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G.J.B.B., VOL.4 (4) 2015: 406 - 411 ISSN 2278 –9103
406
IMPACT OF EBOLA ON FARM PRODUCTIVITY AS PERCEIVED BY
FARMERS AND EXTENSION AGENTS IN SIERRA LEONE
Mohamed Paul Ngegba1,Elizabeth Tiangay Bangura2& Sheku Kenaway Moiforay3
1Department of Extension and Rural Sociology, School of Agriculture, Njala University, Njala Campus
2Department of Community Health and Clinical Sciences, School of Community Health Sciences, Njala University, Bo Campus
3Department of Animal Science, Njala University, Njala Campus
ABSTRACT
The Ebola epidemic outbreak that hit the three West African Countries (Guinea, Liberia, and Sierra Leone) is described as
the largest outbreak in history. The epidemic caused devastating effects on human beings, economic activities and food
security in these countries The magnitude and extent of these activities have been speculative especially that of food
security. This paper reports study that investigated the magnitudes of the impact of Ebola scourge on farm productivity
from farmers’ and extension workers’ perspectives. The study was conducted in two districts – Bo and Moyamba in the
Southern Province of Sierra Leone. Stratified random sampling technique was used to select the two districts. Propulsive
random sampling technique was adapted to select the farmers and extension workers in these districts. A questionnaire
comprising four scales was employed to collect data from 160 (150 farmers and 10 extension workers) community
members selected from 15 quarantined communities in these two districts. The findings of the research revealed that most
of the farmers were in their socio-economically active age, ranging from 36 to 55 years. The study further showed that
post–planting activities- fencing, hunting, bird scaring (28.8%) and crop harvesting (61.3%) were most severely affected
by the Ebola outbreak in quarantined communities. These activities normally take place between the months of June and
November, which coincided with peak of the Ebola epidemic in the country. Further still, it revealed that the disease
outbreak to a very great extent decreased food affordability and financing (99.4%), food availability, storage and protection
(98.1%), processing and preservation, marketing, and food accessibility (97.5%). The major recommendation based on the
findings was that: Government and other donor bodies should consider the deteriorating trend of farmers’ health and food
security to give them priority in time of the after- Ebola rehabilitation.
KEY WORDS: Ebola, Impact, Farm productivity, Household Food security, Quarantine Community
INTRODUCTION
Ebola hemorrhagic fever is a fierce and extremely rapid
killing viral disease which passes to other humans via
blood and other body fluids, and causes death in 50-90%
of clinically diagnosed cases (Leach, 2008). It leads to
rapid onset of symptoms (initially high temperature,
shivering, and aches). It advances to gastric problems and
rashes on appropriately the third day, resulting to throat
lesions by the eight day. This is often accompanied by
spontaneous bleeding and renal failure, and then to
extreme lethargy and hallucinations and usually death
within two weeks (Leach, 2008). Ebola Virus Disease
(EVD) outbreak in parts of Guinea, Liberia, and Sierra
Leone has severely affected these countries and it is
having acute repercussions on the food security of these
affected countries (Welthungerhilfe, 2014). World Bank
Report (2014) states that beyond the toll of human lives
and suffering, the Ebola epidemic currently affecting West
Africa is already having measurable economic impact in
terms of forgone outputs. The report further intimated that
Ebola outbreak has caused higher fiscal deficits and
prices; lower real household incomes and greater poverty.
United Nations Development Programme (UNDP) in 2014
also stated that these economic impacts include costs of
health care and foregone productivity of those farmers
directly affected. In Sierra Leone, the Ebola outbreak
reached an alarming state at the beginning of the rice and
cocoa harvesting season (July/August), which is the time
when business people reach out to farmers to exchange
food and their items with cocoa (Ragozini and Maietta,
2014). The government declared a Public Health
Emergency on the 14thAugust 2014, involving heightened
control measures including limitations on internal
movement, health inspections at borders, mobilization of
all health and security/defense personnel, increased
restrictions on both suspected cases and contacts
undergoing tracing, and ban on movement of corpses
(Biosurveillance Event Report, 2014). Restrictions on
movement negatively impacted not only household
income but also availability of food within households.
For example, the closure of markets, especially the weekly
markets –“Ndoways”, because of fear of infection
curtailed food trade and this caused supply shortages
(West Africa, 2014). According to Glennerster and Suri
(2014), at least 40% of the farmers in Kailahun District
either abandoned their farms or moved to new safer
locations or died, leaving the farms unattended to. The
report also indicated that about 90 percent of the plots in
the inland valley swamps were not cultivated. The major
producers of staple food and to some extent even the cash
crops in Sierra Leone are the smallholder farmers, who
make up 80-85% of the rural population and depend on
Ebola on farm productivity in Sierra Leone
407
farming for their livelihood (Statistics Sierra Leone, 2004).
It was their economic activities that were halted; and their
numbers suffered the highest death from the Ebola disease.
Yet, the necessary data that would show the impact of
Ebola on farm activities, farm productivities, household
food security and economic security in farming
communities is scanty. Also, there is a general perception
that what is reported by government about the epidemic in
the national and international media is not the true
reflection of situation on the ground. Thus, interventions
by the government, NGOs, and International Parties would
not be well targeted. The purpose of this study therefore,
to investigate the effect of Ebola on farm productivity
from the farmers and extension workers perceptive. It is
hoped that results of this study would forecast what the
food security situation would be like after the Ebola crisis.
The government and NGOs and the international
organizations may find such data useful for after Ebola
reconstruction planning. The main objectives were to
identify the demographic and socioeconomic status of the
selected farmers; identify the different farming activities
that were severely affected by the Ebola outbreak;
determine the extent of the impact of Ebola outbreak on
farm productivity’ and to determine the extent to which
reduced farm productivity affected household food
security within the study area.
METHODOLOGY
Research Design
The study design used was descriptive field survey design.
Fraenkel and Wallen (1993) describe descriptive analysis
as that method that involves asking a large group of people
questions about a particular issue. Information is obtained
from a sample rather than the entire population at one
point in time which may range from one day to a few
weeks. The design is considered appropriate because it
focuses on the observation and the perception of an
existing situation, describes and interprets what is
concerned with issue; conditions and practices and
relationship, views, belief, attitudes, process and trends
which are developing concerning the issue of Impact of
Ebola outbreak on food security in Sierra Leone. Also, any
research undertaking involves lots of cost implications
hence this design was deliberately selected for the study
because it allows for quick data collection at a
comparatively cheap cost (Grinnel, 1993).
Study Area
The study was conducted in Bo and Moyamba District in
the Southern region of Sierra Leone. These are two out of
the fourteen districts in Sierra Leone. Bo is one hundred
and fifty two miles (152 miles) from the capital city,
Freetown. It is bounded to the North by Tonkolili District,
North–Northeast by Kenema District, to the South by
Pujehun District, to the Southwest by Bonthe District, and
to the West and West-north by Moyamba District. Bo
district comprises of fifteen (15) administrative sections -
chiefdoms and a total population of 463,668 people with
as much land area as 1,500 km2(SSL, 2004). Moyamba
District is about seventy five miles (120 kilometers) away
from the capital city, Freetown. And it is bounded to the
North by Tonkolili District; to the south by Bo District; to
the southwest by Bonthe District and to the West and
North-West by the Mabam River. The entire district
comprises fourteen (14) chiefdoms with a population of
approximately 261, 000 (SSL2004). Muslims and
Christians mutually live across the districts tolerating one
another’s beliefs. The main occupation of the people of
these districts is farming. Crops usually grown include
rice, maize, yam, cassava, cocoyam, melon, and
vegetables under mixed cropping practices. Livestock
reared in these two districts include goats, pigs, chickens
and sheep, with few growing cattle.
Sampling Procedure and Sample Size
A multistage sampling procedure was used in selecting
respondents for the study. In the first stage, two districts-
Bo and Moyamba, out of four districts in the southern
region of Sierra Leone were purposively selected. These
two neighboring districts were purposively selected
because they are one of the most important Ebola affected
districts and share similar culture in the southern region.
The second stage of the sampling procedure consisted of
purposive selection of five chiefdoms –Boama, Kakua,
Kori, Lower Banta and Tikonko where Ebola outbreak has
actually occurred. The third stage was characterized by the
purposive random sampling of sixteen quarantined
communities from these chiefdoms. The lists of these
communities were provided by the Ebola Task Force
Team and MFS Officers in each of the chiefdoms. The
fourth stage comprised of selection of household which
were quarantined for Ebola outbreak. Here the lists were
provided by local authorities, Ebola Task Force Team,
Ministry of Health, and MSF Workers in the communities.
The fifth stage involved a purposive selection of 150
farmers from 16 communities. The number of farmers per
community was determined by the size and population of
the community as follows: Forgbo (5), Boama (5), Bye-
Largo (5), Moyamba Junction (20), and Gbangbatoke (20)
in Moyamba District; Kailia (5), Negbema(5) Tikonko
Town (20), Bumpeh Town(20), Bawomahun (20),
Yakagie (5), Ngomahun (5), Farma (5), Gbembeh (5), and
Bateima (5) villages in Bo District. In the last stage, 10
Extension workers were randomly sampled from the Bo
(5) and Moyamba (5) districts. This gave a total of 160
respondents.
Instrument and Data Collection
Data for this study were collected from September 20th to
15th November 2014.The use of primary and secondary
data was employed for this study. For the effectiveness of
the primary data collection, 5 welled trained enumerators
(able to communicate in English, Krio and the local
dialects of the respective selected 16 communities/
villages) were engaged in data collection. Secondary data
were the information obtained from literature, published
and unpublished research works, books, academic
journals, project reports, official documents, consultations,
and library materials among others. Primary data were
collected through the use of a structured and validated
questionnaire consisting of open and closed-ended
questions, and focus group discussions to elicit
information from the target respondents the instrument
consisted of four separate sections according to the
purpose and objectives of the study. The first section was
designed to collect data on the demographic and
socioeconomic characteristics of quarantined farmers and
G.J.B.B., VOL.4 (4) 2015: 406 - 411 ISSN 2278 –9103
408
extension workers. The second section was designed to
solicit data concerning farming activities that were
affected by the Ebola outbreak, the third sections gathered
data on the extent of the Ebola breakout on farm
productivity. And the forth section collected information
on the farmers perception on the impact of bola breakout
on household food security. The responses of section three
were categorized using three Point Likert-type scales: very
great extent = 1, great extent = 2, some extent = 3, while
those for section four were categorized using four point
Likert-type scales: highly agreed = 1, disagreed = 2,
highly disagreed= 3, and don’t know = 4. The mean scores
were used for later analysis. The instrument for data
collection was subjected to pre-testing at Kaiyamba
Chiefdom, which was not included in the sample, while
validity and reliability tests were carried out. Validity
testes included face validity and content validity.
i. Face validit
To determine the extent to which the instrument measures
what it was designed to measure, the questionnaire was
assessed by a panel of experts. The panel included
Extension Education officers, Health officers, and
Community Development workers, agricultural
economists, and relevant specialists in tropical diseases.
Each of these experts of the panel was asked to examine
the instruments for content, clarity, wording, length,
format, and overall appearance.
ii. Content validity
This was to measure the representativeness of sampling
adequacy of the contents of rating scale. The reliability
test was employed on 16 respondents with two different
method of test-retest that is, administration of
questionnaires to the same respondents (in the pretest) on
two occasions at two weeks interval. The collected scores
were subjected to Pearson Product Moment Correlation
Test statistics. The second method was the split-half
method that gave measures of the internal consistency of
the instrument. The administered questionnaire had its
items divided into two on odd and even number basis. The
relationship between the two halves was calculated using
Pearson Correlation Test statistics. The value of 0.78 was
obtained which makes the instrument reliable. The results
of these tests were followed by the modification of the
data collection instrument where necessary.
Data Analysis
Data collected were analyzed using computer software
called Statistical Package for Social Sciences (SPSS)
version 20. Descriptive statistics was used for the analysis
of the data that was generated. The descriptive statistics
included frequency counts and percentages which were
used to describe the distribution of socioeconomic
characteristics of the respondents and to measure other
variables of interest in the study.
RESULTS
Personal characteristics of farmers
The result of the demographic data is detailed in Table 1.
It showed that most of the Ebola quarantine farmers are
males (59.4%), and most of them (56.3%) were between
36 and 55 years. Farmers between the age ranges of 15 to
35 years constituted 28.1%, while those at 56 years and
above were 15.6%. Furthermore, Table 1 revealed that
61.3% of the farmers are married, 25.0% single, 12.5% are
widowed/widowers, while 1.2% are divorced. Most of the
farmers (37.5%) had adult literacy education. The data
further revealed that most of the farmers have many years
of practical experience in farming. For example, 50.6%
had 11 to 20 years of farming experience, but most of
them (56.9%) have small size farms –less than 1ha.There
were more Muslims (52.5%) than Christians (43.1%). The
rest were traditionalist (4.4%).
TABLE 1: Socio-economic characteristics of Ebola quarantined farmers by frequencies and percentages
Gender
Age
Marital Status
Educational level
Years of farming
experience
Farm Size(ha
Male 95
(59.4)
Female 65
(40.6)
13-36 years 45
(28.1)
36–55years 90
(56.3)
Above 56 years
25 (15.6)
Single 40 (25.0)
Married 98
(61.3)
Divorced 2(1.2)
Widower 20
(12.5)
No formal education 45(28.1)
Adult literacy Education 60 (37.5)
Primary Education 10( 6.3)
Secondary education 16(10.0)
Tec. Voc. Education 5( 93.1)
Tertiary Education 20(12.5)
Quranic Education 4(2.5)
Less 10 years 63(39.4)
11- 20 years 83(50.6)
31–40 Years 7(5.6)
41-50Years 2(2.5)
Above 51years 1(0.6)
Less 1 91 (56.9)
1–1.5 32(20.0)
1.6 -2.0 16(10.0)
2.1 -2.5 9 (5.6)
2.6 -3.0 7 (4.4)
3.1 -3.5 4 (2.5)
Above 3. 61(0.6)
Table two contains results of the aspects of farming
activities that were severely affected by the Ebola
outbreak. It shows that Ebola outbreak did not affect any
of the pre-planting activities in study the area. The disease
outbreak did not also affect most early post-planting
activities, but greatly affected bird scaring (28.8%),
harvesting (61.3%), while hunting (5.6%) and fencing
(4.4%) were the least affected of the post-planting
activities. The data further indicates that processing and
marketing of harvested crops, (35.6%) each were equally
affected by the disease outbreak, while transportation of
these crops was affected by 28.8%. Table 3, contains
results of factors that affect major limited farming
activities in the study area. It showed that farmers not able
to harvest their crops severely reduced farm productivity
as 93.8% of farmers did not harvest their crops. Loss of
love ones and closure of weekly periodic markets (92.5%
each), is second in causing severe drop in farm
productivity. Farmers fear of harassments by police and
soldiers (87.5%), closure of roads linking communities,
trauma of quarantined village, and restricted movement of
farmers, making the farmers afraid of attending hospitals
(75.0% each) to a very great extent impacted farm
productivity. Lack of treatment for the disease, and
reduced available labour for work, (62.0% each)
accordingly impacted farm productivity to a very great
extent. Pest control on farms (56.3%) was the way in
which farm productivity was very greatly affected by the
Ebola outbreak in the study area.
Ebola on farm productivity in Sierra Leone
409
TABLE 2: Different farming activities as severely affected by the Ebola outbreak
Farm Activities severely affected
Frequency
Percentage (%)
(a) Pre-planting Activities (n = 160)
Brushing
0
-
Felling trees
0
-
Burning
0
-
Clearing debris
0
-
Ploughing
0
-
(b) Post-planting Activities (n =160)
Weeding
0
-
Disease
0
-
Pest control
Fencing
7
4.4
Hunting
9
5.6
Bird scaring
46
28.8
Harvesting
98
61.3
(c) Post Harvest Activities (n =160)
Transporting harvested crop
46
28.8
Processing harvested crops
57
35.6
Marketing of harvested crops
57
35.6
TABLE 3: The extent of the impact of Ebola outbreak on farm productivity
The impact of Ebola outbreak on household food
security
Majority of the Farmers (99.4%), (98.8%), (98.1%),
(97.5%), (96.3%), (93.8%) and (91.3%) claimed that the
Ebola outbreak has decreased food storage and protection,
processing and preservation, food financing, affordability,
availability and accessibility respectively in their
community.
TABLE 4: The impact of Ebola outbreak on household food security
Food Security Indicators
Highly
agreed
Disagreed
Highly
disagreed
Don’t
Know
Food storage and protection decreased
159(99.4)
0(0.0)
0(-)
1(0.6)
Food processing and preservation
158(98.8)
0(0.0)
0(-)
2(1.3)
Food financing severely decreased
157(98.1)
0(0.0)
0(-)
3(1.9)
Food affordability greatly decreased
156(97.5)
0(0.0)
0(-)
4(2.5)
Marketing of food severely decreased
154(96.3)
0(0.0)
0(-)
6(3.8)
Availability of food severely decreased
150(93.8)
2(1.3)
0(-)
8( 5.0)
Accessibility to food greatly decreased
147(91.9)
5(3.1)
0(-)
8( 5.0)
DISCUSSION
According to the research findings, farmers in the Ebola
quarantined communities share common socioeconomic
characteristic; the Ebola outbreak severely obstructed few
post-planted and more post- harvest activities; to the
extent that it negatively impacted farm productivity; and
caused decrease in food security.
1. Socio-economic characteristics of Ebola quarantine
farmers
The study revealed that there are more males than females
farmers. This subscribes to the findings of Ravi and
Gauldin (2014), who found out that gender disparity exist
across care providers and Ebola patients. The difference
between male and female- farmers shown in Table 1 could
have arisen from the random sampling procedure adopted
by this study; which gave every respondent equal chance
irrespective of sex.
Impacts of Ebola Outbreak
Extent of Impact on Farm Productivity
Very Great
Extent
Great Extent
Some
Extent
Farmers who did not harvest their farms
150(93.8%)
10(6.3%)
-
Families lost their loved ones
148(92.5%)
12(7.5 %)
12(7.5%)
Farmers who could not sell their products
148(92.5%)
12(7.5%)
-
Some police and soldiers harassed farmers
140(87.5 %)
20(12.5%)
-
Most roads linking communities were closed down
120(75.0%)
40(25.0%)
-
Farmers whose movement were restricted
120(75.0%)
20(12.5%)
10(6.3%)
Available labour for farm work is reduced
100(62.5%)
35(21.9%)
25 (15.6%)
Pest population has Increased
90(56.3 %)
60 (37.5% )
-
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2. The extent of impact of Ebola outbreak on farm
productivity
The study reveals that the Ebola breakout severely
affected pest control and harvesting activities in
quarantined communities. All three means of pest control,
hunting, fencing and bird scaring were not performed in
farms during the Ebola outbreak. This accelerated pest
buildup, especially rodents and birds which get easy
access to farms without fences, if they are not hunted, or
scared away. This study therefore endorses Boones et al.’s
(2004) and Boone and Coughenour’s (2001) findings that
fencing can be useful in controlling access either by
humans or animals, protecting gardens and landscaping.
Rodents destroy the crops in its vegetative growing age,
while birds do so during flowering stage. It is therefore
very evident from this study that fencing can improve
agricultural production of farms in upland farming .When
farms are not harvested the result is loss of food in the
home. Both lack of pest control and non-harvesting of
farms create food insecurity, hunger and poverty and low
standard of life. The implication of this is that there will be
pressure on government and donor partners for post Ebola
rehabilitations. The findings further reveal that the Ebola
outbreak to a large extent negatively impacted farm
productivity. In the first instance, it showed that most
farmers did not harvest their farms. This finding is in line
with the findings of FAO (2014) that most of the farms in
Kailahun were abandoned and not harvested due to the
Ebola outbreak in May that year. The implication of this is
that there would be inadequate food for the people,
making them susceptible to diseases. Poor health
conditions affect agricultural production. Illness impairs
the farmers’ ability to innovate, experiment, and
implement changes, and to acquire technical information
available through extension activities. Households with
sick members are less able to adopt labour-intensive
techniques. According to the FAO Report (2014), which
stated that in an effort to control Ebola the government of
Sierra Leone imposed restrictions on the movement of
people, and closed down markets and border crossings in
the country. The closure of markets and the imposition of
internal travel restrictions disrupted the marketing of
agricultural produce and curtailed food trade. While the
farmers find it difficult to take their produce to markets,
buying agents who usually provide support to farmers and
function as contact points between traders and their
products refused to enter certain operational areas for fear
of Ebola.
3: The impact of Ebola outbreak on household food
security
According to the findings, the Ebola outbreak caused
decreased food availability, accessibility, affordability,
due to low or virtually lack of processing and preservation,
marketing, financing, and storage and food protection
undertakings. The findings revealed decrease in food
storage and protection within the quarantine communities.
This confirms the findings of Fewsnet, 2014) which stated
that when farm yield are low, food storage and
perseveration is impossible, as food itself is not available.
This is due to the fact that most of the farmers abandoned
their farms and crops at the mercy of pests for destruction.
Where farmers abandon farms or are prevented from
attending to their farms as a result of quarantine or
restriction of their movement, there would be nothing for
storage or preservation. The implication of this is food
insecurity in the community leading to increased
malnutrition and poverty.
CONCLUSION
The revealed Ebola outbreak did not only destroy human
lives of medical personnel in the Ebola outbreak in Sierra
Leone, but the disease affected all facets of the economy,
especially agriculture being the primary industry of
majority of Sierra Leoneans. The disease has also led to
food insecurity, malnutrition and poverty. This may have
great impact on future development plans of the country.
These findings are important for development planners
and Non-government organization for action plans for post
Ebola rehabilitations. An effective strategy to prevent the
spread of the disease in all rural areas of the country will
help in solving the problem of Ebola. Such strategy should
include understanding the socio-cultural characteristics of
the farmers. This would help the farmers trust the
government and its institutions and also enable them to
participate in the prevention activities of the disease.
Government and international donors should consider the
deteriorating trend of farmer’s health and food security to
give them priority in time of after Ebola rehabilitation.
Also, during the first year of the after Ebola rehabilitation,
government should import more food, especially rice into
the rural communities till they settle down as temporary
measure and plan and implement a sustainable food
production Programme. The markets closed should not
only be reopened but farmers and traders should be
allowed to freely move within the communities without
harassment from police and soldiers. If this is not done,
the level of availability of food and income of farmers in
the communities will continue to fall beyond a point un-
bearable. This high food insecurity will make farmers
susceptible to other neglected diseases like diarrhea,
malaria, etc. which may lead to unrest. This is what
Maiderman showed as a concern that food insecurity will
lead to unrest and threaten stability in the West African
Region. This study specifically looked farm productivity
in terms of crop production. There is a need, however, to
further investigate the impact of Ebola on livestock
production and other socioeconomic activities in the
quarantine communities.
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