SUMMARY
The factors underlying the temporal dynamics of rubella outside of Europe and North America are not well known. Here we used 20 years of incidence reports from Mexico to identify variation in seasonal forcing and magnitude of transmission across the country and to explore determinants of inter-annual variability in epidemic magnitude in rubella. We found considerable regional variation in both magnitude of transmission and amplitude of seasonal variation in transmission. Several lines of evidence pointed to stochastic dynamics as an important driver of multi-annual cycles. Since average age of infection increased with the relative importance of stochastic dynamics, this conclusion has implications for the burden of congenital rubella syndrome. We discuss factors underlying regional variation, and implications of the importance of stochasticity for vaccination implementation.
With more emphasis being put on global infectious disease monitoring, viral genetic data are being collected at an astounding rate, both within and without the context of a long-term disease surveillance plan. Concurrent with this increase have come improvements to the sophisticated and generalized statistical techniques used for extracting population-level information from genetic sequence data. However, little research has been done on how the collection of these viral sequence data can or does affect the efficacy of the phylogenetic algorithms used to analyse and interpret them. In this study, we use epidemic simulations to consider how the collection of viral sequence data clarifies or distorts the picture, provided by the phylogenetic algorithms, of the underlying population dynamics of the simulated viral infection over many epidemic cycles. We find that sampling protocols purposefully designed to capture sequences at specific points in the epidemic cycle, such as is done for seasonal influenza surveillance, lead to a significantly better view of the underlying population dynamics than do less-focused collection protocols. Our results suggest that the temporal distribution of samples can have a significant effect on what can be inferred from genetic data, and thus highlight the importance of considering this distribution when designing or evaluating protocols and analysing the data collected thereunder.
We use simulations to highlight how (accounting for the dynamical context) high-quality measles and rubella serological surveys can be used to inform key control and elimination questions if the challenges of conducting, analyzing, and interpreting them are overcome.
SummaryThe objective of this study is to estimate the effective reproductive ratio for the [2003][2004] measles epidemic in Niamey, Niger. Using the results of a retrospective and prospective study of reported cases within Niamey during the 2003-2004 epidemic, we estimate the basic reproductive ratio, effective reproductive ratio (RE) and minimal vaccination coverage necessary to avert future epidemics using a recent method allowing for estimation based on the epidemic case series. We provide these estimates for geographic areas within Niamey, thereby identifying neighbourhoods at high risk. The estimated citywide RE was 2.8, considerably lower than previous estimates, which may help explain the long duration of the epidemic. Transmission intensity varied during the course of the epidemic and within different neighbourhoods (RE range: 1.4-4.7). Our results indicate that vaccination coverage in currently susceptible children should be increased by at least 67% (vaccine efficacy 90%) to produce a citywide vaccine coverage of 90%. This research highlights the importance of local differences in vaccination coverage on the potential impact of epidemic control measures. The spatial-temporal spread of the epidemic from district to district in Niamey over 30 weeks suggests that targeted interventions within the city could have an impact.
Madagascar reports few measles cases annually and high vaccination campaign coverage. However, the underlying age profile of immunity and risk of a measles outbreak is unknown. We conducted a nested serological survey, testing 1,005 serum samples (collected between November 2013 and December 2015 via Madagascar’s febrile rash surveillance system) for measles immunoglobulin G antibody titers. We directly estimated the age profile of immunity and compared these estimates with indirect estimates based on a birth cohort model of vaccination coverage and natural infection. Combining these estimates of the age profile of immunity in the population with an age-structured model of transmission, we further predicted the risk of a measles outbreak and the impact of mitigation strategies designed around supplementary immunization activities. The direct and indirect estimates of age-specific seroprevalence show that current measles susceptibility is over 10%, and modeling suggests that Madagascar may be at risk of a major measles epidemic.
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