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John S Brownstein

Publications and source records attributed to John S Brownstein.

14 recordsLinked to original sources
PubMed2006

An unsupervised classification method for inferring original case locations from low-resolution disease maps.

BACKGROUND: Widespread availability of geographic information systems software has facilitated the use of disease mapping in academia, government and private sector. Maps that display the address of affected patients are often exchanged in public forums, and published in peer-reviewed journal articles. As previously reported, a search of figure legends in five major medical journals found 19 articles from 1994-2004 that identify over 19,000 patient addresses. In this report, a method is presented to evaluate whether patient privacy is being breached in the publication of low-resolution disease maps. RESULTS: To demonstrate the effect, a hypothetical low-resolution map of geocoded patient addresses was created and the accuracy with which patient addresses can be resolved is described. Through georeferencing and unsupervised classification of the original image, the method precisely re-identified 26% (144/550) of the patient addresses from a presentation quality map and 79% (432/550) from a publication quality map. For the presentation quality map, 99.8% of the addresses were within 70 meters (approximately one city block length) of the predicted patient location, 51.6% of addresses were identified within five buildings, 70.7% within ten buildings and 93% within twenty buildings. For the publication quality map, all addresses were within 14 meters and 11 buildings of the predicted patient location. CONCLUSION: This study demonstrates that lowering the resolution of a map displaying geocoded patient addresses does not sufficiently protect patient addresses from re-identification. Guidelines to protect patient privacy, including those of medical journals, should reflect policies that ensure privacy protection when spatial data are displayed or published.

Boston↗
PubMed2006

Lumbar puncture ordering and results in the pediatric population: a promising data source for surveillance systems.

BACKGROUND: The Centers for Disease Control and Prevention is incorporating laboratory data into real-time surveillance systems. When normal patterns of laboratory test orders and results are modeled, aberrations can be detected. Because many test orders are available electronically well before results, atypical patterns of test ordering may signal outbreaks. OBJECTIVES: The authors sought to characterize baseline patterns in the ordering and early results of lumbar punctures, motivated by the possibility of using these data for real-time surveillance for early detection of meningitis or encephalitis outbreaks. METHODS: Retrospective cohorts of pediatric emergency department patients at a single hospital (1993-2003) and from the National Hospital and Ambulatory Medical Care Survey (1992-2000) were used for analysis. RESULTS: Test ordering exhibits seasonal patterns, with monthly peaks in January and August (p < 0.0001). For the hospital cohort, the rate of cerebrospinal fluid pleocytosis exhibits seasonal patterns (p < 0.0001), with a peak from August to October. This is strongly associated with the rate and pattern of clinical neurologic disease (p < 0.0001). A long-term secular decline in daily test ordering is evident, dropping from 5.3 to 2.9 in the hospital sample, and from 371.8 to 185.3 in the national sample (p < 0.001). The long-term rate of pleocytosis has declined (p < 0.0001), though the yield of testing for pleocytosis has improved (p = 0.0104). CONCLUSIONS: Laboratory test patterns correspond with those of clinical disease and are a promising source of surveillance data. Using such data for real-time monitoring requires specific adjustments for patient age, periodicities, and secular trends.

Adolescent↗
PubMed2006

Validation of syndromic surveillance for respiratory infections.

STUDY OBJECTIVE: A key public health question is whether syndromic surveillance data provide early warning of infectious outbreaks. One cause for skepticism is that biological correlates of the administrative and clinical data used in these systems have not been rigorously assessed. This study measures the value of respiratory data currently used in syndromic surveillance systems to detect respiratory infections by comparing it against criterion standard viral testing within a pediatric population. METHODS: We conducted a longitudinal study with prospective validation in the emergency department (ED) of a tertiary care children's hospital. Children aged 7 years or younger who presented with a respiratory syndrome or who were tested for respiratory syncytial virus (RSV), influenza virus, parainfluenza virus, adenovirus, or enterovirus between January 1993 and June 2004 were included. We assessed the predictive ability of the viral tests by fitting generalized linear models to respiratory syndrome counts. RESULTS: Of 582,635 patient visits, 89,432 (15.4%) were for respiratory syndromes, and of these, 7,206 (8.1%) patients were tested for the viruses of interest. RSV was significantly related to respiratory syndrome counts (adjusted rate ratio [RR] 1.33; 95% confidence interval [CI] 1.04 to 1.71). In multivariate models including all viruses tested, influenza virus was also a significant predictor of respiratory syndrome counts (RR 1.47; 95% CI 1.03 to 2.10). This model accounted for 81.6% of the observed variability in respiratory syndrome counts. CONCLUSION: Respiratory syndromic surveillance data strongly correlate with virologic test results in a pediatric population, providing evidence of the biologic validity of such surveillance systems. Real-time outbreak detection systems relying on syndromic data may be an important adjunct to the current set of public health systems for the detection and surveillance of respiratory infections.

Boston↗
PubMed2006

Empirical evidence for the effect of airline travel on inter-regional influenza spread in the United States.

BACKGROUND: The influence of air travel on influenza spread has been the subject of numerous investigations using simulation, but very little empirical evidence has been provided. Understanding the role of airline travel in large-scale influenza spread is especially important given the mounting threat of an influenza pandemic. Several recent simulation studies have concluded that air travel restrictions may not have a significant impact on the course of a pandemic. Here, we assess, with empirical data, the role of airline volume on the yearly inter-regional spread of influenza in the United States. METHODS AND FINDINGS: We measured rate of inter-regional spread and timing of influenza in the United States for nine seasons, from 1996 to 2005 using weekly influenza and pneumonia mortality from the Centers for Disease Control and Prevention. Seasonality was characterized by band-pass filtering. We found that domestic airline travel volume in November (mostly surrounding the Thanksgiving holiday) predicts the rate of influenza spread (r(2) = 0.60; p = 0.014). We also found that international airline travel influences the timing of influenza mortality (r(2) = 0.59; p = 0.016). The flight ban in the US after the terrorist attack on September 11, 2001, and the subsequent depression of the air travel market, provided a natural experiment for the evaluation of flight restrictions; the decrease in air travel was associated with a delayed and prolonged influenza season. CONCLUSIONS: We provide the first empirical evidence for the role of airline travel in long-range dissemination of influenza. Our results suggest an important influence of international air travel on the timing of influenza introduction, as well as an influence of domestic air travel on the rate of inter-regional influenza spread in the US. Pandemic preparedness strategies should account for a possible benefit of airline travel restrictions on influenza spread.

Aircraft↗
PubMed2005

Forest fragmentation predicts local scale heterogeneity of Lyme disease risk.

Fragmentation of the landscape has been proposed to play an important role in defining local scale heterogeneity in Lyme disease risk through influence on mammalian host density and species composition. We tested this observed relationship in a suburban region around Lyme, Connecticut, where we collected data on the density of the tick vector, Ixodes scapularis and prevalence of the Lyme bacterium, Borrelia burgdorferi at 30 sites. Analysis of the landscape pattern of forest patches was performed using satellite imagery. The calculated landscape indices, which included patch size and isolation, revealed a positive link between fragmentation and both tick density and infection prevalence in ticks. In spite of higher entomologic risk, human incidence of Lyme disease is lower in fragmented contexts suggesting that entomologic risk is not the critical driver of human infections. These results represent a departure from the prior claims that fragmentation and human Lyme disease risk are positively linked. A complete understanding of the influence of landscape fragmentation will allow for improved risk mapping and potential environmental management of Lyme disease.

Animals↗
PubMed2005

Identifying pediatric age groups for influenza vaccination using a real-time regional surveillance system.

Evidence is accumulating that universal vaccination of schoolchildren would reduce the transmission of influenza. The authors sought to identify target age groups within the pediatric population that develop influenza the earliest and are most strongly linked with mortality in the population. Patient visits for respiratory illness were monitored, using real-time syndromic surveillance systems, in six Massachusetts health-care settings, including ambulatory care sites and emergency departments at tertiary-care and community hospitals. Visits from January 1, 2000, to September 30, 2004, were segmented into age group subpopulations. Timeliness and prediction of each subpopulation were measured against pneumonia and influenza mortality in New England with time-series analyses and regression models. Study results show that patient age significantly influences timeliness (p = 0.026), with pediatric age groups arriving first (p < 0.001); children aged 3-4 years are consistently the earliest (p = 0.0058). Age also influences the degree of prediction of mortality (p = 0.036), with illness among children under age 5 years, compared with all other patients, most strongly associated with mortality (p < 0.001). Study findings add to a growing body of support for a strategy to vaccinate children older than the currently targeted age of 6-23 months and specifically suggest that there may be value in vaccinating preschool-age children.

Adolescent↗
PubMed2005

Reverse geocoding: concerns about patient confidentiality in the display of geospatial health data.

Widespread availability geographic information systems (GIS) software has facilitated the use health mapping in both academia and government. Maps that display patients as points are often exchanged in public forums (journals, meetings, web). However,even these low resolution maps may reveal confidential patient location information. In this report, we describe a method to test whether privacy is being breached. We reverse geocode from maps with cases and describe the accuracy with which patient addresses can be extracted.

Confidentiality↗
PubMed2004

Interaction and transmission of two Borrelia burgdorferi sensu stricto strains in a tick-rodent maintenance system.

In the northeastern United States, the Lyme disease agent, Borrelia burgdorferi sensu stricto, is maintained by enzoonotic transmission, cycling between white-footed mice (Peromyscus leucopus) and black-legged ticks (Ixodes scapularis). B. burgdorferi sensu stricto is genetically variable and has been divided into three major genotypes based on 16S-23S ribosomal DNA spacer (RST) analysis. To better understand how genetic differences in B. burgdorferi sensu stricto may influence transmission dynamics in nature, we investigated the interaction between an RST1 and an RST3 strain in a laboratory system with P. leucopus mice and I. scapularis ticks. Two groups of mice were infected with either BL206 (RST1) or B348 (RST3). Two weeks later, experimental mice were challenged with the opposite strain, while control mice were challenged with the same strain as that used for the primary infection. The transmission of BL206 and B348 from infected mice was then determined by xenodiagnosis with uninfected larval ticks at weekly intervals for 42 days. Mice in both experimental groups were permissive for infection with the second strain and were able to transmit both strains to the xenodiagnostic ticks. However, the overall transmission efficiencies of BL206 and B348 were significantly different. BL206 was more efficiently transmitted than B348 to xenodiagnostic ticks. Significantly fewer double infections than expected were detected in xenodiagnostic ticks. The results suggest that some B. burgdorferi sensu stricto strains, such as BL206, may be preferentially maintained in transmission cycles between ticks and white-footed mice. Other strains, such as B348, may be more effectively maintained in different tick-vertebrate transmission cycles.

Animals↗
PubMed2004

A dispersal model for the range expansion of blacklegged tick (Acari: Ixodidae).

The blacklegged tick, Ixodes scapularis Say, a vector for the agents of Lyme borreliosis and other diseases, has expanded its range dramatically over the past 20 yr. However, the relative contributions of different vertebrate host species to this expansion have remained largely unexplored. To address this issue, we simulated the expansion of a theoretical tick population across a simple landscape by using a deterministic, spatially explicit, cellular automata model. The model incorporates the ecology of ticks and three vertebrate hosts: white-tailed deer, Odocoileus virginianus Zimmermann; white-footed mouse, Peromyscus leucopus Rafinesque; and American robin, Turdus migratorius L. Host contribution to tick dispersal is modeled as a function of tick burden, home range size, and population density. These parameters were determined using published and unpublished data. Our results suggest that 1) hosts with high tick burdens and large home ranges (e.g., deer) play a critical role in I. scapularis range expansion; 2) hosts with small home ranges (e.g., mice) can limit range expansion if they divert a sufficient number of ticks from feeding on more mobile hosts; and (3) birds that migrate annually (e.g., robins) can play a crucial role in tick range expansion.

Animals↗
PubMed2004

Enhancing West Nile virus surveillance, United States.

We provide a method for constructing a county-level West Nile virus risk map to serve as an early warning system for human cases. We also demonstrate that mosquito surveillance is a more accurate predictor of human risk than monitoring dead and infected wild birds.

Animals↗
PubMed2003

A climate-based model predicts the spatial distribution of the Lyme disease vector Ixodes scapularis in the United States.

An understanding of the spatial distribution of the black-legged tick, Ixodes scapularis, is a fundamental component in assessing human risk for Lyme disease in much of the United States. Although a county-level vector distribution map exists for the United States, its accuracy is limited by arbitrary categories of its reported presence. It is unknown whether reported positive areas can support established populations and whether negative areas are suitable for established populations. The steadily increasing range of I. scapularis in the United States suggests that all suitable habitats are not currently occupied. Therefore, we developed a spatially predictive logistic model for I. scapularis in the 48 conterminous states to improve the previous vector distribution map. We used ground-observed environmental data to predict the probability of established I. scapularis populations. The autologistic analysis showed that maximum, minimum, and mean temperatures as well as vapor pressure significantly contribute to population maintenance with an accuracy of 95% (p < 0.0001). A cutoff probability for habitat suitability was assessed by sensitivity analysis and was used to reclassify the previous distribution map. The spatially modeled relationship between I. scapularis presence and large-scale environmental data provides a robust suitability model that reveals essential environmental determinants of habitat suitability, predicts emerging areas of Lyme disease risk, and generates the future pattern of I. scapularis across the United States.

Animals↗
PubMed2002

Spatial analysis of West Nile virus: rapid risk assessment of an introduced vector-borne zoonosis.

The distribution of human risk for West Nile virus was determined by spatial analysis of the initial case distribution for the New York City area in 1999 using remote sensing and geographic information system technologies. Cluster analysis revealed the presence of a statistically significant grouping of cases, which also indicates the area of probable virus introduction. Within the cluster, habitat suitability for potentially infective adult mosquitoes was measured by the amount of vegetation cover using satellite imagery. Logistic regression analysis revealed satellite-derived vegetation abundance to be significantly and positively associated with the presence of human cases. The logistic model was used to estimate the spatial distribution of human risk for West Nile virus throughout New York City. Accuracy of the resulting risk map was cross-validated using virus-positive mosquito sample sites. These new epidemiological methods aid in rapid entry point identification and spatial prediction of human risk of infection for introduced vector-borne pathogens.

Animals↗