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Ethiop. J. Agric. Sci. 32(1) 79-88 (2022)
Occurrence, Associated Risk Factors and Drug
Resistance Profiles of Salmonella Isolated from
Fish Value Chain, Northwest Ethiopia
Birhan Agmasa, Gizachew Gelawb, Marshet Adugna*c, Yechale Teshomea
aDepartment of Veterinary Science, School of Animal Science and Veterinary Medicine, Bahir Dar University,
Bahir Dar, Ethiopia; bBahir Dar Poly Technic College, Bahir Dar, Ethiopia; cAddis Ababa University, Aklilu
Lemma Institute of pathobiology; dEthiopian Institute of Agricultural Research; National Fishery and Aquatic
Life Research Centre; Corresponding Author E-mail: marshetadu@gmail.com
አህፅሮት
ሳልሞኔላ
በዓለም
ላይ
ከሚተላለፉ
ዋና
ዋና
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ወለድ
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ተህዋሲያን
አንዱ
ሲሆን
የዓሳ
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ደግሞ
ለተዋሃሲው
መተላለፊያ
ዋንኛው
ነው።
ይህ
ጥናት
የተካሄደው
በሰሜን
ምዕራብ
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ካለው
የዓሳ
ዕሴት
ሰንሰለት
ያለውን
የሳልሞኔላ
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መድኃኒትን
የመቋቋም
ችሎታና
እና
ተዛማጅ
አደጋዎችን
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ነው።
የጥናት
ወረዳዎችን፣
ቀበሌዎችን
እና
የማረፊያ
ቦታዎችን
ለመምረጥ
ባለብዙ
ደረጃ
ናሙና
ዘዴ
ተተግብሯል።
የዓሳ
በሳልሞኔላ
መብል
በተመረጡ
ሚዲያዎች
በመጠቀም
በማሳደግና
በመለየት
ጥናት
ተደርጓል፣
በመቀጠል
አንቲባዮሱም
ሳልሞኔላ
ፖሊቫን
-
ኦን
በመጠቀም
የተለመደው
የባዮ-ኬሚካል
ምርመራዎች
እና
የሴሮሎጂ
ማረጋገጫ
ተሰርቷል።
በበሽታው
አጋላጭ
ሊሆኑ
በሚችሉ
የአደጋ
ምክንያቶች
ላይ
መረጃ
የተሰበሰበው
በተዋቀረ
መጠይቅ
በመጠቀም
አምራቾችን
ፊት
ለፊት
ቃለ
-
መጠይቅ
በማድረግ
ነው።
በጥናቱ
አካባቢ
የሳልሞኔላ
አጠቃላይ
ስርጭት
36.43
በመቶ
ነበር።
ከተለዩት
የሳልሞኔላ
ናሙናዎች
መካክል
25
በመቶው
ቢያንስ
በአንድ
መድሃኒት
የመቋቋም
ችሎታ
አሳይቷል።
Ciprofloxacin (CIP-5μg)
ከፍተኛው
የሳልሞኔላ
መድሃኒት
መቋቋም
(9.8
በመቶ
)
ሲሆነ
ሲፍታዚዲሜ
(CAZ-30μg)
በተከታይ
5.88
በመቶ
ሆኖ
ተገኝቷል።
ሁለት
የሳልሞኔላ
ናሙናዎች
(3.92
በመቶ
)
ለሶስት
አንቲባዮቲኮች
የመቋቋም
ችሎታ
አሳይተዋል።
የሳልሞኔላ
መከሰትን
በተናጥል
የሚገመቱ
ምክንያቶች
ብክለት
1.06 (95
በመቶ
CI:
1.04
፣
5.4)
፣
በረዶ
ቤት
ያልተቀመጠ
ዓሳ
2.2 (95
በመቶ
CI: 1.09
፣
11.41)
እና
ደካማ
አያያዝ
1.8
(95
በመቶ
CI: 1.02
፣
13.32)
ናቸው።
በአጠቃላይ
የጥናታችን
ውጤት
ሳልሞኔላ
ለዓሳ
የምግብ
መበከል
እና
የህዝብ
ጤና
አደጋ
ሊጥል
ይችላል።
ስለዚህ
ችግሩን
ለማቃለል
የግንዛቤ
ማስጨበጫ
እና
በአጠቃላይ
አዲስ
ተገቢ
የጥራት
ቁጥጥር
ርምጃዎች
መተግበር
አለባቸው።
በሰሜን
-
ምዕራብ
ኢትዮጵያ
የዓሳ
ፍጆታን
በመጠቀም
የሳልሞኔሎሲስ
አደጋን
ለመቀነስ
በማረፊያ
ጣቢያዎች፣
በዓሳ
ቸርቻሪዎች
በሆቴሎች
እና
በምግብ
ቤቶች
ውስጥ
ብክለትን
ለማስወገድ
በዓሳ
ዕሴት
ሰንሰለት
መካከል
ንፅህናን
ማሻሻል
ወሳኝ
ነው።
Abstract
Salmonella is one of the major foodborne pathogens worldwide that fish food as
one of the vehicles for its transmission. The study was conducted to estimate the
occurrence, drug-resistant profile, and associated risk factors of Salmonella
isolated from the fish value chain in Northwest Ethiopia. A multistage sampling
technique was applied to select study districts, kebeles, and landing sites.
Salmonella contamination of fish muscle was tested using selective media, followed
by conventional biochemical tests and serological confirmation, using Antiserum
Salmonella Polyvalent-O. Salmonella enumeration was accomplished using a
traditional three-tube Most Probable Number (MPN) approach. Data on potential
risk factors were collected using a structured questionnaire through a face-to-face
interview. Data were entered and analyzed using STATA version 12. The overall
prevalence of Salmonella in the study area was 36.4 %. Twenty-five percent of
Salmonella isolates showed resistance to at least one drug. Ciprofloxacin (CIP-5μg)
was found to be the highest Salmonella drug resistance (9.8%) followed by
Ceftazidime (CAZ-30μg) 5.9%. Two isolates (3.9%) of salmonella were resistant to
three antibiotics. Factors that independently predict the occurrence of Salmonella
were the presence of contamination 1.06 (95 % CI: 1.04, 5.4), non-iced fish after
Associated Risk Factors and Drug Resistance Profiles of Salmonella [80]
landing 2.2 (95 % CI: 1.09, 11.41), and poor handling practice 1.8 (95 % CI: 1.02,
13.32). In conclusion, our study results highlighted Salmonella as a potential fish
origin food contaminant and a public health risk. Therefore, appropriate control
measures, including awareness-raising and the creation of a new code of quality in
general, should be implemented to mitigate the problem. Improving hygiene along
the fish value chains to avoid cross-contamination at landing sites, fish retailers,
hotels and restaurants is crucial to reduce the risk of salmonellosis through fish
consumption in North-Western Ethiopia.
Keywords: Drug resistance; fish; risk-factors; Salmonella
Introduction
Fish and shellfish are the most valuable part of the human diet (Venugopal and
Gopakumar, 2017). It offers a noble amount of essential amino acids in the diet, omega-3
fatty acids, vitamins (D and B2), and minerals such as iron, zinc, phosphorus (Bujjamma,
2015). According to FAO (2018), fish contributes around 17% of the global animal
essential amino acid intake.
Fish food, indeed although it is being solid nourishment with wholesome esteem, can act
as a vehicle of food-borne pathogens on the other hand. For instance, the fish's outer
body, gastrointestinal and gills parts, carry a critical amount of microbial quantity (1.72 ±
0.68 × 108 to 7.00 ± 3.39 × 108) (Lin et al., 2017). Hence, fish and fishery products have
known as the main hauler of food-borne pathogens (Nayarit-Ballesteros, 2016; Siciliano,
2019). Food-borne pathogens stay an open wellbeing danger of the globe and Salmonella
is considered as one of the essential bacterial foodborne pathogens to people (Lin et al.,
2017). Salmonella occurs in aquatic environments especially in tropical regions because
of sewage effluents; agricultural run-off and direct fecal contamination from natural
fauna. Aquatic environments, fishery equipment and handling practices are known to
influence the bacterial loads in the harvested fish. Thus, fish and fishery products have
been known as a major transporter of Salmonella especially in fresh and unprocessed
conditions ( Seel et al., 2016, WHO, 2018a).
Salmonella is one of the leading causes of human gastroenteritis. Contaminated shellfish
and fish foods contribute approximately 1.3 million yearly cases of human gastroenteritis
(Kurtz et al, 2017). The non-typhoid Salmonella enterica is a common cause of several
different disease syndromes including gastroenteritis, bacteremia, and typhoid fever, with
the most common being gastroenteritis, which is often characterized by abdominal pain,
nausea, vomiting, diarrhea, and headache in humans (WHO, 2018).
Salmonella has been isolated from fish and other seafood (WHO, 2018b). Nutritional
constituents and water content available in seafood have become useful growth
ingredients for the proliferation of Salmonella. Salmonella, at room temperature highly
proliferate and the pathogenicity of the organism remained high and active in fish foods
(Kumar et al., 2015). It may be transferred to the seafood due to the poor hygienic
conditions during transportation and marketing (Getu et al, 2015). The prevalence of
Salmonella in seafood has been studied in different regions of the world, and health risks
Birhan et al., [81]
were evaluated. The distribution of Salmonella in seafood on a regional basis is indicated
to be highest in the central Pacific and Africa (12%) and lowest in Europe/Russia and
North America (1.6%) ( Kumar et al., 2003). In-country basis, the prevalence of
Salmonella on fish food in Khartoum, Sudan 9.2% (Ali and Hussein, 2010), seafood in
Greece 11.2%, and cooked shellfish in UK 5.2% has been reported (European Food
Safety Authority, 2019).
Despite steady observation and in-depth efforts, fish food born salmonellosis is expanding
in developed countries (Daniel et al., 2018). In developing countries such as Ethiopia,
there is no such ceaseless observing framework and a precise number of cases isn't
documented. In recent years, the increasing popularity of unprocessed foods containing
raw fish potentially increases the risk of salmonellosis (Gezai, 2019). In Ethiopia, in
addition to contamination through handlers along the value chain and undercooked fish,
may also be a cause of human salmonellosis. There is no research on the burden and drug
resistance profile of Salmonella in fish-root nourishments in Ethiopia.
Human activities are distorting antimicrobials use and creating risks of resistance. The
number of resistant organisms, the strain of resistance, and the degree of resistance in
each organism are unknown unless studied for a specific organism (Bujjamma, 2015).
Salmonella is one of the organisms that develop resistance have a hazard for people of the
glove. Infections with Salmonella that are resistant to antimicrobials may result in
increased human morbidity, increased human mortality, reduced effectiveness of related
antibiotics used in humans, increased human care costs, increased potential for carriage
and dissemination, facilitated the emergence of resistance in human pathogens. (EFSA
and EU CDC, 2019). The antibiotic resistance of one microbe can be shared with other
microbes through transduction, conjugation, and transformation (Divek et al., 2018). One
organism can have multiple drug resistance genes, which lead to different resistance traits.
Resistance mechanisms are varied, like the antibiotics themselves (Ali., 2017).
Antibiotic resistance Salmonella monitoring allows the identification of emerging or
specific patterns of resistance. Finally, suggest research priorities and propose
administrative and educational measures that can help to stop this development of
antimicrobial resistance (Gove and Hancock, 2019). Nevertheless; there is no previous
study on the occurrence of Salmonella in fish foods and drug resistance patterns in
Ethiopia. Thus, this study could serve as a source of information for further investigations
and corrective interventions.
Materials and Methods
Description of Study Area
This study was conducted in Northwest Ethiopia along the value chain of Lake Tana fish
production and consumption. Lake Tana is located North West of Ethiopia at latitude and
longitude of 12°0′N; 37° 15′ E, respectively. Lake Tana is the head of the Blue Nile and is
the largest Lake in Ethiopia. The commercially important fish groups in Lake Tana
Associated Risk Factors and Drug Resistance Profiles of Salmonella [82]
include large Labeobarbus spp., African catfish (Clarias gariepinus), and Nile tilapia
(Oreochromis niloticus). There are 55 fishery enterprises with a total of 1217 operators
(1154 males and 63 females). This lake is the major fish contributor of North West
Ethiopia (Amhara Regional State Agriculture and Livestock Development Bureau, 2017).
The samples were taken along the fish value chain of four districts (Bahir Dar Zuriya,
Dembia, North Achefer, and Libokemkem) around Lake Tana (Figure 1).
Sampling Strategy
A multistage sampling technique was applied for selected study districts, ‘kebeles’. The
districts were selected purposively based on annual fish production, number of personnel
or operators involved, and their geographic proximity to Lake Tana and assumed to be
representative of the lake's value chain. Whereas simple random sampling technique was
used for selecting ‘kebeles’ and systematic random sampling was used to sample
individual fish foods/muscle tissue. A total of 140 fish muscle tissue samples were
collected. For identification of associated risk factors of Salmonella from fish, a total of
40 operators, 10 from each district were interviewed.
Questionnaire Survey
Direct interview with a semi-structured questionnaire was used to collect the data with the
respondent of the selected fish meat sellers, fish harvesters, and fish filleters. The
questionnaire consists of their experience and objective of fish harvesting, harvesting
area, and equipment, types of fish species, questions to monitor handling and hygiene,
landing infrastructure, commonly used equipment, and materials.
Laboratory Sample Collection and Analysis
Over a period of 9 months, 140 fish muscle samples were collected along the fish value
chain. The fish tissue samples were weighed, wrapped in a pre-cleaned Aluminum foil,
and then packaged into zip-lock plastic bags. Then were put away in an icebox and
transported to Amhara Public health Institute (APHI) Microbiology Laboratory within
two hours on common for processing and isolation of Salmonella. Of 140 samples among
value chains (50 samples from landing sites, 45 from fish retailers, and 45 from hotels and
restaurants) were collected. Salmonella was isolated from fish samples based on the
conventional biochemical methods following the standard guidelines and finally process
by serological confirmation.
A 25-g portion of fish muscle was added into 225 ml buffer peptone water in a sterile
plastic bag and then homogenized using a stomacher. Salmonella isolation followed the
ISO 6579-1:2017 technique (ISO-6579, 2002) on the enrichment and isolation media. The
combined sample that homogenized one was incubated for 16–20h at 37°C on enrichment
media. Thus 1ml of aliquot inoculated on Muller Kauffmann Tetrathionate (TT) broth and
a Modified Semisolid Rappaport Vassiliadis (MSRV) agar plate was inoculated around 50
μl. Both media were incubated for 16–20h in 37°C. This selection phase was repeated, by
using one loop (approximately 10μl) of TT and MSRV, to inoculate Xylose Lysine
Tergitol 4 (XLT4) and Ramback agar plate selective media. The appearance of brown,
gray, or black per plate were taken for further biochemical confirmation of Salmonella
Birhan et al., [83]
and another one to two colonies to inoculate Nutrient Agar (NA) to grow Salmonella for
serological confirmation, using Antiserum Salmonella Polyvalent-O.
Salmonella concentration was enumerated using a traditional 3-tube MPN (Most Probable
Number) approach (Pavic et al., 2010). The concentrations of 25g of homogenized solute
were buffered 225 ml of buffer peptone water. Then 10 ml of this mixture was added into
3 empty tubes. Another 1ml of homogenized solute and 9 ml of buffered peptone water
mixture into 3 tubes. Finally, 0.1ml solute and 9.99ml buffered peptone water dilution
into 3 tubes then incubate at 370c for 24 hrs. Salmonella detection of each tube was the
same as the qualitative method. The value was cross-read based on the number of positive
tubes in each of the three sets using the MPN standard table (Pavic et al., 2010).
Antibiotic Sensitivity Test
Antimicrobial susceptibility testing was done based on the criteria of the Clinical and
Laboratory Standards Institute (CLSI) (Humphries et al., 2018) for all isolates of
Salmonella. Taking the pure isolated colony, the bacterial suspension was adjusted to
0.5McFarland turbidity standards. According to Mahon and Lehman, (2019) the
recommended control organism for susceptibility testing of gram-negative microorganism
drugs was E. coli (ATCC 25922). Since E. coli (ATCC 25922), which was susceptible to
all tested drugs, was used as a reference control. Anti-microbial was chosen according to
Ethiopian food and drug administration (EFDA), which are commonly used for the
treatment of Salmonella in animals and humans were selected. The anti-microbial
susceptibility test was carried out for six antimicrobials using the disk diffusion method
on Mueller-Hinton agar (MHA). Inhibition zone was measured with caliper meter and
cross read with CLSI guideline standard and the manufacturer's recommendation as
susceptible, intermediate, or resistant in Table 1; (CLSI, 2018). Salmonella isolates that
fall under the resistance inhibition zone for three or more classes of anti-Salmonella drugs
were considered multiple drug-resistant (MDR) (Sweeney et al., 2018).
Data Management and Analysis
Raw data were entered, cleaned, and processed using the statistical software, STATA
12.0. Descriptive statistics was applied to summarize the data and expressed using
frequency and percentages. To identify the potential strong predictors of the outcome
variable, bivariate logistic regression followed by a multiple logistic regression model
was employed. 95% Confidence Interval (CI) and P value less than 0.05 were used as a
cut of point of significance. The odds ratio was used to assess the magnitude of
associations.
Results and Discussion
Occurrence of Salmonellosis
Out of a total of 140 samples collected from fish value chain samples, 51 (36.4%) were
found to be Salmonella positive. The occurrence of Salmonella in this study was found to
be consistent with the previous study conducted by Elhadi (2014) in Saudi Arabia, with an
Associated Risk Factors and Drug Resistance Profiles of Salmonella [84]
occurrence of 31-60 % in freshwater fish samples. This result was found to be higher than
with the occurrence of the previous study in China from the shanghai area of fish farms
(12.4 %) (Zhang, 2015), in Nigeria from selected fish farms and fish collected in the
market (11.5 %) (Raufu et al., 2014) and in Brazil from the fish market (4 %) (Ferreira et
al., 2014). The reasons for these prevalence variations might be due to water quality and
environmental distinctiveness (rainfall, temperature, sewage effluents; agricultural run-
off, and direct fecal contamination from natural fauna) (Percival and Williams, 2014;
Fernandes et al., 2018). In addition, food handlers' characteristics such as poor handling
and processing practices might contribute to such differences along the value chain. This
high prevalence in our study finding might be due to a lack of awareness in fish product
handling and poor post-harvest management practices from fishermen to end users along
the value chain.
Salmonella Concentration and Its Public Health Risk
The estimated microbial concentration of Salmonella in fish muscle varied from zero to >
110 MPN/g. Salmonella concentration in fish muscle was of low levels compared with
that of many studies on Salmonella concentration in meat products (Techathuvanan et al.,
2010, Wang and Mustapha, 2010).
There is too much variability to suggest a definitive cutoff point below which Salmonella
would cause illness (Jennifer et al., 2014). The likelihood of infection is dose-dependent.
While there may be a level of exposure below which illness is unlikely, reducing exposure
to high levels of Salmonella will undoubtedly reduce the risk of Salmonella illnesses, thus
improving public health (Jennifer et al., 2014, Dang-Xuana et al., 2018). Fish products
containing these higher levels of Salmonella pathogen are identified to show a high level
of contamination in Northwest Ethiopia. Thus, fish-origin foods have a public health risk
of salmonella. Qualitative and quantitative (enumerative) measures of Salmonella can
support activities that will reduce the actual levels of Salmonella in fish-origin foods. In
turn, this will allow the development and evaluation of mitigation to reduce both levels
and prevalence and thus, reduce the public health burden of salmonellosis (Dang-Xuana et
al., 2018).
Antibiotic Susceptibility Profile
Twenty-five percent of Salmonella isolates (13 out of 51) showed resistance to at least
one antibiotic. Ciprofloxacin was found to be the highest at 9.8 %, followed by
Ceftazidime at 5.9 %. Similar to our results, a study in Brazil by Carvalho cited by
Fernandes et al. (2018) isolated Salmonella strains of fish origin foods showed 4 %
resistance to tetracycline, 2 % to nalidixic acid, and 2 % to sulfamethoxazole. Slightly
lower levels of resistance for ciprofloxacin (2.3%), gentamicin (3.2%), ceftazidime
(0.5%) were recorded by Zhang (2015) in China. On the other hand, there are also
reports higher than our investigations, for instance, in Morocco, 49 % of Salmonella
isolates showed resistance to ampicillin, nalidixic acid, sulfonamide compounds, and
tetracycline (Setti et al., 2009). In Nigeria, Raufu et al. (2014) Isolated 23(100%)
antimicrobial resistance Salmonella strains from fish food. Zhou et al. (2019) in China, an
antimicrobial resistance profile for Salmonella in fish was evaluated showing resistance to
tetracycline (35.9%), ampicillin (28.2%), nalidixic acid (26.2%), trimethoprim-
Birhan et al., [85]
sulfamethoxazole (25.2%), chloramphenicol (4%) and streptomycin (18.4%). Another
study in Saudi Arabia showed that the highest antibiotic resistance was observed for
tetracycline (90.7%), followed by ampicillin (70%) and amoxicillin-clavulanic acid (45%)
(Elhadi, 2014). The causes for these high antibiotic resistance variations might be
attributed to variation in strain, quality of water, and consequence of natural selection and
genetic mutation variation which exacerbated by human factors such as inappropriate use
of antimicrobials (EFS A and EU CDC, 2019).
Multidrug resistance features of Salmonella were analyzed of which only 2 (3.9%)
isolates were resistant for three antibiotics (Ciprofloxacin (CIP-5 μg), Gentamicin (CN-
10 μg), and Ceftazidime (CAZ-30 μg). Even though a relatively low percentage of drug
resistance of Salmonella isolates in our study area was detected, it showed the potential
significant threat of the resilient isolates along the value chain of fish food. This
resistance in our study area might be due to indiscriminate use of antimicrobials in
human, agriculture, and veterinary medicines, contamination of the aquatic environment,
or poor hygiene condition in filleting of fish food that aids the spread of resistant
Salmonella isolates. In addition, resistance genes can be moved from other bacteria to
Salmonella isolates using transduction, conjugation, and transformation (Divek et al.,
2018). Salmonella antibiotic-resistant strains isolated in fish-origin foods may cause
dissemination of resistance genes to freshwater microbiomes, which can lead to harder
and more problematic to treat food-borne infections (Manyi-Loh et al., 2018; Fernandes
et al., 2018).
Risk Factors Associated with Occurrence of Salmonella
In multivariable logistic regression analysis of contamination of the lake, fish handling
and fish iced after landing were independent predictors of Salmonella in a fish. The
occurrence of Salmonella in a fish in a contaminated environment was about 1.06 (95%
CI: 1.04, 5.4) times extra probable compared with the environment which is kept non-
contaminated. The water quality, the fishery equipment, and landing site have a
straightforward effect on bacteriological fish pollution because the burden of Salmonella
in freshwater fish is on average 3.4 - 64% (Fernandes et al., 2018).
In addition to contamination, putting fish in ice after landing was a predictor of
Salmonella occurring in a fish. Salmonella in fish among non-iced fishes was 2.2 (95 %
CI: 1.09, 11.41) times more likely than those iced. This might be because water content
available in fish food, the temperature is can facilitate fully the proliferation of
Salmonella with virulent genes (Kumar et al., 2015).
Besides, Salmonella in fish with poor handling practices was about 1.8 (95 % CI: 1.02-
13.32) times more likely than those which were in good handling. Similar to our finding,
a study done by Mol and Tosun (2011) in Istanbul found that poor handling was about 2
(95 % CI=1.08, 3.32) times more likely to contaminate than in good handling. Quality
fish food comprises of safety, nutritious, hygienic, and psychologically acceptable (fit the
customer needs, specifications (internal and external /actual production) (Serena et al.,
Associated Risk Factors and Drug Resistance Profiles of Salmonella [86]
2017). Out of those the most uncompromised fish food quality problem is microbial
contamination (Liu, et al., 2018).
Conclusions
Salmonella contamination was common in fish meat products in northwest Ethiopia. This
indicates hygiene protocols needed to be applied to harvesting and processing fish from
harvest to mouth to prevent Salmonella contamination. Isolated Salmonella is resistant to
at least one drug. Thus, regular monitoring of fish muscle sold for consumption to know
the level and types of antimicrobial resistance is important. Among the associated risk
factors considered: contamination, low icing habit soon after landing, and poor handling
practice were statistically significant independent predictors of Salmonella occurrence.
Therefore, fishery associations and traders should undertake training on fish harvesting,
processing, and storage to prevent contamination. Processing plants should be built at
each landing site with the required facilities. A new code of practice to control Salmonella
infection and antimicrobial resistance should be installed in Ethiopia to ensure safe fish
products.
Competing interests
The authors declare that they have no competing interests
Funding
The study was financed by Addis Ababa University (Ref. No. LT/PY-089/2021
) and the National Fishery and Aquatic Life Research Centre of Ethiopian Institute of
Agricultural Research (Ref. No. 17.2/0409/2019).
Acknowledgments
We would like to thank Bahir Dar University for its financial, material, and ideal support.
We would like to thank the fish processors in our area of study for openly providing their
information.
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