Geographical Distribution and Surveillance of Tuberculosis (TB) Using Spatial Statistics (original) (raw)
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International journal of health geographics, 2006
The World Health Organization has declared tuberculosis a global emergency in 1993. It has been estimated that one third of the world population is infected with Mycobacterium tuberculosis, the causative agent of tuberculosis. The emergence of TB/HIV co-infection poses an additional challenge for the control of tuberculosis throughout the world. The World Health Organization is supporting many developing countries to eradicate tuberculosis. It is an agony that one fifth of the tuberculosis patients worldwide are in India. The eradication of tuberculosis is the greatest public health challenge for this developing country. The aim of the present population based study on Mycobacterium tuberculosis is to test a large set of tuberculosis cases for the presence of statistically significant geographical clusters. A spatial scan statistic is used to identify purely spatial and space-time clusters of tuberculosis. Significant (p < 0.05 for primary clusters and p < 0.1 for secondary cl...
Detection of tuberculosis hotspots using spatial interpolation method in Mysuru district, Karnataka
Journal of Applied Biology & Biotechnology, 2021
Identification of tuberculosis (TB) affected sectors always keeps a check over the transmission in urban regions. Despite adequate therapy, the rate of infection is constant for decades in these regions. Information in residential address and identified TB affected sectors need accordance as per the studies by the researchers. In particular, as an intervention method, geographic information system (GIS) tools on TB epidemiology reveal significant geographical heterogeneity of TB spread in the region. The heterogeneous TB patterns in the local region is due to the person to person disease spread. Due to ongoing person-to-person transmission, TB represents heterogeneous spatial patterns with the local aggregation of cases. Many studies on the combination of TB patients based on their residential address and TB infection sites lack accordance. This study aimed to identify TB incidence using the geospatial features in the reported cases of Mysuru district, in Karnataka. The TB spatial epidemiology in Mysuru district was aimed in a defined geographical area which was deciphered by application of GIS (ArcGIS 10.2.2 demo version) with inverse distance weighted interpolation technique. Based on the reported cases, hotspots reveal, the uneven distribution of TB cases was noticed in Mysuru district. Incidence based spatial analysis suggested possible TB transmission sites and its dynamics in urban areas of Mysuru. Implementing these strategies could be useful for detecting the distribution of TB that can be targeted for screening and initiating the treatment regimen which interrupts the transmission and reduces TB incidence.
Local Spatial Knowledge for Eliciting Risk Factors and Disease Mapping of Tuberculosis Epidemics
Environment-Behaviour Proceedings Journal
Predicting risk areas of tuberculosis (TB) epidemics needs a proper understanding of the disease transmission process in identifying holistic risk factors. This study was performed to determine the causative factors triggering the epidemics in Shah Alam, Malaysia by utilising spatial analysis techniques and participation of local-expert knowledge or local spatial knowledge (LSK) approach. LSK approach was conducted to collect data on TB risk factors by combining experienced local experts' opinions, multi-criteria decision making (MCDM) analysis, and GIS mapping. The combination of experts participatory GIS and knowledge elicitation can generate a useful spatial knowledge framework for risk assessment of local epidemics. Keywords: Local spatial knowledge, MCDM method, experts participatory GIS, tuberculosis. eISSN: 2398-4287 © 2020. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license...
Journal of Epidemiology and Global Health, 2015
This retrospective study aimed to address whether or to what extent spatial and non-spatial factors with a focus on a healthcare delivery system would influence successful tuberculosis (TB) treatment outcomes in Urmia, Iran. In this crosssectional study, data of 452 new TB cases were extracted from Urmia TB Management Center during a 5-year period. Using the Geographical Information System (GIS), health centers and study subjectsÕ locations were geocoded on digital maps. To identify the statistically significant geographical clusters, Average Nearest Neighbor (ANN) index was used. Logistic regression analysis was employed to determine the association of spatial and non-spatial variables on the occurrence
The Spatial-Temporal Epidemiology Analysis of Tuberculosis Disease in Pakistan
Quaid-e-Awam University Research Journal of Engineering, Science & Technology, 2021
In spite of significant progress, Tuberculosis (TB) remains a severe national health issue in Pakistan. However, very few studies have been done on the spatial-temporal appraisal of tuberculosis in Pakistan. The current research is based on the TB disease dataset obtained from the Pakistan Bureau of Statistics from 2015 to 2019. The study has focused on assessing Spatial epidemiology statistics and spatial autocorrelation to detect the cluster of TB disease incidence rate (IR) for New, Male, Female and total TB patients at the provincial and territorial levels in Pakistan. The spatial epidemiology statistics and spatial autocorrelation have been measured the temporal trends of TB IR as per 100,000 population. The global and local spatial autocorrelation of TB IR has been analyzed by the global Moran's I and Anselin's Local Moran's using GeoDa software and ArcGIS tool. Results show that the IR in Pakistan exhibited a progressive decrease from 2015 to 2018 but showed an un...
South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde, 1996
To determine the geographical distribution of tuberculosis in the two Western Cape suburbs with the highest reported incidence of tuberculosis. Descriptive illustrative study. Two adjacent Western Cape suburbs covering 2.42 km2 with a population of 34,294 and a reported tuberculosis incidence of > 1,000/100,000. All patients notified as having tuberculosis over a 10-year period (1985-1994). None The geographical distribution of the cases was determined using a geographical information system (GIS) and the National Population Census (1991). One thousand eight hundred and thirty-five of the 5,345 dwelling units (34.3%) housed at least 1 case of tuberculosis during the past decade and in 483 houses 3 or more cases occurred. These cases were distributed unevenly through the community, with the tuberculosis incidence per enumerator subdistrict (ESD) varying from 78 to 3,150/100,000 population. In a small area with a high incidence of tuberculosis, the cases are spread unevenly through...
Using GIS technology to identify areas of tuberculosis transmission and incidence
International Journal of Health Geographics, 2004
Background: Currently in the U.S. it is recommended that tuberculosis screening and treatment programs be targeted at high-risk populations. While a strategy of targeted testing and treatment of persons most likely to develop tuberculosis is attractive, it is uncertain how best to accomplish this goal. In this study we seek to identify geographical areas where on-going tuberculosis transmission is occurring by linking Geographic Information Systems (GIS) technology with molecular surveillance.
International Journal of Computer Applications
Analyzing the spatiotemporal distribution of tuberculosis (TB) is a very important way to understand its epidemiology thereby helping to identify geographic regions at higher risk and to enable proper control and resource allocation. This study was undertaken to ascertain the spatiotemporal distribution of TB cases and treatment outcomes in the Birim Central Municipality (BCM) in the Eastern Region (E/R) of Ghana for the period 2012-2016 and to recommend appropriate preventive measures. In this retrospective study, the locations of the total of 268 TB cases identified from 2012-2016 were geocoded on the BCM digital maps. Spatial visualization using choropleth maps, network analysis, and service area analysis of ArcGIS10.2 was used to identify the geographic concentration of cases and the various treatment outcomes as well as proximity of patient community to health facility. A questionnaire was also used to collect primary data from TB patients diagnosed in year 2017. This data was analyzed using SPSS version 21. The study identified five main communities as hot spots of TB in the municipality with variations in other communities. It was also found that other non-spatial factors such as socioeconomic factors and stigmatization highly influence treatment outcome. Reducing stigmatization, regular sensitization of health staff who are not directly involved in tuberculosis care, and using a formerly cured TB patient as a peer educator were some of the best ways identified to help improve positive treatment outcomes in the municipality.
Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review
BMC medicine, 2018
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. 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 ). 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 setting...
Spatial-temporal Analysis of Tuberculosis Incidence in Burundi Using GIS
Central African Journal of Public Health, 2019
Tuberculosis is one of the most contagious diseases that has been present for over 5000 years and it is still one of the most significant public health problems. This paper is intended to employ GIS in analyzing spatial variations of tuberculosis incidence in Burundi highlighting the main hot spots. Also, the paper aims to evaluate the temporal changes of TB incidence during the period 2009-2017 and guide the resource allocation. For this purpose, data on tuberculosis incidence at both province and health district level were analyzed. Data on incidence rate of TB and demographic data were collected at province level. Also, data on cases of TB recorded at health district level were acquired. The collected data were analyzed at both temporal and spatial scale. Temporal analysis involved identifying the various trends of TB incidence rate in various Burundi provinces during the period 2009-2017. Spatial analysis comprised mapping spatial variations in TB incidence rates and their trend over the period 2009-2017 and TB incidence at health district level. Moreover, Hot Spot analysis was performed to delineate those districts of statistically significant hot spots in TB incidence in Burundi. The temporal analysis of TB incidence rate, at province level, revealed that during the period 2009-2017, Burundi provinces have experienced varied trends of TB incidence with an annual change rate ranging between (-32.9) and (+5.22) in case of TB in all clinical forms and between (-12.2) and (+1.1) in case of Pulmonary TB. TB incidence rates were found to be positively correlated with proportion of urban population and population density. Meanwhile, spatial analysis of TB cases, revealed that eastern parts of Burundi have been experiencing relatively low incidence rates of TB compared to other parts of the country. This was highlighted by Hot Spot analysis that revealed a tendency of Pulmonary TB cases to be clustered and a hot spot in Pulmonary TB incidence was clearly distinguished in western parts of Burundi. Spatial temporal analysis highlights the potentials of GIS in recognizing trends and spatial pattern of such a disease and may support designing and implementing control programs and guide the resource allocation.