Regan Zenas Shayo, Nsiande Lema, Mecky I. N. Matee
{"title":"坦桑尼亚达累斯萨拉姆市自动柜员机表面多重耐药革兰氏阴性菌污染","authors":"Regan Zenas Shayo, Nsiande Lema, Mecky I. N. Matee","doi":"10.24248/easci.v5i1.78","DOIUrl":null,"url":null,"abstract":"Background: In Tanzania, little is known about the proportion of Multi-drug resistance (MDR) Gram-negative bacteria contamination on Automated Teller Machine (ATMs) surfaces. The study aimed to determine the proportion of MDR Gram-negative bacteria contamination on ATMs surfaces, antimicrobial resistance patterns as well as associated factors. Methodology: A cross-sectional study was conducted between January and March -2021 in Dar es Salaam, involving 298 ATMs. Cultures were performed on Mac-Conkey agar while antimicrobial susceptibility was done using the Kirby Bauer disc diffusion method with Klebsiella pneumoniae ATCC 700603 and Escherichia coli ATCC 25922 used as controls. Data analysis was done using STATA version 15.1. Chi-square and Modified Poisson regression was used to assess factors associated with MDR contamination. Data was presented as prevalence ratio (PR) and 95% Confidence Interval. A p-value of <.05 was considered statistically significant. Results: More than half (55.4%) of ATMs in Dar es Salaam are contaminated with Gram negative bacteria, mostly by Klebsiella pneumoniae 18.5% (31/168). The highest level of resistance was observed against ampicillin (68.9%). About one-third (34.5%) of the isolates were MDR. About 35.7% were Extended-Spectrum Beta-Lactamases (ESBL) producers while 19.6% were quinolone/ fluoroquinolones-resistance. Risk factors for contamination of ATMs included highly populated location such as; Ubungo (PR adjusted = 3.62, 95%CI = 1.58-8.30, P=.002), Kigamboni (PR adjusted = 2.78, 95%CI = 1.20-6.42, P=.017), and Temeke (PR adjusted = 2.75, 95%CI = 1.04-3.72, P=.023), and less frequent cleaned ATMs (PR adjusted = 1.98, 95%CI = 1.04-3.73, P=.04). Conclusions: More than half of ATMs in Dar es Salaam are contaminated with Gram-negative and one-third of them with MDR bacteria, especially those located in highly populated areas and those that are less frequently cleaned. This calls for interventional measures regarding public awareness of ATMs as potential vehicles for the transmission of infectious agents.","PeriodicalId":11398,"journal":{"name":"East Africa Science","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Contamination of Automated Teller Machines Surfaces with Multi-drug Resistance Gram-negative Bacteria in Dar es Salaam, Tanzania\",\"authors\":\"Regan Zenas Shayo, Nsiande Lema, Mecky I. N. Matee\",\"doi\":\"10.24248/easci.v5i1.78\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: In Tanzania, little is known about the proportion of Multi-drug resistance (MDR) Gram-negative bacteria contamination on Automated Teller Machine (ATMs) surfaces. The study aimed to determine the proportion of MDR Gram-negative bacteria contamination on ATMs surfaces, antimicrobial resistance patterns as well as associated factors. Methodology: A cross-sectional study was conducted between January and March -2021 in Dar es Salaam, involving 298 ATMs. Cultures were performed on Mac-Conkey agar while antimicrobial susceptibility was done using the Kirby Bauer disc diffusion method with Klebsiella pneumoniae ATCC 700603 and Escherichia coli ATCC 25922 used as controls. Data analysis was done using STATA version 15.1. Chi-square and Modified Poisson regression was used to assess factors associated with MDR contamination. Data was presented as prevalence ratio (PR) and 95% Confidence Interval. A p-value of <.05 was considered statistically significant. Results: More than half (55.4%) of ATMs in Dar es Salaam are contaminated with Gram negative bacteria, mostly by Klebsiella pneumoniae 18.5% (31/168). The highest level of resistance was observed against ampicillin (68.9%). About one-third (34.5%) of the isolates were MDR. About 35.7% were Extended-Spectrum Beta-Lactamases (ESBL) producers while 19.6% were quinolone/ fluoroquinolones-resistance. Risk factors for contamination of ATMs included highly populated location such as; Ubungo (PR adjusted = 3.62, 95%CI = 1.58-8.30, P=.002), Kigamboni (PR adjusted = 2.78, 95%CI = 1.20-6.42, P=.017), and Temeke (PR adjusted = 2.75, 95%CI = 1.04-3.72, P=.023), and less frequent cleaned ATMs (PR adjusted = 1.98, 95%CI = 1.04-3.73, P=.04). Conclusions: More than half of ATMs in Dar es Salaam are contaminated with Gram-negative and one-third of them with MDR bacteria, especially those located in highly populated areas and those that are less frequently cleaned. This calls for interventional measures regarding public awareness of ATMs as potential vehicles for the transmission of infectious agents.\",\"PeriodicalId\":11398,\"journal\":{\"name\":\"East Africa Science\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"East Africa Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24248/easci.v5i1.78\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"East Africa Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24248/easci.v5i1.78","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Contamination of Automated Teller Machines Surfaces with Multi-drug Resistance Gram-negative Bacteria in Dar es Salaam, Tanzania
Background: In Tanzania, little is known about the proportion of Multi-drug resistance (MDR) Gram-negative bacteria contamination on Automated Teller Machine (ATMs) surfaces. The study aimed to determine the proportion of MDR Gram-negative bacteria contamination on ATMs surfaces, antimicrobial resistance patterns as well as associated factors. Methodology: A cross-sectional study was conducted between January and March -2021 in Dar es Salaam, involving 298 ATMs. Cultures were performed on Mac-Conkey agar while antimicrobial susceptibility was done using the Kirby Bauer disc diffusion method with Klebsiella pneumoniae ATCC 700603 and Escherichia coli ATCC 25922 used as controls. Data analysis was done using STATA version 15.1. Chi-square and Modified Poisson regression was used to assess factors associated with MDR contamination. Data was presented as prevalence ratio (PR) and 95% Confidence Interval. A p-value of <.05 was considered statistically significant. Results: More than half (55.4%) of ATMs in Dar es Salaam are contaminated with Gram negative bacteria, mostly by Klebsiella pneumoniae 18.5% (31/168). The highest level of resistance was observed against ampicillin (68.9%). About one-third (34.5%) of the isolates were MDR. About 35.7% were Extended-Spectrum Beta-Lactamases (ESBL) producers while 19.6% were quinolone/ fluoroquinolones-resistance. Risk factors for contamination of ATMs included highly populated location such as; Ubungo (PR adjusted = 3.62, 95%CI = 1.58-8.30, P=.002), Kigamboni (PR adjusted = 2.78, 95%CI = 1.20-6.42, P=.017), and Temeke (PR adjusted = 2.75, 95%CI = 1.04-3.72, P=.023), and less frequent cleaned ATMs (PR adjusted = 1.98, 95%CI = 1.04-3.73, P=.04). Conclusions: More than half of ATMs in Dar es Salaam are contaminated with Gram-negative and one-third of them with MDR bacteria, especially those located in highly populated areas and those that are less frequently cleaned. This calls for interventional measures regarding public awareness of ATMs as potential vehicles for the transmission of infectious agents.