Determinants of catastrophic costs among households affected by multi-drug resistant tuberculosis in Ho Chi Minh City, Viet Nam: a prospective cohort study

Background: Globally, most people with multidrug-resistant tuberculosis (MDR-TB) and their households experience catastrophic costs of illness, diagnosis, and care. However, the factors associated with experiencing catastrophic costs are poorly understood. This study aimed to identify risk factors associated with catastrophic costs incurrence among MDR-TB-affected households in Ho Chi Minh City (HCMC), Viet Nam. Methods: Between October 2020 and April 2022, data were collected using a locally-adapted, longitudinal WHO TB Patient Cost Survey in ten districts of HCMC. Ninety-four people with MDR-TB being treated with a nine-month TB regimen were surveyed at three time points: after two weeks of treatment initiation, completion of the intensive phase and the end of the treatment (approximately five and 10 months post-treatment initiation respectively). The catastrophic costs threshold was defined as total TB-related costs exceeding 20% of annual pre-TB household income. Logistic regression was used to identify variables associated with experiencing catastrophic costs. A sensitivity analysis examined the prevalence of catastrophic costs using alternative thresholds and cost estimation approaches. Results: Most participants (81/93 [87%]) experienced catastrophic costs despite the majority 86/93 (93%) receiving economic support through existing social protection schemes. Among participant households experiencing and not experiencing catastrophic costs, median household income was similar before MDR-TB treatment. However, by the end of MDR-TB treatment, median household income was lower (258 [IQR: 0–516] USD vs. 656 [IQR: 462–989] USD; p = 0.003), and median income loss was higher (2838 [IQR: 1548–5418] USD vs. 301 [IQR: 0–824] USD; p < 0.001) amongst the participant households who experienced catastrophic costs. Being the household’s primary income earner before MDR-TB treatment (aOR = 11.2 [95% CI: 1.6–80.5]), having a lower educational level (aOR = 22.3 [95% CI: 1.5–344.1]) and becoming unemployed at the beginning of MDR-TB treatment (aOR = 35.6 [95% CI: 2.7–470.3]) were associated with experiencing catastrophic costs. Conclusion: Despite good social protection coverage, most people with MDR-TB in HCMC experienced catastrophic costs. Incurrence of catastrophic costs was independently associated with being the household’s primary income earner or being unemployed. Revision and expansion of strategies to mitigate TB-related catastrophic costs, in particular avoiding unemployment and income loss, are urgently required

Application of Sentinel-1 data in mapping land-use and land cover in a complex seasonal landscape: a case study in coastal area of Vietnamese Mekong Delta

The advent of Sentinel-1 SAR data with high temporal and medium spatial resolutions along with its being unaffected by presence of cloud provided opportunities for using remote sensing in mapping LULCs with high temporal detail. The objective of this study is to explore the possibility of applying Sentinel-1 data together with OBIA and machine learning in classifying LULC in a complex agricultural landscape in the coastal area of Vietnamese Mekong Delta (VMD). Three approaches including Sentinel-1 alone, integrative Sentinel-1 and Sentinel-2 and lastly, only Sentinel-2 were deployed to examine chance of improvement of classification accuracy metrics on using Sentinel-1 data. The result showed that SAR data could capture seasonal patterns of different LULC classes. Also, supplementing Sentinel-1 can improve classification overall accuracy especially on integrating with optical data. However, Sentinel-1-alone approach performed poorly in most of LULC cases and bias of optical data can compromise classification accuracy of integrative approach

Identification of Vietnamese Flea Species and Their Associated Microorganisms Using Morphological, Molecular, and Protein Profiling

International audienceFleas are obligatory blood-sucking ectoparasites of medical and veterinary importance. The identification of fleas and associated flea-borne microorganisms, therefore, plays an important role in controlling and managing these vectors. Recently, Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) has been reported as an innovative and effective approach to the identification of arthropods, including fleas. This study aims to use this technology to identify ethanol-preserved fleas collected in Vietnam and to use molecular biology to search for microorganisms associated with these fleas. A total of 502 fleas were collected from wild and domestic animals in four provinces in Vietnam. Morphological identification led to the recognition of five flea species, namely Xenopsylla cheopis, Xenopsylla astia, Pulex irritans, Ctenocephalides canis, and Ctenocephalides felis. The cephalothoraxes of 300 individual, randomly selected fleas were tested using MALDI-TOF MS and molecular analysis for the identification and detection of microorganisms. A total of 257/300 (85.7%) of the obtained spectra from the cephalothoraxes of each species were of good enough quality to be used for our analyses. Our laboratory MALDI-TOF MS reference database was upgraded with spectra achieved from five randomly selected fleas for every species of Ctenocephalides canis and Ctenocephalides felis. The remaining spectra were then queried against the upgraded MALDI-TOF MS database, which showed 100% correspondence between morphology and MALDI-TOF MS identification for two flea species (Ctenocephalides canis and Ctenocephalides felis). The MS spectra of the remaining species (three P. irritans, five X. astia, and two X. cheopis) were visually generated low-intensity MS profiles with high background noise that could not be used to update our database. Bartonella and Wolbachia spp. were detected in 300 fleas from Vietnam using PCR and sequencing with primers derived from the gltA gene for Bartonella and the 16S rRNA gene for Wolbachia, including 3 Bartonella clarridgeiae (1%), 3 Bartonella rochalimae (1%), 1 Bartonella coopersplainsensis (0.3%), and 174 Wolbachia spp. endosymbionts (58%)

Morphological, molecular and MALDI-TOF MS identification of ticks and tick-associated pathogens in Vietnam

International audienceMatrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been reported as a promising and reliable tool for arthropod identification, including the identification of alcohol-preserved ticks based on extracted leg protein spectra. In this study, the legs of 361 ticks collected in Vietnam, including 251 Rhiphicephalus sanguineus s.l, 99 Rhipicephalus ( Boophilus ) microplus , two Amblyomma varanensis , seven Dermacentor auratus , one Dermacentor compactus and one Amblyomma sp. were submitted for MALDI-TOF MS analyses. Spectral analysis showed intra-species reproducibility and inter-species specificity and the spectra of 329 (91%) specimens were of excellent quality. The blind test of 310 spectra remaining after updating the database with 19 spectra revealed that all were correctly identified with log score values (LSV) ranging from 1.7 to 2.396 with a mean of 1.982 ± 0.142 and a median of 1.971. The DNA of several microorganisms including Anaplasma platys , Anaplasma phagocytophilum , Anaplasma marginale , Ehrlichia rustica , Babesia vogeli , Theileria sinensis , and Theileria orientalis were detected in 25 ticks. Co-infection by A . phagocytophilum and T . sinensis was found in one Rh . ( B ) microplus

Rapid method for yearly LULC classification using Random Forest and incorporating time-series NDVI and topography: a case study of Thanh Hoa province, Vietnam

Land-use and land-cover (LULC) mapping in the complex area is a challenging task due to the mixed vegetation patterns, and rough mountains with fast-flowing rivers. In Vietnam, LULC update is not frequently. In this study, we applied a supervised machine learning (Random forest—RF) approach to mapping LULC in Thanh Hoa province, Vietnam from 2011 to 2015 utilizing multi-temporal Normalized Difference Vegetation Index (NDVI) data from MODIS, combined with topographic features. Random forest classification (RFC) reached a total prediction accuracy of 91% and Kappa coefficient (K) of 0.89 across eight LULCs. Besides, the results showed that the features extracted from time-series NDVI comprising the mean of yearly NDVI, the sum of NDVI, and the topography were the important variables controlling the LULC classification. For similar studies on the distribution of LULC, the method proposed in this study could be helpful

Study on the Biological Effects of Oligochitosan Fractions, Prepared by Synergistic Degradation Method, on Capsicum

Chitosan with an initial molecular weight (Mw) of approximately 193 kDa was degraded into about 11.4 and 14.8 kDa by γ-ray irradiation of the solution containing 5% chitosan in 0.2 M acetic acid at 75 kGy and the solution of 5% chitosan in 0.2 M acetic acid supplemented with 1% H2O2 at 10 kGy, respectively. The synergistic degraded chitosan sample with Mw ~14.8 kDa was separated into 5 fractions by using ultrafiltration membranes. The analysis results from UV, FTIR, and NMR spectra indicated that the combined treatment of low irradiation dose and low H2O2 concentration did not cause any change in the molecular structure of degraded chitosan fractions. Separated chitosan fractions with Mw > 1 kDa inhibited the growth of Colletotrichum capsici in vitro. While all separated chitosan fractions remarkably enhanced fresh biomass (11–56%) and chlorophyll content (20–92%) of capsicum seedlings. In the field test, the treatment with oligochitosan fractions with Mw in a range of 1–3 kDa (F2) to 3–10 kDa (F3) gained 9.0–11.4% of the fruit yield and reduced 64.8–67.2% of the rate of anthracnose disease outbreak fruits caused by C. capsici. Thus, the F2 and F3 fractions in degraded chitosan product are the key fractions for the enhancement of both the growth promotion effect and defense respond activity against the infection of pathogenic Colletotrichum fungi causing anthracnose disease in capsicum

A new species of Limnonectes (Amphibia: Anura: Dicroglossidae) from Vietnam

Pham, Cuong The, Do, Dang Trong, Le, Minh Duc, Ngo, Hanh Thi, Nguyen, Luan Thanh, Ziegler, Thomas, Nguyen, Truong Quang (2020): A new species of Limnonectes (Amphibia: Anura: Dicroglossidae) from Vietnam. Zootaxa 4894 (3): 387-402, DOI: https://doi.org/10.11646/zootaxa.4894.3.

Comparative performance evaluation of QIAreach QuantiFERON-TB and tuberculin skin test for diagnosis of tuberculosis infection in Viet Nam

Abstract Current WHO-recommended diagnostic tools for tuberculosis infection (TBI) have well-known limitations and viable alternatives are urgently needed. We compared the diagnostic performance and accuracy of the novel QIAreach QuantiFERON-TB assay (QIAreach; index) to the QuantiFERON-TB Gold Plus assay (QFT-Plus; reference). The sample included 261 adults (≥ 18 years) recruited at community-based TB case finding events. Of these, 226 underwent Tuberculin Skin Tests and 200 returned for interpretation (TST; comparator). QIAreach processing and TST reading were completed at lower-level healthcare facilities. We conducted matched-pair comparisons for QIAreach and TST with QFT-Plus, calculated sensitivity, specificity and area under a receiver-operating characteristic curve (AUC), and analyzed concordant-/discordant-pair interferon-gamma (IFN-γ) levels. QIAreach sensitivity and specificity were 98.5% and 72.3%, respectively, for an AUC of 0.85. TST sensitivity (53.2%) at a 5 mm induration threshold was significantly below QIAreach, while specificity (82.4%) was statistically equivalent. The corrected mean IFN-γ level of 0.08 IU/ml and corresponding empirical threshold (0.05) of false-positive QIAreach results were significantly lower than the manufacturer-recommended QFT-Plus threshold (≥ 0.35 IU/ml). Despite QIAreach’s higher sensitivity at equivalent specificity to TST, the high number of false positive results and low specificity limit its utility and highlight the continued need to expand the diagnostic toolkit for TBI

Optimizing community screening for tuberculosis: Spatial analysis of localized case finding from door-to-door screening for TB in an urban district of Ho Chi Minh City, Viet Nam.

BACKGROUND:Tuberculosis (TB) is the deadliest infectious disease globally. Current case finding approaches may miss many people with TB or detect them too late. DATA AND METHODS:This study was a retrospective, spatial analysis of routine TB surveillance and cadastral data in Go Vap district, Ho Chi Minh City. We geocoded TB notifications from 2011 to 2015 and calculated theoretical yields of simulated door-to-door screening in three concentric catchment areas (50m, 100m, 200m) and three notification window scenarios (one, two and four quarters) for each index case. We calculated average yields, compared them to published reference values and fit a GEE (Generalized Estimating Equation) linear regression model onto the data. RESULTS:The sample included 3,046 TB patients. Adjusted theoretical yields in 50m, 100m and 200m catchment areas were 0.32% (95%CI: 0.27,0.37), 0.21% (95%CI: 0.14,0.29) and 0.17% (95%CI: 0.09,0.25), respectively, in the baseline notification window scenario. Theoretical yields in the 50m-catchment area for all notification window scenarios were significantly higher than a reference yield from literature. Yield was positively associated with treatment failure index cases (beta = 0.12, p = 0.001) and short-term inter-province migrants (beta = 0.06, p = 0.022), while greater distance to the DTU (beta = -0.02, p<0.001) was associated with lower yield. CONCLUSIONS:This study is an example of inter-departmental collaboration and application of repurposed cadastral data to progress towards the end TB objectives. The results from Go Vap showed that the use of spatial analysis may be able to identify areas where targeted active case finding in Vietnam can help improve TB case detection