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Portuguese and British scientists develop mathematical model that explains variability in tuberculosis vaccine efficacy
March 03, 2004Scientists at the Instituto Gulbenkian de Ciencia (IGC), in Portugal, together with colleagues at the Universities of Lisbon and Warwick, in the United Kingdom, have developed a mathematical model that explains why the tuberculosis (TB) vaccine is ineffective in many of the developing countries. The model quantifies the predicted decrease in the number of TB cases in light of both the socioeconomic development of a population and the characteristics of new vaccines. Their research has been published in the Proceedings of the Royal Society (22nd March edition).
The efficacy of the bacille Calmette-Guérin (BCG) vaccine (the only vaccine in current use against tuberculosis) is variable, and there is no consensus about its usefulness. Estimates of protection range from 80% in the United Kingdom to around 0% in India, for example. For 30 years now scientists have tried to unravel the role of socioeconomic, genetic and environmental factors in generating this broad range of protection. This new model highlights socioeconomic factors (namely population density, access to primary healthcare, sanitation and diet, amongst others), which influence the dissemination of the infeccious agent.
The scientists estimate that the efficacy of the BCG vaccine decreases as the number of cases of TB increases, leading to a positive feedback loop, whose effect becomes most evident when the transmission potential reaches the reinfection threshold (a newly-defined concept). Other factors are expected to be involved, but no other model to date has been able to reproduce the magnitude of observed trends.
According to Gabriela Gomes, head of the Theoretical Epidemiology group at the IGC, the model shows that the vaccine is successful in blocking transmission in a population whose transmission potential is below the reinfection threshold (in these cases, most of the TB cases are due to primary infections). In those populations where the transmission potential exceeds the reinfection threshold, on the other hand, the protective effect of the vaccine is literally obliterated by the high levels of reinfection. The model predicts that, in these populations, only a vaccine with a stronger protective effect than a previous infection will successfully reduce transmission of tuberculosis.
In developed countries, the TB transmission potential is well below the reinfection threshold, due, largely, to major improvements in socioeconomic conditions, begun the mid-1800s. In less developed countries, on the other hand, the incidence of TB is up to 100 times higher. The poor socioeconomic conditions increase the potential for transmission, to levels clearly above the reinfection threshold. In these countries, changes in socioeconomic conditions are slow and difficult, therefore the scientists propose that the development of more potent vaccines is a more realistically hopeful measure for keeping TB under control. Their model also indicates the desired characteristics for such vaccines.
In Portugal the situation appears to one of delicate equilibrium, wherein any change may be sharply amplified. The number of reported cases of TB in Portugal points to transmission levels close to the reinfection threshold. The model predicts, therefore, that efforts to control tuberculosis will be greatly rewarded, but inattentiveness may result in a sharp rise in the number of cases.
The conclusions and predictions of this model are applicable to other diseases for which primary infection does not induce solid immunity. These diseases are kept prevalent by the high number of reinfections (malaria is an example of such a disease).
"This research underscores how important it is to combine mathematical modelling with experimental research in order to better understand infectious diseases, and developing effective therapeutical strategies", says Antonio Coutinho, Director of the IGC.
Instituto Gulbenkian de CiÙncia (IGC)
According to Gabriela Gomes, head of the Theoretical Epidemiology group at the IGC, the model shows that the vaccine is successful in blocking transmission in a population whose transmission potential is below the reinfection threshold (in these cases, most of the TB cases are due to primary infections). In those populations where the transmission potential exceeds the reinfection threshold, on the other hand, the protective effect of the vaccine is literally obliterated by the high levels of reinfection. The model predicts that, in these populations, only a vaccine with a stronger protective effect than a previous infection will successfully reduce transmission of tuberculosis.
In developed countries, the TB transmission potential is well below the reinfection threshold, due, largely, to major improvements in socioeconomic conditions, begun the mid-1800s. In less developed countries, on the other hand, the incidence of TB is up to 100 times higher. The poor socioeconomic conditions increase the potential for transmission, to levels clearly above the reinfection threshold. In these countries, changes in socioeconomic conditions are slow and difficult, therefore the scientists propose that the development of more potent vaccines is a more realistically hopeful measure for keeping TB under control. Their model also indicates the desired characteristics for such vaccines.
In Portugal the situation appears to one of delicate equilibrium, wherein any change may be sharply amplified. The number of reported cases of TB in Portugal points to transmission levels close to the reinfection threshold. The model predicts, therefore, that efforts to control tuberculosis will be greatly rewarded, but inattentiveness may result in a sharp rise in the number of cases.
The conclusions and predictions of this model are applicable to other diseases for which primary infection does not induce solid immunity. These diseases are kept prevalent by the high number of reinfections (malaria is an example of such a disease).
"This research underscores how important it is to combine mathematical modelling with experimental research in order to better understand infectious diseases, and developing effective therapeutical strategies", says Antonio Coutinho, Director of the IGC.
Instituto Gulbenkian de CiÙncia (IGC)
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