Resurgence of measles in the United States: how did we get here?

PURPOSE OF REVIEW: In September 2019, the United States was at risk of losing measles elimination status due to several large-scale outbreaks resulting in more than 1200 confirmed cases across 31 states. This resurgence caps approximately 10 years of increasing incidence, marked by a highly publicized outbreak in 2015 associated with Disneyland when an infected traveler from the Philippines unknowingly spread the virus to susceptible park visitors and the recently ended large outbreak in undervaccinated Orthodox Jewish communities in New York City and Rockland counties. This review highlights current literature elucidating factors associated with current trends in measles epidemiology in the United States, the public health implications of current measles outbreaks and a path forward for addressing challenges contributing to the resurgence of measles in the United States and globally. RECENT FINDINGS AND SUMMARY: As the most highly transmissible vaccine preventable disease, measles is especially sensitive to changes in herd immunity, the impact of vaccine refusal and globalization. Results highlight the confluence of these factors in current outbreaks, provide tools to predict outbreak risk, demonstrate the growing impact of misinformation and evaluate the impact of policy approaches for outbreak control and prevention.

Combining serological and contact data to derive target immunity levels for achieving and maintaining measles elimination.

BACKGROUND: Vaccination has reduced the global incidence of measles to the lowest rates in history. However, local interruption of measles virus transmission requires sustained high levels of population immunity that can be challenging to achieve and maintain. The herd immunity threshold for measles is typically stipulated at 90-95%. This figure does not easily translate into age-specific immunity levels required to interrupt transmission. Previous estimates of such levels were based on speculative contact patterns based on historical data from high-income countries. The aim of this study was to determine age-specific immunity levels that would ensure elimination of measles when taking into account empirically observed contact patterns. METHODS: We combined estimated immunity levels from serological data in 17 countries with studies of age-specific mixing patterns to derive contact-adjusted immunity levels. We then compared these to case data from the 10 years following the seroprevalence studies to establish a contact-adjusted immunity threshold for elimination. We lastly combined a range of hypothetical immunity profiles with contact data from a wide range of socioeconomic and demographic settings to determine whether they would be sufficient for elimination. RESULTS: We found that contact-adjusted immunity levels were able to predict whether countries would experience outbreaks in the decade following the serological studies in about 70% of countries. The corresponding threshold level of contact-adjusted immunity was found to be 93%, corresponding to an average basic reproduction number of approximately 14. Testing different scenarios of immunity with this threshold level using contact studies from around the world, we found that 95% immunity would have to be achieved by the age of five and maintained across older age groups to guarantee elimination. This reflects a greater level of immunity required in 5-9-year-olds than established previously. CONCLUSIONS: The immunity levels we found necessary for measles elimination are higher than previous guidance. The importance of achieving high immunity levels in 5-9-year-olds presents both a challenge and an opportunity. While such high levels can be difficult to achieve, school entry provides an opportunity to ensure sufficient vaccination coverage. Combined with observations of contact patterns, further national and sub-national serological studies could serve to highlight key gaps in immunity that need to be filled in order to achieve national and regional measles elimination.

Optimization of frequency and targeting of measles supplemental immunization activities in Nigeria: A cost-effectiveness analysis.

BACKGROUND: Measles causes significant childhood morbidity in Nigeria. Routine immunization (RI) coverage is around 40% country-wide, with very high levels of spatial heterogeneity (3-86%), with supplemental immunization activities (SIAs) at 2-year or 3-year intervals. We investigated cost savings and burden reduction that could be achieved by adjusting the inter-campaign interval by region. METHODS: We modeled 81 scenarios; permuting SIA calendars of every one, two, or three years in each of four regions of Nigeria (North-west, North-central, North-east, and South). We used an agent-based disease transmission model to estimate the number of measles cases and ingredients-based cost models to estimate RI and SIA costs for each scenario over a 10 year period. RESULTS: Decreasing SIAs to every three years in the North-central and South (regions of above national-average RI coverage) while increasing to every year in either the North-east or North-west (regions of below national-average RI coverage) would avert measles cases (0.4 or 1.4 million, respectively), and save vaccination costs (save $19.4 or $5.4 million, respectively), compared to a base-case of national SIAs every two years. Decreasing SIA frequency to every three years in the South while increasing to every year in the just the North-west, or in all Northern regions would prevent more cases (2.1 or 5.0 million, respectively), but would increase vaccination costs (add $3.5 million or $34.6 million, respectively), for $1.65 or $6.99 per case averted, respectively. CONCLUSIONS: Our modeling shows how increasing SIA frequency in Northern regions, where RI is low and birth rates are high, while decreasing frequency in the South of Nigeria would reduce the number of measles cases with relatively little or no increase in vaccination costs. A national vaccination strategy that incorporates regional SIA targeting in contexts with a high level of sub-national variation would lead to improved health outcomes and/or lower costs.

Accelerating measles and rubella elimination through research and innovation - Findings from the Measles & Rubella Initiative research prioritization process, 2016.

The Measles & Rubella Initiative (M&RI) identified five key strategies to achieve measles and rubella elimination, including research and innovation to support cost-effective operations and improve vaccination and diagnostic tools. In 2016, the M&RI Research and Innovation Working Group (R&IWG) completed a research prioritization process to identify key research questions and update the global research agenda. The R&IWG reviewed meeting reports and strategic planning documents and solicited programmatic inputs from vaccination experts at the program operational level through a web survey, to identify previous research priorities and new research questions. The R&IWG then convened a meeting of experts to prioritize the identified research questions in four strategic areas: (1) epidemiology and economics, (2) surveillance and laboratory, (3) immunization strategies, and (4) demand creation and communications. The experts identified 19 priority research questions in the four strategic areas to address key areas of work necessary to further progress toward elimination. Future commitments from partners will be needed to develop a platform for improved coordination with adequate and predictable resources for research implementation and innovation to address these identified priorities.

Stochastic two-group models with transmission dependent on host infectivity or susceptibility.

Stochastic epidemic models with two groups are formulated and applied to emerging and re-emerging infectious diseases. In recent emerging diseases, disease spread has been attributed to superspreaders, highly infectious individuals that infect a large number of susceptible individuals. In some re-emerging infectious diseases, disease spread is attributed to waning immunity in susceptible hosts. We apply a continuous-time Markov chain (CTMC) model to study disease emergence or re-emergence from different groups, where the transmission rates depend on either the infectious host or the susceptible host. Multitype branching processes approximate the dynamics of the CTMC model near the disease-free equilibrium and are used to estimate the probability of a minor or a major epidemic. It is shown that the probability of a major epidemic is greater if initiated by an individual from the superspreader group or by an individual from the highly susceptible group. The models are applied to Severe Acute Respiratory Syndrome and measles.

The Dust Bowl in the US: An Analysis Based on Current Environmental and Clinical Studies.

The Dust Bowl occurred in the Central Plains states in the United States between 1930 and 1940. Prolonged drought, intense recurrent dust storms and economic depression had profound effects on human welfare. The causes included increased farming on marginal land, poor land management, and prolonged drought. There was a significant increase in the number of cases of measles, increased hospitalization for respiratory disorders and increased infant and overall mortality in Kansas during the Dust Bowl. Recent scientific studies have demonstrated that dust transmits measles virus, influenza virus and Coccidioides immitis, and that mortality in the United States increases following dust storms with 2-3-day lag periods. Advances in technology have provided information about the composition of dust and the transfer of microbial pathogens in dust and provided the framework for reducing the economic and health consequences of the next prolonged drought in the United States.

Who is the infector? Epidemic models with symptomatic and asymptomatic cases.

What role do asymptomatically infected individuals play in the transmission dynamics? There are many diseases, such as norovirus and influenza, where some infected hosts show symptoms of the disease while others are asymptomatically infected, i.e. do not show any symptoms. The current paper considers a class of epidemic models following an SEIR (Susceptible  →  Exposed  →  Infectious  →  Recovered) structure that allows for both symptomatic and asymptomatic cases. The following question is addressed: what fraction ρ of those individuals getting infected are infected by symptomatic (asymptomatic) cases? This is a more complicated question than the related question for the beginning of the epidemic: what fraction of the expected number of secondary cases of a typical newly infected individual, i.e. what fraction of the basic reproduction number R0, is caused by symptomatic individuals? The latter fraction only depends on the type-specific reproduction numbers, while the former fraction ρ also depends on timing and hence on the probabilistic distributions of latent and infectious periods of the two types (not only their means). Bounds on ρ are derived for the situation where these distributions (and even their means) are unknown. Special attention is given to the class of Markov models and the class of continuous-time Reed-Frost models as two classes of distribution functions for latent and infectious periods. We show how these two classes of models can exhibit very different behaviour.

Modeling the Transmission of Measles and Rubella to Support Global Management Policy Analyses and Eradication Investment Cases.

Policy makers responsible for managing measles and rubella immunization programs currently use a wide range of different vaccines formulations and immunization schedules. With endemic measles and rubella transmission interrupted in the region of the Americas, all five other regions of the World Health Organization (WHO) targeting the elimination of measles transmission by 2020, and increasing adoption of rubella vaccine globally, integrated dynamic disease, risk, decision, and economic models can help national, regional, and global health leaders manage measles and rubella population immunity. Despite hundreds of publications describing models for measles or rubella and decades of use of vaccines that contain both antigens (e.g., measles, mumps, and rubella vaccine or MMR), no transmission models for measles and rubella exist to support global policy analyses. We describe the development of a dynamic disease model for measles and rubella transmission, which we apply to 180 WHO member states and three other areas (Puerto Rico, Hong Kong, and Macao) representing >99.5% of the global population in 2013. The model accounts for seasonality, age-heterogeneous mixing, and the potential existence of preferentially mixing undervaccinated subpopulations, which create heterogeneity in immunization coverage that impacts transmission. Using our transmission model with the best available information about routine, supplemental, and outbreak response immunization, we characterize the complex transmission dynamics for measles and rubella historically to compare the results with available incidence and serological data. We show the results from several countries that represent diverse epidemiological situations to demonstrate the performance of the model. The model suggests relatively high measles and rubella control costs of approximately $3 billion annually for vaccination based on 2013 estimates, but still leads to approximately 17 million disability-adjusted life years lost with associated costs for treatment, home care, and productivity loss costs of approximately $4, $3, and $47 billion annually, respectively. Combined with vaccination and other financial cost estimates, our estimates imply that the eradication of measles and rubella could save at least $10 billion per year, even without considering the benefits of preventing lost productivity and potential savings from reductions in vaccination. The model should provide a useful tool for exploring the health and economic outcomes of prospective opportunities to manage measles and rubella. Improving the quality of data available to support decision making and modeling should represent a priority as countries work toward measles and rubella goals.

Geospatial characteristics of measles transmission in China during 2005-2014.

Measles is a highly contagious and severe disease. Despite mass vaccination, it remains a leading cause of death in children in developing regions, killing 114,900 globally in 2014. In 2006, China committed to eliminating measles by 2012; to this end, the country enhanced its mandatory vaccination programs and achieved vaccination rates reported above 95% by 2008. However, in spite of these efforts, during the last 3 years (2013-2015) China documented 27,695, 52,656, and 42,874 confirmed measles cases. How measles manages to spread in China-the world's largest population-in the mass vaccination era remains poorly understood. To address this conundrum and provide insights for future public health efforts, we analyze the geospatial pattern of measles transmission across China during 2005-2014. We map measles incidence and incidence rates for each of the 344 cities in mainland China, identify the key socioeconomic and demographic features associated with high disease burden, and identify transmission clusters based on the synchrony of outbreak cycles. Using hierarchical cluster analysis, we identify 21 epidemic clusters, of which 12 were cross-regional. The cross-regional clusters included more underdeveloped cities with large numbers of emigrants than would be expected by chance (p = 0.011; bootstrap sampling), indicating that cities in these clusters were likely linked by internal worker migration in response to uneven economic development. In contrast, cities in regional clusters were more likely to have high rates of minorities and high natural growth rates than would be expected by chance (p = 0.074; bootstrap sampling). Our findings suggest that multiple highly connected foci of measles transmission coexist in China and that migrant workers likely facilitate the transmission of measles across regions. This complex connection renders eradication of measles challenging in China despite its high overall vaccination coverage. Future immunization programs should therefore target these transmission foci simultaneously.

Assessment of the Status of Measles Elimination in the United States, 2001-2014.

We assessed the status of measles elimination in the United States using outbreak notification data. Measles transmissibility was assessed by estimation of the reproduction number, R, the average number of secondary cases per infection, using 4 methods; elimination requires maintaining R at <1. Method 1 estimates R as 1 minus the proportion of cases that are imported. Methods 2 and 3 estimate R by fitting a model of the spread of infection to data on the sizes and generations of chains of transmission, respectively. Method 4 assesses transmissibility before public health interventions, by estimating R for the case with the earliest symptom onset in each cluster (Rindex). During 2001-2014, R and Rindex estimates obtained using methods 1-4 were 0.72 (95% confidence interval (CI): 0.68, 0.76), 0.66 (95% CI: 0.62, 0.70), 0.45 (95% CI: 0.40, 0.49), and 0.63 (95% CI: 0.57, 0.69), respectively. Year-to-year variability in the values of R and Rindex and an increase in transmissibility in recent years were noted with all methods. Elimination of endemic measles transmission is maintained in the United States. A suggested increase in measles transmissibility since elimination warrants continued monitoring and emphasizes the importance of high measles vaccination coverage throughout the population.

Cost analysis of measles in refugees arriving at Los Angeles International Airport from Malaysia.

Background On August 24, 2011, 31 US-bound refugees from Kuala Lumpur, Malaysia (KL) arrived in Los Angeles. One of them was diagnosed with measles post-arrival. He exposed others during a flight, and persons in the community while disembarking and seeking medical care. As a result, 9 cases of measles were identified. Methods We estimated costs of response to this outbreak and conducted a comparative cost analysis examining what might have happened had all US-bound refugees been vaccinated before leaving Malaysia. Results State-by-state costs differed and variously included vaccination, hospitalization, medical visits, and contact tracing with costs ranging from $621 to $35,115. The total of domestic and IOM Malaysia reported costs for US-bound refugees were $137,505 [range: $134,531 - $142,777 from a sensitivity analysis]. Had all US-bound refugees been vaccinated while in Malaysia, it would have cost approximately $19,646 and could have prevented 8 measles cases. Conclusion A vaccination program for US-bound refugees, supporting a complete vaccination for US-bound refugees, could improve refugees' health, reduce importations of vaccine-preventable diseases in the United States, and avert measles response activities and costs.

Application of the World Health Organization Programmatic Assessment Tool for Risk of Measles Virus Transmission-Lessons Learned from a Measles Outbreak in Senegal.

The World Health Organization (WHO) African Region set a goal for regional measles elimination by 2020; however, regional measles incidence was 125/1,000,000 in 2012. To support elimination efforts, the WHO and U.S. Centers for Disease Control and Prevention developed a tool to assess performance of measles control activities and identify high-risk areas at the subnational level. The tool uses routinely collected data to generate district-level risk scores across four categories: population immunity, surveillance quality, program performance, and threat assessment. To pilot test this tool, we used retrospective data from 2006 to 2008 to identify high-risk districts in Senegal; results were compared with measles case-based surveillance data from 2009 when Senegal experienced a large measles outbreak. Seventeen (25%) of 69 districts in Senegal were classified as high or very high risk. The tool highlighted how each of the four categories contributed to the total risk scores for high or very high risk districts. Measles case-based surveillance reported 986 cases during 2009, including 368 laboratory-confirmed, 540 epidemiologically linked, and 78 clinically compatible cases. The seven districts with the highest numbers of laboratory-confirmed or epidemiologically linked cases were within the capital region of Dakar. All except one of these seven districts were estimated to be high or very high risk, suggesting that districts identified as high risk by the tool have the potential for measles outbreaks. Prospective use of this tool is recommended to help immunization and surveillance program managers identify high-risk areas in which to strengthen specific programmatic weaknesses and mitigate risk for potential measles outbreaks.

Measles in Healthcare Facilities in the United States During the Postelimination Era, 2001-2014.

Between 2001 and 2014, 78 reported measles cases resulted from transmission in US healthcare facilities, and 29 healthcare personnel were infected from occupational exposure, 1 of whom transmitted measles to a patient. The economic impact of preventing and controlling measles transmission in healthcare facilities was $19 000-$114 286 per case.

Measles investigation: a moving target.

Measles is a highly contagious respiratory infection with significant transmission risk once thought to be on the verge of elimination. Outbreaks in Europe have resulted in resurgence; however, experience with measles is limited in the United States. We describe the impact of 2 measles cases presenting to our emergency department in May 2011. Exposure criteria were defined and revised. Guidance documents were developed and distributed. Suspect cases were masked and escorted to negative pressure. Lack of prompt IgM and polymerase chain reaction testing resulted in delayed disease confirmation. Computerized flagging systems were established. Exposed individuals were screened to determine the need for prophylaxis. Investigation costs were calculated. A total of 171 patients and visitors and 94 employees met exposure criteria. Employees had proof of immunity to measles. Of these, 43 patients and visitors returned for prophylaxis. No subsequent transmission occurred. The conservative cost for these investigations was $63,176.39. Multiple challenges were identified. Inexperience with measles can result in significant outbreaks. Although transmission did occur at another facility, it was prevented at our facility because of rapid case recognition, isolation, health care worker immunity, and multidisciplinary response. Discordance between the Healthcare Infection Control Practices Advisory Committee and public health guidelines for measles control created unnecessary challenges.

Inference for ecological dynamical systems: a case study of two endemic diseases.

A Bayesian Markov chain Monte Carlo method is used to infer parameters for an open stochastic epidemiological modEL: the Markovian susceptible-infected-recovered (SIR) model, which is suitable for modeling and simulating recurrent epidemics. This allows exploring two major problems of inference appearing in many mechanistic population models. First, trajectories of these processes are often only partly observed. For example, during an epidemic the transmission process is only partly observable: one cannot record infection times. Therefore, one only records cases (infections) as the observations. As a result some means of imputing or reconstructing individuals in the susceptible cases class must be accomplished. Second, the official reporting of observations (cases in epidemiology) is typically done not as they are actually recorded but at some temporal interval over which they have been aggregated. To address these issues, this paper investigates the following problems. Parameter inference for a perfectly sampled open Markovian SIR is first considered. Next inference for an imperfectly observed sample path of the system is studied. Although this second problem has been solved for the case of closed epidemics, it has proven quite difficult for the case of open recurrent epidemics. Lastly, application of the statistical theory is made to measles and pertussis epidemic time series data from 60 UK cities.

A network-based analysis of the 1861 Hagelloch measles data.

In this article, we demonstrate a statistical method for fitting the parameters of a sophisticated network and epidemic model to disease data. The pattern of contacts between hosts is described by a class of dyadic independence exponential-family random graph models (ERGMs), whereas the transmission process that runs over the network is modeled as a stochastic susceptible-exposed-infectious-removed (SEIR) epidemic. We fit these models to very detailed data from the 1861 measles outbreak in Hagelloch, Germany. The network models include parameters for all recorded host covariates including age, sex, household, and classroom membership and household location whereas the SEIR epidemic model has exponentially distributed transmission times with gamma-distributed latent and infective periods. This approach allows us to make meaningful statements about the structure of the population-separate from the transmission process-as well as to provide estimates of various biological quantities of interest, such as the effective reproductive number, R. Using reversible jump Markov chain Monte Carlo, we produce samples from the joint posterior distribution of all the parameters of this model-the network, transmission tree, network parameters, and SEIR parameters-and perform Bayesian model selection to find the best-fitting network model. We compare our results with those of previous analyses and show that the ERGM network model better fits the data than a Bernoulli network model previously used. We also provide a software package, written in R, that performs this type of analysis.