Chaos, Persistence, and Evolution of Strain Structure in Antigenically Diverse Infectious Agents

Gupta, Sunetra; Ferguson, Neil; Anderson, Roy M.

doi:10.1126/science.280.5365.912

Cited by 281 publications

(363 citation statements)

References 12 publications

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“…The empirical evidence for the type of cross-immunity between serotypes therefore does not unequivocally support a particular model, e.g. Kamo & Sasaki (2002) versus Gupta et al (1998), but a combination of models. The particular choice of model, however, does not affect our general conclusion (results not shown).…”

Section: The Mathematical Modelmentioning

confidence: 99%

“…Alternative definitions and models for cross-immunity exist (e.g. Andreasen et al 1997;Gupta et al 1998;Gog & Swinton 2002); we use this representation because volunteer studies have shown that patients re-challenged with the heterologous serotype of cholera rarely become infected. When symptoms do occur, they are milder and V. cholerae excretion levels are reduced (Cash et al 1974), arguing for a concomitant reduction in transmissibility, which is not incorporated in the model framework we use here.…”

Section: The Mathematical Modelmentioning

confidence: 99%

“…In the case of pathogens such as influenza, continual antigenic drift results from partial crossimmunity between sufficiently similar strains and the large number of possible variants. For pathogens with only a few possible strain variants, theoretical studies predict strain cycling as the predominant pattern (Andreasen et al 1997;Gupta et al 1998;Dawes & Gog 2002). However, due to the multiplicity of strains that underlies many diseases and the lack of sufficiently long disease datasets, a clear empirical example of this theoretical expectation is still lacking.…”

Section: Introductionmentioning

confidence: 99%

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Serotype cycles in cholera dynamics

2006

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Interest in understanding strain diversity and its impact on disease dynamics has grown over the past decade. Theoretical disease models of several co-circulating strains indicate that incomplete crossimmunity generates conditions for strain-cycling behaviour at the population level. However, there have been no quantitative analyses of disease time-series that are clear examples of theoretically expected strain cycling. Here, we analyse a 40-year (1966-2005) cholera time-series from Bangladesh to determine whether patterns evident in these data are compatible with serotype-cycling behaviour. A mathematical two-serotype model is capable of explaining the oscillations in case patterns when cross-immunity between the two serotypes, Inaba and Ogawa, is high. Further support that cholera's serotype-cycling arises from population-level immunity patterns is provided by calculations of time-varying effective reproductive rates. These results shed light on historically observed serotype dominance shifts and have important implications for cholera early warning systems.

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Section: The Mathematical Modelmentioning

confidence: 99%

Section: The Mathematical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Serotype cycles in cholera dynamics

2006

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“…Whilst the detailed structure and magnitude of the pattern of these timeseries di¡er, it is striking to note that all suggest signi¢-cant three-or four-year oscillations in dengue infection incidence. Clearly, before such a conclusion can be de¢ni-tively con¢rmed, analysis of other strati¢ed serological surveys will be required, but it is supported by data from hospitalization reports (Briseno-Garcia et al 1996) and clinical observation (Dove 1998 transmission dynamics of the virus (Ferguson et al 1999;Gupta et al 1998), where they are generated by immunemediated competition or cooperation between strains.…”

Section: Applicationmentioning

confidence: 99%

Transmission dynamics and epidemiology of dengue: insights from age–stratified sero–prevalence surveys

Ferguson

Donnelly

Anderson

1999

Phil. Trans. R. Soc. Lond. B

199

194

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The relationship between infection with the four major serotypes of dengue virus and the occurrence of di¡erent forms of disease is complex and not fully understood. Interpreting longitudinal records of the incidence of serious disease to gain insight into the transmission dynamics and epidemiology of the virus is therefore complicated. Since age re£ects duration of exposure, age-strati¢ed, strain-speci¢c serological surveys carried out at one point in time, or over a short time interval, can potentially provide a rich source of information on longitudinal patterns. This paper describes the development and application (to data collected in Thailand) of statistically rigorous methods designed to estimate time-varying, strainspeci¢c forces of infection, and thus basic reproduction numbers, from cross-sectional serological data. The analyses provide support for the hypothesis that antibody-dependent enhancement of transmission in£uences observed epidemiological pattern. Age-strati¢ed serological data also reveal evidence of a propensity for the annual incidence of infection to oscillate over time with a frequency of several years. The latter observation is consistent with the predictions of simple mathematical models of the transmission dynamics of the virus. The estimates of the basic reproduction numbers obtained are similar in magnitude for each dengue serotype, being in the range of four to six. Such values are higher than those obtained from earlier analyses, and the implications of this for dengue control are discussed.

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“…Organisms such as influenza and pneumococcus have well-established interactions [18] and vaccination for one may have additional benefits in preventing a proportion of another infection which is not estimable from this analysis. In addition the impact of vaccination for a subgroup of types, as proposed for the pneumococcus, may have unpredictable results [19].…”

Section: Discussionmentioning

confidence: 99%

Modelling hospital admissions for lower respiratory tract infections in the elderly in England

Müller‐Pebody

Crowcroft²,

Zambon³

et al. 2006

Epidemiol. Infect.

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SUMMARYDespite the importance of lower respiratory-tract infection (LRI) in causing hospitalizations in elderly patients (o65 years of age) and recent advances in vaccine development, a complete picture of the causative organisms is not available. All hospital discharge diagnoses (ICD-10 code) for LRI in elderly patients in England during 1995-1998 were reviewed. Using known seasonality in potential causative agents of LRI, the contribution of different respiratory pathogens to hospitalizations coded as ' unspecified LRI' was estimated by multiple linear regression analysis. Ninety-seven per cent of 551 633 LRI-associated diagnoses had no specific organism recorded. From the statistical model the estimated proportions of admissions attributable to different pathogens were applied to calculate estimated hospitalization rates : 93 . 9 hospitalizations/10 000 population aged o65 years due to S. pneumoniae, 22 . 9 to influenza virus, 22 . 3 to H. influenzae, 17 . 0 to whooping cough, and 12 . 8 to respiratory syncytial virus. There is enormous potential to improve health using existing vaccines and those under development.

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Chaos, Persistence, and Evolution of Strain Structure in Antigenically Diverse Infectious Agents

Cited by 281 publications

References 12 publications

Serotype cycles in cholera dynamics

Serotype cycles in cholera dynamics

Transmission dynamics and epidemiology of dengue: insights from age–stratified sero–prevalence surveys

Modelling hospital admissions for lower respiratory tract infections in the elderly in England

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