A review of data needed to parameterize a dynamic model of measles in developing countries

Wednesday, 11th of December 2013

[source]BioMed Central[|source]

Although future measles incidence and disease burden cannot be known precisely, they can be projected by use of a dynamic model. Dynamic models incorporate transmission mechanisms and thus can describe how incidence evolves due to changes in factors such as demography and vaccine coverage. Dynamic models allow us to analyze the epidemiology of a disease within a population and experiment with various vaccination strategies "in silico" to determine which one would be optimal from a given perspective. Ideally, dynamic models are parameterized with data that are specific to the study population. However, measles epidemiology can vary across populations, which in turn provide implications for how vaccination programmes should be designed

In this article, the authors provide a summary of data needed to develop a dynamic model of measles transmission in Indian and African populations, such as the percent infected by age (age-stratified attack rate) and age-stratified seroprevalence profiles. The authors reviewed several studies, summarized attack rates and seroprevalence and make deductions about transmissibility in African versus Indian populations. The review confirmed previous findings of significant differences in measles epidemiology in low-income versus developed countries, with a distinctly lower mean age at infection in African and Indian populations, where the age of peak attack rates occurs at age 1 or 2 years. The report concludes that estimation of force of infection functions from age-stratified seroprevalence data suggest that the force of infection may decline monotonically with age in those populations. More details on this technical update are available at:  http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2848058/

 

Abstract

BACKGROUND: Dynamic models of infection transmission can project future disease burden within a population. Few dynamic measles models have been developed for low-income countries, where measles disease burden is highest. Our objective was to review the literature on measles epidemiology in low-income countries, with a particular focus on data that are needed to parameterize dynamic models.

METHODS: We included age-stratified case reporting and seroprevalence studies with fair to good sample sizes for mostly urban African and Indian populations. We emphasized studies replicas relojes hublot big bang conducted before widespread immunization. We summarized age-stratified attack rates and seroprevalence profiles across these populations. Using the study data, we fitted a "representative" seroprevalence profile for African and Indian settings. We also used a catalytic model to estimate the age-dependent force of infection for individual African and Indian studies where seroprevalence was surveyed. We used these data to quantify the effects of population density on the basic reproductive number R₀.

RESULTS: The peak attack rate usually occurred at age 1 year in Africa, and 1 to 2 years in India, which is earlier than in developed countries before mass vaccination. Approximately 60% of children were seropositive for measles antibody by age 2 in Africa and India, according to the representative seroprevalence profiles. A statistically significant decline in the force of infection with age was found in 4 of 6 Indian seroprevalence studies, but not in 2 African studies. This implies that the classic threshold result describing the critical proportion immune (p_c) required to eradicate an infectious disease, p_c = 1-1/R₀, may overestimate the required proportion immune to eradicate measles in some developing country populations. A possible, though not statistically significant, positive relation between population density and R₀ for various Indian and African populations was also found. These populations also showed a similar pattern of waning of maternal antibodies. Attack rates in rural Indian populations show little dependence on vaccine coverage or population density compared to urban Indian populations. Estimated R₀ values varied widely across populations which has further implications for measles elimination.

CONCLUSIONS: It is possible to develop a broadly informative dynamic model of measles transmission in low-income country settings based on existing literature, though it may be difficult to develop a model that is closely tailored to any given country. Greater efforts to collect data specific to low-income countries would aid in control efforts by allowing highly population-specific models to be developed.