The other side of surveillance: Monitoring, application, and integration of tuberculosis data to guide and evaluate programme activities in South Africa

Background. The importance of using surveillance data to monitor and evaluate programme activities has been emphasised in international policies for tuberculosis (TB) control.Objectives. A survey was conducted to assess the use of TB surveillance data to monitor and guide TB programme activities in South Africa (SA).Methods. As part of an evaluation of the SA national TB surveillance system, semi-structured interviews were conducted among TB staff at health facilities and offices in three provinces. At each site, all persons involved with TB care, management and surveillance were invited to participate.Results. At least one person (range 1 - 4) was interviewed at 47/54 health facilities (87.0%), 11/13 subdistrict and district TB offices (84.6%), 2/3 provincial TB offices (66.7%), and at the national level (1/1, 100.0%). Of 119 TB staff, 64.7% recognised the purpose of TB surveillance as guiding programme planning, implementation and evaluation. However, only 16.0% reported using data to measure disease burden, 8.4% to monitor trends, and 9.2% to inform resource allocation. The majority reported using TB management tools provided by the national programme, but 44.5% also described using additional tools. Personnel mentioned the need for dedicated surveillance staff, training on recording and reporting, improved computer access, and methods to apply information from surveillance data to the programme.Conclusions. The majority of TB staff understood the purpose of surveillance but did not routinely use data to guide programme planning, implementation and evaluation. Training and supporting TB staff to utilise surveillance data will help improve the TB surveillance system

The other side of surveillance: Monitoring, application, and integration of tuberculosis data to guide and evaluate programme activities in South Africa

Background. The importance of using surveillance data to monitor and evaluate programme activities has been emphasised in international policies for tuberculosis (TB) control.Objectives. A survey was conducted to assess the use of TB surveillance data to monitor and guide TB programme activities in South Africa (SA).Methods. As part of an evaluation of the SA national TB surveillance system, semi-structured interviews were conducted among TB staff at health facilities and offices in three provinces. At each site, all persons involved with TB care, management and surveillance were invited to participate.Results. At least one person (range 1 - 4) was interviewed at 47/54 health facilities (87.0%), 11/13 subdistrict and district TB offices (84.6%), 2/3 provincial TB offices (66.7%), and at the national level (1/1, 100.0%). Of 119 TB staff, 64.7% recognised the purpose of TB surveillance as guiding programme planning, implementation and evaluation. However, only 16.0% reported using data to measure disease burden, 8.4% to monitor trends, and 9.2% to inform resource allocation. The majority reported using TB management tools provided by the national programme, but 44.5% also described using additional tools. Personnel mentioned the need for dedicated surveillance staff, training on recording and reporting, improved computer access, and methods to apply information from surveillance data to the programme.Conclusions. The majority of TB staff understood the purpose of surveillance but did not routinely use data to guide programme planning, implementation and evaluation. Training and supporting TB staff to utilise surveillance data will help improve the TB surveillance system

Simple inclusion of complex diagnostic algorithms in infectious disease models for economic evaluation

INTRODUCTION: Cost-effectiveness models for infectious disease interventions often require transmission models that capture the indirect benefits from averted subsequent infections. Compartmental models based on ordinary differential equations are commonly used in this context. Decision trees are frequently used in cost-effectiveness modeling and are well suited to describing diagnostic algorithms. However, complex decision trees are laborious to specify as compartmental models and cumbersome to adapt, limiting the detail of algorithms typically included in transmission models. METHODS: We consider an approximation replacing a decision tree with a single holding state for systems where the time scale of the diagnostic algorithm is shorter than time scales associated with disease progression or transmission. We describe recursive algorithms for calculating the outcomes and mean costs and delays associated with decision trees, as well as design strategies for computational implementation. We assess the performance of the approximation in a simple model of transmission/diagnosis and its role in simplifying a model of tuberculosis diagnostics. RESULTS: When diagnostic delays were short relative to recovery rates, our approximation provided a good account of infection dynamics and the cumulative costs of diagnosis and treatment. Proportional errors were below 5% so long as the longest delay in our 2-step algorithm was under 20% of the recovery time scale. Specifying new diagnostic algorithms in our tuberculosis model was reduced from several tens to just a few lines of code. DISCUSSION: For conditions characterized by a diagnostic process that is neither instantaneous nor protracted (relative to transmission dynamics), this novel approach retains the advantages of decision trees while embedding them in more complex models of disease transmission. Concise specification and code reuse increase transparency and reduce potential for error

Risk factors for SARS-CoV-2 infection and transmission in households with children with asthma and allergy: A prospective surveillance study

BACKGROUND: Whether children and people with asthma and allergic diseases are at increased risk for severe acute respiratory syndrome virus 2 (SARS-CoV-2) infection is unknown. OBJECTIVE: Our aims were to determine the incidence of SARS-CoV-2 infection in households with children and to also determine whether self-reported asthma and/or other allergic diseases are associated with infection and household transmission. METHODS: For 6 months, biweekly nasal swabs and weekly surveys were conducted within 1394 households (N = 4142 participants) to identify incident SARS-CoV-2 infections from May 2020 to February 2021, which was the pandemic period largely before a vaccine and before the emergence of SARS-CoV-2 variants. Participant and household infection and household transmission probabilities were calculated by using time-to-event analyses, and factors associated with infection and transmission risk were determined by using regression analyses. RESULTS: In all, 147 households (261 participants) tested positive for SARS-CoV-2. The household SARS-CoV-2 infection probability was 25.8%; the participant infection probability was similar for children (14.0% [95% CI = 8.0%-19.6%]), teenagers (12.1% [95% CI = 8.2%-15.9%]), and adults (14.0% [95% CI = 9.5%-18.4%]). Infections were symptomatic in 24.5% of children, 41.2% of teenagers, and 62.5% of adults. Self-reported doctor-diagnosed asthma was not a risk factor for infection (adjusted hazard ratio [aHR] = 1.04 [95% CI = 0.73-1.46]), nor was upper respiratory allergy or eczema. Self-reported doctor-diagnosed food allergy was associated with lower infection risk (aHR = 0.50 [95% CI = 0.32-0.81]); higher body mass index was associated with increased infection risk (aHR per 10-point increase = 1.09 [95% CI = 1.03-1.15]). The household secondary attack rate was 57.7%. Asthma was not associated with household transmission, but transmission was lower in households with food allergy (adjusted odds ratio = 0.43 [95% CI = 0.19-0.96]; P = .04). CONCLUSION: Asthma does not increase the risk of SARS-CoV-2 infection. Food allergy is associated with lower infection risk, whereas body mass index is associated with increased infection risk. Understanding how these factors modify infection risk may offer new avenues for preventing infection