Dataset Information

Periodicity, synchronization and persistence in pre-vaccination measles.

ABSTRACT: We investigate the relationship between periodicity, synchronization and persistence of measles through simulations of geographical spread on the British Isles. We show that the establishment of areas of biennial periodicity depends on the interplay between human mobility and local population size and that locations undergoing biennial cycles tend to be, on average, synchronized in phase. We show however that occurrences of opposition of phase are actually quite common and correspond to stable dynamics. We also show that persistence is strictly related to circulation of the disease in the highly populated area of London and that this ensures survival of the disease even when human mobility drops to extremely low levels.

SUBMITTER: Marguta R

PROVIDER: S-EPMC4938089 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Periodicity, synchronization and persistence in pre-vaccination measles.

Marguta Ramona R Parisi Andrea A

Journal of the Royal Society, Interface 20160601 119

We investigate the relationship between periodicity, synchronization and persistence of measles through simulations of geographical spread on the British Isles. We show that the establishment of areas of biennial periodicity depends on the interplay between human mobility and local population size and that locations undergoing biennial cycles tend to be, on average, synchronized in phase. We show however that occurrences of opposition of phase are actually quite common and correspond to stable d ...[more]

PMID: 27278363

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Project description:Measles is a highly transmissible disease and is one of the leading causes of death among young children under 5 globally. While the use of ongoing surveillance data and-recently-dynamic models offer insight on measles dynamics, both suffer notable shortcomings when applied to measles outbreak prediction. In this paper, we apply the Sequential Monte Carlo approach of particle filtering, incorporating reported measles incidence for Saskatchewan during the pre-vaccination era, using an adaptation of a previously contributed measles compartmental model. To secure further insight, we also perform particle filtering on an age structured adaptation of the model in which the population is divided into two interacting age groups-children and adults. The results indicate that, when used with a suitable dynamic model, particle filtering can offer high predictive capacity for measles dynamics and outbreak occurrence in a low vaccination context. We have investigated five particle filtering models in this project. Based on the most competitive model as evaluated by predictive accuracy, we have performed prediction and outbreak classification analysis. The prediction results demonstrate that this model could predict measles outbreak evolution and classify whether there will be an outbreak or not in the next month (Area under the ROC Curve of 0.89). We conclude that anticipating the outbreak dynamics of measles in low vaccination regions by applying particle filtering with simple measles transmission models, and incorporating time series of reported case counts, is a valuable technique to assist public health authorities in estimating risk and magnitude of measles outbreaks. It is to be emphasized that particle filtering supports estimation of (via sampling from) the entire state of the dynamic model-both latent and observable-for each point in time. Such approach offers a particularly strong value proposition for other pathogens with little-known dynamics, critical latent drivers, and in the context of the growing number of high-velocity electronic data sources. Strong additional benefits are also likely to be realized from extending the application of this technique to highly vaccinated populations.

Project description:Background:There is a global resurgence of measles, consequent upon worldwide stagnating measles vaccination coverage. The study aim was to document trends and characteristics of reported cases of measles, measles-related deaths, and measles vaccination coverage (MCV1-first dose of measles-containing vaccine and MCV2-second dose of measles-containing vaccine) at national and sub-national level in Myanmar over a five year period between 2014 and 2018. Methods:This was a descriptive study using routine data collected and submitted to the Expanded Programme on Immunization. Results:Between 2014 and 2018, there were 2673 measles cases of which 2272 (85%) occurred in 2017 and 2018. Five adjacent regions in lower Myanmar were the most affected: in 2017 and 2018, these regions reported 1647 (73%) of the 2272 measles cases in the country. Overall, 73% of measles cases were laboratory confirmed, 21% were epidemiologically linked, and 6% were clinically compatible (clinical diagnosis only), with more laboratory confirmed cases in recent years. Annual measles-related deaths were either zero or one except in 2016 when there were 21 deaths, all occurring in one remote village. In the recent years, the most commonly affected age groups were 0-8 months, 9 months to 4 years, and ??15 years. Among 1907 measles cases with known vaccination status, only 22% had been vaccinated and 70% of those had only received one dose of vaccine. Annual MCV1 coverage nationally varied from 83 to 93% while annual MCV2 coverage nationally varied from 78 to 87%, with no clear trends over the years. Between 2014 and 2018, a high proportion of the 330 townships had MCV coverage <?95%. Over 80% of measles cases were reported from townships that had MCV coverage <?95%. Conclusion:There have been a large number of measles cases in recent years associated with sub-optimal measles vaccine coverage. Myanmar has already conducted supplemental immunization activities in October and November, 2019. Myanmar also needs to improve routine immunization services and targeted responses to measles outbreaks.

Dataset Information

Periodicity, synchronization and persistence in pre-vaccination measles.

Publications

Periodicity, synchronization and persistence in pre-vaccination measles.

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