Measles Dynamics Research Articles

A 60-year review on the changing epidemiology of measles in capital Beijing, China, 1951-2011

BackgroundChina pledged to join the global effort to eliminate measles by 2012. To improve measles control strategy, the epidemic trend and population immunity of measles were investigated in 1951–2011 in Beijing.MethodsThe changing trend of measles since 1951 was described based on measles surveillance data from Beijing Centre of Disease Control and Prevention (CDC). The measles vaccination coverage and antibody level were assessed by routinely reported measles vaccination data and twenty-one sero-epidemiological surveys.ResultsThe incidence of measles has decreased significantly from 593.5/100,000 in 1951 (peaked at 2721.0/100,000 in 1955), to 0.5/100,000 in 2011 due to increasing vaccination coverage of 95%-99%. Incidence rebounded from 6.6/100,000 to 24.5/100,000 since 2005 and decreased after measles vaccine (MV) supplementary immunization activities (SIAs) in 2010. Measles antibody positive rate was 85%-95% in most of years since 1981. High-risk districts were spotted in Chaoyang, Fengtai and Changping districts in recent 15 years. Age-specific incidence and proportion of measles varied over time. The most affected population were younger children of 1–4 years before 1978, older children of 5–14 years in 1978–1996, infant of <1 years and adults of ≥15 years in period of aim to measles elimination.ConclusionStrategies at different stages had a prevailing effect on the epidemic dynamics of measles in recent 60 years in Beijing. It will be essential to validate reported vaccination coverage, improve vaccination coverage in adults and strengthen measles surveillance in the anticipated elimination campaign for measles.

Impact of Birth Seasonality on Dynamics of Acute Immunizing Infections in Sub-Saharan Africa

We analyze the impact of birth seasonality (seasonal oscillations in the birth rate) on the dynamics of acute, immunizing childhood infectious diseases. Previous research has explored the effect of human birth seasonality on infectious disease dynamics using parameters appropriate for the developed world. We build on this work by including in our analysis an extended range of baseline birth rates and amplitudes, which correspond to developing world settings. Additionally, our analysis accounts for seasonal forcing both in births and contact rates. We focus in particular on the dynamics of measles. In the absence of seasonal transmission rates or stochastic forcing, for typical measles epidemiological parameters, birth seasonality induces either annual or biennial epidemics. Changes in the magnitude of the birth fluctuations (birth amplitude) can induce significant changes in the size of the epidemic peaks, but have little impact on timing of disease epidemics within the year. In contrast, changes to the birth seasonality phase (location of the peak in birth amplitude within the year) significantly influence the timing of the epidemics. In the presence of seasonality in contact rates, at relatively low birth rates (20 per 1000), birth amplitude has little impact on the dynamics but does have an impact on the magnitude and timing of the epidemics. However, as the mean birth rate increases, both birth amplitude and phase play an important role in driving the dynamics of the epidemic. There are stronger effects at higher birth rates.

MATHEMATICAL MODEL FOR CONTROL OF MEASLES EPIDEMIOLOGY

Abstract: An SEIR epidemic model is investigated to ascertain the impact of exposed individuals at latent period (individuals who are infected but not yet infectious) on the transmission dynamics of measles. Mathematical analysis is carried out that completely determine the dynamics of the model. The impact of exposed individuals at latent period are discussed through the stability analysis and numerical simulation.

Effects of the infectious period distribution on predicted transitions in childhood disease dynamics

The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced 'susceptible-exposed-infectious-removed' (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible-infectious-removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions.

Modelling of Infectious Diseases for Providing Signal of Epidemics: A Measles Case Study in Bangladesh

The detection of unusual patterns in the occurrence of diseases is an important challenge to health workers interested in early identification of epidemics. The objective of this study was to provide an early signal of infectious disease epidemics by analyzing the disease dynamics. A two-stage monitoring system was applied, which consists of univariate Box-Jenkins model or autoregressive integrated moving average model and subsequent tracking signals from several statistical process-control charts. The analyses were illustrated on January 2000-August 2009 national measles data reported monthly to the Expanded Programme on Immunization (EPI) in Bangladesh. The results of this empirical study revealed that the most adequate model for the occurrences of measles in Bangladesh was the seasonal autoregressive integrated moving average (3, 1, 0) (0, 1, 1)12 model, and the statistical process-control charts detected no measles epidemics during September 2007-August 2009. The two-stage monitoring system performed well to capture the measles dynamics in Bangladesh without detection of an epidemic because of high measles-vaccination coverage.

Simulasi Pengaruh Laju Kelahiran dan Vaksinasi Terhadap Pola Dinamika Epidemik Campak

The purpose of this research is to get description about influence of birth rates to the epidemic dynamics pattern of measles is presented as system of nonlinear differential equations. In this case, the epidemic dynamics of measles is of the form of the SEIR model with births which is obtained from four compartments: susceptible, exposed, infectious, and recovered. Then we analyze parameter model (α) to know the influence of change of birth rates to the epidemic dynamics pattern of measles. The changes of birth rates do not alter common pattern of epidemic measles, but the number of epidemic cycle, epidemic process, oscillation process, epidemic size, and time of epidemic convergent changes significantly. If the birth rate increases so does the epidemic cycle, but the epidemic process decreases, the oscillation is faster, and epidemic size converges to higher level value. If the birth rate decreases, the number of epidemic cycle decreases, epidemic process and oscillation take a longer, the epidemic size decreases with higher variance and converges to lower value.

The OptAIDS project: towards global halting of HIV/AIDS

The OptAIDS project: towards global halting of HIV/AIDS

Decreasing stochasticity through enhanced seasonality in measles epidemics.

Seasonal changes in the environment are known to be important drivers of population dynamics, giving rise to sustained population cycles. However, it is often difficult to measure the strength and shape of seasonal forces affecting populations. In recent years, statistical time-series methods have been applied to the incidence records of childhood infectious diseases in an attempt to estimate seasonal variation in transmission rates, as driven by the pattern of school terms. In turn, school-term forcing was used to show how susceptible influx rates affect the interepidemic period. In this paper, we document the response of measles dynamics to distinct shifts in the parameter regime using previously unexplored records of measles mortality from the early decades of the twentieth century. We describe temporal patterns of measles epidemics using spectral analysis techniques, and point out a marked decrease in birth rates over time. Changes in host demography alone do not, however, suffice to explain epidemiological transitions. By fitting the time-series susceptible-infected-recovered model to measles mortality data, we obtain estimates of seasonal transmission in different eras, and find that seasonality increased over time. This analysis supports theoretical work linking complex population dynamics and the balance between stochastic and deterministic forces as determined by the strength of seasonality.

A link between the North Atlantic Oscillation and measles dynamics during the vaccination period in England and Wales

Ecologists have become aware of the role played by interannual climatic variability on the temporal dynamics of infectious diseases. In this report, I present evidence from data on measles cases in England and Wales showing that during the post-vaccination period, the interannual variability of winter weather (represented by the North Atlantic Oscillation, NAO) influences the annual dynamics of the disease. Using annual measles data from seven cities and simple logistic models, this study reveals how, after vaccination, NAO increases its effects on measles fluctuations. In addition, this study shows that vaccination may be represented as a simple vertical and lateral perturbation effect (Royama's classification), by reducing the maximum per capita growth rate and the equilibrium number of infected individuals. The results suggest that vaccination will not lead to outbreaks of measles from regular cyclic to irregular chaotic dynamics. In contrast, because of the reduction in per capita growth rates, the disease dynamics appear to be more stable than during the pre-vaccination period. The analysis of annual data on infectious diseases may be useful for detecting long-term effects of climate and complements the classical analyses and modeling based on monthly or seasonal time-step data.

Interpreting changes in measles genotype: the contribution of chance, migration and vaccine coverage

BackgroundIn some populations, complete shifts in the genotype of the strain of measles circulating in the population have been observed, with given genotypes being replaced by new genotypes. Studies have postulated that such shifts may be attributable to differences between the fitness of the new and the old genotypes.MethodsWe developed a stochastic model of the transmission dynamics of measles, simulating the effects of different levels of migration, vaccination coverage and importation of new genotypes on patterns in the persistence and replacement of indigenous genotypes.ResultsThe analyses illustrate that complete replacement in the genotype of the strain circulating in populations may occur because of chance. This occurred in >50% of model simulations, for levels of vaccination coverage and numbers of imported cases per year which are compatible with those observed in several Western European populations (>80% and >3 per million per year respectively) and for the given assumptions in the model.ConclusionThe interpretation of genotypic data, which are increasingly being collected in surveillance programmes, needs to take account of the underlying vaccination coverage and the level of the importation rate of measles cases into the population.

Measles on the Edge: Coastal Heterogeneities and Infection Dynamics

Mathematical models can help elucidate the spatio-temporal dynamics of epidemics as well as the impact of control measures. The gravity model for directly transmitted diseases is currently one of the most parsimonious models for spatial epidemic spread. This model uses distance-weighted, population size-dependent coupling to estimate host movement and disease incidence in metapopulations. The model captures overall measles dynamics in terms of underlying human movement in pre-vaccination England and Wales (previously established). In spatial models, edges often present a special challenge. Therefore, to test the model's robustness, we analyzed gravity model incidence predictions for coastal cities in England and Wales. Results show that, although predictions are accurate for inland towns, they significantly underestimate coastal persistence. We examine incidence, outbreak seasonality, and public transportation records, to show that the model's inaccuracies stem from an underestimation of total contacts per individual along the coast. We rescue this predicted ‘edge effect’ by increasing coastal contacts to approximate the number of per capita inland contacts. These results illustrate the impact of ‘edge effects’ on epidemic metapopulations in general and illustrate directions for the refinement of spatiotemporal epidemic models.

Dynamics and control of measles in Portugal: Accessing the impact of anticipating the age for the first dose of MMR from 15 to 12 months of age

The all-time low incidence of measles in Portugal in the recent years, raises questions regarding whether the disease has been eliminated, the role of recent control measures, and the epidemiological consequences of the rise in the proportion of newborns to vaccinated mothers, as opposed to those born to mothers who acquired immunity by natural infection. We estimate the vaccination coverage against measles in Portugal on a cohort-by-cohort basis, and incorporate this information into an age-structured seasonally-driven mathematical model aimed at reproducing measles dynamics in the past decades. The model reproduces documented trends in disease notifications and the serological profile of the Portuguese population, as estimated by a recent National Serological Survey. We provide evidence that the effective reproduction number (R(e)) of measles has been driven below 1 in Portugal, and that sustained measles elimination is crucially dependent upon the maintenance of a high (>95%) coverage with the MMR I vaccine in the future. If the vaccination coverage decreases to levels around 90% the anticipation of the first dose of the MMR I from 15 to 12 months of age, will ensure that R(e) remains below 1.

The Evolutionary and Epidemiological Dynamics of the Paramyxoviridae

Paramyxoviruses are responsible for considerable disease burden in human and wildlife populations: measles and mumps continue to affect the health of children worldwide, while canine distemper virus causes serious morbidity and mortality in a wide range of mammalian species. Although these viruses have been studied extensively at both the epidemiological and the phylogenetic scales, little has been done to integrate these two types of data. Using a Bayesian coalescent approach, we infer the evolutionary and epidemiological dynamics of measles, mumps and canine distemper viruses. Our analysis yielded data on viral substitution rates, the time to common ancestry, and elements of their demographic history. Estimates of rates of evolutionary change were similar to those observed in other RNA viruses, ranging from 6.585 to 11.350 x 10(-4 )nucleotide substitutions per site, per year. Strikingly, the mean Time to the Most Recent Common Ancestor (TMRCA) was both similar and very recent among the viruses studied, ranging from only 58 to 91 years (1908 to 1943). Worldwide, the paramyxoviruses studied here have maintained a relatively constant level of genetic diversity. However, detailed heterchronous samples illustrate more complex dynamics in some epidemic populations, and the relatively low levels of genetic diversity (population size) in all three viruses is likely to reflect the population bottlenecks that follow recurrent outbreaks.

The impact of a physical geographic barrier on the dynamics of measles

Spatial-temporal patterns of measles incidence reflect the spatial distribution of human hosts. The heterogeneous spatial distribution of communities has been shown to introduce spatially dependent temporal lags in the timing of measles incidence. Incidence patterns reflect internal dynamics within a community and coupling of communities through the movement of infectious individuals. The central role of human movement in coupling dynamics in separate communities suggests that physical geographic barriers to movement should reduce spatial-temporal correlation. We examine measles dynamics in Maryland and Pennsylvania during the period of 1917-1938. The central feature of interest is the Chesapeake Bay, which separates Maryland into two distinct regions. We find that correlation of measles incidences in communities separated by the bay is reduced compared to communities not separated by the bay, suggesting the bay acted as a barrier to human movement during this time sufficient to decouple measles dynamics in Maryland counties.

Realistic population dynamics in epidemiological models: the impact of population decline on the dynamics of childhood infectious diseases: Measles in Italy as an example

Most contributions in the field of mathematical modelling of childhood infectious diseases transmission dynamics have focused on stationary or exponentially growing populations. In this paper an epidemiological model with realistic demography is used to investigate the impact of the non-equilibrium conditions typical of the transition to sustained below replacement fertility (BRF) recently observed in a number of western countries, upon the transmission dynamics of measles. The results depend on the manner we model the relation between the (changing) age distribution of the population and contacts. Under some circumstances the transitional ageing phase typical of BRF populations might complexly interact with epidemiological variables leading to (i) a substantial reduction in the amount of vaccination effort required for eliminating the disease; (ii) a significant magnification of the perverse impact of vaccination in terms of the burden of severe age related morbidity.

Whooping cough metapopulation dynamics in tropical conditions: disease persistence and impact of vaccination

Recent insights in compiling metapopulation models and infectious disease dynamics have enabled a better understanding of spatial and temporal persistence of diseases. The concept of the critical community size (CCS) has been developed with major consideration on analyses of whooping cough and measles dynamics from temperate countries for which large datasets are available. However, few studies have questioned the generality of CCS curves for other regions, i.e. tropical areas, mainly because data are very sparse. This work constitutes, to our knowledge, the first study of whooping cough persistence in a tropical area, in a rural part of Senegal (Western Africa) where the population has been followed for 20 years. In this small community, the CCS is not reached even if we observe CCS-like curves showing persistence increasing with population size. In addition, our analysis supports the idea that vaccination has impacted the spatiotemporal dynamics and persistence of the disease. These findings suggest the need for more comparative analyses of spatio-temporal data series from a wide range of contrasted countries, for example developed and developing nations, so as to have a better understanding of vaccination effects on disease dynamics and persistence.

Disease and Death in the South African War: Changing Disease Patterns from Soldiers to Refugees

The involvement of civilians, Boer women, children, and blacks is increasingly integrated within the military history of the South African War. This article assesses the disease history of the war in this context, collating data on mortality from various sources for the first time. Over 60 per cent of total deaths during the war were among civilians, shared among all ethnic groups (Boer, black, and white), and measles was probably the largest killer. Disaggregation by individual refugee camp shows: the rapidity of the epidemics; the early mortality peaks by July 1901; the varied timing and severity of disease by camp; and the importance of measles in explaining the very high mortality rates. At first sight, the decline in overall mortality appears to coincide with the 'magical effects' of the British commissions so often cited by historians. However, individual camp mortality curves do not support this historical explanation. We emphasize the epidemiological dynamics of measles, as well as the effects of local camp conditions of overcrowding and malnutrition. Providing a less dashing picture, the South African War is best characterized by measles as well as typhoid. The war shows the crossing in importance of a nineteenth-century military disease history represented by typhoid, and a refugee-civilian disease history that extends to the end of the twentieth century.

Measles metapopulation dynamics: a gravity model for epidemiological coupling and dynamics.

Infectious diseases provide a particularly clear illustration of the spatiotemporal underpinnings of consumer-resource dynamics. The paradigm is provided by extremely contagious, acute, immunizing childhood infections. Partially synchronized, unstable oscillations are punctuated by local extinctions. This, in turn, can result in spatial differentiation in the timing of epidemics and, depending on the nature of spatial contagion, may result in traveling waves. Measles epidemics are one of a few systems documented well enough to reveal all of these properties and how they are affected by spatiotemporal variations in population structure and demography. On the basis of a gravity coupling model and a time series susceptible-infected-recovered (TSIR) model for local dynamics, we propose a metapopulation model for regional measles dynamics. The model can capture all the major spatiotemporal properties in prevaccination epidemics of measles in England and Wales.

Measles Metapopulation Dynamics: A Gravity Model for Epidemiological Coupling and Dynamics

Infectious diseases provide a particularly clear illustration of the spatiotemporal underpinnings of consumer‐resource dynamics. The paradigm is provided by extremely contagious, acute, immunizing childhood infections. Partially synchronized, unstable oscillations are punctuated by local extinctions. This, in turn, can result in spatial differentiation in the timing of epidemics and, depending on the nature of spatial contagion, may result in traveling waves. Measles epidemics are one of a few systems documented well enough to reveal all of these properties and how they are affected by spatiotemporal variations in population structure and demography. On the basis of a gravity coupling model and a time series susceptible‐infected‐recovered (TSIR) model for local dynamics, we propose a metapopulation model for regional measles dynamics. The model can capture all the major spatiotemporal properties in prevaccination epidemics of measles in England and Wales.

Measles dynamics and vaccination diffusion

Although numerous mathematical models focusing on measles dynamics have been proposed in the literature, efforts in this area have concentrated essentially on the mechanisms of measles propagation. If present, vaccination diffusion is treated as an exogenous factor. Here we propose a model focused on the course of measles in France in which the mechanisms of vaccination diffusion are explicitly modeled. The parameters in this model are estimated by an original method based on an expectation-maximization algorithm. This model gives indications of the way in which measles propagation and vaccination diffusion interact. It also allows discussion of the possibility of eliminating this disease in France in the near future.