East Afr. J. Biophys. Comput. Sci. (2026), Vol. 7, Issue. 1, 27-33  
ART ICLE  
Prevalence and Determinant Factors of  
Malaria Infection among Patients Attending  
Gimbichu Primary Hospital, Soro District,  
Central Ethiopia, Ethiopia  
ARTICLE INFO  
Volume 7(1), 2026  
https:  
//dx.doi.org/10.4314/eajbcs.v7i1.3S  
Melese Birmeka 1,∗�, Gebremedhin Gebrezgabiher2, Tekleweyni  
Asayehegn3, and Mohammed Kasso4  
ARTICLE HISTORY  
Received: 12 June, 2025  
1Department of Biology, Hawassa University, Hawassa, P. O. Box 05,  
Accepted: 21 January, 2026  
Published Online: 10 June, 2026  
2Department of Veterinary Medicine, College of Veterinary Medicine and Animal Sciences, Samara  
University, P. O. Box 132, Samara, Afar, Ethiopia  
3Department of Aquatic Sciences, Fisheries and Aquaculture, Hawassa University, Hawassa, P. O. Box 05,  
4Department of Biology, Hawassa University, Hawassa, P. O. Box 05.  
CITATION  
Birmeka M. et.al (2026). Prevalence and  
Determinant Factors of Malaria Infection  
among Patients Attending Gimbichu  
Primary Hospital, Soro District, Central  
Ethiopia, Ethiopia. East African Journal  
of Biophysical and Computational  
∗Corresponding author: melesebirmeka@yahoo.com  
Abstract  
Sciences Volume 7(1), 2026. .https://dx.  
doi.org/10.4314/eajbcs.v7i1.3S.27-33  
In the world, particularly in Ethiopia, malaria has a great influence on human health and economy.  
This study intended to determine the prevalence, trends and associated risk factors of malaria patients  
visiting Gimbichu Primary Hospital, Ethiopia. To assess the trend and parasitological examination,  
a hospital-based cross-sectional study was carried out. To determine factors that significantly  
associated with infection, a bivariate and multivariable logistic regression analyses were performed  
with statistical significance set at p < 0.05. The findings of the study revealed the overall malaria  
prevalence of 72.4% among suspected patients. The study also revealed that males (AOR = 3.5, 95%  
CI; 1.5 - 3.8, p<0.001), individuals under five years (AOR = 2.8, 95% CI: 1.13 - 2.2), 5-20 years (AOR  
= 1.75, 95% CI: 1.1 - 1.91) and 21-45 years (AOR = 1.65, 95% CI: 1.01 - 1.49) were at higher risk.  
Additionally, study participants living close to mosquito breeding sites (AOR = 2.54, 95% CI: 2.53 -  
4.14), rural (AOR = 2.13, 95% CI: 1.01 - 2.6), houses with thatch roof (AOR = 1.43, 95% CI: 1.01-2.30),  
not using bed nets (AOR = 1.51, 95% CI: 2.01 - 4.1), homes with wall openings (AOR = 1.6, 95%  
CI: 1.13 - 2.57), monthly income of less than 1,000 Ethiopian Birr (AOR = 2.93, 95% CI: 1.3 - 4.6),  
and pregnant women (AOR = 1.6, 95% CI: 1.13 - 2.57) had maximum risk for malaria infection. The  
analysis from the retrospective data showed the overall decreasing trend in malaria infection rates,  
despite the fluctuations recorded between 2015 - 2021. The study indicates that malaria is persistent  
and a significant public health challenge which is driven by a complex interrelationship of demographic,  
social and environmental factors. Plasmodium vivax infection is the most prevalent species known to  
cause malaria in the study area. These findings necessitate targeted interventions focusing on housing  
improvements, economic support, and vector control measures.  
OPEN ACCESS  
This work is licensed under the Creative  
Commons open access license (CC  
BY-NC 4.0).  
East African Journal of Biophysical and  
Computational Sciences (EAJBCS) is  
already indexed on known databases  
like AJOL, DOAJ, CABI ABSTRACTS and  
FAO AGRIS.  
Keywords: Determinants; Malaria; Prevalence; Soro District, Trend  
both mother and the child. Similarly, children under five are at higher  
risk because their immune systems are not fully developed, with a child  
dying of malaria every 45 seconds worldwide.  
1 Introduction  
Malaria is a contagious disease that is caused by parasitic proatozoa  
(Ferede et al., 2013). It has great impact on world population health and  
economy (Baird, 2013). It is dominantly caused by Plasmodium falciparum  
and Plasmodium vivax. Out of the two species P. falciparum is the stronger  
pathogenic species that causes most deaths by malaria diseases at world  
scale, accounting for more than 90% of the world malaria mortality  
(Baird, 2013; Ferede et al., 2013). The malaria disease is a severe disease  
particularly in children and pregnant women. Pregnant women are more  
susceptible due to decreased immunity during pregnancy, endangering  
As an infectious vector-borne disease, malaria continues to be a key public  
health challenge in the country, with transmission patterns varying across  
regions depending on climatic conditions, rainfall, and altitude. In  
Ethiopia, malaria is known to be dominantly caused by P. falciparum (60%)  
and P. vivax (40%) (FMOH (Federal Ministry of Health), 2018). In the  
country, about 75% of areas located below 2,000 meters above sea level are  
susceptible to malaria epidemics and the persistent risk of transmission  
(Girum et al., 2019). Annually, approximately 4,782,000 reported cases  
Birmeka M., et.al (2026)  
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East Afr. J. Biophys. Comput. Sci. (2026), Vol. 7, Issue. 1, 27-33  
and related deaths, with morbidity and mortality increasing markedly  
during epidemic periods were recorded in the country (Alemayehu et al.,  
2014). Of this, the large-scale epidemics tend to occur every five to eight  
years although smaller, localized outbreaks are reported annually (Tsige  
et al., 2011). An estimated 68% of Ethiopians, a country with a population  
of over 100 million people, are at risk of contracting malaria (WHO (World  
Health Organization), 2016).  
Exclusion criteria: Malaria suspected patients who were not to give  
consent for participation in this study.  
Sampling and Sample Size Determination All patients suspected of  
having malaria were consecutively selected during their visits to the  
outpatient department of Gimbichu Primary Hospital till the compulsory  
sample size was achieved. The sample size was estimated using Daniel’s  
formula (Daniel, 2004).  
z2(1 − p)  
In Ethiopia, malaria transmission shows a considerable variation across  
seasons, years, and geographic settings. The high impact of malaria is  
particularly pronounced in rural areas (Donnelly et al., 2005), largely  
due to proximity to mosquito breeding sites, limited coverage of control  
interventions, widespread poverty, low literacy levels, land-use practices  
and poor housing conditions (Stratton et al., 2008). Exceptionally, a  
yearly based transmission observation is evident in the southwestern  
lowland regions bordering neighboring countries (Zhou et al., 2016).  
The communities with lower socioeconomic status are known to be  
disproportionately affected (WHO (World Health Organization), 2012),  
because it limits access to medical care and preventative measures like  
indoor spraying, bed nets treatment and efficient antimalarial therapy  
(Yamamoto et al., 2010). The drug-resistant strains of P. falciparum and  
P. vivax have also emerged and spread, posing a significant challenge to  
the control of malaria which contributed to the recent increase in malaria  
cases in the nation (Yarcho, 2010).  
N =  
(1)  
d2  
Where - p = 50%, because of the absence of previous malaria prevalence  
studies in the area, - d = margin of error at 5% and - z = 1.96 at 95% CI  
Consequently, the sample size was determined to be 384.  
2.5 Data Collection  
The structured pretested questionnaires were used to collect information  
on socio-demographic and economic status of study participants. Blood  
sample collection was done by finger prick by healthcare professional,  
and on the same slide both thick and thin blood smears were prepared.  
Throughout the data collection process, continuous monitoring and  
supervision were maintained. The activities performed by laboratory  
technicians, interviewers and nurses were closely overseen. Additionally,  
retrospective data spanning for seven years (2015 -2021) was retrieved  
from hospital registration records.  
The Government of Ethiopian has made significant progresses since  
2005 in malaria control interventions such as diagnostic testing, rapid  
case treatment, and prevention strategies for pregnant women through  
intermittent preventive therapy. High efforts also implemented on the  
distribution of IRS and ITNs. However, the widespread emergence of  
drug resistance in parasites and insecticide resistance in vectors have  
obstructed efforts of malaria eradication (Abeku et al., 2015; Tafese  
et al., 2018), particularly in the Hadiya Zone of central Ethiopia. This  
situation underscores the need for continuous evaluation and monitoring  
of malaria control interventions to address existing gaps.  
2.6 Data Analysis  
Following a completeness check, the data was analyzed by using SPSS  
version 24. Logistic regression studies were performed to identify the  
relationship between a few possible risk variables and malaria infection.  
To determine the existence and strength of a connection, AOR at 95% CI  
were calculated; if p < 0.05, statistical significance was proclaimed.  
2 Materials and Methods  
2.1 Study Area  
2.7 Ethical Consideration  
The Institutional Research Ethics Review Committee of CNCS of Hawassa  
University examined and approved the study proposal and ethical  
clearance was received (Ref.no. IRB/279/13). Additional, permission  
was also granted by the Hadiya Zone Health Department and the Soro  
District Primary Hospital. Confidentiality and privacy were strictly  
upheld, and participation in the study was entirely voluntary. After  
awareness made on the objectives of the study, participants gave their  
consent participation. Confidentiality was also maintained.  
The study was conducted at Gimbichu Primary Hospital which provides  
care for the Soro District in Hadiya Zone, central Ethiopia region. The  
district is about 264 kilometers south of the nation’s capital, Addis Ababa.  
Soro District is home to a substantial population of 233,015 people, nearly  
evenly split between genders (115,825 men and 117,190 women), giving  
the hospital a wide and diverse community to serve.  
2.2 Study Design and Period  
3 Results  
An institution-based cross-sectional study was carried out between  
October 2022 and January 2023.  
3.1 Characteristics of Study Participants  
in Retrospective Study of Malaria in  
Soro District, 2015 - 2021  
2.3 Study Population  
All individuals who presented to Gimbichu Primary Hospital with  
suspected malaria during the data collection period and satisfied the  
eligibility requirements were involved in the study population  
A total of 65,211 clients were registered in the laboratory logbooks of  
Gimbichu Primary Hospital. Of these, 36,132(55.4%) were males and  
29,089(44.6%) were females. Between 2015 and 2021, 65,211 blood films  
were microscopically examined. The majority of the cases were males  
accounting 17,813(49.3%). Although malaria prevalence fluctuated from  
2016 to 2021, there was an overall decreasing trend. Over the seven year  
period, a considerable malaria cases were recorded in the age 15 - 24 years  
old (18,718 cases, 28.7%), followed by 5 - 14 years old (15,131 cases, 23.2%).  
The lowest number of cases was over 54 years (8,740 cases, 13.4%) (Table  
1).  
2.4 Eligiblity Criteria  
Inclusion criteria: Malaria suspected patients who were consented to  
participate in the study.  
Birmeka M., et.al (2026)  
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East Afr. J. Biophys. Comput. Sci. (2026), Vol. 7, Issue. 1, 27-33  
Table 1: The social and demographic characteristics of microscopically examined suspected patients in Soro District, 2015 - 2021.  
Socio-demographic  
variables  
Category  
Total  
Smear Microscopy Results  
examined (%)  
Positive (%)  
Negative (%)  
Sex  
Male  
Female  
36132(55.4)  
29089(44.6)  
17813(49.3)  
11868(40.8)  
18319(50.7)  
17221(59.2)  
Total  
65221(100)  
29,681(45.5)  
35540(54.5)  
Age  
<5  
11283(17.3)  
15131(23.2)  
18718(28.7)  
11349(17.4)  
8740(13.4)  
5114(45.3)  
5447(36.0)  
7674(41.0)  
8040(70.0)  
3421(39.1)  
6169(54.6)  
9684(64.0)  
11044(59.0)  
3309(29.0)  
5319(60.8)  
5 - 14  
15 - 24  
25 - 54  
>54  
Total  
65221(100)  
29681(45.5)  
35540(54.5)  
Resident  
Urban  
Rural  
29415(45.1)  
35806(54.9)  
10310(35.05)  
19371(54.1)  
19105(64.95)  
16435(45.9)  
Total  
65221(100)  
29681(45.5)  
35540(54.5)  
3.2 The Prevalence of Malaria cases by  
Mex and Age among the Study  
The age specific prevalence rates of malaria was as follows: 5,114 cases  
(45.3%) in children under five years old, 5,447(36%) in 5 - 14 years old,  
7,674 cases (41%) in the 15-24 years old, 8,040 cases (70%) in the 25  
- 54 years age group, and 3,421 cases (39.1%) in individuals over 54  
years old. The infections malaria was recorded along all age groups  
considered in the study with an overall rate of 70%. The maximum  
prevalence was observed in the age group of 25 - 54 years. The next  
highest prevalence was in children below five years old, at 45.3%, though  
the lowest prevalence was in the 5 - 14 years age group, at 36% (Table 2).  
Population in Soro District, 2015–2021  
Among the 65,211 blood films examined, 36,132 (55.4%) were males  
and 29,089 (44.6%) were females. Of the 29,681 individuals who tested  
positive for malaria, 17,813 (60%) were males 11,868 (40%) were females  
(Table 2).  
Table 2: The Plasmodium species distribution across sex and age among study participants in Soro District, 2015 - 2021  
Variable  
Sex  
Category  
Total  
Positive  
(%)  
Negative  
(%)  
P.  
P. vivax  
(%)  
Mixed  
infection  
(%)  
examined  
falciparum  
(%)  
(%)  
Male  
Female  
36132(55.4)  
29089(44.6)  
17813(49.3)  
11868(40.8)  
18319(50.7)  
17221(59.2)  
9860(55.4)  
6550(55.2)  
7173(40.3)  
4866(41)  
765(4.3)  
452(3.8)  
Total  
65221(100%)  
29,681(45.5)  
35540(54.5)  
16414(55.3)  
12051(40.6)  
1217(4.1)  
<5  
11283(17.3)  
15131(23.2%)  
18718(28.7)  
11349(17.4)  
8740(13.4)  
5114(45.3)  
5447(36.0)  
7674(41.0)  
8040(70.0)  
3421(39.1)  
6169(54.6)  
9684(64)  
2915(57)  
1994(39.0)  
2521(46.0)  
3400(44.3)  
2734(34.0)  
1402(41.0)  
204(4.0)  
202(3.7)  
260(3.4)  
289(3.6)  
262(7.6)  
5 - 14  
15 - 24  
25 - 54  
>54  
2724(50.3)  
4014(52.3)  
5017(62.3)  
1757(51.0)  
11044(59)  
3309(29)  
Age  
5319(60.8)  
Total  
65221(100)  
29681(45.5)  
35540(54.5)  
16414(55.3)  
12051(40.6)  
1217(4.1)  
*The numbers inside the brackets indicate percentages (%)  
3.3 Trends of Malaria Incidence in Soro  
District, 2015 - 2021  
Figure 1 illustrates trends of malaria prevalence among patients from  
2015 - 2021, based on data obtained from the malaria records of Gimbichu  
Primary Hospital. Over seven years period, 65,221 blood films were  
examined for malaria, with 29,663 (45.5%) testing positive. The annual  
prevalence rates were 74.5% in 2015, 54.5% in 2016, 44.6% in 2017, 58.7%  
in 2018, 10.4%; in 2019, 15.7% in 2020 and 13.4 % in 2021. The highest  
annual prevalence was recorded in 2015 at 74.5 %, significantly higher  
than in subsequent years. Overall, the data indicates fluctuating trends in  
malaria cases, with a general decrease over the seven-year period (Figure  
1).  
Figure 1: Malaria Incidence Trends among patients at Gimbichu Primary Hospital  
(2015 -2021)  
Birmeka M., et.al (2026)  
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East Afr. J. Biophys. Comput. Sci. (2026), Vol. 7, Issue. 1, 27-33  
3.4 Annual Malaria Prevalence Trends by  
Plasmodium Species in Soro District,  
2015–2021  
Males were found to have a 3.5 times more likelihood of malaria infection  
compared with females (AOR = 3.5, 95% CI: 1.5 – 3.8, p < 0.001). Higher  
infection rates were observed for children under five years of age (AOR =  
2.8, 95% CI: 1.13 – 2.2), individuals aged 5–20 years (AOR = 1.75, 95% CI:  
1.1 – 1.91), and those aged 21 – 45 years (AOR = 1.65, 95% CI: 1.01 – 1.49)  
when compared with participants older than 45 years.  
From 2015 to 2021, malaria cases at Gimbichu Primary Hospital were  
attributed P. falciparum (16,392 cases, 55.3%), P. vivax (12055 cases, 40.6%),  
and mixed infections (1201 cases, 4.1%). The trends in malaria cases by  
species showed fluctuations and an overall decrease over the years. The  
annual occurrence rates for P. falciparum were 58% in 2015, 54% in 2016,  
42% in 2017, 70.1% in 2018, 42.5% in 2019, 32% in 2020, and 20% in 2021.  
For P. vivax, the rates were 39% in 2015, 44% in 2016, 57% in 2017, 16.9%  
in 2018, 56.7% in 2019, 67.6% in 2020, and 79.9% in 2021. Mixed infections  
were recorded as follows: 3.4% in 2015, 1.5% in 2016, 1% in 2017, 12.9%  
in 2018, 0.8% in 2019, 1.4% in 2020, and 1.7% in 2021. The highest case  
of P. falciparum was recorded in 2018 (70.1%), while P.vivax showed a  
fluctuating trend with the maximum rate in 2021 (79.9%). Mixed infection  
peaked in was recorded 2018 at 12.9% (Figure 2).  
Table 3: The participants socio-demographic characteristics in Soro District,  
South-Central Ethiopia (Oct 2022 – Jan 2023)  
Characteristics  
Gender  
Categories NumberPercent (%)  
Male  
214  
170  
55.7  
44.3  
Female  
Age  
<5  
80  
20.8  
52.6  
15.1  
11.5  
5 - 20  
21 - 45  
>45  
202  
58  
44  
Residence  
Urban  
Rural  
165  
219  
43  
57  
Pregnancy-Self reported  
Income level  
Present  
Absent  
107  
277  
28  
72  
< 1,000  
110  
28.6  
23.7  
30.7  
16.9  
100-3,000 91  
3,000-5,000 118  
>5,000  
65  
Home closer to breeding siteYes  
199  
185  
52  
48  
No  
Opening hole in the wall  
Yes  
No  
107  
277  
28  
72  
Figure 2: Malaria infection distribution trends by Plasmodium species among  
patients at Gimbichu Primary Hospital (2015 - 2021)  
Sleep under mosquito net Yes  
167  
217  
43.5  
56.5  
No  
3.5 Socio-demographic Profile of the  
Study Population in Soro District,  
South-Central Ethiopia (Oct 2022 – Jan  
2023)  
IRS in the past five month Yes  
101  
283  
26.3  
73.7  
No  
House roof type  
Corrugated266  
Thatch 118  
69.3  
30.7  
During the study period, 384 suspected malaria patients were sampled in  
Soro District, comprising of 214 (55.7%) males and 170 (44.3%) females.  
Of these, majority of the participants (52.6%) were 5 - 20 years old, and 80  
(20.8%), 58 (15.1%), and 44 (11.5%) of participants were below five years,  
21 - 45 years, above 45 years, respectively. Most participants (219, 57%)  
resided in rural areas. The monthly income per month distribution of the  
study participants were: 118 (30.7%) had 3,000 - 5,000 ETB, 110 (28.6%)  
had less than 1000 ETB. Additionally, 199 (52%) respondents were homes  
near mosquito breeding sites, 237 (61.7%) respondents had homes with  
wall opening, 167 (43.5%) of respondents were sleeping under mosquito  
net,101(26.3%) respondents had IRS in the past five months, and 266  
(69.3%) respondents had homes with corrugated roofs (Table 3).  
Participants living in households around mosquito breeding sites in the  
surrounding environment were nearly three times more likely to be  
infected than those without such sites (AOR = 2.54, 95% CI: 2.53–4.14,  
p < 0.001). Rural residents had approximately twice the odds of malaria  
infection compared with urban dwellers (AOR = 2.13, 95% CI: 1.01–2.6, p  
= 0.01).  
Housing characteristics were also showed significant association with  
malaria infection. Individuals residing in houses with thatched roofs  
were 1.43 times more likely to be infected compared to those living in  
houses with corrugated iron roofs (AOR = 1.43, 95% CI: 1.01 – 2.30, p <  
0.001). Participants who did not use bed nets had a higher risk of malaria  
infection than their counterparts who used bed nets (AOR = 1.51, 95% CI:  
2.01 – 4.1). Similarly, the existence of wall openings in dwellings increased  
the likelihood of malaria infection by 1.6 times (AOR = 1.6, 95% CI: 1.13 –  
2.57, p = 0.01).  
3.6 Prevalence and Determinant Factors  
of Malaria Infection  
The findings indicated that 278 (72%) of the participants were infected  
with malaria parasites.  
Analyses of determinant risk factors for  
suspected patients found significant associations with sex, age, residence,  
pregnancy status, income level, bed nets usage, IRS in the past five  
months, availability of mosquito breeding places, porous wall for  
mosquito’s entrance, and types of roofing material.  
Furthermore, participants with a monthly income of less than 1,000  
Ethiopian Birr were infected with malaria nearly triple times when  
compared with those earning more than 1,000 Birr per month (AOR =  
2.93, 95% CI: 1.3 – 4.6, p = 0.004) (Table 4).  
Birmeka M., et.al (2026)  
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East Afr. J. Biophys. Comput. Sci. (2026), Vol. 7, Issue. 1, 27-33  
Table 4: Logistic Regression Analysis for Predictors of Malaria in Suspected Patients in Soro District, Central Ethiopia, (Oct 2021 – Jan 2022)  
Characteristics  
Sex  
Category  
Malaria+ve(%) COR(95%CI)  
P-value AOR(95%CI)  
P-value  
Female  
Male  
106(62.4)  
172(80.4)  
1
1
1.67(1.3 - 2.65) < 0.001  
3.5(1.5 - 3.8) < 0.001  
Age  
<5  
27(34)  
161(79)  
50(86)  
40(90)  
1.6(2.13 - 3.1)  
0.01  
2.8(1.13 - 2.2)  
0.024  
5 - 20  
21 - 45  
>45  
1.86(1.14 - 2.16) < 0.001  
1.75(1.1 - 1.91) < 0.001  
1.75(1.01 - 2.79) 0.03  
1
1.65(1.01 - 1.49) 0.03  
1
Residence  
Urban  
Rural  
110(66.7)  
168(76.7)  
1
1
1.43(1.14 - 2.31) < 0.001  
2.13(1.01 - 2.6)  
0.01  
Income level of < 1000  
90(81.8)  
65(71.4)  
83(70.3)  
40(61.5)  
1.55(1.06 - 4.62) < 0.001  
2.93(1.3 - 4.6)  
0.86(0.21 - 5.2)  
2.75(0.14 - 4.3)  
1
0.004  
0.31  
0.22  
Household  
100-3000  
3000-5000  
>5000  
0.56(0.22 - 5.6)  
1.63(0.11 - 2.6)  
1
0.324  
0.234  
Use of bed nets  
Yes  
No  
112(67.1)  
166(76.5)  
1
1
1.54(2.03 - 5.12) < 0.001  
1.51(2.01 - 4.1) < 0.001  
IRS in the past twelve  
month’s  
yes  
No  
70(69.3)  
208(73.5)  
1
1
1.9(1.23 - 2.96) < 0.001  
1.89(1.3 - 2.76) < 0.001  
Mosquito Breeding Site Yes  
145(72.8)  
133(71.9)  
1.54(2.03 - 5.16) < 0.001  
2.54(2.53 - 4.14) < 0.001  
near to home  
No  
Home wall opening  
Yes  
No  
67(62.6)  
211(76.2)  
1.89(1.23 - 2.96) < 0.001  
1
1.6(1.13 - 2.57)  
1
0.01  
House Roof Type  
Corrugated iron sheet 191(71.8)  
Thatch 87(73.7)  
1
1
1.63(1 - 2.2)  
0.02  
1.43(1 - 2.30)  
0.001  
*For each respective characteristic, the percentage calculated is from total examined  
3.7 Discussion  
falciparum transmission is more common in lowland areas. Conversely,  
the predominance of P. vivax observed in this study is agree with reports  
from Wolkite Health Center (Degefie, 2017) , Dilla District (Ehsetu &  
Besha, 2015), Hallaba District (Girum, 2014) , and East Shewa Zone (Firew  
& Andrew, 2018) (Firew and Andrew, 2017). This similarity may be  
related to comparable altitudinal conditions or the relapsing nature of P.  
vivax, particularly during cooler seasons.  
This study was conducted to examine trends in malaria infection over  
time, estimate its prevalence and identify factors associated with malaria  
infection among patients attending Gimbichu Primary Hospital in Soro  
District, South-central Ethiopia.  
A study by Deressa et al., 2006 reported that malaria has been one  
of the major causes of mortality, hospital admissions and outpatient  
visits in Ethiopian health facilities for a long time. In line with these  
findings, the present analysis showed that malaria cases peaked in 2015,  
accounting for 74.5% of all reported cases, while the lowest prevalence  
was observed in 2019 (10.4%). From the year 2015- 2021, overall trend  
analysis demonstrated the fluctuations in malaria incidence, with an  
overall declining pattern across the seven-year period.  
The present study showed as the infection malaria was significantly  
more common among males than females which seem males being 3.5  
times more likely to be infected. This result differs from case reported  
by Graves et al., 2009 , although it is consistent with other Ethiopian  
studies (Abebe et al., 2012; Girum, 2014). More than half proportion of  
the malaria infection was observed among individuals aged 5–20 years,  
followed by those aged 21–40 years. This may be attributed to increased  
outdoor activities such as farming and other productive work, which  
elevate exposure to mosquito bites. Additionally, malaria prevalence  
was assumed to be higher among individuals residing in rural areas  
when compared with those living in urban settings. This observation  
aligns with findings from Dilla District (Ehsetu & Besha, 2015). Such  
higher burden in rural areas may be due to lower levels of awareness,  
substandard housing conditions, limited resources and reduced access to  
effective malaria control measures.  
Results from the current study revealed an overall malaria prevalence of  
72.4% among suspected patients. This prevalence differs from reports  
of similar studies conducted in other parts of Ethiopia either higher  
or lower. For instance, the prevalence rate observed in this study was  
higher than those reported from Dilla District by Ehsetu and Besha, 2015  
, Kola Diba District by Abebe et al., 2012, Wolkite Health Center by  
Degefie, 2017, Arba Minch Hospital by Belayneh, 2014, Sibu Sira District  
by Girum, 2014 and the East Shewa Zone of Oromia Region by Firew  
and Andrew, 2018. In contrast, it was lower than the prevalence reported  
from Hallaba District by Girum (2014). These differences might be due to  
variations in study period, season, altitude, local communities’ awareness  
and differences in malaria prevention and control strategies.  
The record of the higher prevalence of malaria cases among pregnant  
women when compared with non-pregnant women probably due to  
immunity reduction associated with pregnancy. Low household income  
may also significantly associate with increased malaria infection. For  
instance, individuals with lower income levels may face greater malaria  
risk due to limited access to preventive tools and healthcare services,  
inadequate housing that permits mosquito entry, and compromised  
health and nutrition status (Dejene, 2014). These findings are also  
consistent with studies from Muleba District in the Kagera region  
of Tanzania, which reported a similar association between family  
employment status and malaria prevalence among children under five  
(Mushashu, 2012). WHO (World Health Organization), 2012 also pointed  
out as economically disadvantaged households may have limited access  
to healthcare facilities and insufficient resources to afford vector control  
In the study area, P. vivax was the predominant Plasmodium species  
(86.1%), followed by P. falciparum (8.3%) and mixed infections of P.  
falciparum and P. vivax (5.6%). Hence, the result of present study  
contradicts with the national estimates which indicate as P. falciparum  
accounts for approximately 60% of malaria incidences while P. vivax  
accounts for the remaining 40% in Ethiopia (Eliyas, 2014). Similar  
predominance of P. falciparum has been documented in studies conducted  
in Ayire District (Eliyas, 2014) and Arba Minch Hospital (Belayneh, 2014).  
Such inconsistencies may be explained by topographical differences, as P.  
Birmeka M., et.al (2026)  
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East Afr. J. Biophys. Comput. Sci. (2026), Vol. 7, Issue. 1, 27-33  
interventions including insecticide-treated nets (ITNs), indoor residual  
spraying (IRS) and antimalarial medications.  
Acknowledgments  
The authors are grateful for laboratory technical staff of Gimbichu  
Primary Hospital and Hawassa University for technical support.  
The result of present study regarding the use of indoor residual spraying  
within the past 12 months was significantly associated with malaria  
infection. In similar way, Sintasath et al., 2005 also indicated as  
IRS remains a cornerstone of the national malaria control strategy,  
particularly for epidemic prevention and mitigation. Their study also has  
shown substantially reduces in malaria morbidity and mortality. These  
findings are also consistent with reports from the Jiga area in northwest  
Ethiopia (Seble, 2014) , although they contrast with findings from Muleba  
District in Tanzania (Mushashu, 2012).  
References  
Abebe, A., Teshome, G., & Meshesha, B. (2012). Abundance and  
dynamics of anopheline larvae in a highland malarious area  
of south-central ethiopia. Parasites and Vectors, 5, 117.  
Abeku, T., Helinski, M., Kirby, M., Kefyalew, T., Awano, T., Batisso,  
E., Tesfaye, G., Ssekitooleko, J., Nicholas, S., Erdmanis, L.,  
Nalwoga, A., Bass, C., Cose, S., Assefa, A., Kebede, Z., Habte, T.,  
Katamba, V., Nuwa, A., Bakeera-Ssali, S., … Meek, S. (2015).  
Monitoring changes in malaria epidemiology and effectiveness  
of interventions in ethiopia and uganda: Beyond garki project  
baseline survey. Malar J., 14, 337.  
For the malaria infection, the environmental and housing-related factors  
such as proximity to mosquito breeding sites, wall openings, wall type  
and roofing material were identified as important contributors. These  
results agree with previous studies conducted by Ghebreyesus et al., 2000  
and Loha, 2013 which have highlighted the role of housing quality and  
environmental conditions in malaria transmission.  
Alemayehu, N., Gadissa, H., Dawit, G., Solomon, G., Sarah, A., Savitah, S.,  
Tadesse, A., Kifle, G., & Atinafu, D. (2014). Can training  
health extension workers in the integrated pharmaceutical  
logistics system (ipls) be effective, affordable and opportunistic.  
Ethiopian. Medical J., 52(3), 11–12.  
Baird, J. (2013). Evidence and implications of mortality associated with  
acute plasmodium vivax malaria. Clin Microbiol Rev., 26(1),  
36–57.  
Belayneh, R. (2014). Magnitude of malaria infection in ethiopia. Global  
Journal of Medical Research: C Microbiology and Pathology, 14, 7.  
Daniel, W. (2004). Biostatistics, a foundation for the analysis in the health  
sciences (7th). John Wiley; Sons (Asia) Pvt. Ltd.  
Degefie, B. (2017). Prevalence of malaria among patients attending wolkite  
health center, south-central ethiopia [Unpublished work].  
Dejene, H. (2014). Malaria prevention and control in ethiopia [Ph.D. Thesis].  
University of South Africa.  
Deressa, W., Ali, A., & Berhane, Y. (2006). Review of the interplay between  
population dynamics and malaria transmission in ethiopia.  
Ethiop. J. Health Dev., 20(3), 137–144.  
Donnelly, M., McCall, P., Lengeler, C., Bates, I., D’Alessandro, U.,  
Barnish, G., Konradsen, F., Klinkenberg, E., Townson, H.,  
Trape, J., Hastings, I., & Mutero, C. (2005). Malaria and  
urbanization in sub-saharan africa. Malar J., 4, 12.  
4 Conclusions  
The findings of this study indicated that malaria remains a major public  
health concern in Soro District; P. vivax was identified as the predominant  
infecting species. Although retrospective analysis over the seven-year  
period revealed fluctuations in malaria incidence, the overall trend  
showed a gradual decline. Several factors were significantly associated  
with malaria infection, including low household income, proximity to  
mosquito breeding sites, the presence of wall openings, lack of indoor  
residual spraying, and inadequate use of insecticide-treated bed nets.  
Addressing existing burden of malaria in the study area requires  
coordinated and multi-sectorial interventions.  
should be prioritize to strengthen the health service accessibility and  
quality, prompt treatment of infected individuals, enhancement of  
community socio-economic conditions, implementation of effective and  
well-coordinated vector control measures.  
engagement action is also needed to mitigate the identified risk factors  
in Soro District, Ethiopia.  
The control efforts  
The active community  
Ehsetu, M., & Besha, A. (2015). Prevalence of malaria and associated  
factors in dilla town and the surrounding rural areas. Ethiop  
J Health Sci., 25(3), 229–236.  
Declarations  
Eliyas, N. (2014). Prevalence of malaria and its biomedical knowledge  
among households in ayira district, western ethiopia [MSc Thesis].  
Haramaya University.  
Availability of data  
Ferede, G., Worku, A., Getaneh, A., Ahmed, A., Haile, T., Abdu, Y., &  
Tessema, B. (2013). Prevalence of malaria from blood smears  
examination: A seven-year retrospective study from metema  
hospital, northwest ethiopia. Malar Res Treat., 2013, 705730.  
Firew, T., & Andrew, W. (2018). Prevalence and associated risk factors of  
malaria among adults in east shewa zone of oromia regional  
state, ethiopia: A cross-sectional study. Trop Med Health., 46, 4.  
FMOH (Federal Ministry of Health). (2018). Malaria: Diagnosis and  
treatment guidelines for health workers in ethiopia (4th). Addis  
Ababa.  
Ghebreyesus, T., Haile, M., Witten, K., Getachew, A., Yohannes, M., &  
Lindsay, S. (2000). Household risk factors for malaria among  
children in the ethiopian highlands. Trans. R. Soc. Trop. Med.  
Hyg., 94(1), 17–21.  
The data used during this study will be available up on request.  
Conflict of interests  
The authors declare no conflict of interest.  
Consent for publication  
Not applicable.  
Funding  
Girum, T. (2014). Prevalence of malaria and associated factors among  
patients attending at hallaba health center, southern ethiopia.  
Immunol. Infect. Dis., 2(3), 25–29.  
Girum, T., Shumbej, T., & Misgun, S. (2019). Burden of malaria in ethiopia,  
2000–2016: Findings from global health estimates 2016. Trop.  
Dis. Travel Med. Vaccines, 5(1), 11.  
Graves, P., Richards, F., & Ngondi, J. (2009). Individual, household and  
environmental risk factors for malaria infection in amhara,  
oromia and snnp regions of ethiopia. Trans. R. Soc. Trop. Med.  
Hyg., 103(12), 1211–1220.  
None  
Authors’ contributions  
MB was responsible for conceptualization, investigation, data collection,  
analysis and writing the original draft. TA, MK and GG contributed to  
supervision, methodology, data analysis and reviewing and editing the  
manuscript. All authors read and approved the final manuscript.  
Loha, E. (2013). Variation in malaria transmission in southern ethiopia: The  
impact of prevention strategies and a need for targeted intervention  
[Doctoral dissertation, University of Bergen].  
Birmeka M., et.al (2026)  
32  
                                       
East Afr. J. Biophys. Comput. Sci. (2026), Vol. 7, Issue. 1, 27-33  
Mushashu, U. (2012). Prevalence of malaria infection among under-fives and  
the associated factors in muleba district-kagera region tanzania [MSc  
Thesis]. Muhimbili University of Health and Allied Sciences.  
Seble, A. (2014). The prevalence of malaria and the associated risk factors in jiga  
area, northwest ethiopia [MSc Thesis]. Addis Ababa University.  
Sintasath, D., Ghebremeskel, T., Lynch, M., Kleinau, E., Bretas, G.,  
Shililu, J., Brantly, E., Graves, P., & Beier, J. (2005). Malaria  
prevalence & associated risk factors in eritrea. Am J Trop Med  
Hyg., 72(6), 682–687.  
WHO (World Health Organization). (2012). World malaria report 2012.  
Geneva, WHO.  
WHO (World Health Organization). (2016). World malaria report. Geneva,  
WHO.  
Yamamoto, S., Louis, V., Sie, A., & Sauerborn, R. (2010). Household risk  
factors for clinical malaria in a semi-urban area of burkina faso:  
A case–control study. Trans. R. Soc. Trop. Med. Hyg., 104(1),  
61–65.  
Yarcho, Y. (2010). The effect of social and environmental variability on malaria  
epidemiology and transmission in some selected village around  
arbaminch towns’ southern ethiopia [MSc Thesis]. Haramaya  
University.  
Stratton, L., O’Neill, M., Kruk, M., & Bell, M. (2008). The persistent  
problem of malaria: Addressing the fundamental causes of a  
global killer. Soc. Sci. Med., 67(5), 854–862.  
Tafese, H., Hemming-Schroeder, E., Koepfi, C., Tesfaye, G., Lee, M.,  
Kazura, J., Yan, G., & Zhou, G. (2018). Malaria epidemiology  
and interventions in ethiopia from 2001 to 2016.  
Tsige, K., Kefelegn, G., & Ketema, B. (2011). Therapeutic efficacy of  
chloroquine for treatment of plasmodium vivax malaria cases  
in halaba district, south ethiopia. Parasites and Vectors, 4(1), 46.  
Zhou, G., Yewhalaw, D., Lo, E., Zhong, D., Wang, X., Degefa, T.,  
Zemene, E., Lee, M., Kebede, E., Tushune, K., & Yan, G. (2016).  
Analysis of asymptomatic and clinical malaria in urban and  
suburban settings of southwestern ethiopia in the context  
of sustaining malaria control and approaching elimination.  
Malaria J., 15, 250.  
Birmeka M., et.al (2026)  
33