Melioidosis in Patients with COVID-19 Exposed to Contaminated Tap Water, Thailand, 2021.

In September 2021, a total of 25 patients diagnosed with COVID-19 developed acute melioidosis after (median 7 days) admission to a COVID-19 field hospital in Thailand. Eight nonpotable tap water samples and 6 soil samples were culture-positive for Burkholderia pseudomallei. Genomic analysis suggested contaminated tap water as the likely cause of illness.

Collective activities of the Thai Coordinating Unit for One Health (CUOH): Past activities and future directions.

In Thailand, One Health concepts have been implemented among government agencies, academic institutions, intergovernment, and civil society organizations. The Thai Coordinating Unit for One Health (CUOH) was established as a collaborating body for One Health-related activities in the country in 2014. To better understand what activities CUOH has completed thus far and to assess future activities, we conducted a network analysis to identify and visualize linkages between organizations and activities from 2015 to 2021. Activities were divided into four categories: organizing meetings, developing products, providing funds, and managing resources. Most of the 114 CUOH-managed meeting participants were representatives from 72 government and 20 academic institutions. The Thai Ministry of Public Health's Department of Disease Control participated in 148 meetings, the highest attendance among all organizations working with CUOH. The first CUOH guideline or manual was published in 2020, and 11 were published in 2021. In funding management, the CUOH worked with 25 organizations to carry out 71 projects from 2015 to 2021. Additionally, the CUOH played an important role in allocating COVID-19 vaccines during the COVID-19 pandemic. The CUOH has connected organizations working in different health sectors to collaborate jointly through meetings and projects that use a One Health approach, which can holistically improve health management in Thailand. Diverse funding sources are needed to ensure the sustainability of the unit in the future.

Automating the Generation of Notifiable Bacterial Disease Reports: Proof-of-Concept Study and Implementation in Six Hospitals in Thailand.

Information on notifiable bacterial diseases (NBD) in low- and middle-income countries (LMICs) is frequently incomplete. We developed the AutoMated tool for the Antimicrobial resistance Surveillance System plus (AMASSplus), which can support hospitals to analyze their microbiology and hospital data files automatically (in CSV or Excel format) and promptly generate antimicrobial resistance surveillance and NBD reports (in PDF and CSV formats). The NBD reports included the total number of cases and deaths after Brucella spp., Burkholderia pseudomallei, Corynebacterium diphtheriae, Neisseria gonorrhoeae, Neisseria meningitidis, nontyphoidal Salmonella spp., Salmonella enterica serovar Paratyphi, Salmonella enterica serovar Typhi, Shigella spp., Streptococcus suis, and Vibrio spp. infections. We tested the tool in six hospitals in Thailand in 2022. The total number of deaths identified by the AMASSplus was higher than those reported to the national notifiable disease surveillance system (NNDSS); particularly for B. pseudomallei infection (134 versus 2 deaths). This tool could support the NNDSS in LMICs.

Frequency and mortality rate following antimicrobial-resistant bloodstream infections in tertiary-care hospitals compared with secondary-care hospitals.

There are few studies comparing proportion, frequency, mortality and mortality rate following antimicrobial-resistant (AMR) infections between tertiary-care hospitals (TCHs) and secondary-care hospitals (SCHs) in low and middle-income countries (LMICs) to inform intervention strategies. The aim of this study is to demonstrate the utility of an offline tool to generate AMR reports and data for a secondary data analysis. We conducted a secondary-data analysis on a retrospective, multicentre data of hospitalised patients in Thailand. Routinely collected microbiology and hospital admission data of 2012 to 2015, from 15 TCHs and 34 SCHs were analysed using the AMASS v2.0 (www.amass.website). We then compared the burden of AMR bloodstream infections (BSI) between those TCHs and SCHs. Of 19,665 patients with AMR BSI caused by pathogens under evaluation, 10,858 (55.2%) and 8,807 (44.8%) were classified as community-origin and hospital-origin BSI, respectively. The burden of AMR BSI was considerably different between TCHs and SCHs, particularly of hospital-origin AMR BSI. The frequencies of hospital-origin AMR BSI per 100,000 patient-days at risk in TCHs were about twice that in SCHs for most pathogens under evaluation (for carbapenem-resistant Acinetobacter baumannii [CRAB]: 18.6 vs. 7.0, incidence rate ratio 2.77; 95%CI 1.72-4.43, p<0.001; for carbapenem-resistant Pseudomonas aeruginosa [CRPA]: 3.8 vs. 2.0, p = 0.0073; third-generation cephalosporin resistant Escherichia coli [3GCREC]: 12.1 vs. 7.0, p<0.001; third-generation cephalosporin resistant Klebsiella pneumoniae [3GCRKP]: 12.2 vs. 5.4, p<0.001; carbapenem-resistant K. pneumoniae [CRKP]: 1.6 vs. 0.7, p = 0.045; and methicillin-resistant Staphylococcus aureus [MRSA]: 5.1 vs. 2.5, p = 0.0091). All-cause in-hospital mortality (%) following hospital-origin AMR BSI was not significantly different between TCHs and SCHs (all p>0.20). Due to the higher frequencies, all-cause in-hospital mortality rates following hospital-origin AMR BSI per 100,000 patient-days at risk were considerably higher in TCHs for most pathogens (for CRAB: 10.2 vs. 3.6,mortality rate ratio 2.77; 95%CI 1.71 to 4.48, p<0.001; CRPA: 1.6 vs. 0.8; p = 0.020; 3GCREC: 4.0 vs. 2.4, p = 0.009; 3GCRKP, 4.0 vs. 1.8, p<0.001; CRKP: 0.8 vs. 0.3, p = 0.042; and MRSA: 2.3 vs. 1.1, p = 0.023). In conclusion, the burden of AMR infections in some LMICs might differ by hospital type and size. In those countries, activities and resources for antimicrobial stewardship and infection control programs might need to be tailored based on hospital setting. The frequency and in-hospital mortality rate of hospital-origin AMR BSI are important indicators and should be routinely measured to monitor the burden of AMR in every hospital with microbiology laboratories in LMICs.

SARS-CoV-2 Variants Detection Strategies in Wastewater Samples Collected in the Bangkok Metropolitan Region.

Wastewater surveillance is considered a promising approach for COVID-19 surveillance in communities. In this study, we collected wastewater samples between November 2020 and February 2022 from twenty-three sites in the Bangkok Metropolitan Region to detect the presence of SARS-CoV-2 and its variants for comparison to standard clinical sampling. A total of 215 wastewater samples were collected and tested for SARS-CoV-2 RNA by real-time PCR with three targeted genes (N, E, and ORF1ab); 102 samples were positive (42.5%). The SARS-CoV-2 variants were determined by a multiplex PCR MassARRAY assay to distinguish four SARS-CoV-2 variants, including Alpha, Beta, Delta, and Omicron. Multiple variants of Alpha-Delta and Delta-Omicron were detected in the wastewater samples in July 2021 and January 2022, respectively. These wastewater variant results mirrored the country data from clinical specimens deposited in GISAID. Our results demonstrated that wastewater surveillance using multiple signature mutation sites for SARS-CoV-2 variant detection is an appropriate strategy to monitor the presence of SARS-CoV-2 variants in the community at a low cost and with rapid turn-around time. However, it is essential to note that sequencing surveillance of wastewater samples should be considered complementary to whole genome sequencing of clinical samples to detect novel variants.