Modeling age- and time-specific incidence from seroprevalence:toxoplasmosis.
ABSTRACT New forms of catalytic epidemic models were developed to estimate the incidence of primary toxoplasmosis infection from age- and time-specific seroprevalence data collected from persons aged 0-100 years in South Yorkshire, England, 1969-1990. Piecewise constant and exponential polynomial functions were used to assess the way in which incidence depended on age and time, and to guide the choice of parametric models suitable for prediction. Incidence estimates were biased unless both age- and time-dependence were allowed for. New findings on the epidemiology of this infection emerged. Incidence appears to have fallen sixfold between 1915 and 1970, but has remained stable for the last 20 years. There is a marked peak in incidence in childhood. The incidence throughout the childbearing period is currently estimated to be 0.07 or less per 100 susceptible persons per year. However, these predictions were highly sensitive to assumptions about incidence in childhood, and the 95% confidence limits for a range of models were between 0.003 and 0.32% per year. Age- and time-specific seroprevalence data can be collected inexpensively on a mass population basis, and, with appropriate incidence modeling, may prove to be a powerful method for the study of infectious disease and for incidence prediction.
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ABSTRACT: We undertook a representative survey of measles antibodies in Addis Ababa, Ethiopia 1994, to characterize immunity and transmission. Specific-antibody levels (IU/l) were determined by ELISA for 4654 sera from individuals aged 0-49 years (1805 < 15 years) collected by stratified household-cluster sampling. The proportion seronegative (< 100 IU/l) was 20% (95% CI: 16-25) in children 9-59 months old, declining to 9% (7-12) in 5-9 year olds, 5% (4-7) in 10-14 year olds, and < 1% in adults. The proportion of children (< 15 years old) with low-level antibody (100-255 IU/l) was 8% (7-10). Vaccination and an absence of a history of measles illness were strongly associated with low-level antibody. History of measles vaccination in 9 months to 14-year-old children was approximately 80%. We estimate a primary vaccine failure rate of 21% (12-34) and continued high measles incidence of 22 per 100 susceptibles (19-24) per annum. Our data support the introduction of campaign vaccination in the city in 1998, although higher routine vaccine coverage is required to sustain the impact. The implications of a high prevalence of low-level antibody are discussed.Epidemiology and Infection 06/2003; 130(3):507-19. · 2.87 Impact Factor
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ABSTRACT: We develop methods for the analysis of infectious disease data when age-specific contact rates vary over time. Our methods are valid when contact rates vary slowly on the time scale of the infection process, and are applicable to a variety of data types including serial seroprevalence surveys and case reports. The methods exploit approximate endemic equilibria, and require numerical solution of an associated integral equation in age and time. We also estimate summary statistics such as time-dependent analogs of the basic reproduction number and critical immunization threshold. We illustrate the methods with data on varicella (chickenpox) in the United Kingdom.Biometrics 10/2004; 60(3):615-23. · 1.41 Impact Factor
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ABSTRACT: This article reviews quantitative methods to estimate the basic reproduction number of pandemic influenza, a key threshold quantity to help determine the intensity of interventions required to control the disease. Although it is difficult to assess the transmission potential of a probable future pandemic, historical epidemiologic data is readily available from previous pandemics, and as a reference quantity for future pandemic planning, mathematical and statistical analyses of historical data are crucial. In particular, because many historical records tend to document only the temporal distribution of cases or deaths (i.e. epidemic curve), our review focuses on methods to maximize the utility of time-evolution data and to clarify the detailed mechanisms of the spread of influenza.First, we highlight structured epidemic models and their parameter estimation method which can quantify the detailed disease dynamics including those we cannot observe directly. Duration-structured epidemic systems are subsequently presented, offering firm understanding of the definition of the basic and effective reproduction numbers. When the initial growth phase of an epidemic is investigated, the distribution of the generation time is key statistical information to appropriately estimate the transmission potential using the intrinsic growth rate. Applications of stochastic processes are also highlighted to estimate the transmission potential using similar data. Critically important characteristics of influenza data are subsequently summarized, followed by our conclusions to suggest potential future methodological improvements.Physics of Life Reviews 01/2008; · 6.58 Impact Factor