ABSTRACT
Assessment of bacterial and fungal contamination of Automated Teller Machines (ATMs) in some banks in Michael Okpara University Agriculture was investigated. Two Automated Teller Machines from each of five banks in the school were used and three machine parts, screen, button and shutters were swabbed and cultured for bacteria and fungi growth and antibiogram. Results obtained show mean bacteria load of 2.2 x 105 cfu/ml to 5.5 x 105 cfu/ml in the screen, 3.5 x 105 cfu/ml to 6.5 x 105 cfu/ml in the buttons and 2.0 x 105 cfu/ml to 3.0 x 105 cfu/ml in the shutter. The fungal load 1.0 – 2.5 x 102 cfu/ml in the screen and buttons each and 0.5 – 1.5 cfu/ml in the shutter. Also up to seven bacteria species and four fungi species were isolated with varying occurrences. The bacteria isolates included Staphylococcus, Streptococcus, Bacillus as Gram positive while Enterobacter, Escherichia and Pseudomonas as Gram negative bacteria isolates are with occurrences in the range of 11.0% (Pseudomonas), Staphylococcus 21.5%; Escherichia coli 15%, Streptococcus spp. 22.5%, Enterobacter 12.5%, Coagulase negative Staphylococcus 14.0%, Penicillium spp. 18.8%, spp. 13.5%. Occurrence was from 15.0% (Rhizopus), Aspergillus niger 30%, Penicillium spp. 18.5%, Yeast 36.5% to 30.0% . The bacteria isolates antibiogram show a high resistance in the range of 44.4% (Bacillus) to 88.9% (Pseudomonas). The react further show that there are more variations in the occurrence of the isolates in the different parts of the machines on one hand and between the Automated Teller Machines in the different banks within the school. First bank Automated Teller Machines and Eco bank Automated Teller Machines had more organisms than the other banks with records of 75% to 100% (1.5/ to 2/2). Also the screen and buttons were more contaminated than the shutter and that was reflected in all the banks studied. The different drugs had varying effects on the organism. Ampiclox, Ampicillin, Pefloxacin were the least potent as all the test organisms exhibited resistance to them while Oflaxacine, Gentamycin and Ciprofloxacin were the most potent drugs having recorded susceptibility of more than four isolates each. It was concluded that the high prevalence of different microbial isolates in the Automated Teller Machines implying equally high level of contamination and which calls for public health concern.
TABLE OF CONTENTS
Title page i
Certification ii
Dedication
iii
Acknowledgement
iv
Table
of Contents v
List
of Tables vii
Abstract viii
CHAPTER ONE: INTRODUCTION
1.1 Background of the study 1
1.2 History
of Automated Teller Machine 2
1.2.1 The
Spread of Automated Teller Machines 3
1.2.2 Automated
Teller Machines Today 4
1.3 Aims and Objectives 4
1.4 Justification 5
1.5 Scope of Work 5
1.6 Statistical analysis 6
CHAPTER
TWO: LITERATURE REVIEW
2.1 Automated
Teller Machines (ATM) 7
2.2 Types
of Automated Teller Machine 7
2.2.1 Benefits
of Automated Teller Machines 9
2.3 Uses
of Automated Teller Machine 9
2.4 Places
to Find Automated Teller Machine in Nigeria 12
2.5 Microbes
Associated With Automated Teller Machines (ATMs) 12
2.6 Microorganisms
in Automated Teller Machines and where they can be found 14
2.6.1
Automated Teller Machine Screen 15
2.7 Microorganisms
Isolated From the Keypads of the Automated Teller Machine 15
2.8 Ways
to Reduce Microbial Contamination on Automated Teller Machines 16
(ATMs)
2.8.1 Assumption on how Microorganism can be
reduced on Automated 17
Teller
Machine
Screen
2.9 How
Microorganism Contaminate the Automated Teller Machine Screen 18
2.10 Research
Works on Automated Teller Machine (ATM) Microbiology 19
CHAPTER THREE: MATERIALS AND METHODS
3.1 Sources
and Materials 22
3.2 Sample
Collection 22
3.3 Procedure 22
3.4 Inoculation
of Media 23
3.5 Identification and Characterization of
Bacteria and Fungi Isolate 23
3.5.1 Gram
Staining 23
3.5.2 Catalase
Test 24
3.5.3 Methyl
Red Test 24
3.5.4 Citrate
Test 25
3.5.5 Coagulase
Test 25
3.5.6 Oxidase
Test 25
3.5.7 Indole
Test 25
3.5.8 Voges Proskauer Test 26
3.5.9 Motility
Test 26
3.6 Identification
of Fungi Isolates 28
3.7 Identification
of Bacteria Isolates 28
3.8 Antibiotics
Susceptibility Testing 28
CHAPTER FOUR: RESULTS
4.0 Results 30
CHAPTER FIVE: DISCUSSION,
CONCLUSION AND RECOMMENDATIONS
5.1 Discussion
44
5.2
Conclusion 46
5.3 Recommendations 46
References
Appendices
LIST
OF TABLES
Table Title Page
1: Biochemical
test for identification of microorganism 33
2: Morphological
and characterization of fungal isolates 34
3: Occurrence
of bacteria isolates from Automated Teller Machines in
Michael
Okpara University of Agriculture Umudike, Umuahia 35
4: Occurrence of fungal
isolates from Automated Teller Machine in
Michael Okpara
University of Agriculture Umudike, Umuahia 36
5: Total
heterotrophic count (cfu/ml) of screen samples obtained from
Automated
Teller Machine in banks in Michael Okpara University of
Agriculture, Umudike 37
6: Total
heterotrophic count (cfu/ml) of button samples obtained from
Automated
Teller Machine in banks in Michael Okpara University of
Agriculture, Umudike 38
7: Total
heterotrophic count (cfu/ml) of shutter samples obtained from
Automated
Teller Machine in banks in Michael Okpara University of
Agriculture, Umudike 39
8: Total
fungal count (cfu/ml) of screen samples obtained from Automated
Teller
Machine in banks in Michael Okpara University of Agriculture,
Umudike 40
9: Total
fungal count (cfu/ml) of button samples obtained from Automated
Teller
Machine in banks in Michael Okpara University of Agriculture,
Umudike 41
10:
Total fungal count
(cfu/ml) of shutter samples obtained from Automated
Teller
Machine in banks in Michael Okpara University of Agriculture,
Umudike 42
11: Susceptibility
of bacteria isolates in Automated Teller Machines to some
antibiotics 43
CHAPTER ONE
1.0 INTRODUCTION
1.1 BACKGROUND OF
THE STUDY
Increasing
number of people are using Automated Teller Machine (ATM) as time crawls by
(Tekerekoglu et al., 2012).
Microorganisms are very small that they can’t be seen unaided natural human
eyes except by the use of a microscope (Christner et al., 2008). Jansen
(2001) observed that microorganisms are ubiquitous and have an amazing ability
to adapt to new environment and further multiply in large numbers within a
short time. According to Christner et al.,
(2008) pathogens spread among people with direct and indirect contact on
hands or inanimate object and this makes health care settings to put in place
control measures to reduce microbial transmission in their ways. (Dogan et al., 2008) stressed the importance of
improving hand hygiene as an important strategy for significant reduction of
spread of pathogens in the public as supplements to vaccination and public
enlightenment programs
Automated
Teller Machines (ATMs) in Banks have become an essential requirements of social
life while their machines are frequently localize in city centers, trade areas
and elsewhere, hundreds of people of diverse social economic and hygiene state
use these machines daily. Customers make contact with the surface of the
machines including keypads, screen and buttons. Hand born transmission is said
to be one of the important routes for many infectious agents to spread in a
community (Janson, 2001), given that handshakes, patting etc are regular
greeting associate in our culture and tradition. Iquo et al., (2015), observed that most users of Automated Teller
Machine (ATM) are largely ignorant of the potential hazards they face each time
they use an Automated Teller Machine. Also studies by the United States Center
for disease control (USCDC, 2005) revealed that microorganism could be passed
from contaminated hands to cyber appliances such as surface of keyboard of
Automated Teller Machine (ATM) and subsequently passed into other unsuspecting
users of the appliance.
Some
research report on Automated Teller Machines (ATM) in other parts of the
country has recorded varied level of contamination of the machines by microbes
and this has been attributed to different possible factor which include of user
as well as the environmental condition around the Automated teller machines. (Chairman
et al., 2011). Also Automated Teller
Machines (ATMs) at various locations showed strong variation in the microbial
load and flora. It has been suggested that public health professionals need to
know the hygiene status of Bank Automated teller machines in order to develop
preventive measures against the health risk caused by such devices. The
investigation of microbial quality of Automated Teller Machine (ATM) devices
may be a valuable tool to increase ones knowledge and awareness about possible transmission
ways of pathogens in public.
1.2 HISTORY OF AUTOMATED TELLER MACHINE
Many
experts believe that the first Automated Teller Machine was the creation of an
American inventor and businessman named Luther Simjian. Simjian held patents on
all kinds of things-including an array flight simulator, a colour x-ray
machine, a bicycle and a teleprompter but he was best known for his work on
bankography, a machine that could accept cash or check deposits at any hour of
the day (Batiz-lazo et al., 2014).
In
1960, Simjian managed to persuade a New York City Bank to take a few of his
automatic deposit machines. So that customers could trust that they would see
their money again, there was a microfilm camera inside the bankograph that took
a snapshot of every deposit. Customers received a copy of the photo as their
receipt. Still, the Bankograph did not catch on. The only people using the
machines were prostitutes and gamblers who didn’t want to deal with tellers
face to face. Simjian explained, and there were not enough of them to make the
machines a worthwhile investment.
By
the end of the 1960s, however, times were changing and a broader segment of the
population more comfortable with the idea of self-service and more willing to
trust unfamiliar technologies was willing to give automated banking a try. In
1967, a Scottish inventor named John Shepherd Barron was sitting in the bathtub
when he had a flash of genius: if vending machines could dispense chocolate
bars, why couldn’t they dispense cash? (John, 1967). Barclays, a London bank,
loved the idea, and Shepherd Barron’s did not use plastic cards. Instead, he
used paper vouchers printed with radioactive ink so that the machine could read
them. The customer entered an identification code and took her cash a maximum
of £10 at a time (Mary, 2011). The first Automated Teller Machine in the United
State was devised by a Dallas engineer and former professional baseball player
named Donald Wetzel. Wetzel’s machine used plastic cards like the ones we use
today (instead of radioactive ink, the cards stored account information in
magnetic strips) in September 1969, a chemical Bank branch on long Island
installed the first of Wetzel’s machines.
1.2.1 The Spread of Automated Teller Machines
By
1970, Dozens of United State banks had jumped on the Automated Teller Machine
bandwagon. To introduce this new machine to customers, banks used all kinds of
advertising tricks. For example, to get the attention of female customers, a
bank in Columbus, ohio, sponsored a six-hours Paul Newman movie marathon on a
local television channel. Every 25 minutes during the movies, commercials for
the bank touted the advantages of its new cash-dispensing machine.
However,
it took a corporate gamble and a blizzard for the Automated Teller Machine to
win the confidence of American consumers. In 1977, the chairman of Citibank
took a huge risk, spending more than $100 million to install Automated Teller
Machines all over New York City. That investment paid off the following January
when a huge blizzard hit New York, dumping 17 inches of snow on the city. Banks
were closed for days. Meanwhile, Automated Teller Machine use increased by 20
percent within days, Citibank had launched its by-now-familiar “The citi never
sleeps” and campaign. Posters and billboards showed customers trudging through
snow to get to Citibank Automated Teller Machines. After that, almost every one
of the country’s banks followed citi’s lead. The era of the Automated Teller
Machine was underway.
1.2.2 Automated Teller Machines Today
Today,
there are almost 2 million Automated Teller Machines around the globe. Although
use of the machines has declined in recent years, likely because more people
make purchases using credit and debit cards instead of cash, the Automated
Teller Machine continues to have a place in modern culture. Today’s machines
sell everything from airtime tickets to movie tickets to medicine (Harper et al., 2013).
1.3 AIMS
AND OBJECTIVES
The
aim is to study the microbial contamination of Automated Teller Machines
(ATMs). The aim of this study is to assess the level of microbial contamination
of Automated Teller Machines (ATMs) in some banks in Umuahia. The objective
includes specifically, the following:
a. To determine the bacteria and fungi
load of different part of Automated Teller Machines (ATMs) in banks in Umuahia.
b. To determine the prevalence
(occurrence) of the different bacteria and fungi isolate from the different
parts of the test Automated Teller Machines (ATMs) in the different banks
c. To evaluate the potential health
risk (if any) to which Automated Teller Machine (ATM) users in Umuahia are
exposed on the basis of findings from the project work.
1.4 JUSTIFICATION
This work
was done to compare existing knowledge and research associated with the use of
Automated Teller Machines (ATMs) like Bacteria Found On Banks Automated Teller
Machines by Tekerekoglu et al., (2012) may lead to undue
exposure of users to health risks whereas a compared knowledge of such risks
(as may be seen from this work) may enable users to be cautious in their
contact with the Automated Teller Machines (ATMs). Again such information as
may be obtained from this work may assist health official in handling health
situation and planning preventive health care for the public.
1.5 SCOPE
OF WORK
The
project work will cover the isolation, characterization and identification of
bacteria and fungi isolates from the test Automated Teller Machine (ATM),
Antibiotic susceptibility test. The work will also evaluate the relative
occurrence of the different isolates, assessment of their respective occurrence
(prevalence) as well as their pathogenecity as a basis of projecting possible health
risk to users.
Against the
above background, this project work was conceived to assess the microbial
(Bacteria and fungi) contamination of Automated Teller Machines (ATMs) in banks
in Michael Okpara University, Umuahia.
1.6 STATISTICAL
ANALYSIS
A
statistical analysis of the level of variation (ANOVA) between the Automated
Teller Machines (ATMs) from the different banks on one hand between the status
of the different Automated Teller Machines (ATMs) parts studied.
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