Strains of Mycobacterium tuberculosis transmitting infection in Brazilian households and those associated with community transmission of tuberculosis.

Molecular epidemiologic studies have shown that the dynamics of tuberculosis transmission varies geographically. We sought to determine which strains of Mycobacterium tuberculosis (MTB) were infecting household contacts (HHC), and which were causing clusters of tuberculosis (TB) disease in Vitoria-ES, Brazil. A total of 741 households contacts (445 TST +) and 139 index cases were characterized according to the proportion of contacts in each household that had a tuberculin skin test positive: low (LT) (≤40% TST+), high (HT) (≥70% TST+) and (40-70% TST+) intermediate (IT) transmission. IS6110-RFLP and spoligotyping analysis were performed only 139 MTB isolates from index cases and 841 community isolates. Clustering occurred in 45% of the entire study population. There was no statistically significant association between MTB household transmission category and clustering. Within the household study population, the proportion of clusters in HT and LT groups was similar (31% and 36%, respectively; p = 0.82). Among index cases isolates associated with households demonstrating TST conversion, the frequency of unique pattern genotypes was higher for index cases of the LT compared to HT households (p = 0.03). We concluded that clusters and lineages associated with MTB infection in HT households had no proclivity for increased transmission of TB in the community.

Distance-based mapping of disease risk.

In this article, we consider the problem of comparing the distribution of observations in a planar region to a pre-specified null distribution. Our motivation is a surveillance setting where we map locations of incident disease, aiming to monitor these data over time, to locate potential areas of high/low incidence so as to direct public health actions. We propose a non-parametric approach to distance-based disease risk mapping inspired by tomographic imaging. We consider several one-dimensional projections via the observed distribution of distances to a chosen fixed point; we then compare this distribution to that expected under the null and average these comparisons across projections to compute a relative-risk-like score at each point in the region. The null distribution can be established from historical data. Scores are displayed on the map using a color scale. In addition, we give a detailed description of the method along with some desirable theoretical properties. To further assess the performance of this method, we compare it to the widely used log ratio of kernel density estimates. As a performance metric, we evaluate the accuracy to locate simulated spatial clusters superimposed on a uniform distribution in the unit disk. Results suggest that both methods can adequately locate this increased risk but each relies on an appropriate choice of parameters. Our proposed method, distance-based mapping (DBM), can also generalize to arbitrary metric spaces and/or high-dimensional data.

Estimation of the reproductive number and the serial interval in early phase of the 2009 influenza A/H1N1 pandemic in the USA.

BACKGROUND: The United States was the second country to have a major outbreak of novel influenza A/H1N1 in what has become a new pandemic. Appropriate public health responses to this pandemic depend in part on early estimates of key epidemiological parameters of the virus in defined populations. METHODS: We use a likelihood-based method to estimate the basic reproductive number (R(0)) and serial interval using individual level U.S. data from the Centers for Disease Control and Prevention (CDC). We adjust for missing dates of illness and changes in case ascertainment. Using prior estimates for the serial interval we also estimate the reproductive number only. RESULTS: Using the raw CDC data, we estimate the reproductive number to be between 2.2 and 2.3 and the mean of the serial interval (mu) between 2.5 and 2.6 days. After adjustment for increased case ascertainment our estimates change to 1.7 to 1.8 for R(0) and 2.2 to 2.3 days for mu. In a sensitivity analysis making use of previous estimates of the mean of the serial interval, both for this epidemic (mu = 1.91 days) and for seasonal influenza (mu = 3.6 days), we estimate the reproductive number at 1.5 to 3.1. CONCLUSIONS: With adjustments for data imperfections we obtain useful estimates of key epidemiological parameters for the current influenza H1N1 outbreak in the United States. Estimates that adjust for suspected increases in reporting suggest that substantial reductions in the spread of this epidemic may be achievable with aggressive control measures, while sensitivity analyses suggest the possibility that even such measures would have limited effect in reducing total attack rates.

Risk factors and viruses associated with hospitalization due to lower respiratory tract infections in Canadian Inuit children : a case-control study.

OBJECTIVES: To examine risk factors for lower respiratory tract infections (LRTI) hospital admission in the Canadian Arctic. METHODS: This was a case-control study during a 14-month period among children less than 2 years of age. Cases were admitted to the Baffin Regional Hospital in Iqaluit, Nunavut with LRTI. Controls were age matched and came from Iqaluit and 2 communities. Odds ratios (ORs) of hospital admission for LRTI were estimated through multivariate conditional logistic regression modeling for following risk factors: smoking in pregnancy, Inuit race, prematurity, adoption status, breast-feeding, overcrowding, and residing outside of Iqaluit. Viruses in nasophayngeal aspirates were sought at the time of each hospital admission. RESULTS: There were 101 age-matched cases and controls. The following risk factors were significantly associated with an increased risk of admission for LRTI (adjusted OR): smoking in pregnancy (OR = 4.0; 95% CI: 1.1-14.6), residence outside of Iqaluit (OR = 2.7; 95% CI: 1.0 -7.2), full Inuit race (OR = 3.8; 95% CI: 1.1-12.8), and overcrowding (OR = 2.5, 95% CI: 1.1- 6.1). Non-breast-fed children had a 3.6-fold risk of being admitted for LRTI (95% CI: 1.2-11.5) and non-breast-fed adopted children had a 4.4-fold increased risk (95% CI: 1.1-17.6) when compared with breast-fed, nonadopted children. Prematurity was not associated with an increased risk of admission. Viruses were identified in 88 (72.7%) of admissions, with respiratory syncytial virus being identified in the majority of admissions, 62 (51.2%). Multiple viruses were isolated in 19 (15.7%) admissions. CONCLUSIONS: Smoking during pregnancy, place of residence, Inuit race, lack of breast-feeding, and overcrowding were all independently associated with increased risk of hospital admission for LRTI among Inuit children less than 2 years of age. Future research on the role of adoption and genetics on the health of Inuit children are required.

The Choice of the Number of Bins for the M Statistic.

Methods to monitor spatial patterns of disease in populations are of interest in public health practice. The M statistic uses interpoint distances between cases to detect abnormalities in the spatial patterns of diseases. This statistic compares the observed distribution of interpoint distances with that which is expected when no unusual spatial patterns exist. We show the relationship of M to Pearson's Chi Square statistic, xn2. Both statistics require the discretization of continuous data into bins and then are formed by creating a quadratic form, scaled by an appropriate variance covariance matrix. We seek to choose the number and type of these bins for the M statistic so as to maximize the power to detect spatial anomalies. By showing the relationship between M to xn2, we argue for the extension of the theory that has been developed for the selection of the number and type of bins for xn2 to M. We further show that spatial data provides a unique insight into the problem through examples with simulated data and spatial data from a health care provider. In the spatial setting, these indicate that the optimal number of bins depends on the size of the cluster. For large clusters, a smaller number of bins appears to be preferrable, however for small clusters having many bins increases the power. Further, results indicate that the number of bins does not appear to vary with m, the number of spatial locations. We discuss the implications of this result for further work.

Effects of presentation and electrocardiogram on time to treatment of hyperkalemia.

OBJECTIVES: To assess the time to treatment for emergency department (ED) patients with critical hyperkalemia and to determine whether the timing of treatment was associated with clinical characteristics or electrocardiographic abnormalities. METHODS: The authors performed a retrospective chart review of ED patients with the laboratory diagnosis of hyperkalemia (potassium level > 6.0 mmol/L). Patients presenting in cardiac arrest or who were referred for hyperkalemia or dialysis were excluded. Patient charts were reviewed to find whether patients received specific treatment for hyperkalemia and, if so, what clinical attributes were associated with the time to initiation of treatment. RESULTS: Of 175 ED visits that occurred over a 1-year time period, 168 (96%) received specific treatment for hyperkalemia. The median time from triage to initiation of treatment was 117 minutes (interquartile range [IQR] = 59 to 196 minutes). The 7 cases in which hyperkalemia was not treated include 4 cases in which the patient was discharged home, with a missed diagnosis of hyperkalemia. Despite initiation of specific therapy for hyperkalemia in 168 cases, 2 patients died of cardiac arrhythmias. Among the patients who received treatment, 15% had a documented systolic blood pressure (sBP) < 90 mmHg, and 30% of treated patients were admitted to intensive care units. The median potassium value was 6.5 mmol/L (IQR = 6.3 to 7.1 mmol/L). The predominant complaints were dyspnea (20%) and weakness (19%). Thirty-six percent of patients were taking angiotensin-converting enzyme (ACE) inhibitors. Initial electrocardiograms (ECGs) were abnormal in 83% of patient visits, including 24% of ECGs with nonspecific ST abnormalities. Findings of peaked T-wave morphology (34%), first-degree atrioventricular block (17%), and interventricular conduction delay (12%) did not lead to early treatment. Vital sign abnormalities, including hypotension (sBP < 90 mmHg), were not associated with early treatment. The chief complaint of "unresponsive" was most likely to lead to early treatment; treatment delays occurred in patients not transported by ambulance, those with a chief complaint of syncope and those with a history of hypertension. CONCLUSIONS: Recognition of patients with severe hyperkalemia is challenging, and the initiation of appropriate therapy for this disorder is frequently delayed.

Transmissibility of the influenza virus in the 1918 pandemic.

BACKGROUND: With a heightened increase in concern for an influenza pandemic we sought to better understand the 1918 Influenza pandemic, the most devastating epidemic of the previous century. METHODOLOGY/PRINCIPAL FINDINGS: We use data from several communities in Maryland, USA as well as two ships that experienced well-documented outbreaks of influenza in 1918. Using a likelihood-based method and a nonparametric method, we estimate the serial interval and reproductive number throughout the course of each outbreak. This analysis shows the basic reproductive number to be slightly lower in the Maryland communities (between 1.34 and 3.21) than for the enclosed populations on the ships (R(0) = 4.97, SE = 3.31). Additionally the effective reproductive number declined to sub epidemic levels more quickly on the ships (within around 10 days) than in the communities (within 30-40 days). The mean serial interval for the ships was consistent (3.33, SE = 5.96 and 3.81, SE = 3.69), while the serial intervals in the communities varied substantially (between 2.83, SE = 0.53 and 8.28, SE = 951.95). CONCLUSIONS/SIGNIFICANCE: These results illustrate the importance of considering the population dynamics when making statements about the epidemiological parameters of Influenza. The methods that we employ for estimation of the reproductive numbers and the serial interval can be easily replicated in other populations and with other diseases.

Effect of spatial resolution on cluster detection: a simulation study.

BACKGROUND: Aggregation of spatial data is intended to protect privacy, but some effects of aggregation on spatial methods have not yet been quantified. METHODS: We generated 3,000 spatial data sets and evaluated power of detection at 12 different levels of aggregation using the spatial scan statistic implemented in SaTScan v6.0. RESULTS: Power to detect clusters decreased from nearly 100% when using exact locations to roughly 40% at the coarsest level of spatial resolution. CONCLUSION: Aggregation has the potential for obfuscation.