16 research outputs found
Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making.
The dominant approach to decision-making in public health policy for infectious diseases relies heavily on expert opinion, which often applies empirical evidence to policy questions in a manner that is neither systematic nor transparent. Although systematic reviews are frequently commissioned to inform specific components of policy (such as efficacy), the same process is rarely applied to the full decision-making process. Mathematical models provide a mechanism through which empirical evidence can be methodically and transparently integrated to address such questions. However, such models are often considered difficult to interpret. In addition, models provide estimates that need to be iteratively re-evaluated as new data or considerations arise. Using the case study of a novel diagnostic for tuberculosis, a framework for improved collaboration between public health decision-makers and mathematical modellers that could lead to more transparent and evidence-driven policy decisions for infectious diseases in the future is proposed. The framework proposes that policymakers should establish long-term collaborations with modellers to address key questions, and that modellers should strive to provide clear explanations of the uncertainty of model structure and outputs. Doing so will improve the applicability of models and clarify their limitations when used to inform real-world public health policy decisions
Performance of the G4 Xpert(R) MTB/RIF assay for the detection of Mycobacterium tuberculosis and rifampin resistance: a retrospective case-control study of analytical and clinical samples from high- and low-tuberculosis prevalence settings
BACKGROUND: The Xpert(R) MTB/RIF (Xpert) assay is a rapid PCR-based assay for the detection of Mycobacterium tuberculosis complex DNA (MTBc) and mutations associated with rifampin resistance (RIF). An updated version introduced in 2011, the G4 Xpert, included modifications to probe B and updated analytic software.
METHODS: An analytical study was performed to assess Xpert detection of mutations associated with rifampin resistance in rifampin-susceptible and -resistant isolates. A clinical study was performed in which specimens from US and non-US persons suspected of tuberculosis (TB) were tested to determine Xpert performance characteristics. All specimens underwent smear microscopy, mycobacterial culture, conventional drug-susceptibility testing and Xpert testing; DNA from isolates with discordant rifampin resistance results was sequenced.
RESULTS: Among 191 laboratory-prepared isolates in the analytical study, Xpert sensitivity for detection of rifampin resistance associated mutations was 97.7% and specificity was 90.8%, which increased to 99.0% after DNA sequencing analysis of the discordant samples. Of the 1,096 subjects in the four clinical studies, 49% were from the US. Overall, Xpert detected MTBc in 439 of 468 culture-positive specimens for a sensitivity of 93.8% (95% confidence interval [CI]: 91.2%-95.7%) and did not detect MTBc in 620 of 628 culture-negative specimens for a specificity of 98.7% (95% CI: 97.5%-99.4%). Sensitivity was 99.7% among smear-positive cases, and 76.1% among smear-negative cases. Non-determinate MTBc detection and false-positive RIF resistance results were low (1.2 and 0.9%, respectively).
CONCLUSIONS: The updated Xpert assay retained the high sensitivity and specificity of the previous assay versions and demonstrated low rates of non-determinate and RIF resistance false positive results
Outbreak of Antiviral Drug–Resistant Influenza A in Long-Term Care Facility, Illinois, USA, 2008
An outbreak of oseltamivir-resistant influenza A (H1N1) occurred in a long-term care facility. Eight (47%) of 17 and 1 (6%) of 16 residents in 2 wards had oseltamivir-resistant influenza A virus (H1N1) infections. Initial outbreak response included treatment and prophylaxis with oseltamivir. The outbreak abated, likely because of infection control measures
Child, Household, and Caregiver Characteristics Associated with Hospitalization for Influenza Among Children 6–59 Months of Age
Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making
HIV treatment regimens and adherence to national guidelines in Australia: an analysis of dispensing data from the Australian pharmaceutical benefits scheme
Abstract Background Treatment guidelines for antiretroviral therapy (ART) have evolved to emphasize newer regimens that address ageing-related comorbidities. Using national Australian dispensing data we compare ART regimens with Australian HIV treatment guidelines in the context of treated comorbidities. Methods The study population included all individuals in a 10% sample of national data from the Australian Pharmaceutical Benefits Scheme (PBS) who purchased a prescription of ART during 2016. We defined each patient’s most recently dispensed ART regimen and characterized them to evaluate regimen complexity and adherence to national HIV treatment guidelines. We then analyzed ART regimens in the context of other co-prescriptions purchased for defined comorbidities. Results The 1995 patients in our sample purchased 212 different ART regimens during 2016; 1524 (76.4%) purchased one of the top ten most common regimens of which 62.3% were integrase strand transfer inhibitor-based. Among the 1786 (90%) patients that purchased the most common regimens, 83.7% purchased a regimen recommended by the guidelines for initial antiretroviral therapy and 11.4% purchased antiretrovirals that are not recommended for initial therapy; < 1% of the entire cohort purchased medications not recommended for use. While most patients purchased optimal ART regimens with low potential for significant drug interactions, regimen choices in the setting of risk factors for heart disease, renal disease and low bone mineral density appeared suboptimal. Conclusions Australian HIV providers are prescribing ART regimens in accordance with updated treatment guidelines, but could further optimize regimens in the setting of important medical comorbidities
Improving the Sensitivity of the Xpert MTB/RIF Assay on Sputum Pellets by Decreasing the Amount of Added Sample Reagent: a Laboratory and Clinical Evaluation
Clinical and laboratory features of COVID-19 illness and outcomes in immunocompromised individuals during the first pandemic wave in Sydney, Australia
Child, household, and caregiver characteristics associated with hospitalization for influenza among children 6-59 months of age: an emerging infections program study.
BackgroundYoung children are at increased risk of severe outcomes from influenza illness, including hospitalization. We conducted a case-control study to identify risk factors for influenza-associated hospitalizations among children in US Emerging Infections Program sites.MethodsCases were children 6-59 months of age hospitalized for laboratory-confirmed influenza infections during 2005-2008. Age- and zip-code-matched controls were enrolled. Data on child, caregiver and household characteristics were collected from parents and medical records. Conditional logistic regression was used to identify independent risk factors for hospitalization.ResultsWe enrolled 290 (64%) of 454 eligible cases and 1089 (49%) of 2204 eligible controls. Risk for influenza hospitalization increased with maternal age <26 years [odds ratio (OR): 1.8, 95% confidence interval (CI): 1.1-2.9]; household income below the poverty threshold (OR: 2.2, 95% CI: 1.4-3.6); smoking by >50% of household members (OR: 2.9, 95% CI: 1.4-6.6); lack of household influenza vaccination (OR: 1.8, 95% CI: 1.2-2.5) and presence of chronic illnesses, including hematologic/oncologic (OR: 11.8, 95% CI: 4.5-31.0), pulmonary (OR: 2.9, 95% CI: 1.9-4.4) and neurologic (OR: 3.8, 95% CI: 1.6-9.2) conditions. Full influenza immunization decreased the risk among children 6-23 months of age (OR: 0.5, 95% CI: 0.3-0.9) but not among those 24-59 months of age (OR: 1.5, 95% CI: 0.8-3.0; P value for difference = 0.01).ConclusionsChronic illnesses, young maternal age, poverty, household smoking and lack of household influenza vaccination increased the risk of influenza hospitalization. These characteristics may help providers to identify young children who are at greatest risk for severe outcomes from influenza illness