Journal: PLoS ONE

Article Title: Performance of GenoType MTBDR sl assay for detection of second-line drugs and ethambutol resistance directly from sputum specimens of MDR-TB patients in Bangladesh

doi: 10.1371/journal.pone.0261329

Figure Lengend Snippet: Demographic and clinical characteristics of 218 MDR-TB patients.

Article Snippet: The majority (85.8%) of the MDR-TB patients were from the three divisional regions of Chittagong, Rajshahi and Mymensingh (Individual data points are provided in the ).

Techniques:

Journal: BMC Infectious Diseases

Article Title: Time trend prediction and spatial–temporal analysis of multidrug-resistant tuberculosis in Guizhou Province, China, during 2014–2020

doi: 10.1186/s12879-022-07499-9

Figure Lengend Snippet: The SI of MDR-TB cases distribution in each month from 2014 to 2020 in Guizhou Province

Article Snippet: One most likely cluster and two secondary clusters were shown in Fig. . Fig. 7 The detected spatial–temporal cluster map of MDR-TB cases in Guizhou (2014–2020) The most likely cluster was detected from January 2015 to December 2016 with 154 reported cases (LLR = 272.06), covering 1 county (Nanming) in Guiyang prefecture.

Techniques:

Journal: BMC Infectious Diseases

Article Title: Time trend prediction and spatial–temporal analysis of multidrug-resistant tuberculosis in Guizhou Province, China, during 2014–2020

doi: 10.1186/s12879-022-07499-9

Figure Lengend Snippet: Comparison of actual and predicted cases of MDR-TB in Guizhou China. the black and green lines represent the observed values and predicted values, respectively; blue line represents 95% confidence intervals; after grey vertical line, the orange and yellow part represent 80% and 95% confidence intervals, respectively

Article Snippet: One most likely cluster and two secondary clusters were shown in Fig. . Fig. 7 The detected spatial–temporal cluster map of MDR-TB cases in Guizhou (2014–2020) The most likely cluster was detected from January 2015 to December 2016 with 154 reported cases (LLR = 272.06), covering 1 county (Nanming) in Guiyang prefecture.

Techniques: Comparison

Journal: BMC Infectious Diseases

Article Title: Time trend prediction and spatial–temporal analysis of multidrug-resistant tuberculosis in Guizhou Province, China, during 2014–2020

doi: 10.1186/s12879-022-07499-9

Figure Lengend Snippet: The geographical distribution of total MDR-TB cases in Guizhou from 2014 to 2020. a The geographical location of Guizhou in China; b The geographical location of 9 prefectures in Guizhou; c The geographical location of 88 counties in 9 prefectures, and distribution of total MDR-TB cases over seven years in each county

Article Snippet: One most likely cluster and two secondary clusters were shown in Fig. . Fig. 7 The detected spatial–temporal cluster map of MDR-TB cases in Guizhou (2014–2020) The most likely cluster was detected from January 2015 to December 2016 with 154 reported cases (LLR = 272.06), covering 1 county (Nanming) in Guiyang prefecture.

Techniques:

Journal: BMC Infectious Diseases

Article Title: Time trend prediction and spatial–temporal analysis of multidrug-resistant tuberculosis in Guizhou Province, China, during 2014–2020

doi: 10.1186/s12879-022-07499-9

Figure Lengend Snippet: Maps of local spatial autocorrelation cluster of MDR-TB for each county in Guizhou province from 2014 to 2020 by ArcMap software. Only those counties whose local Moran’s I have reached the significance level of 0.05 will be present on the map: a MDR-TB clusters in 2014; b MDR-TB clusters in 2015; c MDR-TB clusters in 2016; d MDR-TB clusters in 2017; e MDR-TB clusters in 2018; f MDR-TB clusters in 2019; g MDR-TB clusters in 2020

Article Snippet: One most likely cluster and two secondary clusters were shown in Fig. . Fig. 7 The detected spatial–temporal cluster map of MDR-TB cases in Guizhou (2014–2020) The most likely cluster was detected from January 2015 to December 2016 with 154 reported cases (LLR = 272.06), covering 1 county (Nanming) in Guiyang prefecture.

Techniques: Software

Journal: BMC Infectious Diseases

Article Title: Time trend prediction and spatial–temporal analysis of multidrug-resistant tuberculosis in Guizhou Province, China, during 2014–2020

doi: 10.1186/s12879-022-07499-9

Figure Lengend Snippet: The detected spatial–temporal cluster map of MDR-TB cases in Guizhou (2014–2020)

Article Snippet: One most likely cluster and two secondary clusters were shown in Fig. . Fig. 7 The detected spatial–temporal cluster map of MDR-TB cases in Guizhou (2014–2020) The most likely cluster was detected from January 2015 to December 2016 with 154 reported cases (LLR = 272.06), covering 1 county (Nanming) in Guiyang prefecture.

Techniques:

Journal: BMC Infectious Diseases

Article Title: Time trend prediction and spatial–temporal analysis of multidrug-resistant tuberculosis in Guizhou Province, China, during 2014–2020

doi: 10.1186/s12879-022-07499-9

Figure Lengend Snippet: Demographic characteristics of MDR-TB cases in Guizhou Province, 2014–2020 (n, %)

Article Snippet: One most likely cluster and two secondary clusters were shown in Fig. . Fig. 7 The detected spatial–temporal cluster map of MDR-TB cases in Guizhou (2014–2020) The most likely cluster was detected from January 2015 to December 2016 with 154 reported cases (LLR = 272.06), covering 1 county (Nanming) in Guiyang prefecture.

Techniques:

Journal: BMC Infectious Diseases

Article Title: Time trend prediction and spatial–temporal analysis of multidrug-resistant tuberculosis in Guizhou Province, China, during 2014–2020

doi: 10.1186/s12879-022-07499-9

Figure Lengend Snippet: The geographical distribution of MDR-TB cases in Guizhou Province, 2014–2020

Article Snippet: One most likely cluster and two secondary clusters were shown in Fig. . Fig. 7 The detected spatial–temporal cluster map of MDR-TB cases in Guizhou (2014–2020) The most likely cluster was detected from January 2015 to December 2016 with 154 reported cases (LLR = 272.06), covering 1 county (Nanming) in Guiyang prefecture.

Techniques:

Journal: BMC Infectious Diseases

Article Title: Time trend prediction and spatial–temporal analysis of multidrug-resistant tuberculosis in Guizhou Province, China, during 2014–2020

doi: 10.1186/s12879-022-07499-9

Figure Lengend Snippet: Spatial − temporal scan of MDR-TB in Guizhou from 2014 to 2020

Article Snippet: One most likely cluster and two secondary clusters were shown in Fig. . Fig. 7 The detected spatial–temporal cluster map of MDR-TB cases in Guizhou (2014–2020) The most likely cluster was detected from January 2015 to December 2016 with 154 reported cases (LLR = 272.06), covering 1 county (Nanming) in Guiyang prefecture.

Techniques:

Journal: BMC Infectious Diseases

Article Title: Time trend prediction and spatial–temporal analysis of multidrug-resistant tuberculosis in Guizhou Province, China, during 2014–2020

doi: 10.1186/s12879-022-07499-9

Figure Lengend Snippet: The geographical distribution of MDR-TB cases in Guizhou Province, 2014–2020

Article Snippet: The descriptive analysis gave a rough impression that 4 prefectures (Bijie, Guiyang, Liupanshui, Zunyi) had higher MDR-TB burden than other prefectures.

Techniques:

Journal: Health Economics Review

Article Title: Analysis of multi drug resistant tuberculosis (MDR-TB) financial protection policy: MDR-TB health insurance schemes, in Chhattisgarh state, India

doi: 10.1186/s13561-018-0187-5

Figure Lengend Snippet: Universal Health Insurance Scheme (UHIS) as managed by RSBY and MSBY (Developed from Cotlear et al. , 2015)

Article Snippet: Primary claims data on the uptake of ‘RSBY and MSBY MDR-TB’ packages under the routine national health insurance programme setting were collected from the server, accessible at the RSBY and MSBY State Nodal Agency of Directorate of Health Services, Raipur, from January 2013 to December 2015.

Techniques:

Journal: Health Economics Review

Article Title: Analysis of multi drug resistant tuberculosis (MDR-TB) financial protection policy: MDR-TB health insurance schemes, in Chhattisgarh state, India

doi: 10.1186/s13561-018-0187-5

Figure Lengend Snippet: RSBY and MSBY, a business model, an organization as a nexus of contracts/ institutions (Developed from Kutzin J. Health financing for universal coverage and health system performance: concepts and implications for policy, Bulletin of World Health Organization, 2013;91(8): 602–11; and concept of organization as a nexus of contracts by Bruno Messen, Institute of Tropical Medicine, Antwerp. 2016)

Article Snippet: Primary claims data on the uptake of ‘RSBY and MSBY MDR-TB’ packages under the routine national health insurance programme setting were collected from the server, accessible at the RSBY and MSBY State Nodal Agency of Directorate of Health Services, Raipur, from January 2013 to December 2015.

Techniques:

Journal: Health Economics Review

Article Title: Analysis of multi drug resistant tuberculosis (MDR-TB) financial protection policy: MDR-TB health insurance schemes, in Chhattisgarh state, India

doi: 10.1186/s13561-018-0187-5

Figure Lengend Snippet: Key characteristics of the beneficiaries of all MDR-TB Packages (2013–2015)

Article Snippet: Primary claims data on the uptake of ‘RSBY and MSBY MDR-TB’ packages under the routine national health insurance programme setting were collected from the server, accessible at the RSBY and MSBY State Nodal Agency of Directorate of Health Services, Raipur, from January 2013 to December 2015.

Techniques:

Journal: Health Economics Review

Article Title: Analysis of multi drug resistant tuberculosis (MDR-TB) financial protection policy: MDR-TB health insurance schemes, in Chhattisgarh state, India

doi: 10.1186/s13561-018-0187-5

Figure Lengend Snippet: Pooled (RSBY and MSBY) MDR-TB hospital stay package utilization in the public and private sector from 2013 to 2015

Article Snippet: Primary claims data on the uptake of ‘RSBY and MSBY MDR-TB’ packages under the routine national health insurance programme setting were collected from the server, accessible at the RSBY and MSBY State Nodal Agency of Directorate of Health Services, Raipur, from January 2013 to December 2015.

Techniques:

Journal: Health Economics Review

Article Title: Analysis of multi drug resistant tuberculosis (MDR-TB) financial protection policy: MDR-TB health insurance schemes, in Chhattisgarh state, India

doi: 10.1186/s13561-018-0187-5

Figure Lengend Snippet: Pooled (RSBY and MSBY) MDR-TB follow-up package utilization in the public and private sector from 2013 to 2015

Article Snippet: Primary claims data on the uptake of ‘RSBY and MSBY MDR-TB’ packages under the routine national health insurance programme setting were collected from the server, accessible at the RSBY and MSBY State Nodal Agency of Directorate of Health Services, Raipur, from January 2013 to December 2015.

Techniques:

Journal: Health Economics Review

Article Title: Analysis of multi drug resistant tuberculosis (MDR-TB) financial protection policy: MDR-TB health insurance schemes, in Chhattisgarh state, India

doi: 10.1186/s13561-018-0187-5

Figure Lengend Snippet: Disaggregated pooled (RSBY and MSBY) data on claims utilization of MDR-TB pre-treatment evaluation package by poor in the public sector from 2013 to 2015

Article Snippet: Primary claims data on the uptake of ‘RSBY and MSBY MDR-TB’ packages under the routine national health insurance programme setting were collected from the server, accessible at the RSBY and MSBY State Nodal Agency of Directorate of Health Services, Raipur, from January 2013 to December 2015.

Techniques:

Journal: Health Economics Review

Article Title: Analysis of multi drug resistant tuberculosis (MDR-TB) financial protection policy: MDR-TB health insurance schemes, in Chhattisgarh state, India

doi: 10.1186/s13561-018-0187-5

Figure Lengend Snippet: Disaggregated pooled (RSBY and MSBY) data on claims utilization of MDR-TB pre-treatment evaluation package by non-poor in the private sector from 2013 to 2015

Article Snippet: Primary claims data on the uptake of ‘RSBY and MSBY MDR-TB’ packages under the routine national health insurance programme setting were collected from the server, accessible at the RSBY and MSBY State Nodal Agency of Directorate of Health Services, Raipur, from January 2013 to December 2015.

Techniques: