Using GIS technology to identify areas of tuberculosis transmission and incidence

Assessment of tuberculosis case notification rate: spatial mapping of hotspot, coverage and diagnostics in Katsina State, north-western Nigeria

Tuberculosis (TB) is prevalent in Nigeria, and Katsina, along with other 12 states in the country, accounts for a high proportion of unnotified TB cases: constituting the high priority-intervention States in the country. Interventions focused on TB detection and coverage in the state could benefit from a better understanding of hotspot Local Government Areas (LGAs) that trigger and sustain the disease. Therefore, this study investigated the spatial distribution of TB Case Notification Rates (CNRs), diagnostics and coverage across the LGAs. Using 2017 to 2019 TB case finding data, the geocoordinates of diagnostic facilities and shapefiles, a retrospective ecological study was conducted. The data were analysed with QGIS and GeoDa. Moran's I and LISA were used to locate and quantify hotspots. The coverage of microscopy and GeneXpert facilities was assessed on QGIS using a 5 km and 20 km radius, respectively. The CNR in the state, and 29 of the 34 LGAs, increased steadily from 2017 to 2019. Hotspots of high CNRs were also identified in 2017 (Moran's I=0.106, p-value=0.090) and 2018 (Moran's I=-0.020, p-value=0.370). While CNRs increased along with presumptive TB rates across most LGAs over the years, the positivity yield and bacteriological and Xpert diagnostic rates decreased. Bacteriological and GeneXpert coverage were 78% and 49% respectively. Additionally, only 51% of the state's population lived within 20km of a GeneXpert facility. These results suggest that TB program interventions had some positive impact on the CNR, however, diagnostic facilities need to be equitably distributed and more innovative approaches need to be explored to find the missing cases.

Incidence and geographical distribution of tuberculosis disease in Erbil city, Iraq

OBJECTIVES

This study aimed to identify the geographical distribution of TB in Erbil city, Kurdistan Region, Iraq, determine potential risk factors associated with TB distribution, and provide recommendations to improve TB control programs in the region.

METHODS

The records of TB patients registered at the Chest and Respiratory Disease Center in Erbil, Iraqi Kurdistan Region, from January 2012 to December 2016 were reviewed and analyzed. The number of cases by the quarter of residence within Erbil city were analyzed spatially and presented in an appropriate map.

RESULTS

The estimated annual incidence of TB in Erbil city constantly increased from 16 per 100,000 inhabitants in the year 2012 to 21.7 per 100,000 inhabitants in the year 2016. Most of the TB cases were from the middle zone of Erbil city (44%), followed by the outer zone (43.8%) and the central zone (12.2%). The largest number of the cases were from Brayaty quarter (40), followed by Badawa (35) Nawroz (35) and Kurdistan (31) quarters. Clusters with a large number of cases were mainly located in the southern part of the city.

CONCLUSION

The estimated TB incidence constantly increased in Erbil city from 2012 to 2016. Mapping the distribution of TB cases in Erbil city provided useful information about the epidemiological situation of TB that can be used to direct future TB control strategies.

Geospatial Clustering of Mobile Phone Use and Tuberculosis Health Outcomes Among African Health Systems

Background

While multiple studies have documented the impacts of mobile phone use on TB health outcomes for varied settings, it is not immediately clear what the spatial patterns of TB treatment completion rates among African countries are. This paper used Exploratory Spatial Data Analysis (ESDA) techniques to explore the clustering spatial patterns of TB treatment completion rates in 53 African countries and also their relationships with mobile phone use. Using an ESDA approach to identify countries with low TB treatment completion rates and reduced mobile phone use is the first step toward addressing issues related to poor TB outcomes.

Methods

TB notifications and treatment data from 2000 through 2015 that were obtained from the World Bank database were used to illustrate a descriptive epidemiology of TB treatment completion rates among African health systems. Spatial clustering patterns of TB treatment completion rates were assessed using differential local Moran's I techniques, and local spatial analytics was performed using local Moran's I tests. Relationships between TB treatment completion rates and mobile phone use were evaluated using ESDA approach.

Result

Spatial autocorrelation patterns generated were consistent with Low-Low and High-Low cluster patterns, and they were significant at different p-values. Algeria and Senegal had significant clusters across the study periods, while Democratic Republic of Congo, Niger, South Africa, and Cameroon had significant clusters in at least two time-periods. ESDA identified statistically significant associations between TB treatment completion rates and mobile phone use. Countries with higher rates of mobile phone use showed higher TB treatment completion rates overall, indicating enhanced program uptake (p < 0.05).

Conclusion

Study findings provide systematic evidence to inform policy regarding investments in the use of mHealth to optimize TB health outcomes. African governments should identify turnaround strategies to strengthen mHealth technologies and improve outcomes.

Effectiveness of spatially targeted interventions for control of HIV, tuberculosis, leprosy and malaria: a systematic review

BACKGROUND

As infectious diseases approach global elimination targets, spatial targeting is increasingly important to identify community hotspots of transmission and effectively target interventions. We aimed to synthesise relevant evidence to define best practice approaches and identify policy and research gaps.

OBJECTIVE

To systematically appraise evidence for the effectiveness of spatially targeted community public health interventions for HIV, tuberculosis (TB), leprosy and malaria.

DESIGN

Systematic review.

DATA SOURCES

We searched Medline, Embase, Global Health, Web of Science and Cochrane Database of Systematic Reviews between 1 January 1993 and 22 March 2021.

STUDY SELECTION

The studies had to include HIV or TB or leprosy or malaria and spatial hotspot definition, and community interventions.

DATA EXTRACTION AND SYNTHESIS

A data extraction tool was used. For each study, we summarised approaches to identifying hotpots, intervention design and effectiveness of the intervention.

RESULTS

Ten studies, including one cluster randomised trial and nine with alternative designs (before-after, comparator area), satisfied our inclusion criteria. Spatially targeted interventions for HIV (one USA study), TB (three USA) and leprosy (two Brazil, one Federated States of Micronesia) each used household location and disease density to define hotspots followed by community-based screening. Malaria studies (one each from India, Indonesia and Kenya) used household location and disease density for hotspot identification followed by complex interventions typically combining community screening, larviciding of stagnant water bodies, indoor residual spraying and mass drug administration. Evidence of effect was mixed.

CONCLUSIONS

Studies investigating spatially targeted interventions were few in number, and mostly underpowered or otherwise limited methodologically, affecting interpretation of intervention impact. Applying advanced epidemiological methodologies supporting more robust hotspot identification and larger or more intensive interventions would strengthen the evidence-base for this increasingly important approach.

PROSPERO REGISTRATION NUMBER

CRD42019130133.

Leveraging Polio GIS platforms in the African Region for mitigating Covid-19 contact tracing and Surveillance challenges

Background

The ongoing COVID-19 pandemic in Africa is an urgent public health crisis. Estimated models projected over 150,000 deaths and 4,600,000 hospitalizations in the first year of the disease in the absence of adequate interventions. Therefore, electronic contact tracing and surveillance have critical roles in decreasing COVID-19 transmission; yet, if not conducted properly, these methods can rapidly become a bottleneck for synchronized data collection, case detection, and case management. While the continent is currently reporting relatively low COVID-19 cases, digitized contact tracing mechanisms and surveillance reporting are necessary for standardizing real-time reporting of new chains of infection in order to quickly reverse growing trends and halt the pandemic.

Objective

This paper aims to describe a COVID-19 contact tracing smartphone app that includes health facility surveillance with a real-time visualization platform. The app was developed by the AFRO (African Regional Office) GIS (geographic information system) Center, in collaboration with the World Health Organization (WHO) emergency preparedness and response team. The app was developed through the expertise and experience gained from numerous digital apps that had been developed for polio surveillance and immunization via the WHO’s polio program in the African region.

Methods

We repurposed the GIS infrastructures of the polio program and the database structure that relies on mobile data collection that is built on the Open Data Kit. We harnessed the technology for visualization of real-time COVID-19 data using dynamic dashboards built on Power BI, ArcGIS Online, and Tableau. The contact tracing app was developed with the pragmatic considerations of COVID-19 peculiarities. The app underwent testing by field surveillance colleagues to meet the requirements of linking contacts to cases and monitoring chains of transmission. The health facility surveillance app was developed from the knowledge and assessment of models of surveillance at the health facility level for other diseases of public health importance. The Integrated Supportive Supervision app was added as an appendage to the pre-existing paper-based surveillance form. These two mobile apps collected information on cases and contact tracing, alongside alert information on COVID-19 reports at the health facility level; the information was linked to visualization platforms in order to enable actionable insights.

Results

The contact tracing app and platform were piloted between April and June 2020; they were then put to use in Zimbabwe, Benin, Cameroon, Uganda, Nigeria, and South Sudan, and their use has generated some palpable successes with respect to COVID-19 surveillance. However, the COVID-19 health facility–based surveillance app has been used more extensively, as it has been used in 27 countries in the region.

Conclusions

In light of the above information, this paper was written to give an overview of the app and visualization platform development, app and platform deployment, ease of replicability, and preliminary outcome evaluation of their use in the field. From a regional perspective, integration of contact tracing and surveillance data into one platform provides the AFRO with a more accurate method of monitoring countries’ efforts in their response to COVID-19, while guiding public health decisions and the assessment of risk of COVID-19.

Geographic analysis of latent tuberculosis screening: A health system approach

Background

Novel approaches are required to better focus latent tuberculosis infection (LTBI) efforts in low-prevalence regions. Geographic information systems, used within large health systems, may provide one such approach.

Methods

A retrospective, cross-sectional design was used to integrate US Census and Duke Health System data between January 1, 2010 and October 31, 2017 and examine the relationships between LTBI screening and population tuberculosis risk (assessed using the surrogate measure of proportion of persons born in tuberculosis-endemic regions) by census tract.

Results

The median proportion of Duke patients screened per census tract was 0.01 (range 0–0.1, interquartile range 0.01–0.03). The proportion of Duke patients screened within a census tract significantly but weakly correlated with the population risk. Furthermore, patients residing in census tracts with higher population tuberculosis risk were more likely to be screened with TST than with an IGRA (p<0.001).

Conclusion

The weak correlation between patient proportion screened for LTBI and our surrogate marker of population tuberculosis risk suggests that LTBI screening efforts should be better targeted. This type of geography-based analysis may serve as an easily obtainable benchmark for LTBI screening in health systems with low tuberculosis prevalence.

Spatial distribution of Mycobacterium Tuberculosis in metropolitan Harare, Zimbabwe

INTRODUCTION

The contribution of high tuberculosis (TB) transmission pockets in propagating area-wide transmission has not been adequately described in Zimbabwe. This study aimed to describe the presence of hotspot transmission of TB cases in Harare city from 2011 to 2012 using geospatial techniques.

METHODS

Anonymised TB patient data stored in an electronic database at Harare City Health department was analysed using geospatial methods. Confirmed TB cases were mapped using geographic information system (GIS). Global Moran's I and Anselin Local Moran's I (LISA) were used to assess clustering and the local Getis-Ord Gi* was used to estimate hotspot phenomenon of TB cases in Harare City for the period between 2011 and 2012.

RESULTS

A total of 12,702 TB cases were accessed and mapped on the Harare City map. In both 2011 and 2012, ninety (90%) of cases were new and had a high human immunodeficiency virus (HIV)/TB co-infection rate of 72% across all suburbs. Tuberculosis prevalence was highest in the Southern district in both 2011 and 2012. There were pockets of spatial distribution of TB prevalence across West South West, Southern, Western, South Western and Eastern health districts. TB hot spot occurrence was restricted to the West South West, parts of South Western, Western health districts. West South West district had an increased peri-urban population with inadequate social services including health facilities. These conditions were conducive for increased intensity of TB occurrence, a probable indication of high transmission especially in the presence of high HIV co-infection.

CONCLUSIONS AND RECOMMENDATIONS

Increased TB transmission was limited to a health district with high informal internal migrants with limited health services in Harare City. To minimise spread of TB into greater Harare, there is need to improve access to TB services in the peri-urban areas.

Contextualizing tuberculosis risk in time and space: comparing time-restricted genotypic case clusters and geospatial clusters to evaluate the relative contribution of recent transmission to incidence of TB using nine years of case data from Michigan, USA

PURPOSE

Novel approaches must address the underlying factors sustaining the tuberculosis (TB) epidemic in the United States, specifically what maintains new Mycobacterium tuberculosis (Mtb) transmission.

METHODS

Culture-confirmed TB cases reported to the Michigan Department of Health and Human Services (2004-2012) were analyzed for time-restricted genotypic and/or geospatial clustering. Cases with both types of clustering were used as a proxy for recent, local transmission. Modified, multivariate Poisson regression models were fit to estimate this prevalence in relation to various individual- and neighborhood-level demographic and socio-economic variables.

RESULTS

Those individuals that were spatially clustered were 1.7 times as likely to also be time-restricted genotypically clustered. The prevalence of recent, local transmission was higher among U.S.-born cases, males, and non-Hispanic blacks. Moreover, people living in neighborhoods in the highest poverty quartile had 13.8 times the prevalence of recent, local transmission compared with those in the lowest poverty neighborhoods.

CONCLUSIONS

Our results suggest geographic areas with high concentration of TB cases are likely driven by ongoing transmission, rather than enclaves of individuals who have reactivated a case of latent TB. Furthermore, efforts to continue reducing Mtb transmission in the United States, and other low-incidence settings, must better identify community-level sources of risk, manifested through the complex social interactions among people and their environments.

Spatial and temporal analysis of tuberculosis in an area of social inequality in Northeast Brazil

BACKGROUND

Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis. It is a disease known worldwide for its vulnerability factors, magnitude and mortality. The objective of the study was to analyze the spatial and temporal dynamics of TB in the area of social inequality in northeast Brazil between the years 2001 and 2016.

METHODS

An ecological time series study with the use of spatial analysis techniques was carried out from 2001 to 2016. The units of analysis were the 75 municipalities in the state of Sergipe. Data from the Notification of Injury Information System were used. For the construction of the maps, the cartographic base of the state of Sergipe, obtained at the Instituto Brasileiro de Geografia e Estatística, was used. Georeferenced data were analysed using TerraView 4.2.2 software (Instituto Nacional de Pesquisas Espaciais) and QGis 2.18.2 (Open Source Geospatial Foundation). Spatial analyses included the empirical Bayesian model and the global and local Moran indices. The time trend analyses were performed by the software Joinpoint Regression, Version 4.5.0.1, with the variables of sex, age, cure and abandonment.

RESULTS

There was an increasing trend of tuberculosis cases in patients under 20 years old and 20-39 years old, especially in males. Cured cases showed a decreasing trend, and cases of treatment withdrawal were stationary. A spatial dependence was observed in almost all analysed territories but with different concentrations. Significant spatial correlations with the formation of clusters in the southeast and northeast of the state were observed. The probability of illness among municipalities was determined not to occur in a random way.

CONCLUSION

The identification of risk areas and priority groups can help health planning by refining the focus of attention to tuberculosis control. Understanding the epidemiological, spatial and temporal dynamics of tuberculosis can allow for improved targeting of strategies for disease prevention and control.

Identifying and mapping TB hot spots in an urban slum by integratingGeographic positioning system and the local postman - A pilot study

SETTING

Mahavir DOT Centre, Hyderabad, Telangana, India INTRODUCTION: Urban slums are characterized by crowding, poverty. In such setting due to lack of infection control the transmission of tuberculosis is known to rise, thereby creating a "Hot" spot. Distribution of residences in such areas does not necessarily follow postal codes, making it difficult for health workers to locate TB patients unless accompanied by the STLS.

OBJECTIVE

To investigate the utility of integrating the help of local postman and geographic positioning system (GPS) to identify and create map of hot spots in an area under a regional DOT centre.

MATERIALS & METHODS

Retrospective and prospective demographic data of TB patients enrolled during 12 years (1999-2011) was analysed from the TB register at a ward where number of cases continued to increase despite active implementation of DOTS strategy. Non-Spatial data was generated with the local postman identifying individual house addresses. The corresponding co-ordinates were recorded with GPS and uploaded in Google Earth to identify the locations. Area map was created by software (AutoCAD, Map R3, MapInfo Pro 7.5 Trial Version and MS office Tools). Residences of Index patients were marked in different colours year wise on the map.

RESULTS

Maps displayed in the DOT centre area helped in identifying HOT SPOT and visualization of the clustering of TB cases in the area. Time interval between subsequent infections (3 months-5 years) could be calculated in the locality, within household, neighbourhood and random contacts. Average distances (<1 m) between houses indicated the probable source of infection. Risk factors included crowding, poor ventilation and sanitation contributed to TB transmission in HOT spot area.

CONCLUSION

Integrating local postman and information technology to identify HOT SPOT in RNTCP, will help in early intervention by health personnel to arrest TB transmission.

The Evolution of Genotyping Strategies To Detect, Analyze, and Control Transmission of Tuberculosis

The introduction of genotypic tools to analyze Mycobacterium tuberculosis isolates has transformed our knowledge of the transmission dynamics of this pathogen. We discuss the development of the laboratory methods that have been applied in recent years to study the epidemiology of M. tuberculosis. This review integrates two approaches: on the one hand, it considers how genotyping techniques have evolved over the years; and on the other, it looks at how the way we think these techniques should be applied has changed. We begin by examining the application of fingerprinting tools to suspected outbreaks only, before moving on to universal genotyping schemes, and finally we describe the latest real-time strategies used in molecular epidemiology. We also analyze refined approaches to obtaining epidemiological data from patients and to increasing the discriminatory power of genotyping by techniques based on genomic characterization. Finally, we review the development of integrative solutions to reconcile the speed of PCR-based methods with the high discriminatory power of whole-genome sequencing in easily implemented formats adapted to low-resource settings. Our analysis of future considerations highlights the need to bring together the three key elements of high-quality surveillance of transmission in tuberculosis, namely, speed, precision, and ease of implementation.

Use of Geographically Weighted Poisson Regression to examine the effect of distance on Tuberculosis incidence: A case study in Nam Dinh, Vietnam

Objectives

This study aimed to examine the potential of combining routine tuberculosis (TB) surveillance and demographic and socioeconomic variables into the Geographic Information System (GIS) to describe the geographical distribution of TB notified incidence in relation to distances to health services as well as local demographic and socioeconomic factors, including population density, urban/rural status, and household poverty rates in Nam Dinh, Vietnam. It also aimed to compare the conventional Generalized Linear Models (GLM) Poisson regression model and Geographically Weighted Poisson Regression (GWPR) models in order to determine the best fitting model that can be used to investigate the relationship between TB notified incidence and distances and the social risk factors.

Methods

The data of new and relapse patients with all forms of TB aged ≥15 years residing in Nam Dinh (Vietnam) from 2012 to 2015 were collected from the Administration of Medical Services’ (Ministry of Health of Vietnam) TB surveillance database. Data on the population and household poverty rates from 2012 to 2015 were gathered from the Nam Dinh Statistical Office. Distances between communes and the nearest TB diagnostic facilities in districts were computed. The TB notified incidence per 100,000 population was denoted by indirect age and sex standardized incidence ratio. GLM Poisson regression and GWPR were performed to assess the relationship between distance and TB incidence.

Results

The average notified TB incidence level measured from 2012 to 2015 is 82 per 100,000 population (range: 79-84/100,000). The distance to the nearest TB diagnosis presents a negative effect on TB notified incidence. By capturing spatial heterogeneity, the GWPR may be better at fitting data (corrected Aikake information criterion [AICc] = 245.71, residual deviance = 221.12) than the traditional GLM (AICc = 251.53, residual deviance = 241.21)

Conclusions

GIS technologies benefit TB surveillance system. Distances should be considered when planning methods of improving access for those who live far from TB diagnostic services, thereby improving TB detection. Additional studies must confirm the association between geographic distance and TB case detection and must explore other factors that may affect TB notified incidence.

Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review

BACKGROUND

Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden.

METHODS

We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO ( CRD42016036655 ).

RESULTS

We identified 168 eligible studies with spatial methods used to describe the spatial distribution (n = 154), spatial clusters (n = 73), predictors of spatial patterns (n = 64), the role of congregate settings (n = 3) and the household (n = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff's spatial scan statistic followed by local Moran's I and Getis and Ord's local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined.

CONCLUSIONS

A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control.

Spatial clusters of latent tuberculous infection, Connecticut, 2010-2014

SETTING

In the United States, tuberculosis (TB) control is increasingly focusing on the identification of persons with latent tuberculous infection (LTBI).

OBJECTIVE

To characterize the local epidemiology of LTBI in Connecticut, USA.

METHODS

We used spatial analyses 1) to identify census tract-level clusters of reported LTBI and TB disease in Connecticut, 2) to compare persons and populations in clusters with those not in clusters, and 3) to compare persons with LTBI to those with TB disease.

RESULTS

Significant census tract-level spatial clusters of LTBI and TB disease were identified. Compared with persons with LTBI in non-clustered census tracts, those in clustered census tracts were more likely to be foreign-born and less likely to be of white non-Hispanic ethnicity. Populations in census tract clusters of high LTBI prevalence had greater crowding, persons living in poverty, and persons lacking health care insurance than populations not in clustered census tracts. Persons with LTBI were less likely than those with TB disease to be of Asian ethnicity, and persons with LTBI were more likely than those with TB disease to reside in a clustered census tract.

CONCLUSIONS

Characterizing fine-scale populations at risk for LTBI supports effective and culturally accessible screening and treatment programs.

Detecting Spatial Patterns of Disease in Large Collections of Electronic Medical Records Using Neighbor-Based Bootstrapping

We introduce a method called neighbor-based bootstrapping (NB2) that can be used to quantify the geospatial variation of a variable. We applied this method to an analysis of the incidence rates of disease from electronic medical record data (International Classification of Diseases, Ninth Revision codes) for ∼100 million individuals in the United States over a period of 8 years. We considered the incidence rate of disease in each county and its geospatially contiguous neighbors and rank ordered diseases in terms of their degree of geospatial variation as quantified by the NB2 method. We show that this method yields results in good agreement with established methods for detecting spatial autocorrelation (Moran's I method and kriging). Moreover, the NB2 method can be tuned to identify both large area and small area geospatial variations. This method also applies more generally in any parameter space that can be partitioned to consist of regions and their neighbors.

Identification of High and Low-Risk Areas of Tuberculosis in Lorestan Province, West of Iran

BACKGROUND

Nowadays, tuberculosis (TB)-an infectious disease caused by Mycobacterium tuberculosis-presents with different location patterns. Spatial analysis is one of the most important tools to detect and monitor public health disease patterns. This study aimed to identify the low and high-risk areas in Lorestan Province (west of Iran) to help the health programmer for the best intervention.

MATERIALS AND METHODS

Lorestan has 9 counties, 22 cities, 25 zones, 81 villages, and 2842 residential villages. Our study cases were 1481 patients registered in the TB center of Lorestan Province. We investigated the spatial distribution of TB in Lorestan between 2002 and 2008 using a multilevel model. STATA Ver. 10 software was used for the data analysis.

RESULTS

The multilevel model was a better fit to the data for the spatial correlation structure. It adjusted relative risks by borrowing information of the neighboring areas in each village. Maximum risk of disease was seen in the central zone of Koram-Abad, and all villages of Delphan were identified as low-risk areas.

CONCLUSION

Various factors such as improvement of socio-economic conditions, implementation of programs, culture, genetic background, health-related behavior, and lifestyle can influence TB control substantially. A deprived region located in the southern part of Khoram-Abad was identified as the highest risk area in our study. The poor socio-economic structure can be an important factor for the increased risk of TB in this region.

Use of Activity Space in a Tuberculosis Outbreak: Bringing Homeless Persons Into Spatial Analyses

BACKGROUND

Tuberculosis (TB) causes significant morbidity and mortality in US cities, particularly in poor, transient populations. During a TB outbreak in Fulton County, Atlanta, GA, we aimed to determine whether local maps created from multiple locations of personal activity per case would differ significantly from traditional maps created from single residential address.

METHODS

Data were abstracted for patients with TB disease diagnosed in 2008-2014 and receiving care at the Fulton County Health Department. Clinical and activity location data were abstracted from charts. Kernel density methods, activity space analysis, and overlay with homeless shelter locations were used to characterize case spatial distribution when using single versus multiple addresses.

RESULTS

Data were collected for 198 TB cases, with over 30% homeless US-born cases included. Greater spatial dispersion of cases was found when utilizing multiple versus single addresses per case. Activity spaces of homeless and isoniazid (INH)-resistant cases were more spatially congruent with one another than non-homeless and INH-susceptible cases (P < .0001 and P < .0001, respectively).

CONCLUSIONS

Innovative spatial methods allowed us to more comprehensively capture the geography of TB-infected homeless persons, who made up a large portion of the Fulton County outbreak. We demonstrate how activity space analysis, prominent in exposure science and chronic disease, supports that routine capture of multiple location TB data may facilitate spatially different public health interventions than traditional surveillance maps.

Clustering of Pulmonary Tuberculosis in Hamadan Province, western Iran: A Population Based Cross Sectional Study (2005-2013)

BACKGROUND

This study was conducted to detect clusters of pulmonary TB cases in Hamadan Province, west of Iran.

METHODS

All patients with pulmonary tuberculosis recorded in the surveillance system from 2005 to 2013 were studied. The spatial scan statistic was used to detect significant clusters in status of unadjusted and adjusted for age, sex and location residence variables.

RESULTS

Clusters with high rate for both purely spatial and space-time analyses were seen in the same geographical areas composed of four city of Asadabad, Bahar, Toyserkan and Nahavand. Adjustment for mentioned variables did not change location of detected clusters with high rates.

CONCLUSIONS

Findings revealed evidence of significant clusters in Hamadan Province. Study results may help the health system to develop effective public health interventions and extend preventive interventions. However more study are needed to better explain of detected clusters due to limited access to effecting factors.

Protocol for a population-based molecular epidemiology study of tuberculosis transmission in a high HIV-burden setting: the Botswana Kopanyo study

INTRODUCTION

Mycobacterium tuberculosis (Mtb) is transmitted from person to person via airborne droplet nuclei. At the community level, Mtb transmission depends on the exposure venue, infectiousness of the tuberculosis (TB) index case and the susceptibility of the index case's social network. People living with HIV infection are at high risk of TB, yet the factors associated with TB transmission within communities with high rates of TB and HIV are largely undocumented. The primary aim of the Kopanyo study is to better understand the demographic, clinical, social and geospatial factors associated with TB and multidrug-resistant TB transmission in 2 communities in Botswana, a country where 60% of all patients with TB are also infected with HIV. This manuscript describes the methods used in the Kopanyo study.

METHODS AND ANALYSIS

The study will be conducted in greater Gaborone, which has high rates of HIV and a mobile population; and in Ghanzi, a rural community with lower prevalence of HIV infection and home to the native San population. Kopanyo aims to enrol all persons diagnosed with TB during a 4-year study period. From each participant, sputum will be cultured, and for all Mtb isolates, molecular genotyping (24-locus mycobacterial interspersed repetitive units-variable number of tandem repeats) will be performed. Patients with matching genotype results will be considered members of a genotype cluster, a proxy for recent transmission. Demographic, behavioural, clinical and social information will be collected by interview. Participant residence, work place, healthcare facilities visited and social gathering venues will be geocoded. We will assess relationships between these factors and cluster involvement to better plan interventions for reducing TB transmission.

ETHICS

Ethical approval from the Independent Review Boards at the University of Pennsylvania, US Centers for Disease Control and Prevention, Botswana Ministry of Health and University of Botswana has been obtained.

Spatial epidemiology and risk factors of pulmonary tuberculosis morbidity in Wenchuan earthquake-stricken area

OBJECTIVE

China is a country that experiences frequent earthquakes and has a high pulmonary tuberculosis burden. In this study, we aimed to explore the spatial clustering and risk factors of the reported incidence of pulmonary tuberculosis burden before and after the Wenchuan earthquake.

METHODS

Data on the location and the demographic, socioeconomic, and health service characteristics of the 181 counties of Sichuan province from 2004 to 2012 were collected. Global and local spatial autocorrelation analyses were performed to explore spatial clustering. The associated factors were screened using stepwise multiple linear regression, and a spatial lag model was fitted to explore the influence factors.

RESULTS

The incidence of pulmonary tuberculosis burden showed a global and local spatial autocorrelation relationship. The high-incidence counties shifted gradually over time from east to west and finally clustered in the "Aba-Ganzi" region. Factors influencing the incidence of pulmonary tuberculosis burden included minority areas, the proportion of the working population, county latitude, and the severity of the earthquake. The influence factors varied over time; the impact of minority regions, occupation, and health resources allocation weakened, whereas the economic development and mobility of the population became more significant.

CONCLUSION

The spatial structural relationship is an important factor related to pulmonary tuberculosis burden incidence. More attention should be paid to high-incidence areas and populations susceptible to pulmonary tuberculosis burden.

Correlation Assessment of Climate and Geographic Distribution of Tuberculosis Using Geographical Information System (GIS)

BACKGROUND

Tuberculosis (TB) spread pattern is influenced by geographic and social factors. Nowadays Geographic Information System (GIS) is one of the most important epidemiological instrumentation identifying high-risk population groups and geographic areas of TB. The aim of this study was to determine the correlation between climate and geographic distribution of TB in Khuzestan Province using GIS during 2005-2012.

METHODS

Through an ecological study, all 6363 patients with definite diagnosis of TB from 2005 until the end of September 2012 in Khuzestan Province, southern Iran were diagnosed. Data were recorded using TB- Register software. Tuberculosis incidence based on the climate and the average of annual rain was evaluated using GIS. Data were analyzed through SPSS software. Independent t-test, ANOVA, Linear regression, Pearson and Eta correlation coefficient with a significance level of less than 5% were used for the statistical analysis.

RESULTS

The TB incidence was different in various geographic conditions. The highest mean of TB cumulative incidence rate was observed in extra dry areas (P= 0.017). There was a significant inverse correlation between annual rain rate and TB incidence rate (R= -0.45, P= 0.001). The lowest TB incidence rate (0-100 cases per 100,000) was in areas with the average of annual rain more than 1000 mm (P= 0.003).

CONCLUSION

The risk of TB has a strong relationship with climate and the average of annual rain, so that the risk of TB in areas with low annual rainfall and extra dry climate is more than other regions. Services and special cares to high-risk regions of TB are recommended.

Detection of Tuberculosis Infection Hotspots Using Activity Spaces Based Spatial Approach in an Urban Tokyo, from 2003 to 2011

Background

Identifying ongoing tuberculosis infection sites is crucial for breaking chains of transmission in tuberculosis-prevalent urban areas. Previous studies have pointed out that detection of local accumulation of tuberculosis patients based on their residential addresses may be limited by a lack of matching between residences and tuberculosis infection sites. This study aimed to identify possible tuberculosis hotspots using TB genotype clustering statuses and a concept of “activity space”, a place where patients spend most of their waking hours. We further compared the spatial distribution by different residential statuses and describe urban environmental features of the detected hotspots.

Methods

Culture-positive tuberculosis patients notified to Shinjuku city from 2003 to 2011 were enrolled in this case-based cross-sectional study, and their demographic and clinical information, TB genotype clustering statuses, and activity space were collected. Spatial statistics (Global Moran’s I and Getis-Ord Gi* statistics) identified significant hotspots in 152 census tracts, and urban environmental features and tuberculosis patients’ characteristics in these hotspots were assessed.

Results

Of the enrolled 643 culture-positive tuberculosis patients, 416 (64.2%) were general inhabitants, 42 (6.5%) were foreign-born people, and 184 were homeless people (28.6%). The percentage of overall genotype clustering was 43.7%. Genotype-clustered general inhabitants and homeless people formed significant hotspots around a major railway station, whereas the non-clustered general inhabitants formed no hotspots. This suggested the detected hotspots of activity spaces may reflect ongoing tuberculosis transmission sites and were characterized by smaller residential floor size and a higher proportion of non-working households.

Conclusions

Activity space-based spatial analysis suggested possible TB transmission sites around the major railway station and it can assist in further comprehension of TB transmission dynamics in an urban setting in Japan.

Spatio-Temporal Pattern of Tuberculosis in the Regions Supervised by Shiraz University of Medical Sciences 2006-2012

BACKGROUND

The present study aimed to identify the spatial distribution of tuberculosis and determine the TB control program parameters in the regions supervised by Shiraz University of Medical Sciences in 2006-2012.

METHODS

The present ecological study was performed on 1797 TB patients in Shiraz University in 2006-2012 which were recorded by health centers using TB Register software. The study data were collected through over-counting and analyzed using the SPSS statistical software (ver. 19). Besides, the maps were drawn by ArcGIS, version 10.

RESULTS

The incidence rate of TB was 4.8 in 100,000 at the end of 2012. Success in treatment was adequate only in 2012 (89.7%). However, recovery of pulmonary TB was not adequate in any of the study years. In our study, the majority of the patients belonged to the 25-34 years age group that constitutes the active faction of the society. Moreover, the maps provided by GIS showed a high incidence rate of extra pulmonary TB in Firozabad Township during 7 years (2.7 in 100000 populations).

CONCLUSION

Incidence of TB in the regions supervised by Shiraz University of Medical Sciences follows a specific pattern, which requires exclusive studies for further evaluation of the incidence determinatives in various environmental and social conditions.

Eliminating tuberculosis one neighborhood at a time

OBJECTIVES

We evaluated a strategy for preventing tuberculosis (TB) in communities most affected by it.

METHODS

In 1996, we mapped reported TB cases (1985-1995) and positive tuberculin skin test (TST) reactors (1993-1995) in Smith County, Texas. We delineated the 2 largest, densest clusters, identifying 2 highest-incidence neighborhoods (180 square blocks, 3153 residents). After extensive community preparation, trained health care workers went door-to-door offering TST to all residents unless contraindicated. TST-positive individuals were escorted to a mobile clinic for radiography, clinical evaluation, and isoniazid preventive treatment (IPT) as indicated. To assess long-term impact, we mapped all TB cases in Smith County during the equivalent time period after the project.

RESULTS

Of 2258 eligible individuals, 1291 (57.1%) were tested, 229 (17.7%) were TST positive, and 147 were treated. From 1996 to 2006, there were no TB cases in either project neighborhood, in contrast with the preintervention decade and the continued occurrence of TB in the rest of Smith County.

CONCLUSIONS

Targeting high-incidence neighborhoods for active, community-based screening and IPT may hasten TB elimination in the United States.

Neighborhood socioeconomic position and tuberculosis transmission: a retrospective cohort study

Background

Current understanding of tuberculosis (TB) genotype clustering in the US is based on individual risk factors. This study sought to identify whether area-based socioeconomic status (SES) was associated with genotypic clustering among culture-confirmed TB cases.

Methods

A retrospective cohort analysis was performed on data collected on persons with incident TB in King County, Washington, 2004–2008. Multilevel models were used to identify the relationship between area-level SES at the block group level and clustering utilizing a socioeconomic position index (SEP).

Results

Of 519 patients with a known genotyping result and block group, 212 (41%) of isolates clustered genotypically. Analyses suggested an association between lower area-based SES and increased recent TB transmission, particularly among US-born populations. Models in which community characteristics were measured at the block group level demonstrated that lower area-based SEP was positively associated with genotypic clustering after controlling for individual covariates. However, the trend in higher clustering odds with lower SEP index quartile diminished when additional block-group covariates.

Conclusions

Results stress the need for TB control interventions that take area-based measures into account, with particular focus on poor neighborhoods. Interventions based on area-based characteristics, such as improving case finding strategies, utilizing location-based screening and addressing social inequalities, could reduce recent rates of transmission.

Eliminación de la tuberculosis, un vecindario por vez

Objetivos. Evaluamos una estrategia para la prevención de la tuberculosis en las comunidades más afectadas por esta enfermedad.

Métodos. En 1996, trazamos un mapa de los casos de tuberculosis notificados (1985–1995) y de las personas con reacción positiva a la prueba de la tuberculina (1993–1995) en el condado de Smith, Texas, Estados Unidos de América. Definimos los dos conglomerados de mayor tamaño y densidad, identificando los dos vecindarios con mayor incidencia (180 manzanas y 3 153 residentes). Tras una preparación intensiva de la comunidad, personal sanitario capacitado ofreció a todos los residentes, de vivienda en vivienda, la posibilidad de hacerse la prueba de la tuberculina, a menos que estuviera contraindicado. A las personas con resultados positivos en esta prueba se las acompañó a un consultorio móvil para realizarles ahí radiografías, una evaluación clínica y, según fuera pertinente, proceder con el tratamiento preventivo con isoniazida. Para evaluar las repercusiones a largo plazo, trazamos un mapa de todos los casos de tuberculosis que se registraron en el condado de Smith durante el período equivalente después del proyecto.

Resultados. De las 2 258 personas que cumplían los requisitos para participar, 1 291 (57,1%) se sometieron a la prueba de la tuberculina, 229 (17,7%) presentaron resultados positivos en dicha prueba y 147 fueron tratadas. De 1996 al 2006, no se registró ningún caso de tuberculosis en ninguno de los vecindarios del proyecto, a diferencia de lo ocurrido en el decenio anterior a la intervención y en el resto del condado de Smith, donde aparecieron continuamente casos de tuberculosis.

Conclusiones. Dirigirse a los vecindarios con una incidencia alta para realizar el tamizaje activo en la comunidad y aplicar tratamiento preventivo con isoniazida puede acelerar la eliminación de la tuberculosis en los Estados Unidos.

Clustered tuberculosis incidence in Bandar Lampung, Indonesia

BACKGROUND

The incidence of tuberculosis (TB) in the city of Bandar Lampung, Indonesia, increased during the period 2009-2011, although the cure rate for TB cases treated under the directly observed treatment, short course (DOTS) strategy in the city has been maintained at more than 85%. Cluster analysis is recognized as an interactive tool that can be used to identify the significance of spatially grouping sites of TB incidence. This study aimed to identify space-time clusters of TB during January to July 2012 in Bandar Lampung, and assess whether clustering co-occurred with locations of high population density and poverty.

METHODS

Medical records were obtained of smear-positive TB patients who were receiving treatment at DOTS facilities, located at 27 primary health centres and one hospital, during the period January to July 2012. Data on home addresses from all cases were geocoded into latitude and longitude coordinates, using global positioning system (GPS) tools. The coordinate data were then analysed using SaTScan.

RESULTS

Two significant clusters were identified with P value of 0.05 for the primary cluster and 0.1 for the secondary cluster. Clusters occurred in areas with high population density and a high proportion of poor families and poor housing conditions. The short radius of the clusters also indicated the possibility of local transmission of TB.

CONCLUSIONS

The incidence of TB in Bandar Lampung was not randomly distributed, but significantly concentrated in two clusters. Identification of clusters of TB, together with its etiological factors such as social determinants, and risk factors, can be used to support TB control programmes, particularly those aiming to reach vulnerable populations, and intensified case-finding.

Geo-epidemiologic and molecular characterization to identify social, cultural, and economic factors where targeted tuberculosis control activities can reduce incidence in Maryland, 2004-2010

OBJECTIVES

Tuberculosis (TB) disproportionately affects members of socioeconomically disadvantaged and minority populations in the U.S. We describe the geospatial distribution of TB cases in Maryland, identify areas at high risk for TB, and compare the geospatial clustering of cases with genotype clustering and demographic, socioeconomic, and TB risk-factor information.

METHODS

Addresses of culture-positive, genotyped TB cases reported to the Maryland Department of Health and Mental Hygiene from January 1, 2004, to December 31, 2010, were geocoded and aggregated to census tracts. Geospatial clusters with higher-than-expected case numbers were identified using Poisson spatial cluster analysis. Case distribution and geospatial clustering information were compared with (1) genotype clustering (spoligotypes and 12-locus MIRU-VNTR), (2) individual-level risk and demographic data, and (3) census tract-level demographic and socioeconomic data.

RESULTS

We genotoyped 1,384 (98%) isolates from 1,409 culture-positive TB cases. Two geospatial clusters were found: one in Baltimore City and one in Montgomery and Prince George's counties. Cases in these geospatial clusters were equally or less likely to share genotypes than cases outside the geospatial clusters. The two geospatial clusters had poverty and crowding in common but differed significantly by risk populations and behaviors.

CONCLUSIONS

Genotyping results indicated that recent transmission did not explain most geospatial clustering, suggesting that geospatial clustering is largely mitigated by social determinants. Analyses combining geospatial, genotyping, and epidemiologic data can help characterize populations most at risk for TB and inform the design of targeted interventions.

A spatial analysis of social and economic determinants of tuberculosis in Brazil

We investigated the spatial distribution, and social and economic correlates, of tuberculosis in Brazil between 2002 and 2009 using municipality-level age/sex-standardized tuberculosis notification data. Rates were very strongly spatially autocorrelated, being notably high in urban areas on the eastern seaboard and in the west of the country. Non-spatial ecological regression analyses found higher rates associated with urbanicity, population density, poor economic conditions, household crowding, non-white population and worse health and healthcare indicators. These associations remained in spatial conditional autoregressive models, although the effect of poverty appeared partially confounded by urbanicity, race and spatial autocorrelation, and partially mediated by household crowding. Our analysis highlights both the multiple relationships between socioeconomic factors and tuberculosis in Brazil, and the importance of accounting for spatial factors in analysing socioeconomic determinants of tuberculosis.

The clustering of smear-positive tuberculosis in Dabat, Ethiopia: a population based cross sectional study

BACKGROUND

In Ethiopia where tuberculosis epidemic remains high, studies that describe hotspots of the disease are unavailable. This study tried to detect the spatial distribution and clustering of smear-positive tuberculosis cases in Dabat, Ethiopia.

METHODS AND FINDINGS

A population-based cross sectional study conducted in the Dabat Health and Demographic Surveillance System site from October 2010 to September 2011 identified smear-positive tuberculosis cases. Trained field workers collected demographic and location data from each study participant through house-to-house visits. A spatial scan statistic was used to identify purely spatial and space-time clusters of tuberculosis among permanent residents. Two significant (p<0.001) spatial and space-time clusters were identified in the study district.

CONCLUSION

Tuberculosis is concentrated in certain geographic locations in Dabat, Ethiopia. This kind of clustering can be common in the country, so the National Tuberculosis Control Program can be more effective by identifying such clusters and targeting interventions.

Genotyping and drug resistance patterns of Mycobacterium tuberculosis strains observed in a tuberculosis high-burden municipality in Northeast, Brazil

Objectives

This study has used a combination of clinical information, spoligotyping, and georeferencing system to elucidate the genetic diversity of the Mycobacterium tuberculosis isolates circulating in a TB-prevalent municipality of Northeast Brazil.

Methods

A total of 115 M. tuberculosis strains were isolated from pulmonary tuberculosis patients from January 2007 to March 2008 in Fortaleza. Drug susceptibility and spoligotyping assays were performed and place of residence of the patients were georeferenced.

Results

Of the M. tuberculosis strains studied, 51 (44.3%) isolates were resistant to at least one drug (R-TB) and 64 (55.7%) were sensitive to all the drugs tested (S-TB). A high frequency of resistance was found in previously treated cases (84%) and among new cases (16%; p < 0.001). A total of 74 (64%) isolates were grouped into 22 spoligotyped lineages, while 41 (36%) isolates were identified as new. Among the predominant genotypes, 33% were Latim American Mediterranean (LAM), 12% Haarlem (H), and 5% U. There was no association of geographic distribution of RT-TB patients as compared to the controls and also the geographic location to the spoligotype patterns. The geospatial analysis revealed that 24 (23%) patients (hot spot zones) either shared the same residence or lived in a close neighborhood of a case. Among these concentration zones, the patients lived in the same residence and shared a common genotype pattern and resistance pattern.

Discussion

It was observed that the spoligopatterns family distribution was similar to that reported for South America, prevailing the LAM and H lineages. A high rate-case among the resistant TB group occurs as a result of transmitted and acquired resistance. A more effective surveillance program is needed in order to succeed in reducing tuberculosis in Northeast Brazil.

The contribution of spatial analysis to understanding HIV/TB mortality in children: a structural equation modelling approach

BACKGROUND

South Africa accounts for more than a sixth of the global population of people infected with HIV and TB, ranking her highest in HIV/TB co-infection worldwide. Remote areas often bear the greatest burden of morbidity and mortality, yet there are spatial differences within rural settings.

OBJECTIVES

The primary aim was to investigate HIV/TB mortality determinants and their spatial distribution in the rural Agincourt sub-district for children aged 1-5 years in 2004. Our secondary aim was to model how the associated factors were interrelated as either underlying or proximate factors of child mortality using pathway analysis based on a Mosley-Chen conceptual framework.

METHODS

We conducted a secondary data analysis based on cross-sectional data collected in 2004 from the Agincourt sub-district in rural northeast South Africa. Child HIV/TB death was the outcome measure derived from physician assessed verbal autopsy. Modelling used multiple logit regression models with and without spatial household random effects. Structural equation models were used in modelling the complex relationships between multiple exposures and the outcome (child HIV/TB mortality) as relayed on a conceptual framework.

RESULTS

Fifty-four of 6,692 children aged 1-5 years died of HIV/TB, from a total of 5,084 households. Maternal death had the greatest effect on child HIV/TB mortality (adjusted odds ratio=4.00; 95% confidence interval=1.01-15.80). A protective effect was found in households with better socio-economic status and when the child was older. Spatial models disclosed that the areas which experienced the greatest child HIV/TB mortality were those without any health facility.

CONCLUSION

Low socio-economic status and maternal deaths impacted indirectly and directly on child mortality, respectively. These factors are major concerns locally and should be used in formulating interventions to reduce child mortality. Spatial prediction maps can guide policy makers to target interventions where they are most needed.

Eliminating tuberculosis one neighborhood at a time

OBJECTIVES

We evaluated a strategy for preventing tuberculosis (TB) in communities most affected by it.

METHODS

In 1996, we mapped reported TB cases (1985-1995) and positive tuberculin skin test (TST) reactors (1993-1995) in Smith County, Texas. We delineated the 2 largest, densest clusters, identifying 2 highest-incidence neighborhoods (180 square blocks, 3153 residents). After extensive community preparation, trained health care workers went door-to-door offering TST to all residents unless contraindicated. TST-positive individuals were escorted to a mobile clinic for radiography, clinical evaluation, and isoniazid preventive treatment (IPT) as indicated. To assess long-term impact, we mapped all TB cases in Smith County during the equivalent time period after the project.

RESULTS

Of 2258 eligible individuals, 1291 (57.1%) were tested, 229 (17.7%) were TST positive, and 147 were treated. From 1996 to 2006, there were no TB cases in either project neighborhood, in contrast with the preintervention decade and the continued occurrence of TB in the rest of Smith County.

CONCLUSIONS

Targeting high-incidence neighborhoods for active, community-based screening and IPT may hasten TB elimination in the United States.

Spatial and temporal distribution of tuberculosis in the State of Mexico, Mexico

Tuberculosis (TB) is one of the oldest human diseases that still affects large population groups. According to the World Health Organization (WHO), there were approximately 9.4 million new cases worldwide in the year 2010. In Mexico, there were 18,848 new cases of TB of all clinical variants in 2010. The identification of clusters in space-time is of great interest in epidemiological studies. The objective of this research was to identify the spatial and temporal distribution of TB during the period 2006–2010 in the State of Mexico, using geographic information system (GIS) and SCAN statistics program. Nine significant clusters (P < 0.05) were identified using spatial and space-time analysis. The conclusion is that TB in the State of Mexico is not randomly distributed but is concentrated in areas close to Mexico City.

Rapid spoligotyping of Mycobacterium tuberculosis complex bacteria by use of a microarray system with automatic data processing and assignment

Membrane-based spoligotyping has been converted to DNA microarray format to qualify it for high-throughput testing. We have shown the assay's validity and suitability for direct typing from tissue and detecting new spoligotypes. Advantages of the microarray methodology include rapidity, ease of operation, automatic data processing, and affordability.

Mapping late testers for HIV in Texas

Understanding the spatial patterns of late testing for HIV infection is critically important for designing and evaluating intervention strategies to reduce the social and economic burdens of HIV/AIDS. Traditional mapping methods that rely on frequency counts or rates in predefined areal units are known to be problematic due to issues of small numbers and visual biases. Additionally, confidentiality requirements associated with health data further restrict the ability to produce cartographic representations at fine geographic scales. While kernel density estimation methods produce stable and geographically detailed patterns of the late testing burden, the resulting pattern depends critically on the definition of the at-risk population. Using three definitions of at risk groups, we examine the cartographic representation of HIV late testers in Texas and show that the resulting spatial patterns and the interpretation of disease burdens are different based on the choice of the at-risk population. Disease mappers should exercise considerable caution in selecting the denominator population for mapping.

Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain

Background

Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information.

Methods

Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database.

Results

The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts.

Conclusions

In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This study is an attempt to demonstrate how web processing services together with web-based mapping capabilities suit the needs of health practitioners in epidemiological analysis scenarios.

[Spatial analysis of tuberculosis/HIV coinfection: its relation with socioeconomic levels in a city in south-eastern Brazil]

INTRODUCTION

Spatial analysis of the distribution of tuberculosis/HIV coinfection was performed and associated with socioeconomic indicators in São José do Rio Preto, from 1998 to 2006.

METHODS

New TB/HIV coinfection cases were georeferenced and incidence coefficients were calculated for spatial units. Moran's index was used to evaluate spatial associations of incidences. Multiple regressions selected variables that could best explain the spatial association of incidences. The local indicator of spatial association was used to identify significant spatial groupings.

RESULTS

Moran's index was 0.0635 (p=0.0000) indicating that the incidence association occurred. The variable that best explained the spatial association of incidence was the percentage of heads of families with up to three years of education. The LISA cluster map for TB/HIV coinfection incidence coefficients showed groups with high incidence rates in the North and low incidence in the South and West regions of the municipality.

CONCLUSIONS

The study elucidated the spatial geographic distribution of TB/HIV coinfection and determined its association with socioeconomic variables, thus providing data for oriented planning, prioritizing socially disadvantaged regions that present a higher incidence of the disease.

Tracking the polio virus down the Congo River: a case study on the use of Google Earth in public health planning and mapping

BACKGROUND

The use of GIS in public health is growing, a consequence of a rapidly evolving technology and increasing accessibility to a wider audience. Google Earth (GE) is becoming an important mapping infrastructure for public health. However, generating traditional public health maps for GE is still beyond the reach of most public health professionals. In this paper, we explain, through the example of polio eradication activities in the Democratic Republic of Congo, how we used GE Earth as a planning tool and we share the methods used to generate public health maps.

RESULTS

The use of GE improved field operations and resulted in better dispatch of vaccination teams and allocation of resources. It also allowed the creation of maps of high quality for advocacy, training and to help understand the spatiotemporal relationship between all the entities involved in the polio outbreak and response.

CONCLUSION

GE has the potential of making mapping available to a new set of public health users in developing countries. High quality and free satellite imagery, rich features including Keyhole Markup Language or image overlay provide a flexible but yet powerful platform that set it apart from traditional GIS tools and this power is still to be fully harnessed by public health professionals.

Communicable Diseases, Globalization of

This article examines the spatial distribution of leading infectious causes of morbidity and mortality worldwide. Beginning with simple models explaining the spatial pattern of infectious diseases, the epidemiologic transition, and disease ecology models, the article focuses on HIV/AIDS, tuberculosis, polio, SARS, and influenza as well as sexually transmitted infections such as gonorrhea. It addresses the problem of disease strain mutation and especially drug resistance, and argues for the application of genotyping in medical geography research. The article emphasizes how migration and increased global interaction are producing a globalization of infectious diseases while at the same time, ethnic residential segregation is producing spatial concentrations of infectious disease or different strains of disease.

Distribuição espacial dos casos novos de tuberculose em Vitória, Estado do Espírito Santo, no período entre 2000 e 2005

Realizou-se um estudo ecológico com a análise da distribuição espacial dos 979 novos casos de tuberculose entre 2000 e 2005. Utilizou-se o Método Bayesiano Empírico Local para estimação do risco. O Índice de Moram Local foi calculado para avaliação das autocorrelações entre as incidências de bairros limítrofes. Observou-se que a tuberculose distribui-se heterogeneamente entre os bairros, sendo possível identificar regiões com alto risco de adoecimento.

Foreign-Born Status and Geographic Patterns of Tuberculosis Genotypes in Tarrant County, Texas

Regardless of destination, immigrants arrive with health profiles typical of people in their previous surroundings. Thus, immigrants change the epidemiological profile of destination communities, and immigrant neighborhoods may represent islands of infectious disease. Genotyping has emerged as a useful surveillance tool to track the spread of disease at the molecular level. Yet the spatial distribution of infectious disease at the molecular level associated with migration and immigrant neighborhoods has received little attention. Using molecular genotyping to characterize M. tuberculosis isolated from tuberculosis cases, this article analyzes spatial variations of unique molecular M. tuberculosis strains by zip code in Tarrant County, Texas. The results suggest that immigrant neighborhoods have higher rates of unique isolates of tuberculosis (suggestive of remote transmission) compared to neighborhoods occupied by the native-born. Neighborhoods dominated by the native-born have higher rates of clustered isolates (suggestive of recent transmission). Therefore, in addition to being culturally distinct, immigrant neighborhoods may also be pathogenically distinct from surrounding neighborhoods.

Tuberculosis incidence in Portugal: spatiotemporal clustering

BACKGROUND

The statistics of disease clustering is one of the most important tools for epidemiologists to detect and monitor public health disease patterns. Nowadays, tuberculosis (TB)--an infectious disease caused by the Mycobacterium tuberculosis--presents different (development in populations and antibiotics resistance) patterns and specialists are very concerned with it and its association to several other diseases and factors. Each year, tuberculosis kills about three million people in the world. In particular, it is responsible for the death of more than one-third of HIV-infected people, who prove particularly susceptible due to a decline in their immune defences. The purpose of this study is to determine if there are spatiotemporal tuberculosis incidence clusters in continental Portugal. The presented case study is based on the notification of new tuberculosis cases (disease incidence), between 2000 and 2004. In methodological terms, the spatial scan statistic, used to identify spatiotemporal clusters, was improved by including two new approaches: definition of window sizes in the cluster scanning processes considering empirical mean spatial semivariograms and an independent and posterior validation of identified clusters (based on geostatistical simulations).

RESULTS

Continental Portugal is organized in 18 districts with 278 sub-districts. For this case study, the number of new notified cases of TB, per sub-district and per year (2000-2004) was available. TB incidence presents clear spatial patterns: a semivariogram consistent with 40% of nugget effect and 60% of spatial contribution, following an exponential model with a range of 143 kilometres. Temporal semivariograms were not conclusive, as only 5 years of data were available. The spatial and temporal persistence of clusters were analyzed considering different models. Significant high incidence rate space-time clusters were identified in three areas of Portugal (between 2000 and 2004) and a purely temporal cluster was identified covering the whole country, during 2002.

CONCLUSION

In terms of spatiotemporal clustering of tuberculosis disease, the proposed methodology allowed the identification of critical spatiotemporal areas. In Portugal there were 3 critical districts (Porto, Setúbal and Lisbon) with high rates of notified incidences between 2000 and 2004. In methodological terms, semivariogram parameters were successfully applied to define spatiotemporal scan window sizes and shapes (ellipsoidal cylinders), showing very good results and performances in the case study. After defining the clusters, these were authenticated through a validation method, based on geostatistical simulations.

Geomatics in injury prevention: the science, the potential and the limitations

BACKGROUND

Geomatics describes the activities involved in acquiring and managing geographical data and producing geographical information for scientific, administrative and technical endeavors. As an emerging science, geomatics has a great potential to support public health. Geomatics provides a conceptual foundation for the development of geographic information systems (GIS), computerized tools that manage and display geographical data for analytical applications. As descriptive epidemiology typically involves the examination of person, place and time in the occurrence of disease or injury, geomatics and GIS can play an important role in understanding and preventing injury.

AIM

This article provides a background to geomatics for those in the injury prevention field who are unfamiliar with spatial analysis. We hope to stimulate researchers and practitioners to begin to use geomatics to assist in the prevention of injury.

METHODS

The authors illustrate the potential benefits and limitations of geomatics in injury prevention in a non-technical way through the use of maps and analysis.

RESULTS

By analysing the location of patients treated for fall injuries in Central Toronto using GIS, some demographic and land use variables, such as household income, age, and the location of homeless shelters, were identified as explanatory factors for the spatial distribution.

CONCLUSION

By supporting novel approaches to injury prevention, geomatics has a great potential for efforts to combat the burden of injury. Despite some limitations, those with an interest in injury prevention could benefit from this science.

On the use of ZIP codes and ZIP code tabulation areas (ZCTAs) for the spatial analysis of epidemiological data

BACKGROUND

While the use of spatially referenced data for the analysis of epidemiological data is growing, issues associated with selecting the appropriate geographic unit of analysis are also emerging. A particularly problematic unit is the ZIP code. Lacking standardization and highly dynamic in structure, the use of ZIP codes and ZIP code tabulation areas (ZCTA) for the spatial analysis of disease present a unique challenge to researchers. Problems associated with these units for detecting spatial patterns of disease are explored.

RESULTS

A brief review of ZIP codes and their spatial representation is conducted. Though frequently represented as polygons to facilitate analysis, ZIP codes are actually defined at a narrower spatial resolution reflecting the street addresses they serve. This research shows that their generalization as continuous regions is an imposed structure that can have serious implications in the interpretation of research results. ZIP codes areas and Census defined ZCTAs, two commonly used polygonal representations of ZIP code address ranges, are examined in an effort to identify the spatial statistical sensitivities that emerge given differences in how these representations are defined. Here, comparative analysis focuses on the detection of patterns of prostate cancer in New York State. Of particular interest for studies utilizing local, spatial statistical tests, is that differences in the topological structures of ZIP code areas and ZCTAs give rise to different spatial patterns of disease. These differences are related to the different methodologies used in the generalization of ZIP code information. Given the difficulty associated with generating ZIP code boundaries, both ZIP code areas and ZCTAs contain numerous representational errors which can have a significant impact on spatial analysis. While the use of ZIP code polygons for spatial analysis is relatively straightforward, ZCTA representations contain additional topological features (e.g. lakes and rivers) and contain fragmented polygons that can hinder spatial analysis.

CONCLUSION

Caution must be exercised when using spatially referenced data, particularly that which is attributed to ZIP codes and ZCTAs, for epidemiological analysis. Researchers should be cognizant of representational errors associated with both geographies and their resulting spatial mismatch, especially when comparing the results obtained using different topological representations. While ZCTAs can be problematic, topological corrections are easily implemented in a geographic information system to remedy erroneous aggregation effects.

What is the outcome of targeted tuberculosis screening based on universal genotyping and location?

RATIONALE AND OBJECTIVES

Identifying and treating persons with latent tuberculosis (TB) infection (LTBI) at high risk for developing TB is part of the current TB elimination strategy. There are no specific criteria, other than medical risks, to designate groups as high risk for developing TB. We hypothesized that, if location-based screenings were done in communities where persons with genotypically clustered Mycobacterium tuberculosis resided, then persons with LTBI from recent transmission and with undiagnosed TB could be identified.

METHODS

Location-based TB screenings were done in partnership with multiple community-based organizations using resources previously used for other types of screening.

MAIN RESULTS

Location-based screenings identified one person with TB for every 83 screened, and one person with LTBI for every five screened. The yield of this targeted screening program for discovering persons with TB and LTBI exceeded what would be expected from nontargeted screening in a county with a TB incidence of 5.7 per 100,000 population.

CONCLUSIONS

Genotyping combined with geographic information systems analysis can potentially be used to define high-risk status and to define areas for location-based TB screenings.