Detection of tuberculosis hotspots using spatial interpolation method in Mysuru district, Karnataka (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...
Geographical Distribution and Surveillance of Tuberculosis (TB) Using Spatial Statistics
International Journal of Applied Geospatial Research, 2013
Socio-demographic and health indices vary across the administrative units in a country. Thus, reported morbidity and mortality figures vary and inter/intra state comparison becomes a challenge. To handle such issues and administer a centralized health management system, identifying disease clusters and providing services to high risk population become important. Exploring a small part of the immense potential of geographic information systems (GIS) in centralized health management, this study presents a method of generating effective information for proper health management at local level. Such information is important for infectious diseases like tuberculosis (TB). The present paper discusses quarterly GIS mapping and assessment of TB in 1,965 villages of Almora district, Uttarakhand, India from 2003 to 2008. The values for Morbidity Rate (MBR) are depicted in risk maps for each quarter. Moran's I indices were used to estimate the global spatial autocorrelation between the morbidity rates. Local Moran's I (LISA) was used to detect spatial clusters and outliers, and for the prediction of hotspots of the disease. The result of this study has the potential to reflect a realistic assessment of the disease situation at the local level. Future work on this study can be utilized for planning and policy framework related to TB and other diseases.
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.
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.
Asian Journal of Healthy and Science
According to WHO data in 2018, the largest proportion of pulmonary TB cases was in the Asian region at 45%, Indonesia was the 2nd highest for pulmonary TB cases in the world after India. Based on data from the Kuningan District Health Office in 2021, the prevalence of pulmonary TB cases was 0.92% with a total of 1,389 cases. The purpose of this study was to describe the distribution of risk factors for the incidence of pulmonary tuberculosis (Pulmonary TB) using a Geographic Information System (GIS) in Kuningan District 2022. This study uses a descriptive type of research with a quantitative approach. The population and sample in this study were 32 sub-districts in Kuningan Regency with a total of 1,389 cases. The sample in this study is total sampling. Data analysis in this study includes univariate analysis using SPSS application and spatial distribution using ArcGIS application. The distribution of the incidence of pulmonary tuberculosis (pulmonary TB) in Kuningan Regency showed ...
Analysis of the Tuberculosis Occurrence Through the Use of Geoprocessing
International Archives of Medicine, 2016
Background: For the control of tuberculosis (TB), it must be adopted specific measures in areas of high transmission. Thus, it was aimed to identify the spatial pattern of new tuberculosis cases in Juazeiro do Norte-CE/Brazil, from 2001 to 2012. Methods and Findings: It is a hybrid design, ecological study and temporal trend. The new cases reported with TB were included as subjects of research. It was outlined the socio demographic profile; the spatial analysis of cases was made through the Kernel technique and the nearest neighbor method with simulation. Among 914 new TB cases, there was a predominance of males (56.0%), aged between 20 to 39 years (42.0%), with incomplete elementary school (43.2%), pulmonary clinical form (89.1%). 79.1% of patients achieved a cure and 5.3% abandoned the treatment. In the studied period, it was identified homogeneous spatial distribution and non-random pattern, with the highest concentration of cases in the southern region of the city. Conclusion: The identification of spatial pattern becomes relevant, in order that it can contribute to the strengthening of the TB control by providing information that optimizes activities such as: active search, health education, notification of new cases and supervising the treatment performed by health professionals.
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...
Bali Medical Journal
Background: Indonesia will be free of TB (Tuberculosis) in 2050, and elimination will begin in 2030. TB cases are still high in Bandar Lampung City, so efforts are needed to solve the problem. Mapping of TB cases using a Geographic Information Spatial (GIS) approach was performed in this study to evaluate the spreading patterns of TB patients so that policies can be taken to deal with TB cases in an epidemiological manner. Methods: The research was conducted in 31 public health centers in Bandar Lampung City. The number of TB patients in this study was 879 people. Making maps for visualizing the spread of TB patients using Archgis software, data were analyzed with Geoda and Moran's Index to see the spatial relationship between variables. Results: The spatial analysis using Geoda found a spatial relationship between TB patients and population density (p=0.00079) and the distance between the TB patient's house and the health center (p=0.00000). However, there was a significant...
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...
2020
Background: Tuberculosis (TB) depicts heterogeneous spatial patterns with geographical aggregation of TB cases due to either ongoing person-to-person transmission or reactivation of latent infection in a community sharing risk factor. In this regard, we aimed to assess the spatiotemporal aggregation of drug-resistant TB (DR-TB) patients notified to the national TB program (NTP) from 2015 to 2018 in selected districts of Karnataka, South India. Methods: This was a cross-sectional study among DR-TB patients notified from Dakshina Kannada, Udupi, and Chikamagalur districts of the state of Karnataka. Clinico-demographic details were extracted from treatment cards. The registered addresses of the patients were geocoded (latitude and longitude) using Google Earth. Using the QGIS software, spot map, heat maps and grid maps 25 km 2 with more than the expected count of DR-TB patients were constructed.