Browsing by Author "Musyoki, Victor"

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    Antimicrobial resistant coliforms across four poultry production systems in Arusha and Moshi, Tanzania
    (Pan African Medical Journal, 2022-01-11) Maganga, Ruth; Sindiyo, Emmanuel; Musyoki, Victor; Shirima, Gabriel; Maina, Brian; Mmbaga, Blandina
    Introduction: resistance to antimicrobials poses a threat to human and animal health. This study aimed to determine the prevalence of resistant coliforms in poultry cloacal samples collected from different poultry systems in Arusha and Moshi districts, Tanzania. Methods: ten administrative wards were randomly chosen in Moshi and Arusha urban districts, with a random selection of one representative farm in each ward per production system (extensive, semi-intensive, intensive, and broiler systems). Per farm, 10 chickens were sampled using cloacal swabs. Samples were tested for the presence of coliforms using MacConkey agar without or with tetracycline, ciprofloxacin, ceftazidime, and Imipenem. R software was used for data analysis. Results: of the 80 farms targeted, samples were collected from 79 farms representing a total of 746 samples, of which 648 (86.8%) had coliforms corresponding to 74 of the 79 sampled farms. There was no significant difference in the overall prevalence of coliforms between Moshi (86%) and Arusha districts (87%) (p=0.81). The overall proportions of resistant coliforms in Arusha and Moshi varied depending on each antimicrobial type. The prevalence of coliforms resistant to tetracycline (95%) across all farm types in both districts was higher compared to ciprofloxacin (72%), imipenem (71%), and ceftazidime (84%) (p<0.0001). The median counts of coliform resistance (in log cfu) ranged from 4 to 10, with no significant distinctions between antimicrobial types. Conclusion: there is a widespread presence of antimicrobial resistant coliforms in poultry production systems. High tetracycline resistance was observed across all farm types in both districts.
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    Comparative analysis of clinical breakpoints, normalized resistance interpretation and epidemiological cut-offs in interpreting antimicrobial resistance of Escherichia coli isolates originating from poultry in different farm types in Tanzania
    (Microbiology Society, 2014-07-14) Maganga, Ruth; Sindiyo, Emmanuel; Musyoki, Victor; Shirima, Gabriel; Mmbaga, Blandina
    Introduction. Existing breakpoint guidelines are not optimal for interpreting antimicrobial resistance (AMR) data from animal studies and low-income countries, and therefore their utility for analysing such data is limited. There is a need to integrate diverse data sets, such as those from low-income populations and animals, to improve data interpretation. Gap statement. There is very limited research on the relative merits of clinical breakpoints, epidemiological cut-offs (ECOFFs) and normalized resistance interpretation (NRI) breakpoints in interpreting microbiological data, particularly in animal studies and studies from low-income countries. Aim. The aim of this study was to compare antimicrobial resistance in Escherichia coli isolates using ECOFFs, CLSI and NRI breakpoints. Methodology. A total of 59 non-repetitive poultry isolates were selected for investigation based on lactose fermentation on MacConkey agar and subsequent identification and confirmation as E. coli using chromogenic agar and uidA PCR. Kirby Bauer disc diffusion was used for susceptibility testing. For each antimicrobial agent, inhibition zone diameters were measured, and ECOFFs, CLSI and NRI bespoke breakpoints were used for resistance interpretation. Results. According to the interpretation of all breakpoints except ECOFFs, tetracycline resistance was significantly higher (TET) (67.8 –69.5 %), than those for ciprofloxacin (CIPRO) (18.6 –32.2 %), imipenem (IMI) (3.4 –35 %) and ceftazidime (CEF) (1.7 –45.8 %). Prevalence estimates of AMR using CLSI and NRI bespoke breakpoints did not differ for CEF (1.7 % CB and 1.7 % COWT ), IMI (3.4 % CB and 4.0 % COWT ) and TET (67.8 % CB and 69.5 % COWT ). However, with ECOFFs, AMR estimates for CEF, IMI and CIP were sig- nificantly higher (45.8, 35.6 and 64.4 %, respectively; P<0.05). Across all the three breakpoints, resistance to ciprofloxacin varied significantly (32.2 % CB, 64.4 % ECOFFs and 18.6 % COWT , P<0.05). Conclusion. AMR interpretation is influenced by the breakpoint used, necessitating further standardization, especially for microbiological breakpoints, in order to harmonize outputs. The AMR ECOFF estimates in the present study were significantly higher compared to CLSI and NRI.