357 extractive question-and-answer pairs built from Annual Report, published by ncdc.mohfw.gov.in. The source is a 67-page publication. Source-evidenced topics include national antimicrobial resistance surveillance network, nars-net, antimicrobial resistance, ncdc, bacterial amr surveillance, fungal pathogens, staphylococcus aureus, escherichia coli. Every answer is a verbatim span of text the source prints, and each row carries the passage it sits in, its offset in that passage, the source quote, the page and the location in the document, so any row can be checked against the original. Question types in the export: 188 factual, 89 table, 22 list, 21 relationship, 18 comparison, 13 summary, 6 definition. 80 of the 357 pairs (22.4%) ask explanatory questions; the remaining 277 are factual or table-based questions. 97.76% of rows pass the corpus quality gate.
This dataset contains 357 question-and-answer pairs derived from the 2024 Annual Report on antimicrobial resistance (AMR) surveillance in India, published by ncdc.mohfw.gov.in. The data spans various pathogens, specimen types, and resistance trends, with questions categorized into factual, explanatory, and analytical types. Key topics include bacterial and fungal AMR surveillance, resistance patterns, and laboratory methodologies. The dataset provides verbatim answers sourced from the report, enabling validation against the original document.
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# One-time install: pip install desidata
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import desidata
df = desidata.load("ncdc-mohfw-gov-in-68f9f99befc2b12385afb3bcac6be410")
df.head()First 10 of 357 rows
| question | answer | context | answer_start | question_type | knowledge_quality_score | source_document | source_quote | source_page | source_location | confidence | validation_status |
|---|---|---|---|---|---|---|---|---|---|---|---|
| How were Wickerhamomyces anomalus isolates categorized in the absence of breakpoints? | wild type and non-wild type | Wickerhamomyces anomalus: Breakpoints for antifungal susceptibility testing of W. anomalus are not available, however epidemiological cut-off values (ECV) are given in CLSI M57SEd.48 which were used to categorise the isolates into wild type and non-wild type. All strains (n=27) exhibited low MICs for all the tested antifungals except fluconazole (Fig 31). Out of 27, 4 isolates (15%) were non- wild type as they exhibited MIC value of >8 mg/L for fluconazole. 8 CLSI . 2022. M57SEd.4. Epidemiological cutoff values for antifungal susceptibility testing. CLSI, Wayne, PA. | 231 | definition | 1.000 | https://ncdc.mohfw.gov.in/uploads/pdf/amr30.pdf | anomalus are not available, however epidemiological cut-off values (ECV) are given in CLSI M57SEd.48 which were used to categorise the isolates into wild type and non-wild type. | 60 | page=60,block=3 | 0.700 | valid |
| What is the goal of Antimicrobial Resistance surveillance? | tracking and combating the growing threat of AMR | Executive Summary Antimicrobial Resistance (AMR) surveillance is crucial for tracking and combating the growing threat of AMR. This is the eighth report of National AMR Surveillance Network (NARS-Net) established under the National Programme on AMR Containment coordinated by the National Centre for Disease Control (NCDC). This report includes bacterial AMR surveillance data from 54 sentinel surveillance sites and Fungal AMR Surveillance data from 28 sites being strengthened under NARS-Net. NARS-Net which has been expanded in a phased manner currently includes 60 laboratories in 33 states/UTs (as of March 2025). This report provides insights into resistance patterns, trends and emerging resistance across the network sites. The current report includes data of bacterial and fungal AMR Surveillance for the reporting period from 01 January 2024 to 31 December 2024. | 77 | definition | 1.000 | https://ncdc.mohfw.gov.in/uploads/pdf/amr30.pdf | Executive Summary Antimicrobial Resistance (AMR) surveillance is crucial for tracking and combating the growing threat of AMR. | 13 | page=13,block=1 | ||
| What scheme does the National Reference Laboratory implement for network labs? | External Quality Assessment Scheme (EQAS) | National Reference Laboratory (NRL) has been established at NCDC in 2018-19 to implement External Quality Assessment Scheme (EQAS) for the network labs so as to ensure quality AMR Surveillance data. NRL also confirms all antibiotic-resistant alert strains, as defined under the programme, submitted by network sites and only the confirmed alerts are included in the annual report. Feedback on EQAS and Alert confirmation is shared with the respective sentinel sites. The network sites are mandated to perform Internal quality control testing as per the programme SoPs. onsite support visits and trainings on data management are conducted to strengthen bacteriology laboratory capacity, identify the challenges and improve the quality of culture, identification and AST practices. The programme unit at NCDC also frequently organizes workshops on use of WHONET AMR data management software to | 89 | definition | 1.000 | https://ncdc.mohfw.gov.in/uploads/pdf/amr30.pdf | National Reference Laboratory (NRL) has been established at NCDC in 2018-19 to implement External Quality Assessment Scheme (EQAS) for the network labs so as to ensure quality AMR Surveillance data. | ||||
| What software is used for microbiology data management in the AMR programme at NCDC? | WHONET, a microbiology data management open-source offline software | sites to AMR programme unit at NCDC is being collated and analyzed at NCDC after validation using WHONET, a microbiology data management open-source offline software. After data validation, the annual National AMR surveillance report2 and the semi-annual bulletins3 are developed which are then made available on NCDC website for use by various stakeholders at national and state level. The network data is also submitted annually by NCDC to the World Health Organization's Global AMR Surveillance and Use System (WHO-GLASS) since 2018. MoHFW designated NCDC as the National Coordinating Centre for AMR Surveillance in India in the year 2017. Table 1: Priority Pathogens and specimens included under Bacterial AMR Surveillance Specimen S. aureus Enterococcus spp. Klebsiella spp. Escherichia coli Acinetobacter spp. Pseudom onas spp. | 98 | definition | 1.000 | https://ncdc.mohfw.gov.in/uploads/pdf/amr30.pdf | sites to AMR programme unit at NCDC is being collated and analyzed at NCDC after validation using WHONET, a microbiology data management open-source offline software. | 16 | |||
| What is Introduction Antimicrobial resistance (AMR)? | a rapidly escalating global health threat | 1.1. Introduction Antimicrobial resistance (AMR) is a rapidly escalating global health threat. As pathogens evolve to resist the existing antimicrobials, once-manageable diseases become increasingly difficult or impossible to cure. | 52 | definition | 0.980 | https://ncdc.mohfw.gov.in/uploads/pdf/amr30.pdf | Introduction Antimicrobial resistance (AMR) is a rapidly escalating global health threat. | 15 | page=15,block=2 | 0.850 | valid |
| Why is High proportion of isolates from neonates (29%) particularly noteworthy and points to their increased susceptibility to Candida infections? | underdeveloped immunity, frequent use of invasive devices, and prolonged stays in NICUs | albicans, which historically dominated invasive candidiasis, reflects a broader global trend likely influenced by antifungal exposure and changing host demographics. High proportion of isolates from neonates (29%) is particularly noteworthy and points to their increased susceptibility to Candida infections due to underdeveloped immunity, frequent use of invasive devices, and prolonged stays in NICUs. Overall, most isolates across species were recovered from ICUs especially from NICU settings, underlining critical care environments as high-risk reservoirs for opportunistic yeast infections. | 315 | relationship | 0.970 | https://ncdc.mohfw.gov.in/uploads/pdf/amr30.pdf | High proportion of isolates from neonates (29%) is particularly noteworthy and points to their increased susceptibility to Candida infections due to underdeveloped immunity, frequent use of invasive devices, and prolonged stays in NICUs. | 63 | page=63,block=1 | 0.800 | |
| How did the resistance trend to nitrofurantoin in urinary isolates change over three years? | increased from 9% in 2022 to 19% in 2024 | High proportion of resistance to ciprofloxacin was observed ranging between 73% to 78% in all specimen types. Resistance to nitrofurantoin in urinary isolates showed an increasing trend over last 3 years (increased from 9% in 2022 to 19% in 2024). (Table 8) Amongst third generation cephalosporins tested, resistance ranging between 79% to 83% was observed in all specimen types. β-lactam inhibitor combination i.e. amoxicillin-clavulanate also had high resistance of 68% in blood isolates. Among carbapenems, ertapenem (49%) had higher resistance rate than imipenem (40%) and meropenem (36%) in E. coli blood isolates (Table 8). For colistin susceptibility testing, isolates tested using colistin agar screen and broth microdilution method as per CLSI-M100 Ed. 34 were only considered in this report. | 205 | relationship | 0.970 | https://ncdc.mohfw.gov.in/uploads/pdf/amr30.pdf | Resistance to nitrofurantoin in urinary isolates showed an increasing trend over last 3 years (increased from 9% in 2022 to 19% in 2024). | 32 | page=32,block=3 | 0.700 | |
| How did vancomycin resistance among urinary isolates change from 2023 to 2024? | 6% in 2023 to 12% in 2024 | Resistance to linezolid (1.7%, CI: 1.3-2.2) among blood isolates is similar to last year’s report. Among the urinary isolates, 58% were resistant to first-line antibiotic ampicillin (CI: 57.1 – 58.9) and 53% to gentamicin-high (CI: 52.2-54.1). Highest resistance was observed to ciprofloxacin (82%, CI: 81.1 - 82.8) and lowest was observed to linezolid 0.44 % (CI: 0.3-0.6). Resistance to vancomycin among urinary isolates was higher than that in last year’s report (6% in 2023 to 12% in 2024) (Table 7). Enterococcus spp. isolates from inpatient wards were almost double the outpatient patient isolates which were in turn nearly twice the isolates from ICU patients. (Table 5). AST analysis of blood isolates of Enterococcus spp. showed higher resistance to linezolid in isolates from patients in intensive care units in comparison to those from inpatient wards and outpatient clinics. | 467 | relationship | 0.970 | https://ncdc.mohfw.gov.in/uploads/pdf/amr30.pdf | Resistance to vancomycin among urinary isolates was higher than that in last year’s report (6% in 2023 to 12% in 2024) (Table 7). | 28 | page=28,block=0 | ||
| What criterion was used for including multiple isolates from the same patient in the data analysis? | only the first isolate of a given species isolated during the investigated time interval | For data analysis, only the first antibiotic susceptibility result has been considered for each patient per specimen type and pathogen. if two blood cultures from the same patient yielded growth of E. coli, only the first has been included in the data; if the growth of E. coli was detected in one culture and of K. pneumoniae in the other, both results have been considered. If there was growth of E. coli in one blood culture and in one urine culture from the same patient, both specimen types have been included. From each patient, only the first isolate of a given species isolated during the investigated time interval was included, regardless of its susceptibility profile. Deduplication of reported data of 2,06,745 isolates using WHONET revealed 1,95,077 unique patients isolate data. For the surveillance period, only one result has been 5 Clinical Laboratory Standard Institute. | 535 | relationship | 0.970 | https://ncdc.mohfw.gov.in/uploads/pdf/amr30.pdf | From each patient, only the first isolate of a given species isolated during the investigated time interval was included, regardless of its susceptibility profile. | ||||
| What emerging resistance pattern in antifungal drugs is concerning? | emerging resistance to echinocandins in some species | most isolates across species were recovered from ICUs especially from NICU settings, underlining critical care environments as high-risk reservoirs for opportunistic yeast infections. The antifungal susceptibility patterns revealed fluconazole resistance in several species, most notably C. auris (66%), C. parapsilosis (16%), W. anomalus (15%), C. albicans (8%), and C. tropicalis (7%). Although resistance to amphotericin B, itraconazole and 5-fluorocytosine remained low, emerging resistance to echinocandins in some species is concerning. These findings underscore the necessity for routine species-level identification and susceptibility testing to guide appropriate therapy. The presence of rare yeasts such as C. jadanii, Clavispora lusitaniae and Trichosporon spp. further highlights the value of advanced diagnostic techniques in uncovering uncommon pathogens. | 475 | relationship | 0.970 | https://ncdc.mohfw.gov.in/uploads/pdf/amr30.pdf | Although resistance to amphotericin B, itraconazole and 5-fluorocytosine remained low, emerging resistance to echinocandins in some species is concerning. | 63 | page=63,block=1 |
Read straight from the file — download or use the API URL for the full dataset.
| 0.700 |
| valid |
| 17 |
| page=17,block=2 |
| 0.700 |
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| page=16,block=0 |
| 0.700 |
| valid |
| valid |
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| 0.700 |
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| 18 |
| page=18,block=4 |
| 0.700 |
| valid |
| 0.700 |
| valid |