ArticlesProspects for worldwide tuberculosis control under the WHO DOTS strategy
Introduction
Short-course chemotherapy is currently the most effective treatment for most patients with tuberculosis, and direct observation helps many patients to complete the 6-8 month treatment regimen.1, 2, 3 Passive case detection is recommended because countrywide, active case finding would be prohibitively expensive in most countries, and because population surveys typically find that four in five cases have already sought medical attention at the time of detection by mass screening.4 Moreover, evidence from more developed countries indicates that active case finding has only a limited impact on the transmission of infection. Passive case detection, coupled with treatment that ensured high cure rates, contributed to the rapid decline in rates of tuberculosis in more developed countries after 1950.5 Preventive therapy, the main alternative to treatment of active cases, is recommended for people at high risk of developing tuberculosis (for example, contacts of known cases, HIV-1-positive individuals6), but not for entire populations, because incidence rates are lower than 0·2% per year in most parts of the world. For these reasons, WHO's DOTS strategy for worldwide tuberculosis control embraces passive case detection by means of smear microscopy, directly observed short-course therapy (DOTS) with the recording and reporting of treatment outcomes, together with mechanisms to ensure a regular drug supply.7, 8
This partial justification for the DOTS stategy lacks two critical elements. First, we require a formal quantitative assessment of the likely worldwide effect of improvement in rates of case detection and cure. Second, there is a need to investigate how to reach and cure more patients. This paper deals with the first of these questions. We used a mathematical model that brings together data from studies of the biology of tuberculosis, and from the history of successful tuberculosis control in industrialised countries, to assess the potential effect of DOTS in those developing countries where the disease is most prevalent.
Section snippets
Tuberculosis model
We developed an age-structured tuberculosis model framed in difference equations (discrete time). Our aim was to construct the simplest model able to answer the questions at hand, although the result is a moderately complex compartmental model.9, 10, 11 Details of the model are in a technical appendix available from the investigators or The Lancet's website (http://www.thelancet.com).
Tuberculosis arises as progressive primary disease in people who have been newly infected, or by endogenous
Results
We identified a series of general characteristics of tuberculosis control by DOTS.
Discussion
WHO's 1996 appraisal23 of best buys for research on major microbial diseases concluded that the development of strategies to extend DOTS coverage is a priority. Our findings lend support to that conclusion by quantifying the large numbers of cases and deaths that could be prevented through improvements in case detection and cure rates.
We found that the potential effect of DOTS on tuberculosis in many developing countries is even greater than the results achieved in industrialised countries when
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2022, Infectious Disease ModellingCitation Excerpt :Obviously, the property is lost if the “day cohorts” are not identical to each other (e.g., if they experience different case-detection rates). The general principles of our mathematical model follow the vast majority of published models of TB epidemiology (e.g., (Avilov et al., 2015; Baltussen et al., 2005; Blower et al., 1995; Brogger, 1967; Dye et al., 1998; Murray & Salomon, 1998; Perelman et al., 2004; Waaler et al., 1962; Yaesoubi & Cohen, 2013)): we used a compartmental epidemiological model based on ordinary differential equations; it had no stratification by age or sex in the model population, but clearly differentiated T- and T+ TB cases by using two separate groups for them (thus forming the submodel of the progression of active TB). Transitions between model groups were defined by constant or time-dependent per capita rates.