Periodic Reporting for period 4 - TBornotTB (What is Tuberculosis? Challenging the Current Paradigm of Tuberculosis Natural History using Mathematical Modelling Techniques)
Período documentado: 2022-09-01 hasta 2023-11-30
TBornotTB was a project that aimed to better understand how tuberculosis (TB) develops in individuals and spreads in populations. For a public health threat that has caused over two billion deaths in human history the so-called natural history of TB has remained stubbornly elusive. The classic paradigm of TB natural history typically accounted for two distinct stages of infection and disease, and one-way progression between them. However, data from past and present showed that individuals actually experience disease across a spectrum intensity, which varies over time.
When the TBornotTB project started, little was known on how many individuals were currently in the different states of disease, how long they remained there, and how much they contributed to ongoing transmission. There was not even agreement how many disease states there were. If we do not even know those basic things, we are unlikely to help reduce the number of people and communities who suffer from TB.
That is why TBornotTB had two main objectives. First to bring together old and new data to understand what the relevant states of TB infection and disease are, and the pathways people take. Secondly, we show how this new understanding can help make better choices TB in reducing TB.
At completion of the project, our work helped to show the TB community that multiple disease states not only exist, but that these states also matter for individual TB care and transmission in the population. We have supported funders and policy makers to grapple with the consequences of these new insights for development and testing of new vaccines, treatments and diagnostics, as well as bold strategies to really reduce the burden of this persistent old foe of global health.
When the TBornotTB project started, little was known on how many individuals were currently in the different states of disease, how long they remained there, and how much they contributed to ongoing transmission. There was not even agreement how many disease states there were. If we do not even know those basic things, we are unlikely to help reduce the number of people and communities who suffer from TB.
That is why TBornotTB had two main objectives. First to bring together old and new data to understand what the relevant states of TB infection and disease are, and the pathways people take. Secondly, we show how this new understanding can help make better choices TB in reducing TB.
At completion of the project, our work helped to show the TB community that multiple disease states not only exist, but that these states also matter for individual TB care and transmission in the population. We have supported funders and policy makers to grapple with the consequences of these new insights for development and testing of new vaccines, treatments and diagnostics, as well as bold strategies to really reduce the burden of this persistent old foe of global health.
Our work has shown not just that there are different states of TB disease, but also how important these states are, with around half of infectious individuals not reporting symptoms (Figure 1), what happens after people become infected (Figure 2), and how relevant these states are for transmission (Figure 3).
To do this, we looked at all relevant data from 1905 until now, and put those together in a single modelling framework. We looked at what were the most likely states and disease pathways to fit the data, and then put it all together in a single framework to understand how people experience TB disease. Our results show that only 10% of people who are infected develop TB, and the majority of those who do not progress to disease actually clear their infection instead of remaining at risk lifelong (Figure 2). If someone gets disease, only a third will develop classic disease where an individual both has symptoms and is infectious. The remainder will have tissue damage and may be infectious, but either remain in that state or recover after a long period. Because of that, around half of transmission comes from people who either never develop classic disease, or are yet to do so.
In our final pieces of work we are looking at how these new insights change the likely impact and cost of current and potential future TB policies, in terms of finding and treating people with TB. We found that current approaches, where people with TB have to report to clinics before they receive care, do not interrupt transmission, which explains why we still see so much TB, even if fewer people die from the disease. Instead, if we screen people regardless of symptoms, we can quickly reduce new infections occurring.
We also contributed our experience to the COVID-19 response by estimating how much of SARS-CoV-2 transmission was due to non-symptomatic individuals using data from the outbreak on the Diamond Princess cruise ship (Figure 4). We showed that non-symptomatic transmission was a major issue during the pandemic, which was confirmed by other work.
To make our results as useful as possible, we have presented our work at scientific conferences, but also focussed on discussions with those who decide on global policy (World Health Organisation), funding for product development and research (Bill and Melinda Gates Foundation, Wellcome Trust) and global research groups. We also organised a large consensus meeting with people from across professions, countries and lived TB experience to set a new framework for describing and researching TB.
For more information and related publications, please see: https://erc-tbornottb.github.io/
To do this, we looked at all relevant data from 1905 until now, and put those together in a single modelling framework. We looked at what were the most likely states and disease pathways to fit the data, and then put it all together in a single framework to understand how people experience TB disease. Our results show that only 10% of people who are infected develop TB, and the majority of those who do not progress to disease actually clear their infection instead of remaining at risk lifelong (Figure 2). If someone gets disease, only a third will develop classic disease where an individual both has symptoms and is infectious. The remainder will have tissue damage and may be infectious, but either remain in that state or recover after a long period. Because of that, around half of transmission comes from people who either never develop classic disease, or are yet to do so.
In our final pieces of work we are looking at how these new insights change the likely impact and cost of current and potential future TB policies, in terms of finding and treating people with TB. We found that current approaches, where people with TB have to report to clinics before they receive care, do not interrupt transmission, which explains why we still see so much TB, even if fewer people die from the disease. Instead, if we screen people regardless of symptoms, we can quickly reduce new infections occurring.
We also contributed our experience to the COVID-19 response by estimating how much of SARS-CoV-2 transmission was due to non-symptomatic individuals using data from the outbreak on the Diamond Princess cruise ship (Figure 4). We showed that non-symptomatic transmission was a major issue during the pandemic, which was confirmed by other work.
To make our results as useful as possible, we have presented our work at scientific conferences, but also focussed on discussions with those who decide on global policy (World Health Organisation), funding for product development and research (Bill and Melinda Gates Foundation, Wellcome Trust) and global research groups. We also organised a large consensus meeting with people from across professions, countries and lived TB experience to set a new framework for describing and researching TB.
For more information and related publications, please see: https://erc-tbornottb.github.io/
For more than forty years, people were taught that TB only existed in latent infection and active disease states. This included the PI when they first started. Our work has made sure that teaching can and should now change. We have not just provided evidence, but also the alternative approach to talking about TB, and how it fits the data and how it can be used to improve TB care for the millions of people suffering from TB, and the many more who are affected by this persistent threat to healthy life in mainly disadvantaged communities.