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FOOD SCIENCE & TECHNOLOGY | RESEARCH ARTICLE
COGENT FOOD & AGRICULTURE
2024, VOL. 10, NO. 1, 2303792
Eect of Covid 19 on butchers and their coping strategies in
Kampala district
Joan Namakulaa and John Ilukora,b
aAgriculture and Natural Resource Economics, Makerere University Kampala, Kampala, Uganda; bDevelopment Data Group- Survey
Unit, Uganda
ABSTRACT
The study examined the effect of Covid-19 on butchers and their coping strategies using data
collected from120 butchers in Kampala City. The results show that COVID-19 reduced volumes
of meat supplied and sold, number of consumers and increased the buying and selling prices
during the lockdown. After the lockdown was lifted, number of consumers, Quantity of meat
supplied and sold increased but below original levels while prices continued to increase. The
effects of Covid-19 were associated with butcher’s experience, age, liquidity, and number of
meat sources. The main coping strategies were to increase the sales price, reducing quantity
bought from the source, using E-transactions and diversification to alternative economic
activities mainly farming, trading and boda-boda riding. Based on results, we recommend that
any support to butcher men should target youths and inexperienced butcher men to boost
their liquidity and encourage them to diversify by selling different types of meat.
1. Introduction
Meat is one of the most significant, nutritious, and
favored food items available to masses or people to
aid the fulfilment of most of their body requirements
(Higgs, 2000). It is a valuable source of high biological
value protein, iron, vitamin B12 as well as other B
complex vitamins, zinc, selenium, and phosphorus.
These micronutrients are important in maintaining a
healthy and balanced diet for optimal human growth
and development. Although these nutrients can be
supplied in sufficient amounts by consumption of a
range of fruit and vegetables, in many developing
countries and poor households, where the availability
of such foods may be limited, access to meat often
protects against malnutrition and improves child cog-
nitive development (Salters, 2018). However, the out-
break of the COVID-19 pandemic that disrupted the
economic activities across the world thus generating
wide-ranging public health, economic, and social
impacts including food value chains (The Covid-19
pandemic and meat supply chains; Hobbs, 2021).
Uganda reported its first Covid-19 case on 21
March 2020 (Ronald & Bongomin, 2020) and to curb
the spread of the virus, the government of Uganda
imposed two lockdowns. The first lockdown was
imposed on 20 March 2020 where the government
banned all international movements, closed all schools
and institutions, stopped public gatherings including
churches, non-agricultural places were allowed to con-
tinue operating while observing the Standard
Operating Procedures set by the ministry of health, all
monthly agricultural markets were suspended, public
means of transport were allowed to operate while
observing the SOPs and all these directives were to be
followed for 32 days (Ssebwami, 2020). After the lock-
down, the country was opened however after some
time the lockdown was re-imposed to curb the
covid19 cases that were increasing. The second lock-
down was imposed on 6 June, and this was imposed
for 42 days. In total Uganda experienced 170,504 coro-
navirus cases, 3630 deaths and 100,431 recoveries
(Worldometer, 2023) (Figure 1).
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
CONTACT Joan Namakula jnamakula8477@gmail.com Agriculture and Natural Resource Economics, Makerere University Kampala, Kampala,
Uganda
https://doi.org/10.1080/23311932.2024.2303792
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unre-
stricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the
posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
ARTICLE HISTORY
Received 29 August 2023
Revised 4 January 2024
Accepted 7 January 2024
KEYWORDS
Butchers; covid-19;
Kampala; beef; and goat’s
meat
REVIEWING EDITOR
Escudero-Gilete M. Luisa,
Universidad de Sevilla,
Spain
SUBJECTS
Agriculture; Agricultural
Economics; Agriculture
and Food
2 J. NAMAKULA AND J. ILUKOR
The COVID-19 pandemic and the response of gov-
ernment of closing schools, bars, hotels, recreation
sites and limiting movements adversely affected many
sectors of life and forced the governments globally to
enforce a lock down where movements were restricted
as public means of transport were stopped from oper-
ating (Ronald & Bongomin, 2020). As results, the eco-
nomic activities including agricultural production,
trade/marketing, and employment as well as con-
sumption were negatively affected (Patricia et al.,
2021). In Uganda, more than two thirds of the people
experienced a shock in their income because of the
Covid-19 crisis thus leading to worsening of food
security and dietary quality scores (Kansiime et al.,
2021). The pandemic preventive measures including
travel restrictions, border controls, and country lock-
downs, did not only take a huge toll on the economy
but also the livestock industry, such as global meat
production and supply chain.
The Covid 19 pandemic indirectly or directly
affected the supply and demand of meat through
the restrictions and lockdowns imposed by most of
the governments. The sudden closure of livestock
markets in March to October 2020 left cattle traders,
who are the critical part of the beef value chains
with market-ready animals and unable to access
buyers (Lynch 2020). Ilukor et al. (2022) found that
COVID-19 negatively affected cattle trades and
resulted into reduction in cattle sales, erosion in
operating capital, failure to sell animals while others
abandoned the business. Also, the unemployment
caused by the pandemic also forced consumers to
substitute the highly priced products like meat for
cheaper substitutes. However, the effect of Covid on
incomes of different households is different basing
on if the household stayed working full time during
the lockdown or the household was fully subjected
to unemployment. Households that stayed working
full time saved a lot of money with the reduced
expenditures on costs like transport while house-
holds that were fully subjected to unemployment
lost a lot of their incomes (The Covid-19 pandemic
and meat supply chains; Hobbs, 2021). In addition,
in other countries there was reduction in meat pro-
duction as some meat packaging facilities stopped
operating while others reduced on the number of
working hours (Ijaz et al., 2021).
Although many studies have been conducted on
the effect of covid-19 on the meat value chain and
its actors, no study to best of our knowledge at least
in Uganda has been undertaken to understand
impact of COVID-19 on the butcher shops and
butcher men yet and yet their role in linking con-
sumers and the meat producers especially abattoirs
and cattle traders is very critical in meat value chain
(Kyayesimira etal., 2018). They are the main custom-
ers of fresh meat and to a limited extent of meat
products but play acritical role in ensuring that cus-
tomers have access to enough and quality meat.
Butchers are important actors in the commercial
chain of meat where with all their knowledge and
beliefs, they are able to select the best types of meat
and meet the consumers’ expectations.
In this study, we assess the impact of COVID-19
on Butchers and their coping strategies in Kampala
with objective of generating strategies to ensure sus-
tainable to supply of meat products during similar
kind of the pandemics. More specifically, we deter-
mine whether Covid-19 affect the butchers in
Kampala or not, we characterize butchers based on
whether they affected or not; assess the effects of
COVID-19 on meat supply, sales, identify the
Figure 1. Stringency index and cumulative number of Covid-19 cases in Uganda from January 2020 to July 2022.
COGENT FOOD & AGRICULTURE 3
variables that lead to magnitude of effect and recov-
ery. The hypotheses were; Covid19 led to a reduction
in the volume of sales of meat, Covid 19 led to a
reduction in the number of meat customers. In this
paper we define Butcher shop as any place that has
been licensed for the sale of raw meat and a Butcher
as any person that has received a license to sell raw
meat (KCC., 2006). In the next section, we present
study area, methodology, results, discussion, conclu-
sion, and recommendations.
2. Literature review
2.1. Overview of Covid-19 out-break in Uganda
The Chinese authorities notified the World Health
Organization (WHO) on 31 December 2019 about a
mysterious respiratory infection which was spreading in
one of its provinces and by 12 January 2020 World
Health Organization (WHO) had confirmed that a novel
coronavirus (SARS-CoV-2) was the cause of the respira-
tory illness with pneumonia symptoms and it was later
named COVID-19 (Ssonko & Kawooya, 2020). Kiwanuka
(2020) reported that Uganda’s preparedness to Covid-19
started before its first case where the Ministry of Health
implemented four public orders that included notifica-
tion of Covid-19, prohibition of entry in the country,
control of Covid 19 and prevention of Covid 19. On 21
March, 2020 Uganda reported its first case of Covid-19
and by the end of 30th July there were 1147 cases
with 1028 recoveries, Uganda reported its first death
on23rd July 2020 (Kawuki et al., 2020).
Basing on the WHO guidelines and the global prac-
tice, Uganda instituted various restrictions to contain
the spread of the disease around the country (Kansiime
et al., 2021). On 30 March 2020, the government of
Uganda introduced 33 measures that were to help
prevent on the spread of the virus and these included
closure of schools, colleges and universities; prohibi-
tion of gatherings of 10 or more people; country-wide
travel restrictions and a curfew running between 19:00
and 06:30 hrs, among other measures and these mea-
sures were enforced till 2 June 2020 and during that
period between March and June, the number of cases
were observed to have fallen (Matovu et al., 2021).
With the relaxation of the measures, a sharp increase
was reported and by December, Kampala was having
the highest cases (Matovu et al. 2021).
According to Okello et al. (2020) the preventive
measures that have been popularized by WHO, gov-
ernments and ministry of health worldwide include
washing hands regularly using soap and water, social
distancing, not touching the face, covering the
mouth and nose while sneezing, wearing masks,
staying at home while not feeling well and seeking
medical attention when one has any symptoms.
2.2. Overview of meat sales and consumption
Meat is a good source of energy and some essential
nutrients including proteins and some micro nutri-
ents such as iron, zinc vitamin B12 (Godfray et al.,
2018). According to (Oil et al.), beef is the most
important source of meat for human consumption
and its demand has greatly increased because of the
increasing population, change in tastes and growth
in people’s income, the sector has been identified as
the most vibrant in the meat industry.
The global average per capita consumption of
meat and the amount of meat consumed are rising
and this is because of the different factors which are
increasing individual incomes and growing population
growth (Godfray etal., 2018). The per capita consump-
tion of all meat in Uganda is 12.1 kg, which is far from
the 50 kg advised by both FAO and WHO leaving the
country with a big consumption gap and therefore
there’s a lot that needs to be done to satisfy the local
market plus the export market. The main markets of
meat are divided into two segments are these are the
mainstream and premium segments, at the retail level
the markets are serviced by a network of road side
and market stall butcheries and these account for
75–80% of the meat sales in the country and on the
other hand are the premium markets that account for
about 16% of the meat sales and these are served by
the modern butcheries and supermarkets. Also, the
Ugandan market for processed meat is still undevel-
oped with a few companies with small scale establish-
ments producing meat products and meat value
addition has only been done by meat processors with
only one in Kampala with a notable operation.
According to Merlino (2017), it has been reported
that the global meat consumption is undergoing a
qualitative and quantitative change with a shift from
red meat consumption to white meat consumption,
(Godfray et al., 2018) reports that although meat is
source of nutrients for families, it also increases the
risk of chronical illnesses for example colorectal cancer
and cardiovascular disease.
2.3. Eect of Covid-19 on the sale of meat and
meat products
The pandemic affected the livestock industry by tak-
ing a hug toll on the meat production and supply
chains (Waltenburg et al., 2020). Due to several
4 J. NAMAKULA AND J. ILUKOR
countries’ travel restrictions, border controls, and
country lockdowns, compromised meat production
and supply due to difficulty in purchasing animal
feeds plus other inputs (Aday, 2020). This caused
problems of restriction of transportation of live ani-
mals and hence a drop in the capacity of meat and
meat products causing a decreased sale condition
that slowed down market activity. Additionally, there
was a decrease in government capacities to treat,
prevent and control animal diseases due to realloca-
tion of funds needed to respond to the pandemic
effectively. Trans-boundary diseases like foot and
mouth disease, African swine fever, avian influenza
plus other infectious diseases severely compromised
meat production and supply (Hashem et al., 2020).
According to FAO (2020), the virus directly and
indirectly impacted overall meat production due to
the rapid spread among meat plant workers. As a
result of prolonged contact with infected co-workers,
inability to follow social distancing at the work place,
shared working areas and common transportation
methods to and from work (ILO, 2020). Many plants
began to close to stop the spread of the virus on
larger scale and this contributed to the sharp decline
in the supply chain causing a decreased meat pro-
duction capacity. According to Marchant and Boyle,
the production capacity loss reached 25–43% in the
United States slaughterhouses.
The decrease in production, processing, distribu-
tion and marketing potential made it difficult for
farmers while searching for a more suitable market
to sell their animals (WHO, 2020). Furthermore, due
to temporary shutdown of food eateries, the sale of
expensive primal meat cuts was decreased hence
income coming from meat and meat products
declined. During this circumstance, meat production
decreased from 338.9 metric tons (carcass weight) in
2019 to 333.0 metric tons in 2020 (Yang etal., 2020).
2.4. Coping strategies to shocks
According to Isaac etal. (2021), coping strategy deci-
sions depend on shock characteristics which include
nature, intensity, frequency and duration, these
shocks may be isolated individual shocks, a sequence
of two or more shocks that may be independent of
the other or related. The different coping strategies
one would choose to reduce on the effects of the
shock depend on the costs where more intense
shocks may cause higher costs and one might be
forced to adopt different strategies when dealing
with less intense shocks (Isaac et al., 2021). A more
intense shock may lead to depletion of assets in
order to maintain the pre- shock levels especially
where savings are not enough for coping (Isaac
et al., 2021).
According to FAO (2020) among the main impacts of
Covid 19 are potential shortages of food items, food
price spikes and lost incomes as markets have been dis-
rupted, however its critical to preserve livelihood and
food production as well as support incomes to ensure
that the vulnerable people can access food and to
reduce on the increased post-harvest losses due to lim-
itations in transport and access to markets, improved
storage facilities and minimal processing of meat prod-
ucts has been introduced.
Hashem et al. (2020) in their study reported that
the experience acquired through the Covid 19 crisis
may also contribute to optimizing the part of live-
stock supply chain that includes processing, retail
and marketing by strengthening the relationship
between producers, retailers, targeted markets and
consumers, the inefficient relationship among the
mentioned parties led to wastage of meat which
would have been saved by using the internet and
online platforms.
With the Covid-19 situation, there are only two
alternatives of which one is to try to go back to the
normal we knew before so to avoid the social
impacts of high levels of unemployment or to con-
sider the new scenario as a turning point so as to
make a new start (Carracedo et al. 2021). For busi-
nesses to survive, it will depend on their ability to
adapt to the new situation and since small busi-
nesses have been hit hardest, they will have to rein-
vent themselves so as to survive in this scenario
(Carracedo et al. 2021).
3. Materials and methods
3.1. Study design and study area
The study adopted a cross sectional research design,
which involved both the descriptive and quantita-
tive design and it, helped to understand the descrip-
tive characteristics between traders dealing in the
different types of meat (beef & goatmeat) and the
impact of Covid-19 on their business. The target
population were butchers found in the five divi-
sions of Kampala that is Lubaga, Kawempe, Nakawa,
Central and Makindye divisions. The area was cho-
sen because it’s the most densely populated city in
Uganda with an estimate of 7 million people (day
population) in 2020 by UBOS in an area of
8451.9 km2 (Bamweyana et al., 2020). The sample
interviewed were selected using proportional
COGENT FOOD & AGRICULTURE 5
stratified random sampling using sampling frame
obtained from Kampala City Authority. The study
was conducted between 7 January 2022 and 2
February 2022 and a total of 120 butchers were
interviewed with 38 out of 77 from Lubaga division,
31 out of 56 from Makindye division, 21 out of 58
from Kawempe division, 18 out of 30 from central
division and 12 out of 36 from Nakawa division
(Figure 2).
Primary data was collected using a Computer
Assisted Personal Interview (CAPI) and the question-
naire was program using the Kobo collect tool. Data
collected included the socio-demographic data
including age, marital status, education level, gender,
the impact of Covid-19 on meat sales, meat supply,
prices, and customers. The summary of the data col-
lected is presented in Table 1.
3.2. Analysis
The main research questions were as follows that
we set out to answer were: (i) did COVID-19 out-
break affect butchers?, (ii) How were the butcher’s
affected?, (iii) which category of the Butchers were
affected by COVID-19?, (iv) Was there a significant
difference in meat supply, sales, and prices before
and during COVID-19 and during and after covid-19
restrictions were relaxed?, and (v) How did the
Butchers adapt to the COVID-19 restrictions? To
answer these questions, the two-sample test of pro-
portions for the difference in proportion using
group and two-sample t test for differences in
means as well as a two-sample test of proportions
using variables to test the changes in pre-COVID-19,
during COVID-19 restrictions and after the lifting of
COVID-19 restrictions using the STATA software
were ran. In addition, the bar and line graphs were
used to compare the changes in selected variables
in pre-COVID-19, during COVID-19 restrictions and
after the lifting of COVID-19 restrictions.
Also, we generated the variables of effect (during
the lockdown-before Covid19) and recovery (after
the lockdown-during the lockdown) for meat supply
and meat sales for both beef and goats’ meat. We
then estimate a truncated Tobit model to assess the
correlates of the magnitude of the effect of COVID-19
and recovery after the restrictions on different vari-
ables including supply and sales between
pre-COVID-19 and during the COVID-19 restriction.
The Tobit model on the magnitude of effect of
COVID-19 and the recovery after the COVID-19
restrictions on meat supply and sales is presented
as below.
The Tobit model can be represented as;
yXy
y
it
it
T
it it it
it
=++≥
αβ ε
0
0<<
0
where
yit
is the dependent variable,
β
T
is the
unknown parameters and
εσ
it N∼
()
0 2, . X
it
are the
independent variables and these include respon-
dent’s age, years in business, youth, primary, married,
sole owner, if covid affected transport costs, rent
costs, utility costs and the wages. In estimating Tobit
model, the variable of magnitude of effect for both
meat supply and sales were mostly negative and
they were transformed to positive by multiplying
them with −1.
Figure 2. Map of showing the dierent divisions in Kampala.
6 J. NAMAKULA AND J. ILUKOR
4. Results
4.1. Characteristics of butchers by type of meat
sold
As shown in Table 2, most of the Butchers that sell goat
meat are male (98.11%), married (75.47), have secondary
education (54.72) as their highest level of education and
their source their meat from abattoir (64.15%). Also,
most of the Butchers who deal in beef are male (97.32),
married (79.46) and most of them have secondary
(52.68) as their highest level of education. Majority of
the beef Butchers get their meat supply from slaughter-
houses, and some (3.57%) buy their meat from slaugh-
ter sheds. Most of the butchers are solely owned (75%)
and 29% are operated by youths. Results also reveal
that the share of beef butchers getting their meat from
abattoir is significantly higher compared to the goat-
meat butchers. Also, the share of butchers who reported
Covid to have affected their wages were higher in beef
than from goat.
4.2. How did Covid-19 aect or change butcher
business in Kampala
All the Butchers interviewed reported that they were
affected by Covid 19. Results from the t test reveal
that there was a significant difference between the
periods of during the lockdown and before Covid 19
in the quantity meat supplied, the buying price of
beef, meat sales, selling price of meat number of
employees and customers. The quantity of beef and
goats’ meat supplied and sold declined while the
prices increased except that there was no significant
difference in the buying price of goat meat (Table 3).
Table 1. Description of variables.
Variable Number Mean Std.Dev
Trader’s years in business 120 11.4 7.8
Age of the trader 120 36 8.7
If the trader completed primary = 1 and zero otherwise 120 0.4 0.5
If the trader is married = 1 and zero otherwise 120 0.8 0.4
If the trader is male = 1 and zero otherwise 120 0.97 0.2
If the trader is solely owned = 1 and zero otherwise 120 0.7 0.4
If the trader deals in beef = 1 and zero otherwise 120 0.9 0.3
If the trader’s transport costs were aected = 1 and zero otherwise 120 0.98 0.1
If the trader’s rent costs were aected = 1 and zero otherwise 120 0.4 0.5
If the trader’s utilities costs were aected = 1 and zero otherwise 120 0.4 0.5
If the trader’s wage costs were aected = 1 and zero otherwise 120 0.6 0.5
If the trader’s beef sales declined = 1 and zero otherwise 120 0.9 0.3
If the trader’s beef sales recovered = 1 and zero otherwise 120 0.99 0.9
If the trader’s goat meat sales declined = 1 and zero otherwise 120 0.4 0.5
If the trader’s goatmeat sales recovered = 1 and zero otherwise 120 0.98 0.2
If the traders beef supply declined = 1 and zero otherwise 120 0.9 0.3
If the traders beef supply recovered = 1 and zero otherwise 120 0.98 0.1
If the traders goatmeat supply declined = 1 and zero otherwise 120 0.4 0.5
If the traders goatmeat supply recovered = 1 and zero otherwise 120 0.97 0.2
If the trader’s meat sales declined = 1 and zero otherwise 120 0.98 0.2
If the trader’s meat sales recovered = 1 and zero otherwise 120 0.98 0.1
If the trader’s customers declined = 1 and zero otherwise 120 0.98 0.1
If the trader’s beef supply price reduced = 1 and zero otherwise 120 0.2 0.4
If the trader’s beef supply price recovered = 1 zero otherwise 120 0.8 0.4
If the trader’s goatmeat supply price declined = 1 and zero otherwise 120 0.2 0.4
If the trader’s goatmeat supply price recovered = 1 zero otherwise 120 0.9 0.3
If the trader’s beef selling price declined = 1 and zero otherwise 120 0.4 0.5
If the trader’s beef selling price recovered = 1 and zero otherwise 120 0.8 0.4
If the trader’s goatmeat selling price declined = 1 and zero otherwise 120 0.4 0.5
If the trader’s goatmeat selling price declined = 1 and zero otherwise 120 0.98 0.2
If the trader acquired credit = 1 and zero otherwise 120 0.26 0.44
Table 2. Characteristics of butcher traders by type of meat.
Variable Goat (%) Beef (%) Dierence
Gender
Male traders 98.11 97.32 0.79
Female 1.89 2.68 −0.79
Marital status
Married traders 75.47 79.46 −3.99
Not married 24.53 20.54 3.99
Education
Primary education 37.74 43.75 −6.01
Secondary 54.72 52.68 2.04
Tertiary 7.55 3.57 3.98
Source of meat
Abattoir 64.15 70.54 −6.39**
Slaughter house 56.6 74.11 −17.51
Slaughter shed 1.89 3.57 −1.68
Youth traders 30.19 28.57 1.62
Solely owned 67.92 75 −7.08
Covid 19 aected
Transport costs 100 53 57
Rent costs 11 46 −35
Utility costs 8 43 −35
Aected wages 28 69 −41***
Acquired credit 18 29 −11
***p < 0.001; **p < 0.01.
COGENT FOOD & AGRICULTURE 7
4.3. How are the butcher business performing
post Covid-19
Also results reveal that there was a significant differ-
ence between the periods of after and during the
lockdown in the quantity of meat supplied and sold,
the buying and selling price of meat, the weekly cus-
tomers, and the number of employees (Table 4).
Therefore, butchers recovered from the effect of
Covid-19 with the quantity of beef and goats’ meat
supplied and sold increasing. However, the prices
increased instead of declining.
4.4. Eect of Covid 19 on daily beef and goat
meat supply
Results from the study reveal that the quantity of
beef and goat meat bought by the butchers from
their sources during the lockdown reduced from the
pre-COVID and after lifting the lockdown, the quan-
tity of meat bought increased. The average daily sup-
ply of meat reduced to 55.99 kgs in beef and 15.74
kgs in goatmeat during the lockdown. However, after
the lockdown was lifted, there was a gradual increase
in the daily quantity of beef supplied (90.74 kgs) and
goatmeat (27.27 kgs1). Goat meat was more affected
during Covid 19 and also during the recovery pro-
cess it recovered higher than beef (Figure 3).
4.5. Eect of Covid19 on weekly meat sales
The results from the study reveal that Covid 19
resulted to significant reduction in the weekly beef
sales by 60.58% during the lockdown and significant
increase of 68.46% after the COVID-19 restrictions
were lifted (Figure 4). Also, the weekly average
goatmeat sales significantly reduced by 68.09% during
the Covid-19 and significantly increased by 71.69%
after the lockdown was lifted. The effect for during
and after the lockdown was higher in goatmeat than
in beef (Figure 4).
4.6. Eect of Covid19 on the buying and selling
price of meat
Results reveal that COVID-19 led to increase in both the
buying and selling price of both beef and goatmeat.
During Covid, the average buying price of beef signifi-
cantly increased from ugx 9995.536 ($2.78) to
ugx11636.36 ($3.14) and later significantly increased to
ugx11830.36 ($3.2) after the Covid 19 restrictions were
lifted. The average buying price of goat meat signifi-
cantly increased from ugx 13990.57 ($ 3.89) to
ugx14452.83 ($3.91) during the COVID-19 and then sig-
nificantly increased to ugx15235.85 ($4.12) after lifting
of COVID-19 restrictions. Also, the selling price of beef
significantly increased from ugx 12339.29 ($3.43) to
ugx13339.29 ($3.61) during the lockdown and then sig-
nificantly increased to ugx13870.54 ($3.75) after the
Covid-19 restrictions were lifted. The selling price of
goat meat slightly increased from ugx 16905.66 ($4.69)
to ugx17037.74 ($4.60) during the lockdown and then
significantly increased to ugx18396.23 ($4.97) after the
Covid-19 restrictions were lifted (Figure 5).
4.7. Eect of Covid 19 on the number of
customers served every week
Results from the study show that Covid 19 had an
impact on meat customers. There was decline in the
average number of customers during the lockdown
but later after the Covid 19 restrictions were lifted,
Table 3. T-test for eect of Covid 19.
Variable During Before Dierence
Beef
Quantity of beef
supplied (kg/wk)
391.94 924 −532.06***
Buying price of beef
(shs)
11636.36 9968.18 1668.18***
Beef sold (kg/wk) 325.29 825.29 −500***
Selling price of beef
(shs)
13339.29 12339.29 1000***
Goat meat
Quantity of goat meat
sold (kg/wk)
110.15 359.44 −249.29***
Buying price of goat’s
meat (shs)
14452.83 13990.57 462.26
Goat sold (kg/wk) 103.81 325.36 −221.55***
Selling price of
goatmeat (shs)
17037.74 16905.66 132.08
Number of employees 1 2 −1**
Weekly customers 141 340 −199.01***
***p < 0.001; **p < 0.01.
Table 4. T test for post Covid behavior.
Variable After During Dierence
Beef
Qty of beef supply (Kg/
wk)
635.19 391.94 243.25***
Buying price of beef 11830.36 9995.54 1834.82***
Beef sales (kg/wk) 547.97 325.29 222.68***
Selling price of beef 13870.54 13339.29 531.25***
Goat
Qty of goat meat
supply (kg/wk)
190.87 110.15 80.72**
Buying price of goat’s
meat
15235.85 14452.83 783.02*
Goat sales (kg/wk) 178.23 103.81 74.42***
Selling price of
goatmeat
18396.23 17037.74 1358.49**
Number of employees 1.65 1.12 0.54**
Weekly customers 216.98 141.19 75.78***
***p < 0.001; **p < 0.01; *p < 0.05.
8 J. NAMAKULA AND J. ILUKOR
132
55.99
90.74
51.35
15.74
27.27
0
20
40
60
80
100
120
140
retfAgniruDerofeB
Mean (kgs/day)
period
Beef supply Goat supply
Figure 3. Impact of Covid 19 on daily beef and goat supply.
825.29
325.29
547.97
325.36
103.81
178.23
0
200
400
600
800
1000
1200
1400
retfAgniruDerofeB
Mean ( Kgs)
Period
Weekly Beef sales Weekly goat sales
Figure 4. Eect of Covid 19 on weekly meat sales.
9995.536
11636.36 11830.36
13990.57 14452.83 15235.85
12339.29 13339.29 13870.54
16905.66 17037.74 18396.23
0
5000
10000
15000
20000
retfAgniruDerofeB
Mean (ugx)
Period
beefsupply price goatsupplypricebeefselling pricegoatselling price
Figure 5. Covid eect on buying and selling price.
COGENT FOOD & AGRICULTURE 9
there was a gradual increase in the average custom-
ers (Figure 6).
4.8. Correlates of the magnitude of Covid 19
eect on meat supply and meat sales
The magnitude of beef supply is positively correlated
with customer effect, butchers that have attained
primary level of education and married butchers,
butchers whose utility costs were affected and nega-
tively correlated with goat supply effect and butch-
ers’ wages were affected by Covid 19. And the
magnitude of goat supply is positively correlated
with beef supply price effect, and traders who
acquired credit because of Covid 19 and negatively
correlated with goat supply price effect and beef
supply effect.
For sales, the magnitude of beef sales is nega-
tively correlated with the respondent’s age, customer
effect and butchers whose wages were affected and
positively correlated with the goat sale price effect
and butchers whose utility costs were affected. And
the magnitude of goat sales is negatively correlated
with the number of years in business and the beef
sale price effect (Table 5).
4.9. Correlates of the recovery on meat supply
and meat sales
The key variable explaining recovery in beef supply
are goat supply recovery, customer recovery and the
fact that Covid 19 affected the utility costs. The
degree of recovery increases for all those variables.
For goat supply, the key variables explaining it are
the goat supply price recovery and beef supply
recovery and the degree of recovery increases for
both variables. Meanwhile, the key variables explain-
ing recovery of beef sales are respondents age, goat
sale price recovery, customer recovery and married
butchers. The degree of recovery increases with cus-
tomer recovery, among married butchers and it
reduces for respondent age and goat sale price
recovery. For goat sales, the degree of recovery
increases for beef sale price recovery (Table 6).
4.10. Coping strategies
Butchers were asked if Covid-19 affected their meat
supply and 99% butchers reported that Covid 19 had
affected their beef supply and 98% reported Covid
19 to have affected their goat supply. When asked
how they coped up with the decrease in meat sup-
ply, 99.17% traders reported to have reduced on the
quantity bought from the source, 32.5% used more
than one source of supply and 0.83% coped up in
other ways like borrowing money to buy the meat,
stopped supplying goat’s meat (Figure 7).
Butchers were also asked about the effect of
Covid 19 on their supply price. 96.43% and 83.02%
butchers reported that Covid the beef supply price
and goat supply price respectively. Most of the trad-
ers (92.5%) coped up by reducing the quantity of
meat bought from the source and the least (2.5%)
reported to have done nothing (Figure 8).
All traders reported Covid to have affected their
sales and when asked how they coped with the
decrease in sales, most of them (99.17%) reported to
have reduced their volume of sales and the least
48 20 31
340
141216
1236
507
828
0
200
400
600
800
1000
1200
1400
retfAgniruDerofeB
mean
period
Daily customers Weekly customers Monthly customers
Figure 6. Eect on the number of customers served every week.
10 J. NAMAKULA AND J. ILUKOR
(6.67) reported to have coped in other ways like
reducing the selling price of meat and stopping the
daily supply (Figure 9).
Butchers reported to have engaged in other
activities like farming (43.48%), trading (34.78%),
boda-boda (13.04%) on top on the meat business
(Figure 10).
5. Discussion
The results show that traders were affected. The
quantities for both supply and sales were signifi-
cantly affected plus the number of employees and
customers reduced. Butchers who buy their meat
from abattoirs reduced significantly. This is because
butchers started sourcing their meat from local sup-
plies. This is because with the Covid 19 restrictions.
Moving from one place to another was restricted
and the therefore workers were not able to go to
their places of work. This agrees with finding by
Nuwematsiko et al. (2022) who stated that the clo-
sure of public transport except for those offering
essential services led to consequences and increased
vulnerability among the different groups of people.
The average daily supply of meat (beef and goat-
meat) reduced during the lockdown. Butchers
attributed this to the restriction on movement which
limited cattle movement and to decrease in volume
of sales and in the butcher’s income. This is
consistent with Ilukor et al. (2022) (Md. Tanvir
Rahman et al., 2022) who reported that due to the
restriction on movement resulted to reduction in cat-
tle sales, erosion in operating capital, and failure to
sell animals while others diversified or moved to
other businesses thus leading to decline in cattle
sales and consequently beef supply and sales. In
addition, a decrease in the meat sales during the
lockdown could also be attributed to reduction in
number of customers because places like schools,
bars, hotels, and recreational sites were closed and
yet these are the main consumers of meat (Ndaiye
et al. 2022). Also, the closure of businesses led to
decrease in the purchasing power of both the poor
and the unemployed leading to low demand of cer-
tain goods in both rural and urban areas.
After the Covid 19 restriction were lifted, the
quantity supplied and sold increased however these
haven’t gone back to the way there were before the
pandemic. This was because of the increased demand
for meat as some institutions like hotels were opened
and allowed to operate. In addition, the buying price
of meat from the different sources has either
remained high or increased during the lockdown
and even after the lockdown was lifted which is
butchers attribute to the increased costs incurred by
the cattle traders while transporting the cattle to the
cattle markets (Mercy Corps, 2020). This has reduced
consumer purchasing power and its reason why the
Table 5. Tobit results for meat supply and sales eect.
Variable
Magnitude
Beef supply Goat supply Beef sale Goat sale
Respondent age −1.792 0.713 −25.045*** 9.582
Years in business 1.302 −1.359 26.071** −18.745*
Beef supply price
eect
−0.011 0.01*
Goat supply price
eect
0.006 −0.015***
Beef supply eect −0.307**
Goat supply
eect
−0.38**
Beef sale eect −0.193
Goat sale eect −0.161
Beef sale price
eect
−0.041 −0.08***
Goat sale price
eect
0.052*** −0.198
Customer eect 0.041*** −0.016 −0.339*** −0.032
Primary 27.225* 6.222 78.793 135.788
Married 24.712* 0.346 93.175 10.794
Sole owner 9.037 6.891 25.85 15.981
Rent costs were
aected
10.858 0.108 −22.356 132.279
Utility costs were
aected
38.176** −21.054 203.019* −74.009
Wages were
aected
−30.884** 10.477 −265.162*** 72.113
Covid led to
credit
−3.092 19.115* 2.356 106.837
***p < 0.001;**p < 0.01;*p < 0.05.
Table 6. Linear regression and Tobit results for meat supply
recovery.
Variable
Recovery
Beef supply
Goat
supply Beef sales Goat sales
Respondent age 0.546 0.393 −7.295* 0.756
Years in business 0.414 −0.647 5.21 −2.644
Beef supply price
recovery
0.003 −0.002
Goat supply price
recovery
−0.001 0.003***
Beef supply recovery 0.424*** −0.005
Goat supply recovery 0.708***
Goat sale price
recovery
−0.017* 0.002
Beef sale price
recovery
0.017 0.021**
Beef sale recovery
Goat sale recovery 0.181
Customer recovery 0.017* 0.006 0.271*** 0.023
Primary 10.788 −0.446 52.54 9.225
Married 3.027 7.732 93.808* 19.327
Sole owner −4.593 1.731 −2.567 −11.275
Rent costs were
aected
4.948 3.206 22.271 17.27
Utility costs were
aected
14.979* −9.046 5.269 −45.294
Wages were aected −3.909 8.155 −52.487 57.572
Covid led to credit −3.801 −2.526 0.96 −38.502
***p < 0.001;**p < 0.01;*p < 0.05.
COGENT FOOD & AGRICULTURE 11
quantity supplied and sold haven’t gone back to the
way there were before the pandemic These suggests
that COVID-19 is likely to impact longer-term meat
consumption and may affect nutrition.
The correlates for magnitude of effect and recov-
ery of both meat supply and effect show that the
two types of meat are not affected by the same vari-
ables. According to the effect of meat supply, with
increase in the supply of beef there is reduction in
supply of goat meat, and this shows that the two
commodities are substitutes. This agrees with
Chanyalew and Abenet (1997) who state that goat
and beef are substitutes. The beef sale recovery leads
to an increase in the goat sales recovery and this
shows that the two commodities are complements.
Customers are significant in both effect and recovery,
99.17
32.5
0.83
020406080100 120
Reduce on supply
Use more than one source
others
Percentage
strategy
Figure 7. Cope up with decrease in meat supply.
35.83
92.5
3.33
49.17
2.5
2.5
0102030405060708090100
Change source of supply
Reduce quanty supplied
Buy meat in a group
Charge higher prices
Did nothing
Others
percentage
strategy
Figure 8. Cope up with increase in supply price.
99.17
15
23.33
6.67
020406080100 120
reduced supply
Reach out on phone
customery deliver
others
percentage
Strategy
percent
Figure 9. Cope up with decrease in volume of sales.
12 J. NAMAKULA AND J. ILUKOR
and this is because the driving factor of the meat
business are the customers. A reduction in the cus-
tomers will negatively affect the business and an
increase in the number of customers will lead
increase recovery.
To cope up with the effect of the pandemic, butch-
ers adopted various method for example reducing the
quantity bought from the source, charging higher prices
to customers, using phones to make orders, using boda
bodas and engaging in other activities. However, the
idea of customer delivery was not higher adopted, and
this was because of the technicality involved while
using the system and this agrees with (Hashem et al.,
2021) who reported that agricultural stakeholders in
developing countries have difficulty in use and availabil-
ity of the agricultural ICTs. The slow adoption of the sys-
tem associated with fact that some individuals find
happiness in physically going to the shops (Freathy &
Calderwood, 2014).
6. Summary and conclusion
The findings from the study revealed that butchers
were negatively affected with decrease in the quantity
of meat bought from the source, increase in the buy-
ing prices of meat, decrease in the volume of sales
and in the number of customers as the main effects.
The findings also show that butchers came up with
different mechanisms to cope up with the negative
effects of Covid 19. Majority of the butchers reduced
the quantity of meat bought, increased the price of
meat, adopting the customer delivery method and
some butchers decided to engage in other economic
activities to increase on their incomes. For the butch-
ers to fully recover from the shock caused by the
Covid 19 pandemic and for them not to be very
affected in case another pandemic happens. The gov-
ernment should provide a favourable environment for
financial institutions to offer loans to the butchers so
that they can recovery from the pandemic. Stake
holders in the meat business should prioritize the
youths. This is because according to the results, adult
traders recovered faster than the youth. Further stud-
ies need to be done on the role of agricultural ICT on
meat marketing to know if this can help farmers in
case a shock happens.
Acknowledgement
We would like to acknowledge Makerere University
department of agribusiness the Beef Research Platform.
The authors would also like to acknowledge the butchers
who agreed to spare time to respond to the interviews.
Disclosure statement
No potential conict of interest was reported by the
author(s).
Data availability statement
Data for this manuscript is availability and it can be pro-
vided when requested for.
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