of wildlife epidemics, notably in gregarious species such as many marine mammals and seabirds.

Measles outbreak response immunization is context-specific: insight from the recent experience of Médecins Sans Frontières

Andrea Minetti and colleagues compare measles outbreak responses from the Democratic Republic of the Congo and Malawi and argue that outbreak response strategies should be tailored to local measles epidemiology. Please see later in the article for the Editors' Summary.

Age-appropriate vaccination against measles and DPT-3 in India - closing the gaps

Background

In 2010, India accounted for 65,500 (47%) of the 139,300 measles-related deaths that occurred globally. Data on the quality of age-appropriate measles vaccination in rural India is sparse. We explored the following issues: (i) What proportion of Indian children were appropriately vaccinated against measles at 9 months of age, and DPT-3 at 4 months? (ii) Which health facilities administered measles vaccine to children prior to 9 months of age and DPT-3 prior to 14 weeks?

Methods

We analyzed data from the 2008 Indian District Level Health Survey (DLHS-3) to determine the extent of age-appropriate measles and DPT-3 vaccinations. Among 192,969 households in the dataset, vaccination cards with detailed records were available for 18,670 children aged between 12 and 23 months.

Results

Among this cohort, 72.4% (13,511 infants) had received the first dose of measles vaccine. Only 30% of vaccinated infants received the measles vaccine at the recommended age of 9 months. Similarly, only 31% of infants in the cohort received DPT-3 vaccine at the recommended age of 14 weeks. About 82% of all prematurely vaccinated children were vaccinated at health sub-centres, ICDS and Pulse Polio centres.

Conclusions

Age-inappropriate vaccination impacts adversely on the effectiveness of India’s measles immunisation program due to sub-optimal seroconversion, if premature, and increased vulnerability to vaccine preventable diseases, if delayed. Capacity building approaches to improve age-appropriate vaccination are discussed.

Who are the children at risk? Lessons learned from measles outbreaks

We investigated a measles outbreak in the Jerusalem district in 2007-2008 (992 cases). Most cases (72·6%) were aged <15 years, 42·9% aged <5 years, and 12·8% were infants aged <1 year. The peak incidence rate was in infants aged 6-12 months (916·2/100 000). This represents a significant shift from former outbreaks in 2003-2004, where the peak incidence was in the 1-4 years age group. Of children aged <5 years the proportion aged 6-12 months tripled (7·7% vs. 25·6%). In a case-control study (74 cases, 148 controls) children who developed measles were less likely to be registered in a well-baby clinic and had lower overall immunization coverage. The differences in proportions for registration, DTaP3 and MMR1 coverage were 35·1%, 48·6% and 80·8%, respectively (all P<0·001). Rising birth order of cases and their siblings was associated with non-registration and non-compliance with MMR immunization. The vulnerability of young infants and the risk markers noted above should be taken into account in planning intervention programmes.

Synthesizing epidemiological and economic optima for control of immunizing infections

Epidemic theory predicts that the vaccination threshold required to interrupt local transmission of an immunizing infection like measles depends only on the basic reproductive number and hence transmission rates. When the search for optimal strategies is expanded to incorporate economic constraints, the optimum for disease control in a single population is determined by relative costs of infection and control, rather than transmission rates. Adding a spatial dimension, which precludes local elimination unless it can be achieved globally, can reduce or increase optimal vaccination levels depending on the balance of costs and benefits. For weakly coupled populations, local optimal strategies agree with the global cost-effective strategy; however, asymmetries in costs can lead to divergent control optima in more strongly coupled systems--in particular, strong regional differences in costs of vaccination can preclude local elimination even when elimination is locally optimal. Under certain conditions, it is locally optimal to share vaccination resources with other populations.