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.

Local and timely antimicrobial resistance data for local and national actions: the early implementation of an automated tool for data analysis at local hospital level in Thailand.

Background: In low- and middle-income countries (LMICs), hospitals can rarely utilize their own antimicrobial resistance (AMR) data in a timely manner. Objectives: To evaluate the utility of local AMR data generated by an automated tool in the real-world setting. Methods: From 16 December 2022 to 10 January 2023, on behalf of the Health Administration Division, Ministry of Public Health (MoPH) Thailand, we trained 26 public tertiary-care and secondary-care hospitals to utilize the AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) with their own microbiology and hospital admission data files via two online meetings, one face-to-face meeting and online support. All meetings were recorded on video, and feedback was analysed. Results: Twenty-five hospitals successfully generated and shared the AMR reports with the MoPH by 28 February 2023. In 2022, the median frequency of hospital-origin bloodstream infections (BSIs) caused by carbapenem-resistant Escherichia coli (CREC) was 129 (range 0-1204), by carbapenem-resistant Klebsiella pneumoniae (CRKP) was 1306 (range 0-5432) and by carbapenem-resistant Acinetobacter baumannii (CRAB) was 4472 (range 1460-11 968) per 100 000 patients tested for hospital-origin BSI. The median number of all-cause in-hospital deaths with hospital-origin AMR BSI caused by CREC was 1 (range 0-18), by CRKP was 10 (range 0-77) and by CRAB was 56 (range 7-148). Participating hospitals found that the data obtained could be used to support their antimicrobial stewardship and infection prevention control programmes. Conclusions: Local and timely AMR data are crucial for local and national actions. MoPH Thailand is inviting all 127 public tertiary-care and secondary-care hospitals to utilize the AMASS. Using any appropriate analytical software or tools, all hospitals in LMICs that have electronic data records should analyse and utilize their data for immediate actions.

Clinical Epidemiology of 7126 Melioidosis Patients in Thailand and the Implications for a National Notifiable Diseases Surveillance System.

BACKGROUND: National notifiable diseases surveillance system (NNDSS) data in developing countries are usually incomplete, yet the total number of fatal cases reported is commonly used in national priority-setting. Melioidosis, an infectious disease caused by Burkholderia pseudomallei, is largely underrecognized by policy-makers due to the underreporting of fatal cases via the NNDSS. METHODS: Collaborating with the Epidemiology Division (ED), Ministry of Public Health (MoPH), we conducted a retrospective study to determine the incidence and mortality of melioidosis cases already identified by clinical microbiology laboratories nationwide. A case of melioidosis was defined as a patient with any clinical specimen culture positive for B. pseudomallei. Routinely available microbiology and hospital databases of secondary care and tertiary care hospitals, the national death registry, and NNDSS data were obtained for analysis. RESULTS: A total of 7126 culture-confirmed melioidosis patients were identified from 2012 to 2015 in 60 hospitals countrywide. The total number of cases diagnosed in Northeast, Central, South, East, North, and West Thailand were 5475, 536, 374, 364, 358, and 19 cases, respectively. The overall 30-day mortality was 39% (2805/7126). Only 126 (4%) deaths were reported to the NNDSS. Age, presentation with bacteremia and pneumonia, prevalence of diabetes, and 30-day mortality differed by geographical region (all P < .001). The ED at MoPH has agreed to include the findings of our study in the next annual report of the NNDSS. CONCLUSIONS: Melioidosis is an important cause of death in Thailand nationwide, and its clinical epidemiology may be different by region. In developing countries, NNDSS data can be supplemented by integrating information from readily available routine data sets.

Psychosocial and Behavioral Characteristics of High-Risk Men Who Have Sex with Men (MSM) of Unknown HIV Positive Serostatus in Bangkok, Thailand.

HIV prevalence remains high in men who have sex with men (MSM) in Bangkok. Even though resources for HIV testing and treatment are available for all, a large proportion of MSM still do not get HIV tested. We studied high risk MSM who are unaware of their HIV status to help maximize effectiveness of our resources. Convenience sampling was conducted among MSM who came for HIV testing at the Thai Red Cross Anonymous Clinic and two popular drop-in centers in Bangkok. Inclusion criteria were MSM aged >18 years, have not been tested positive for HIV, who reported ≥1 of the following in the previous 6 months: condomless sex with a male, being a sex worker, or having a sexual transmitted infection diagnosis. Audio-Computer-Assisted Self-Interview was used to assess psychosocial profile, sexual risks, and HIV testing patterns prior to being informed of their HIV positive status. Among 499 high-risk MSM enrolled, the median age was 24.8 years and 112 (22 %) tested HIV-positive. Among the HIV-positive participants, 92 % self-identified as gay (versus bisexual), 39 % attained a bachelors degree or higher, 65 % had monthly income 10,000-29,999 baht ($280-830 USD), 10 % had vaginal or anal sex with a woman in the past 12 months, 39 % had condomless receptive sex with men and 21 % went to Lat Phrao to find a sexual partner. Compared to HIV negative MSM, HIV-positive MSM had less HIV testing: 31 % had ever been tested for HIV, 12 % had been tested in the past 6 months; but were more likely to guess correctly their positive status (31 %). Regarding psychosocial variables among HIV-positive MSM, 7 % had regular methamphetamine use in the past 3 months, 10 % had >2 sources of discrimination, and 8 % had >2 sources of discrimination due to being MSM. In multivariable model, age<30 year old, self-identified as gay, had monthly income <50,000 baht ($1400 USD), had anal sex with men in past 12 months, had >2 sources of discrimination because of being MSM, did not get HIV test in past 6 months, and guess of positive HIV were significantly associated with HIV positive status. Young MSM with lower socioeconomic status (SES) should be prioritized for innovative approaches to promoting awareness and uptake of HIV testing. Societal stigmatization of MSM should be addressed as a potential barrier to uptake of voluntary HIV testing. Resilience factors among these marginalized MSM who still test frequently and remain HIV-negative despite residing in a context with community viral loads and discrimination should also be studied in order to curb the HIV epidemic in Bangkok.