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Identifying multidrug resistant tuberculosis transmission hotspots using routinely collected data.

ABSTRACT: In most countries with large drug resistant tuberculosis epidemics, only those cases that are at highest risk of having MDRTB receive a drug sensitivity test (DST) at the time of diagnosis. Because of this prioritized testing, identification of MDRTB transmission hotspots in communities where TB cases do not receive DST is challenging, as any observed aggregation of MDRTB may reflect systematic differences in how testing is distributed in communities. We introduce a new disease mapping method, which estimates this missing information through probability-weighted locations, to identify geographic areas of increased risk of MDRTB transmission. We apply this method to routinely collected data from two districts in Lima, Peru over three consecutive years. This method identifies an area in the eastern part of Lima where previously untreated cases have increased risk of MDRTB. This may indicate an area of increased transmission of drug resistant disease, a finding that may otherwise have been missed by routine analysis of programmatic data. The risk of MDR among retreatment cases is also highest in these probable transmission hotspots, though a high level of MDR among retreatment cases is present throughout the study area. Identifying potential multidrug resistant tuberculosis (MDRTB) transmission hotspots may allow for targeted investigation and deployment of resources.

SUBMITTER: Manjourides J

PROVIDER: S-EPMC3323731 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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Identifying multidrug resistant tuberculosis transmission hotspots using routinely collected data.

Manjourides Justin J Lin Hsien-Ho HH Shin Sonya S Jeffery Caroline C Contreras Carmen C Cruz Janeth Santa JS Jave Oswaldo O Yagui Martin M Asencios Luis L Pagano Marcello M Cohen Ted T

Tuberculosis (Edinburgh, Scotland) 20120306 3

In most countries with large drug resistant tuberculosis epidemics, only those cases that are at highest risk of having MDRTB receive a drug sensitivity test (DST) at the time of diagnosis. Because of this prioritized testing, identification of MDRTB transmission hotspots in communities where TB cases do not receive DST is challenging, as any observed aggregation of MDRTB may reflect systematic differences in how testing is distributed in communities. We introduce a new disease mapping method, w ...[more]

PMID: 22401962

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Project description:OBJECTIVE:The positive deviance approach seeks to identify and learn from exceptional performers. Although a framework exists to apply positive deviance within healthcare organisations, there is limited guidance to support its implementation. The approach has also rarely explored exceptional performance on broad outcomes, been implemented at ward level, or applied within the UK. This study develops and critically appraises a pragmatic method for identifying positively deviant wards using a routinely collected, broad measure of patient safety. DESIGN:A two-phased observational study was conducted. During phase 1, cross-sectional and temporal analyses of Safety Thermometer data were conducted to identify a discrete group of positively deviant wards that consistently demonstrated exceptional levels of safety. A group of matched comparison wards with above average performances were also identified. During phase 2, multidisciplinary staff and patients on the positively deviant and comparison wards completed surveys to explore whether their perceptions of safety supported the identification of positively deviant wards. SETTING:34 elderly medical wards within a northern region of England, UK. PARTICIPANTS:Multidisciplinary staff (n=161) and patients (n=188) clustered within nine positively deviant and comparison wards. RESULTS:Phase 1: A combination of analyses identified five positively deviant wards that performed best in the region, outperformed their organisation and performed consistently well over 12 months. Five above average matched comparator wards were also identified. Phase 2: Staff and patient perceptions of safety generally supported the identification of positively deviant wards using Safety Thermometer data, although patient perceptions of safety were less concordant with the routinely collected data. CONCLUSIONS:This study tentatively supports a pragmatic method of using routinely collected data to identify positively deviant elderly medical wards; however, it also highlights the various challenges that are faced when conducting the first stage of the positive deviance approach. TRIAL REGISTRATION NUMBER:UK Clinical Research Network Portfolio (reference-18050).

Project description:BackgroundMolecular epidemiological approaches provide opportunities to characterize HIV transmission dynamics. We analyzed HIV sequences and virus load (VL) results obtained during routine clinical care, and individual's zip-code location to determine utility of this approach.MethodsHIV-1 pol sequences aligned using ClustalW were subtyped using REGA. A maximum likelihood (ML) tree was generated using IQTree. Transmission clusters with ≤3% genetic distance (GD) and ≥90% bootstrap support were identified using ClusterPicker. We conducted Bayesian analysis using BEAST to confirm transmission clusters. The proportion of nucleotides with ambiguity ≤0.5% was considered indicative of early infection. Descriptive statistics were applied to characterize clusters and group comparisons were performed using chi-square or t-test.ResultsAmong 2775 adults with data from 2014-2015, 2589 (93%) had subtype B HIV-1, mean age was 44 years (SD 12.7), 66.4% were male, and 25% had nucleotide ambiguity ≤0.5. There were 456 individuals in 193 clusters: 149 dyads, 32 triads, and 12 groups with ≥ four individuals per cluster. More commonly in clusters were males than females, 349 (76.5%) vs. 107 (23.5%), p < 0.0001; younger individuals, 35.3 years (SD 12.1) vs. 44.7 (SD 12.3), p < 0.0001; and those with early HIV-1 infection by nucleotide ambiguity, 202/456 (44.3%) vs. 442/2133 (20.7%), p < 0.0001. Members of 43/193 (22.3%) of clusters included individuals in different jurisdictions. Clusters ≥ four individuals were similarly found using BEAST. HIV-1 viral load (VL) ≥3.0 log10 c/mL was most common among individuals in clusters ≥ four, 18/21, (85.7%) compared to 137/208 (65.8%) in clusters sized 2-3, and 927/1169 (79.3%) who were not in a cluster (p < 0.0001).DiscussionHIV sequence data obtained for HIV clinical management provide insights into regional transmission dynamics. Our findings demonstrate the additional utility of HIV-1 VL data in combination with phylogenetic inferences as an enhanced contact tracing tool to direct HIV treatment and prevention services. Trans-jurisdictional approaches are needed to optimize efforts to end the HIV epidemic.

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Project description:BackgroundThere is substantial evidence that systemic anticancer therapies and radiotherapy can increase the long-term risk of cardiovascular disease (CVD). Optimal management decisions for cancer patients therefore need to take into account the likely risks from a proposed treatment option, as well as its likely benefits. For CVD, the magnitude of the risk depends on the incidence of the disease in the general population to which the patient belongs, including variation with age and sex, as well as on the treatment option under consideration. The aim of this paper is to provide estimates of CVD incidence rates in the general population of England for use in cardio-oncology and in other relevant clinical, research and health policy contexts.MethodsWe studied a population-based representative cohort, consisting of 2,633,472 individuals, derived by electronic linkage of records from primary care with those of admitted-patient care in England during April 1, 2010, to April 1, 2015. From 38 individual CVDs available via the linked dataset we identified five relevant categories of CVD whose risk may be increased by cancer treatments: four of heart disease and one of stroke.ResultsWe calculated incidence rates by age-group and sex for all relevant CVD categories combined, for the four relevant categories of heart disease combined, and for the five relevant CVD categories separately. We present separate incidence rates for all 38 individual CVDs available via the linked dataset. We also illustrate how our data can be used to estimate absolute CVD risks in a range of people with Hodgkin lymphoma treated with chemotherapy and radiotherapy.ConclusionsOur results provide population-based CVD incidence rates for a variety of uses, including the estimation of absolute risks of CVD from cancer treatments, thus helping patients and clinicians to make appropriate individualized cancer treatment decisions. Graphical Abstract: Cardiovascular incidence rates for use in cardio-oncology and elsewhere: A presentation of age- and sex-specific cardiovascular disease (CVD) incidence rates for use in calculation of absolute cardiovascular risks of cancer treatments, and in other clinical, research and health policy contexts. Abbreviations - CVD: cardiovascular disease; y: years.

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Identifying multidrug resistant tuberculosis transmission hotspots using routinely collected data.

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Identifying multidrug resistant tuberculosis transmission hotspots using routinely collected data.

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