Molecular epidemiology of tuberculosis transmission: Contextualizing the evidence through social network theory

Exploring News Media Epidemiology of "Embitterment": A Content Analysis of Korean News Coverage between 1990 and 2018

Embitterment is a newly emerging mental problem that requires a social epidemiological approach. As this emotional state is varied in its manifestation and is pervasive in South Korea, we examined the embittered, those embittering, and causes of embitterment covered in news media in the nation. All news stories appearing between January 1, 1990 and August 31, 2018 in seven major daily newspapers in South Korea were searched for headlines containing "embitterment". A total of 321 news stories were identified for content analysis, which was conducted by two trained coders who examined each article to determine the identity of the embittered and embitters and the causes of and reponses from the embitterment. An inductive method was used to establish major levels for each variable. As a result, victims of disaster and accidents (and their families) were the most frequently embittered group, followed by politicians, laborers, persons of interest and the general public without specification. The three major causes of embitterment were: deprivation of basic life needs and rights, defamation/insult and abuse of power. Liberal newspapers published more "embitterment" stories, especially during conservative regimes. Since the periods of conservative regimes were longer than liberal regimes during the time under investigation, liberal newspapers published more "embitterment" stories than conservative newspapers. The patterns of coverage for the embittered, those embittering, and causes of embitterment also differed according to the political orientation of the newspaper. The implications of the findings from a social epidemiological approach and points requiring further study are discussed.

Investigating extradomiciliary transmission of tuberculosis: An exploratory approach using social network patterns of TB cases and controls and the genotyping of Mycobacterium tuberculosis

Extradomiciliary contacts have been overlooked in the study of TB transmission due to difficulties in identifying actual contacts in large populations. Complex network analysis provides a framework to model the structure of contacts, specially extradomiciliary ones. We conducted a study of incident sputum-positive TB cases and healthy controls occurring in a moderate TB burden city. Cases and controls were interviewed to obtain data regarding the usual locations of residence, work, study, and leisure. Mycobacterium tuberculosis isolated from sputum was genotyped. The collected data were used to build networks based on a framework of putative social interactions indicating possible TB transmission. A user-friendly open source environment (GraphTube) was setup to extract information from the collected data. Networks based on the likelihood of patient-patient, patient-healthy, and healthy-healthy contacts were setup, depending on a constraint of geographical distance of places attended by the volunteers. Using a threshold for the geographical distance of 300 m, the differences between TB cases and controls are revealed. Several clusters formed by social network nodes with high genotypic similarity were characterized. The developed framework provided consistent results and can be used to support the targeted search of potentially infected individuals and to help to understand the TB transmission.

Tuberculosis Prevalence Among US Crop-Workers, 2000 to 2012: Trends and Contributing Factors

OBJECTIVE

We intend to study tuberculosis (TB) in one of the poorest communities in the US, hired agriculture workers, for most recent years (2000 to 2012) including the last recession period.

METHODS

Time-chart, simple mean differences, and logistic regressions were used to describe TB-prevalence and risk factors among US crop-workers. Data were drawn from the National Agricultural Workers Survey (NAWS).

RESULTS

A high TB-prevalence was found among crop-workers with a dramatically increasing trend in recent years. Hispanic ethnicity, having farmworker family members, the presence of health insurance, and good spoken English were associated with an increased TB-prevalence.

CONCLUSION

We found risk factors related to ethnicity and poor access to health care, a strong association between agriculture activity and TB, and an increase of TB-cases due to the 2008 downturn in this underserved population. We urge the health authorities to control this epidemic.

Slowdown in the Decline of Tuberculosis Rates in California, 2000-2016

OBJECTIVES

To determine the impact of the 2007-2009 economic crisis on tuberculosis (TB) trends among California residents.

METHODS

We analyzed available data from 4 different population-representative data sets. We used time charts, trend lines, and change-point detection tests during 2000 to 2016 to describe TB trends in California.

RESULTS

We found statistically significant changes in California TB trends with the time of the onset of the economic downturn based on age-adjusted TB case rates and TB mortality rates, crude rate of TB hospitalizations, and self-reported TB. Change on TB incidence was especially apparent among racial/ethnic minority groups.

CONCLUSIONS

To our knowledge, changes in TB trends in the United States matching in time with the 2007-2009 economic crisis have not been previously reported. This study identified a slowdown in the decline of TB rates by 2007 to 2009 and provides new knowledge on TB trends that can be used to achieve California's goal of eliminating TB by 2040 and in the prevention and control of TB in the United States.

A Novel Tool Improves Existing Estimates of Recent Tuberculosis Transmission in Settings of Sparse Data Collection

In any setting, a proportion of incident active tuberculosis (TB) reflects recent transmission (“recent transmission proportion”), whereas the remainder represents reactivation. Appropriately estimating the recent transmission proportion has important implications for local TB control, but existing approaches have known biases, especially where data are incomplete. We constructed a stochastic individual-based model of a TB epidemic and designed a set of simulations (derivation set) to develop two regression-based tools for estimating the recent transmission proportion from five inputs: underlying TB incidence, sampling coverage, study duration, clustered proportion of observed cases, and proportion of observed clusters in the sample. We tested these tools on a set of unrelated simulations (validation set), and compared their performance against that of the traditional ‘n-1’ approach. In the validation set, the regression tools reduced the absolute estimation bias (difference between estimated and true recent transmission proportion) in the ‘n-1’ technique by a median [interquartile range] of 60% [9%, 82%] and 69% [30%, 87%]. The bias in the ‘n-1’ model was highly sensitive to underlying levels of study coverage and duration, and substantially underestimated the recent transmission proportion in settings of incomplete data coverage. By contrast, the regression models’ performance was more consistent across different epidemiological settings and study characteristics. We provide one of these regression models as a user-friendly, web-based tool. Novel tools can improve our ability to estimate the recent TB transmission proportion from data that are observable (or estimable) by public health practitioners with limited available molecular data.

Visualization and analytics tools for infectious disease epidemiology: a systematic review

BACKGROUND

A myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) identify public health user needs and preferences for infectious disease information visualization tools; (2) identify existing infectious disease information visualization tools and characterize their architecture and features; (3) identify commonalities among approaches applied to different data types; and (4) describe tool usability evaluation efforts and barriers to the adoption of such tools.

METHODS

We identified articles published in English from January 1, 1980 to June 30, 2013 from five bibliographic databases. Articles with a primary focus on infectious disease visualization tools, needs of public health users, or usability of information visualizations were included in the review.

RESULTS

A total of 88 articles met our inclusion criteria. Users were found to have diverse needs, preferences and uses for infectious disease visualization tools, and the existing tools are correspondingly diverse. The architecture of the tools was inconsistently described, and few tools in the review discussed the incorporation of usability studies or plans for dissemination. Many studies identified concerns regarding data sharing, confidentiality and quality. Existing tools offer a range of features and functions that allow users to explore, analyze, and visualize their data, but the tools are often for siloed applications. Commonly cited barriers to widespread adoption included lack of organizational support, access issues, and misconceptions about tool use.

DISCUSSION AND CONCLUSION

As the volume and complexity of infectious disease data increases, public health professionals must synthesize highly disparate data to facilitate communication with the public and inform decisions regarding measures to protect the public's health. Our review identified several themes: consideration of users' needs, preferences, and computer literacy; integration of tools into routine workflow; complications associated with understanding and use of visualizations; and the role of user trust and organizational support in the adoption of these tools. Interoperability also emerged as a prominent theme, highlighting challenges associated with the increasingly collaborative and interdisciplinary nature of infectious disease control and prevention. Future work should address methods for representing uncertainty and missing data to avoid misleading users as well as strategies to minimize cognitive overload.

Multidrug-resistant tuberculosis among patients in Baja California, Mexico, and Hispanic patients in California

OBJECTIVES

We sought to compare prevalence and determinants of multidrug-resistant tuberculosis (MDR-TB) between tuberculosis patients in Baja California, Mexico, and Hispanic patients in California.

METHODS

Using data from Mexico's National TB Drug Resistance Survey (2008-2009) and California Department of Public Health TB case registry (2004-2009), we assessed differences in MDR-TB prevalence comparing (1) Mexicans in Baja California, (2) Mexico-born Hispanics in California, (3) US-born Hispanics in California, and (4) California Hispanics born elsewhere.

RESULTS

MDR-TB prevalence was 2.1% in Baja California patients, 1.6% in Mexico-born California patients, 0.4% in US-born California patients, and 2.7% in Hispanic California patients born elsewhere. In multivariate analysis, previous antituberculosis treatment was associated with MDR-TB (odds ratio [OR] = 6.57; 95% confidence interval [CI] = 3.34, 12.96); Mexico-born TB patients in California (OR = 5.08; 95% CI = 1.19, 21.75) and those born elsewhere (OR = 7.69; 95% CI = 1.71, 34.67) had greater odds of MDR-TB compared with US-born patients (reference category).

CONCLUSIONS

Hispanic patients born outside the US or Mexico were more likely to have MDR-TB than were those born within these countries. Possible explanations include different levels of exposure to resistant strains and inadequate treatment.