Abstract
Tuberculosis is a major source of global mortality caused by infection, partly because of a tremendous ongoing burden of undiagnosed disease. Improved diagnostic technology may play an increasingly crucial part in global efforts to end tuberculosis, but the ability of diagnostic tests to curb tuberculosis transmission is dependent on multiple factors, including the time taken by a patient to seek health care, the patient's symptoms, and the patterns of transmission before diagnosis. Novel diagnostic assays for tuberculosis have conventionally been evaluated on the basis of characteristics such as sensitivity and specificity, using assumptions that probably overestimate the impact of diagnostic tests on transmission. We argue for a shift in focus to the evaluation of such tests' incremental value, defining outcomes that reflect each test's purpose (for example, transmissions averted) and comparing systems with the test against those without, in terms of those outcomes. Incremental value can also be measured in units of outcome per incremental unit of resource (for example, money or human capacity). Using a novel, simplified model of tuberculosis transmission that addresses some of the limitations of earlier tuberculosis diagnostic models, we demonstrate that the incremental value of any novel test depends not just on its accuracy, but also on elements such as patient behaviour, tuberculosis natural history and health systems. By integrating these factors into a single unified framework, we advance an approach to the evaluation of new diagnostic tests for tuberculosis that considers the incremental value at the population level and demonstrates how additional data could inform more-effective implementation of tuberculosis diagnostic tests under various conditions.
Highlights
E very year, nearly three million people develop active tuberculosis (TB), but are not notified to health authorities[1]
We use principles of infectious-disease modelling and diagnostic epidemiology to argue for a change in conceptual approach, from one that has focused primarily on a test’s sensitivity to one that centres on its incremental value
We explore three hypothetical settings for how transmission varies during the course of TB disease: late diagnostic gap, in which the transmission rate β is four-fold higher at each subsequent stage of TB disease; early diagnostic gap, in which β falls by a factor of four at each stage; and high access disparity, in which those with least access to care are assumed to have a rate of diagnosis and treatment that is 10% that of the general population
Summary
E very year, nearly three million people develop active tuberculosis (TB), but are not notified to health authorities[1]. The impact of TB diagnostics on transmission reflects the accuracy of the test, and the way in which patients with infectious TB interact with members of the community and with health systems over time[16,17] These infection pathways have at least three crucial dimensions: the transmission rate (number of transmission events per unit time), the frequency at which people contact health systems (often slower in subpopulations with poor access to care), and the probability of starting effective TB treatment after such contact[18]. The projected epidemiological impact of a more sensitive diagnostic test in this framework is tremendous This conceptualization of the diagnostic process (constant transmission, constant health-system contact and constant probability of successful diagnosis) over time has permeated most projections of expected epidemiological impact from novel diagnostic tests for pulmonary TB — and it is almost certainly wrong. We use principles of infectious-disease modelling and diagnostic epidemiology to argue for a change in conceptual approach, from one that has focused primarily on a test’s sensitivity to one that centres on its incremental value
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