Use of network analysis multidrug-resistant tuberculosis contact investigation in Kanchanaburi, Thailand

A network analysis of the local pig supply chain in a repeated outbreak area of human streptococcosis in Thailand

AIMS

The present study employed a network analysis approach to scrutinize a pig supply chain in a repeated outbreak province for human streptococcosis in Thailand and identified important actors that should be focused on for tailoring appropriate interventions.

METHODS AND RESULTS

Nakhon Sawan province was chosen as the study site as the cases of human streptococcosis have been consecutively reported since 2014, with the number of cases ranging from 21 to 63. A questionnaire survey was used to collect data from actors along the pig supply chain, including pig farms, slaughterhouses, pork sellers, restaurants and customers. A one-mode-directed network was then constructed. Degree and betweenness centrality values were measured. We found that the supply chain of pork products comprised 314 nodes and 296 directed ties. A retailer got the highest overall degree, out-degree and betweenness centrality values at 35, 34, and 65.3, respectively. For in-degree centrality, the highest was identified in a customer at 9. Interestingly, this customer bought pork products from nine different mobile groceries.

CONCLUSIONS

Both public health and veterinary authorities should extend their surveillance activities to cover all actors in the supply chain to strengthen overall disease prevention and control for streptococcosis.

Clusters of Drug-Resistant Mycobacterium tuberculosis Detected by Whole-Genome Sequence Analysis of Nationwide Sample, Thailand, 2014-2017

Multidrug-resistant tuberculosis (MDR TB), pre-extensively drug-resistant tuberculosis (pre-XDR TB), and extensively drug-resistant tuberculosis (XDR TB) complicate disease control. We analyzed whole-genome sequence data for 579 phenotypically drug-resistant M. tuberculosis isolates (28% of available MDR/pre-XDR and all culturable XDR TB isolates collected in Thailand during 2014–2017). Most isolates were from lineage 2 (n = 482; 83.2%). Cluster analysis revealed that 281/579 isolates (48.5%) formed 89 clusters, including 205 MDR TB, 46 pre-XDR TB, 19 XDR TB, and 11 poly–drug-resistant TB isolates based on genotypic drug resistance. Members of most clusters had the same subset of drug resistance-associated mutations, supporting potential primary resistance in MDR TB (n = 176/205; 85.9%), pre-XDR TB (n = 29/46; 63.0%), and XDR TB (n = 14/19; 73.7%). Thirteen major clades were significantly associated with geography (p<0.001). Clusters of clonal origin contribute greatly to the high prevalence of drug-resistant TB in Thailand.

Genomic evidence supporting the clonal expansion of extensively drug-resistant tuberculosis bacteria belonging to a rare protoBeijing genotype

Tuberculosis disease (TB), caused by Mycobacterium tuberculosis, is a major public health issue in Thailand. The high prevalence of modern Beijing (Lineage 2.2.1) strains has been associated with multi- and extensively drug-resistant infections (MDR-, XDR-TB), complicating disease control. The impact of rarer proto-Beijing (L2.1) strains is less clear. In our study of thirty-seven L2.1 clinical isolates spanning thirteen years, we found a high prevalence of XDR-TB cases (32.4%). With ≤ 12 pairwise SNP distances, 43.2% of L2.1 patients belong to MDR-TB or XDR-TB transmission clusters suggesting a high level of clonal expansion across four Thai provinces. All XDR-TB (100%) were likely due to transmission rather than inadequate treatment. We found a 47 mutation signature and a partial deletion of the fadD14 gene in the circulating XDR-TB cluster, which can be used for surveillance of this rare and resilient M. tuberculosis strain-type that is causing increasing health burden. We also detected three novel deletion positions, a deletion of 1285 bp within desA3 (Rv3230c), large deletions in the plcB, plcA, and ppe38 gene which may play a role in the virulence, pathogenesis or evolution of the L2.1 strain-type.

Molecular Epidemiological Information System to Support Management of Multidrug-Resistant Tuberculosis in Thailand: Abstract

OBJECTIVE

To support the End TB strategy with an informatics system that integrates genomic data and the geographic information system (GIS) of Mycobacterium tuberculosis (MTB) clinical isolates. We aim to develop a system prototype for implementing genomic data to support multiple drug-resistant tuberculosis (MDR-TB) control.

METHODS

A 12-step data value chain was applied to describe the information flow within the system. A prototyping-oriented system development method was utilized to test the feasibility of certain technical aspects of a system, and as specification tools to determine user requirements. A simulated dataset was entered as input for initial system testing.

RESULTS

System prototype, namely Integrated MOL Outbreak detection and Joint investigation (iMoji), was established. The data entry modules consisted of (1) patient registration, (2) sample registration, (3) laboratory data entry and data analysis, and (4) verification and approval of the analyzed data. The initial system test demonstrated connectivity among modules without error. The system was able to report integrated genomic data and GIS information of MDR-TB for clustering analysis.

CONCLUSION

iMoji provides an interactive model for determining molecular epidemiological links of MDR-TB and corresponding spatial information to guide public health interventions for tuberculosis control.