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

Cherry Lim Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand;
Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom;

Search for other papers by Cherry Lim in
Current site
Google Scholar
PubMed
Close
,
Preeyarach Klaytong Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand;

Search for other papers by Preeyarach Klaytong in
Current site
Google Scholar
PubMed
Close
,
Viriya Hantrakun Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand;

Search for other papers by Viriya Hantrakun in
Current site
Google Scholar
PubMed
Close
,
Chalida Rangsiwutisak Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand;

Search for other papers by Chalida Rangsiwutisak in
Current site
Google Scholar
PubMed
Close
,
Chadaporn Phiancharoen Division of Communicable Diseases, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand;

Search for other papers by Chadaporn Phiancharoen in
Current site
Google Scholar
PubMed
Close
,
Ratanaporn Tangwangvivat Division of Communicable Diseases, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand;

Search for other papers by Ratanaporn Tangwangvivat in
Current site
Google Scholar
PubMed
Close
,
Somkid Kripattanapong Division of Epidemiology, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand;

Search for other papers by Somkid Kripattanapong in
Current site
Google Scholar
PubMed
Close
,
Charuttaporn Jitpeera Division of Epidemiology, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand;

Search for other papers by Charuttaporn Jitpeera in
Current site
Google Scholar
PubMed
Close
,
Wiratya Poldech Amnatcharoen Hospital, Amnatcharoen, Thailand;

Search for other papers by Wiratya Poldech in
Current site
Google Scholar
PubMed
Close
,
Punya Jiramahasan Kantharalak Hospital, Srisaket, Thailand;

Search for other papers by Punya Jiramahasan in
Current site
Google Scholar
PubMed
Close
,
Bangon Laosatiankit Srisaket Provincial Health Office, Srisaket, Thailand;

Search for other papers by Bangon Laosatiankit in
Current site
Google Scholar
PubMed
Close
,
Orawan Photivet Mukdahan Hospital, Mukdahan, Thailand;

Search for other papers by Orawan Photivet in
Current site
Google Scholar
PubMed
Close
,
Punchawee Sukbut Mukdahan Hospital, Mukdahan, Thailand;

Search for other papers by Punchawee Sukbut in
Current site
Google Scholar
PubMed
Close
,
Warintorn Thongsri Mukdahan Hospital, Mukdahan, Thailand;

Search for other papers by Warintorn Thongsri in
Current site
Google Scholar
PubMed
Close
,
Kailas Kosasaeng Nakhon Phanom Hospital, Nakhon Phanom, Thailand;

Search for other papers by Kailas Kosasaeng in
Current site
Google Scholar
PubMed
Close
,
Bongkoch Chiwehanyon Phatthalung Hospital, Phattalung, Thailand;

Search for other papers by Bongkoch Chiwehanyon in
Current site
Google Scholar
PubMed
Close
,
Nutjamee Leesahud Phatthalung Hospital, Phattalung, Thailand;

Search for other papers by Nutjamee Leesahud in
Current site
Google Scholar
PubMed
Close
,
Preecha Ritthong Phatthalung Hospital, Phattalung, Thailand;

Search for other papers by Preecha Ritthong in
Current site
Google Scholar
PubMed
Close
,
Wandee Linreung Phatthalung Hospital, Phattalung, Thailand;

Search for other papers by Wandee Linreung in
Current site
Google Scholar
PubMed
Close
,
Panatda Aramrueang Sunpasitthiprasong Hospital, Ubon Ratchathani, Thailand;

Search for other papers by Panatda Aramrueang in
Current site
Google Scholar
PubMed
Close
,
Wichan Bhunyakitikorn Division of Communicable Diseases, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand;

Search for other papers by Wichan Bhunyakitikorn in
Current site
Google Scholar
PubMed
Close
,
Sopon Iamsirithaworn Division of Epidemiology, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand;

Search for other papers by Sopon Iamsirithaworn in
Current site
Google Scholar
PubMed
Close
, and
Direk Limmathurotsakul Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand;
Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom;
Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand

Search for other papers by Direk Limmathurotsakul in
Current site
Google Scholar
PubMed
Close

ABSTRACT.

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.

The National Notifiable Disease Surveillance System (NNDSS) is established in most countries to control infections, detect outbreaks, and monitor the impact of interventions. The list of notifiable diseases may include a wide range of communicable and noncommunicable diseases such as anthrax, botulism, campylobacteriosis, and silicosis.1,2 The reporting methods vary across countries; some diseases require urgent notification within a few hours by phone, whereas others may be reported to defined systems within a certain time frame. For example, the Department of Disease control (DDC), Thailand, has the Director Critical Information Requirement (DCIR) criteria, which define the situations of notifiable diseases that must be notified within 2 hours.3 Many high-income countries have modernized the NNDSS and use automated and computerized data management system.4,5

The information of notifiable diseases reported to the NNDSS in low and middle-income countries (LMICs) is often incomplete. Most countries rely on manual (or semiautomated) reporting of cases by responsible officers in healthcare facilities.6 However, healthcare facilities frequently lack laboratory capacity to detect the notifiable diseases. Referral hospitals that can provide a definite diagnosis of a notifiable disease also lack the human resources to prepare, verify, and submit the data to the NNDSS. Priority diseases, such as COVID-19, could also reduce the data completeness of other notifiable diseases due to high levels of burnout.7

The incomplete information of notifiable diseases can have a negative impact on policymakers and stakeholders. For example, melioidosis,8 an infection cause by the Gram-negative bacteria Burkholderia pseudomallei, has been a notifiable disease in Thailand since 2002.9 The disease is highly prevalent and fatal in Thailand.10 However, only approximately 10 deaths from melioidosis are reported yearly to the NNDSS. This is mainly because referral hospitals do not report the cases and deaths of culture-confirmed melioidosis to the NNDSS.9,10 The Ministry of Public Health (MoPH) of Thailand advises against using the number of cases and deaths reported to the NNDSS to represent the disease burden. Nonetheless, policymakers and stakeholders often use those numbers to represent the burden of melioidosis in the country, which hinders the efforts to improve awareness, diagnosis, treatment, and prevention of melioidosis in Thailand.9

We recently developed the AutoMated tool for Antimicrobial resistance Surveillance System (AMASS), an offline application that can automatically analyze and generate standardized antimicrobial resistance (AMR) surveillance reports from routine microbiology and hospital data.11 We tested the application in seven hospitals in seven countries.11 The AMASS version 1.0 (called AMASSv1.0) was released on February 1, 2019.11 The aim of this study was to extend the AMASS to additionally analyze and generate notifiable bacterial disease (NBD) reports (called AMASSplus). The AMASSplus was released on March 25, 2021. In this study, we tested the AMASSplus in six referral hospitals with microbiology laboratories in Thailand. Among the six referral hospitals, only Sunpasitthiprasong Hospital participated in testing both AMASSv1.011 and AMASSplus (in this study) but using data from different years.

We based the AMASSplus on the AMASSv1.0,11 which is an open access, user-friendly, and highly compatible application with high data security. The AMASSplus was similarly built and included both R portable (version 3.4.3; R Project for Statistical Computing) and RStudio (version 1.1.423; RStudio, Inc., Vienna, Austria) within the downloadable package so that the application can used without the need to install R or any program before running the application. The AMASSplus also uses data dictionary files (in Excel format) to accommodate data (in either CSV or Excel) exported from different systems or programs used by microbiology laboratories and hospitals that may have different ways to name data variables and data values. The AMASSplus can also be run by double clicking on the application file without any further user input. In addition to AMASSv1.0,11 the AMASSplus additionally generated the Annex reporting NBDs caused by 11 pathogens including 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. We selected the NBDs based on their priority in Thailand and in collaboration with the DDC, MoPH, Thailand. The NBD cases were defined as having a clinical specimen culture positive for a pathogen. The AMASSplus deduplicated the laboratory data by reporting the total number of patients with a clinical specimen culture positive for a pathogen during the evaluation period, using the hospital number (i.e., the patient identifier) and specimen collection dates. For each clinical specimen type (e.g., blood, cerebrospinal fluid, urine), the AMASSplus also deduplicated and reported the total number of patients with each clinical specimen type culture positive for a pathogen during the evaluation period. Then AMASSplus merged the deduplicated laboratory data with the hospital admission data, using the hospital number (i.e., the patient identifier) present in both data files.11 Mortality was defined using the discharge summary (in the hospital admission data), which was regularly completed by the attending physicians and reported to the MoPH. If a patient was admitted with an NBD more than once during the evaluation period, the mortality outcome of the first admission was presented.

In 2022, we tested the AMASSplus in six referral hospitals in six provinces, including Amnatcharoen Hospital, Kantharalak Hospital, Mukdahan Hospital, Nakhon Phanom Hospital, Phatthalung Hospital, and Sunpasitthiprasong Hospital (Figure 1). The hospitals were selected based on agreement with the DDC. We requested that each hospital independently export their hospital admission file (from their hospital information systems) and microbiology data file (from their laboratory information systems) as either CSV or Excel format and ran the AMASSplus. We held at least one virtual or face-to-face meeting with each hospital and additional online support as needed. Common issues observed were inaccurate formatting of date variables in the Excel files and incomplete data dictionary files, resulting in inaccurate reports.11 Together, the study team and the participating hospitals validated the reports and log files carefully.11 The participating hospitals then addressed the issues (e.g., correcting date formats and completing the data dictionary files), and reran the AMASSplus until the generated reports and log files confirmed their completeness. Ethical permission for this study was obtained from the Institute for the Committee of the Faculty of Tropical Medicine, Mahidol University (TMEC 23-086).

Figure 1.
Figure 1.

Locations of the six participating hospitals, including (1) Amnatcharoen Hospital, (2) Kantharalak Hospital, (3) Mukdahan Hospital, (4) Nakhon Phanom Hospital, (5) Phatthalung Hospital, and (6) Sunpasitthiprasong Hospital.

Citation: The American Journal of Tropical Medicine and Hygiene 111, 1; 10.4269/ajtmh.23-0848

All six hospitals successfully generated and deposited their AMR plus NBD summary reports in an open-access platform.1217 The median bed number was 453 (range: 281–1,158). Mukdahan Hospital and Sunpasitthiprasong Hospital used data from 2020, whereas the other four hospitals used the data from 2021. Sunpasitthiprasong Hospital changed its laboratory information system in 2020 and thus generated two reports. All hospitals included in this study obtained both microbiology data and hospital admission data (which included discharge summaries), except Amnatcharoen Hospital, which obtained only microbiology data. Therefore, mortality data from Amnatcharoen Hospital were not available.

During the evaluation period (Table 1), the NBD with the highest number of cases was B. pseudomallei infection (n = 834 patients), followed by infections with nontyphoidal Salmonella spp. (n = 281), Vibrio spp. (n = 78), Streptococcus suis (n = 32), Neisseria gonorrhoeae (n = 7), Shigella spp. (n = 3), Brucella spp. (n = 2), and Corynebacterium diphtheriae (n = 1). The NBD with the highest number of deaths was B. pseudomallei infection (n = 134 deaths), followed by nontyphoidal Salmonella spp. (n = 17), Vibrio spp. (n = 5), S. suis (n = 4), and Shigella spp. (n = 1).

Table 1

Total number of cases and deaths after notifiable bacterial diseases in six hospitals in Thailand

Notifiable Bacterial Diseases Amnatcharoen Hospital Kantharalak Hospital Mukdahan Hospital Nakhon Phanom Hospital Phatthalung Hospital Sunpasitthiprasong Hospital
Total no. of cases*
Brucella spp. 0 0 1 0 0 1
Burkholderia pseudomallei 134 22 265 82 14 317
Corynebacterium diphtheriae 0 0 0 0 0 1
Neisseria gonorrhoeae 4 0 0 0 0 3
Neisseria meningitidis 0 0 0 0 0 0
 Nontyphoidal Salmonella spp. 34 14 85 7 74 67
Salmonella enterica serovar Paratyphi 0 0 0 0 0 0
Salmonella enterica serovar Typhi 0 0 0 0 0 0
Shigella spp. 2 0 0 0 1 0
Streptococcus suis 0 4 0 5 3 20
Vibrio spp. 9 0 45 2 5 17
Mortality (%)
Brucella spp. NA N/A 0% (0/1) N/A N/A 0% (0/1)
Burkholderia pseudomallei NA 5% (1/21) 14% (25/174) 32% (23/73) 18% (2/11) 29% (83/283)
Corynebacterium diphtheriae NA N/A N/A N/A N/A 0% (0/1)
Neisseria gonorrhoeae NA N/A N/A N/A N/A 0% (0/1)
Neisseria meningitidis NA N/A N/A N/A N/A N/A
 Nontyphoidal Salmonella spp. NA 8% (1/12) 6% (4/68) 20% (1/5) 11% (4/37) 12% (7/57)
Salmonella enterica serovar Paratyphi NA N/A N/A N/A N/A N/A
Salmonella enterica serovar Typhi NA N/A N/A N/A N/A N/A
Shigella spp. NA N/A N/A N/A 100% (1/1) N/A
Streptococcus suis NA 0% (0/3) N/A 0% (0/4) 100% (1/1) 2% (3/18)
Vibrio spp. NA N/A 2% (1/40) 50% (1/2) 100% (1/1) 1% (2/14)

NA = not available; N/A = not applicable.

AutoMated tool for the Antimicrobial resistance Surveillance System plus (AMASSplus) identified notifiable bacterial diseases cases with a clinical specimen culture positive for a pathogen during the evaluation period. Total number of cases identified by the AMASSplus included outpatient cases, inpatient cases and cases whose only clinical specimens were sent to the microbiology laboratories of the study hospitals.

Mortality was estimated among inpatient cases. Death was defined using the discharge summary regularly completed by the attending physicians and reported to the Ministry of Public Health. Amnatcharoen Hospital did not obtain hospital admission data file and used only microbiology data file. Therefore, mortality data was not available.

We compared total number of cases and deaths following culture-confirmed NBDs identified by the AMASSplus with the relevant NBDs reported to the NNDSS from the six provinces during the same period (Table 2).18 For melioidosis, gonorrhea, food poisoning, typhoid, and shigellosis, the total number of cases identified by the AMASSplus were lower than those reported to the NNDSS. This was because the NNDSS included reports of suspected, probable, and confirmed cases using a wide range of case definitions of each notifiable disease,19 whereas the AMASSplus only identified patients with culture positivity. The total number of cases with Brucella spp., C. diptheriae, and S. suis infections identified by the AMASSplus were higher than those reported to the NNDSS. For NBDs with fatality cases, the total number of deaths identified by the AMASSplus was higher than those reported to the NNDSS; particularly for B. pseudomallei infection (134 versus two deaths, Table 2).

Table 2

Total number of cases and deaths after culture-confirmed NBDs identified using the AMASSplus in six participating hospitals compared with total number of cases and deaths with relevant notifiable diseases reported to the NNDSS in six provinces during the same period

Notifiable Bacterial Diseases AMASSplus Relevant Notifiable Diseases in the NNDSS NNDSS
Total number of cases*
Brucella spp. 2 Brucellosis 1
Burkholderia pseudomallei 834 Melioidosis 953
Corynebacterium diphtheriae 1 Diphtheria 0
Neisseria gonorrhoeae 7 Gonorrhea 1,009
Neisseria meningitidis 0 Meningococcal meningitis 0
 Nontyphoidal Salmonella spp. and Vibrio spp. 359 Food poisoning and cholera 12,659
Salmonella enterica serovar Paratyphi and Typhi 0 Typhoid and paratyphoid 11
Shigella spp. 3 Shigellosis 63
Streptococcus suis 32 Streptococcus suis infection 5
Total number of deaths§
Brucella spp. 0 Brucellosis 0
Burkholderia pseudomallei 134 Melioidosis 2
Corynebacterium diphtheriae 0 Diphtheria 0
Neisseria gonorrhoeae 0 Gonorrhea 0
Neisseria meningitidis 0 Meningococcal meningitis 0
 Nontyphoidal Salmonella spp. and Vibrio spp. 22 Food poisoning and cholera 1
Salmonella enterica serovar Paratyphi and Typhi 0 Typhoid and paratyphoid 0
Shigella spp. 1 Shigellosis 0
Streptococcus suis 4 Streptococcus suis 2

AMASSplus = AutoMated tool for the Antimicrobial resistance Surveillance System plus; NBDs = notifiable bacterial diseases; NNDSS = national notifiable disease surveillance systems.

The AMASSplus identified culture-confirmed NBDs with a clinical specimen culture positive for a pathogen during the evaluation period, whereas the NNDSS included reports of suspected, probable, and confirmed cases using a wide range of case definitions of each notifiable disease.18,19

Cases with food poisoning (n = 12,659) and cholera (n = 0).

Case with typhoid (n = 11) and paratyphoid (n = 0).

Total number of deaths after relevant notifiable diseases in the NNDSS were from five provinces: Mukdahan, Nakhon Phanom, Phattalung, Srisaket, and Ubon Ratchathani (excluding Amnatcharoen province).

Deaths following food poisoning (n = 1) and cholera (n = 0).

This study demonstrated the feasibility of using the AMASSplus to report the incidence and mortality of culture-confirmed NBDs in LMICs. We showed that electronic data of microbiology laboratories and hospital admission records could be used to support the information of NBDs to the NNDSS. The high burden of melioidosis is consistent with the previous clinical studies.9,10 This user-friendly and time-efficient tool enables individual hospitals to generate and share standardized reports in a timely manner. This could facilitate collaborative works across different settings, both nationally and globally, to support prioritization of public health resources.

We discussed the findings with the staff in each participating hospital and shared the reports with the DDC of the MoPH. The main barriers for the referral hospitals to report NBDs were that all levels of healthcare workers are not aware that those culture-confirmed cases should be reported to the NNDSS and that the responsible officers use the International Classification of Diseases, 10th revision (ICD-10) without using culture results to identify and report NBDs. However, the ICD-10 codings are often delayed, incomplete, or inaccurate.

The AMASSplus is now considered as an important tool by the DDC, MoPH of Thailand. The key measure of the national plan for melioidosis prevention and control, launched by the DDC in 2021, is to improve melioidosis surveillance.20 The DDC is using the AMASSplus to understand the total number of cases and deaths after culture-confirmed NBDs nationwide and supplement the information of NBDs officially reported to the NNDSS. The additional information of culture-confirmed NBDs would help the DDC design strategic interventions and allocate resources against the NBDs.

The study has some limitations. Comparisons of incidence and mortality between hospitals and between diseases need to be made with great caution because there are multiple confounding factors. The reported mortality could be an underestimation because the tool cannot identify moribund patients who were discharged against advice and died at home. Moreover, the reported mortality was based on the first admission, which had a clinical specimen culture positive for a pathogen and could be an underestimation for patients who experienced multiple readmissions due to the NBDs. The reports generated by the AMASSplus are designed to be retrospective and could not be used in outbreak situations as an alert system.

In conclusion, the AMASSplus can support the information of NBDs in Thailand. We suggest that stakeholders in LMICs should consider supporting hospitals that have microbiology laboratories and electronic data records to use any appropriate analytical software or tools, analyze and generate reports on NBDs, and use the data for their actions and decision-making.

ACKNOWLEDGMENTS

We thank the directors, epidemiological team, and laboratory team of participating hospitals for their administrative support. We thank Prapass Wanapinij (Mahidol-Oxford Tropical Medicine Research Unit) for technical support.

REFERENCES

  • 1.

    Thomas K , Jajosky R , Coates RJ , Calvert GM , Dewey-Mattia D , Raymond J , Singh SD , 2017. Summary of notifiable noninfectious conditions and disease outbreaks: Surveillance data published between April 1, 2016 and January 31, 2017 – United States. MMWR Morb Mortal Wkly Rep 64: 16.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Adams DA , Thomas KR , Jajosky RA , Foster L , Baroi G , Sharp P , Onweh DH , Schley AW , Anderson WJ , for the Nationally Notifiable Infectious Conditions Group , 2017. Summary of notifiable infectious diseases and conditions – United States, 2015. MMWR Morb Mortal Wkly Rep 64: 1143.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Division of Epidemiology, Department of Disease Control, Ministry of Public Health, Thailand , 2020. Standard Operating Procedures for Surveillance and Rapid Response Team, Thailand, 2020. Available at: https://ddc.moph.go.th/uploads/publish/1119320210312043053.pdf. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 4.

    Azar FE , Masoori N , Meidani Z , Paul L , 2010. Proposal for a modernized Iranian notifiable infectious diseases surveillance system: Comparison with USA and Australia. East Mediterr Health J 16: 771777.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Vlieg WL et al., 2017. Comparing national infectious disease surveillance systems: China and the Netherlands. BMC Public Health 17: 415.

  • 6.

    Jayatilleke K , 2020. Challenges in implementing surveillance tools of high-income countries (HICs) in low middle income countries (LMICs). Curr Treat Options Infect Dis 12: 191201.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Nansikombi HT , Kwesiga B , Aceng FL , Ario AR , Bulage L , Arinaitwe ES , 2023. Timeliness and completeness of weekly surveillance data reporting on epidemic prone diseases in Uganda, 2020–2021. BMC Public Health 23: 647.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Meumann EM , Limmathurotsakul D , Dunachie SJ , Wiersinga WJ , Currie BJ , 2023. Burkholderia pseudomallei and melioidosis. Nat Rev Microbiol 22: 155169.

  • 9.

    Hinjoy S et al., 2018. Melioidosis in Thailand: Present and future. Trop Med Infect Dis 3: 38.

  • 10.

    Hantrakun V , Kongyu S , Klaytong P , Rongsumlee S , Day NPJ , Peacock SJ , Hinjoy S , Limmathurotsakul D , 2019. Clinical epidemiology of 7126 melioidosis patients in Thailand and the Implications for a National Notifiable Diseases Surveillance System. Open Forum Infect Dis 6: ofz498.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Lim C et al., 2020. Automating the generation of antimicrobial resistance surveillance reports: Proof-of-concept study involving seven hospitals in seven countries. J Med Internet Res 22: e19762.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Amnatcharoen Hospital , 2022. Antimicrobial Resistance Surveillance Report, Amnatcharoen Hospital, Amnatcharoen, Thailand, 01 Jan 2021 to 31 Dec 2021. Available at: https://doi.org/10.6084/m9.figshare.19709929. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 13.

    Kantharalak Hospital , 2022. Antimicrobial Resistance Surveillance Report, Kantharalak Hospital, Sisaket, Thailand, 01 Jan 2021 to 31 Dec 2021. Available at: https://doi.org/10.6084/m9.figshare.19706662. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 14.

    Mukdahan, Thailand , 2022. Antimicrobial Resistance Surveillance Report, Mukdahan Hospital, Mukdahan, Thailand, 01 Jan 2020 to 31 Jan 2021. Available at: https://doi.org/10.6084/m9.figshare.19710568. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 15.

    Nakhonphanom Hospital , 2022. Antimicrobial Resistance Surveillance Report, Nakhonphanom Hospital, Nakhonphanom, Thailand, 01 Jan 2021 to 31 Dec 2021. Available at: https://doi.org/10.6084/m9.figshare.19709911. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 16.

    Phatthalung Hospital , 2022. Antimicrobial Resistance Surveillance Report, Phatthalung Hospital, Phatthalung, Thailand, 01 Jan 2021 to 26 Aug 2021. Available at: https://doi.org/10.6084/m9.figshare.19706728. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 17.

    Sunpasitthiprasong Hospital , 2022. Antimicrobial Resistance Surveillance Report, Sunpasitthiprasong Hospital, Ubon Ratchathani, Thailand, 23 Jul 2020 to 31 Jan 2021. Available at: https://doi.org/10.6084/m9.figshare.19710724. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 18.

    Division of Epidemiology, Department of Disease Control Ministry of Public Health, Thailand National Disease Surveillance (Report 506). Available at: http://doe.moph.go.th/surdata/. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 19.

    Division of Epidemiology , Department of Disease Control, Ministry of Public Health, Thailand, 2020. Case definition for Communicable Diseases Surveillance, Thailand, 2020. Available at: https://ddc.moph.go.th/uploads/publish/1142920210518092542.pdf. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 20.

    Bureau of General Communicable Diseases, Department of Disease Control, Ministry of Public Health, Thailand , 2021. Melioidosis Guideline. Available at: http://klb.ddc.moph.go.th/dataentry/handbook/form/129. Accessed November 11, 2022.

    • PubMed
    • Export Citation

Author Notes

Financial support: This study was supported by the Department of Disease Control (DDC), Ministry of Public Health (MoPH), Thailand, and the U.S. Defense Threat Reduction Agency. The study was funded in part by the Wellcome Trust (224681/Z/21/Z and Wellcome Trust Institutional Translational Partnership Award—Mahidol-Oxford Tropical Medicine Research Unit).

Authors’ addresses: Cherry Lim, Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand and Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom, E-mail: cherry.lim@ndm.ox.ac.uk. Preeyarach Klaytong, Viriya Hantrakun, and Chalida Rangsiwutisak, Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand, E-mails: preeyarach@tropmedres.ac, viriya.hantrakun@iqvia.com, chalida@tropmedres.ac. Chadaporn Phiancharoen and Ratanaporn Tangwangvivat, Division of Communicable Diseases, Department of Disease, Control, Ministry of Public Health, Nonthaburi, Thailand, E-mails: chadaphiancharoen@gmail.com and ratanaporn.tw@gmail.com. Somkid Kripattanapong and Charuttaporn Jitpeera, Division of Epidemiology, Department of Disease Control, Ministry of Public Health,Nonthaburi, Thailand, E-mails: skongyu@gmail.com and charuttaporn@gmail.com. Wiratya Poldech, Amnatcharoen Hospital, Amnatcharoen, Thailand, E-mail: yayeepol@gmail.com. Punya Jiramahasan, Kantharalak Hospital, Srisaket, Thailand, E-mail: cd_ktlhos@hotmail.com. Bangon Laosatiankit, Srisaket Provincial Health Office, Srisaket, E-mail: L_bangon@yahoo.com. Orawan Photivet, Punchawee Sukbut, and Warintorn Thongsri, Mukdahan Hospital, Mukdahan, Thailand, E-mails: micromuk@gmail.com, Mbdsmuk@yahoo.co.th, and Warintornt@hotmail.com. Kailas Kosasaeng, Nakhon Phanom Hospital, Nakhon Phanom, Thailand, E-mail: Kailas_ko@hotmail.com. Bongkoch Chiwehanyon, Nutjamee Leesahud, Preecha Ritthong, Wandee Linreung, Phatthalung Hospital, Phattalung, Thailand, E-mails: B_chiewchanyon@yahoo.com, nutmee5@gmail.com, nutmee5@gmail.com, itpharmacy@gmail.com, and kluay_kk25@hotmail.com. Panatda Aramrueang, Sunpasitthiprasong Hospital, Ubon Ratchathani, Thailand, E-mail: noki_a@hotmail.com. Wichan Bhunyakitikorn, Division of Communicable Diseases, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand, E-mail: vichan_pawun@yahoo.com. Sopon Iamsirithaworn, Division of Epidemiology, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand, E-mail: iamsiri@gmail.com. Direk Limmathurotsakul, Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom and Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand, E-mail: direk@tropmedres.ac.

Address correspondence to Direk Limmathurotsakul, Faculty of Tropical Medicine, Mahidol University, 420/6 Rajvithi Rd., Bangkok 10400, Thailand. E-mail: direk@tropmedres.ac
  • Figure 1.

    Locations of the six participating hospitals, including (1) Amnatcharoen Hospital, (2) Kantharalak Hospital, (3) Mukdahan Hospital, (4) Nakhon Phanom Hospital, (5) Phatthalung Hospital, and (6) Sunpasitthiprasong Hospital.

  • 1.

    Thomas K , Jajosky R , Coates RJ , Calvert GM , Dewey-Mattia D , Raymond J , Singh SD , 2017. Summary of notifiable noninfectious conditions and disease outbreaks: Surveillance data published between April 1, 2016 and January 31, 2017 – United States. MMWR Morb Mortal Wkly Rep 64: 16.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Adams DA , Thomas KR , Jajosky RA , Foster L , Baroi G , Sharp P , Onweh DH , Schley AW , Anderson WJ , for the Nationally Notifiable Infectious Conditions Group , 2017. Summary of notifiable infectious diseases and conditions – United States, 2015. MMWR Morb Mortal Wkly Rep 64: 1143.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Division of Epidemiology, Department of Disease Control, Ministry of Public Health, Thailand , 2020. Standard Operating Procedures for Surveillance and Rapid Response Team, Thailand, 2020. Available at: https://ddc.moph.go.th/uploads/publish/1119320210312043053.pdf. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 4.

    Azar FE , Masoori N , Meidani Z , Paul L , 2010. Proposal for a modernized Iranian notifiable infectious diseases surveillance system: Comparison with USA and Australia. East Mediterr Health J 16: 771777.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Vlieg WL et al., 2017. Comparing national infectious disease surveillance systems: China and the Netherlands. BMC Public Health 17: 415.

  • 6.

    Jayatilleke K , 2020. Challenges in implementing surveillance tools of high-income countries (HICs) in low middle income countries (LMICs). Curr Treat Options Infect Dis 12: 191201.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Nansikombi HT , Kwesiga B , Aceng FL , Ario AR , Bulage L , Arinaitwe ES , 2023. Timeliness and completeness of weekly surveillance data reporting on epidemic prone diseases in Uganda, 2020–2021. BMC Public Health 23: 647.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Meumann EM , Limmathurotsakul D , Dunachie SJ , Wiersinga WJ , Currie BJ , 2023. Burkholderia pseudomallei and melioidosis. Nat Rev Microbiol 22: 155169.

  • 9.

    Hinjoy S et al., 2018. Melioidosis in Thailand: Present and future. Trop Med Infect Dis 3: 38.

  • 10.

    Hantrakun V , Kongyu S , Klaytong P , Rongsumlee S , Day NPJ , Peacock SJ , Hinjoy S , Limmathurotsakul D , 2019. Clinical epidemiology of 7126 melioidosis patients in Thailand and the Implications for a National Notifiable Diseases Surveillance System. Open Forum Infect Dis 6: ofz498.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Lim C et al., 2020. Automating the generation of antimicrobial resistance surveillance reports: Proof-of-concept study involving seven hospitals in seven countries. J Med Internet Res 22: e19762.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Amnatcharoen Hospital , 2022. Antimicrobial Resistance Surveillance Report, Amnatcharoen Hospital, Amnatcharoen, Thailand, 01 Jan 2021 to 31 Dec 2021. Available at: https://doi.org/10.6084/m9.figshare.19709929. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 13.

    Kantharalak Hospital , 2022. Antimicrobial Resistance Surveillance Report, Kantharalak Hospital, Sisaket, Thailand, 01 Jan 2021 to 31 Dec 2021. Available at: https://doi.org/10.6084/m9.figshare.19706662. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 14.

    Mukdahan, Thailand , 2022. Antimicrobial Resistance Surveillance Report, Mukdahan Hospital, Mukdahan, Thailand, 01 Jan 2020 to 31 Jan 2021. Available at: https://doi.org/10.6084/m9.figshare.19710568. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 15.

    Nakhonphanom Hospital , 2022. Antimicrobial Resistance Surveillance Report, Nakhonphanom Hospital, Nakhonphanom, Thailand, 01 Jan 2021 to 31 Dec 2021. Available at: https://doi.org/10.6084/m9.figshare.19709911. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 16.

    Phatthalung Hospital , 2022. Antimicrobial Resistance Surveillance Report, Phatthalung Hospital, Phatthalung, Thailand, 01 Jan 2021 to 26 Aug 2021. Available at: https://doi.org/10.6084/m9.figshare.19706728. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 17.

    Sunpasitthiprasong Hospital , 2022. Antimicrobial Resistance Surveillance Report, Sunpasitthiprasong Hospital, Ubon Ratchathani, Thailand, 23 Jul 2020 to 31 Jan 2021. Available at: https://doi.org/10.6084/m9.figshare.19710724. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 18.

    Division of Epidemiology, Department of Disease Control Ministry of Public Health, Thailand National Disease Surveillance (Report 506). Available at: http://doe.moph.go.th/surdata/. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 19.

    Division of Epidemiology , Department of Disease Control, Ministry of Public Health, Thailand, 2020. Case definition for Communicable Diseases Surveillance, Thailand, 2020. Available at: https://ddc.moph.go.th/uploads/publish/1142920210518092542.pdf. Accessed November 11, 2022.

    • PubMed
    • Export Citation
  • 20.

    Bureau of General Communicable Diseases, Department of Disease Control, Ministry of Public Health, Thailand , 2021. Melioidosis Guideline. Available at: http://klb.ddc.moph.go.th/dataentry/handbook/form/129. Accessed November 11, 2022.

    • PubMed
    • Export Citation
Past two years Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 712 712 423
PDF Downloads 187 187 79
 
 
 
 
Affiliate Membership Banner
 
 
Research for Health Information Banner
 
 
CLOCKSS
 
 
 
Society Publishers Coalition Banner
Save