Magnitude of urban malaria and its associated risk factors: the case of Batu town,Oromia Regional State,Ethiopia

Abstract

Objective

This study aimed to assess the magnitude of malaria and its associated risk factors in urban, Batu town, Oromia Regional State, Ethiopia.

Methods

This health-facility based prospective cross-sectional study enrolled 356 febrile malaria patients to assess risk factors associated with malaria infection.

Results

An overall positivity rate of 17.13% (61/356) for malaria infection was observed. Among the malaria-positive patients, 50.8% (31/61) of them were positive for Plasmodium vivax, 45.90% (28/61) were positive for Plasmodium falciparum, and 3.3% (2/61) had mixed infections of P. falciparum and P. vivax. Logistic regression analysis revealed that individuals who possessed insecticide-treated net (Odds ratio [OR] = 0.38, 95% confidence interval [CI] [0.194, 0.743]) and whose houses were sprayed with insecticides (OR = 0.18, 95% CI [0.097, 0.34]) were significantly less likely to have a malaria infection. Individuals living closer to stagnant water had a significantly greater chance of malaria infection than those who lived a distance from stagnant water (OR = 0.34, 95% CI [0.19, 0.59]).

Conclusion

The present study revealed that malaria remains a public health problem in the urban area of Batu town, which suggests that the same might be true for other urban areas in the country.

Keywords

Batu town magnitude of malaria plasmodium falciparum plasmodium vivax risk factor urban.

Introduction

Malaria is a life-threatening protozoan disease caused by one of the five Plasmodium parasites: P. falciparum, P. vivax, P. ovale, P. malariae, and P. knowlesi, and it is transmitted by the bite of female Anopheles (An.) mosquitoes. P. falciparum is the deadliest parasite in terms of its morbidity and mortality, and it is the most prevalent malaria parasite in sub-Saharan Africa (SSA), accounting for 99% of malaria cases in 2016, while P. vivax is the most prevalent in Asia and South America.¹ An estimated 219 million cases of malaria occurred worldwide in 2017, which is a slightly higher trend compared with 216 million cases of infection in 2016 in 91 countries; globally, there were 435,000 malaria deaths in 2017 compared with 451,000 estimated deaths in 2016.¹ Malaria deaths mainly occur (90%) in SSA, where children under 5 years of age account for 78% of all malaria deaths.²

Ethiopia is the SSA country that is most affected by malaria, and malaria ranks at the top of the communicable infectious diseases in the country.³ It is a leading cause of morbidity and mortality in Ethiopia.⁴ Approximately 68% of Ethiopia’s population is at risk of malaria infection,⁵ and nearly three-fourths of the Ethiopia landmass is considered to be malarious, with malaria mainly being associated with rainfall and altitude.⁶ Malaria transmission occurs from September to December, while minor transmission occurs after short rainfalls from April to May.⁷ In Ethiopia, P. falciparum and P. vivax are the two dominant species, accounting for 60% and 40%, respectively, of malaria cases reported in the country.^7,8 However, this proportion varies by location and season.⁷ For example, recent studies showed a trend in the shift of dominance from P. falciparum to P. vivax.^9–11 Since 2004, artemether-lumefantrine (AL) (Coartem®) and chloroquine (CQ) have been used as first-line drug treatments for P. falciparum and P. vivax, respectively, in Ethiopia.⁷ An. arabiensis, a member of the An. gambiae species complex, is the main malaria vector, while An. pharoensis, An. funestus, and An. nili are secondary vectors in some areas.^12,13 Recently, a new malaria vector, An. stephensi, was detected in Ethiopia using molecular and morphological methods.¹⁴

Compared with rural areas, urban areas are considered to have a low risk for malaria because of the improved housing, socioeconomic status, expanded personal protection, effective diagnosis and treatment, and limited breeding sites for Anopheles mosquitoes.^15,16 However, urban malaria cases were shown to account for 6% to 28% of the estimated global malaria incidence,¹⁵ and therefore, in the era of malaria elimination, attention should be paid to urban malaria. Urban agricultural practices and small irrigations surrounding towns in African cities might create a conducive environment for Anopheles mosquito breeding.^11,16 Additionally, most African cities including Ethiopia are characterized by poor housing conditions, a lack of proper sanitation, and poor water drainage systems, which likely increase human and malaria vector contacts and thereby facilitate urban malaria transmission.¹⁷ There is a paucity of information about the magnitude of malaria in Ethiopian towns located in malarious areas including Batu town. Therefore, the aim of the current study was to assess the magnitude of P. falciparum and P. vivax and the associated risk factors in Batu town, East Shoa, Oromia Regional State, Ethiopia.

Materials and methods

Description of study area

Batu town, which was formerly Zeway town, is located in the central part of Ethiopia, 165 km south of Addis Ababa, which is the capital of Ethiopia, in the middle of the Ethiopian Rift Valley (Figure 1).¹¹ Briefly, the town’s geographical coordinates are 7°56ʹ03ʹʹ N latitude and 38°42ʹ56ʹʹ E longitude. Batu town is located at an average altitude of 1657 m above sea level. Batu town has a total population of 78,784 (40,180 men and 38,604 women) in two kebeles (government administrative entities below the district level). Batu town has two hospitals (one government and one private), two government health centers, and eight private medium clinics (unpublished data from the Batu town Health Office, 2018). Lake Batu (Zeway) is located near the town, and this lake covers an area of about 434 km² and has an average depth of 4 m.¹⁸ The lake is used for fishing, recreation, and irrigating small farms. The lake area maintains malaria transmission even during the dry season by creating conducive breeding ground for Anopheles mosquitoes on the lake’s shoreline.¹⁹ The area receives between 700 and 800 mm of annual rainfall, with the heavy rains from June to September and short rains in April and May. The mean temperature for 4 months (April–July) was 22°C, with a mean maximum and minimum temperatures of 29°C and 15°C, respectively (unpublished information from the South Ethiopia District Meteorological Agency, 2018). Malaria transmission in the Batu area is generally unstable (seasonal), with peak transmission occurring between September and November, and another transmission period falls between April and May in the short rainy season. The major malaria vector in this area is An. Arabiensis, while An. pharoensis plays secondary role.¹⁸

Figure 1.

Map of the study area. Batu town was formerly known as Zeway town.

Study design

A health institution-based prospective cross-sectional study was conducted among patients from Batu town who attended governmental and private health facilities from April to July 2018. Understanding the magnitude of the malaria situation and risk factors during the minor transmission season enables us to deduce the larger picture of malaria during the major transmission season (September–December). Patients from the outpatient departments of the health facilities who were suspected of having malaria were included in the study. Patients who were suspected of having malaria who left the town and patients with severe malaria were excluded. We used the STROBE cross-sectional checklist when writing our report.²⁰

Sample size and sampling techniques

The sample size was estimated using a single-population proportion formula²¹ and the 95% confidence interval (CI) (Z (1−(1−α/2) = 1.96), a 0.05 margin of error, and a 15% non-responder rate. The slide positivity rate was assumed to be 28.1%, which was previously reported at Chichu and Wonago health centers, South Ethiopia.²² On the basis of the above assumptions, the sample size was calculated as follows:

\begin{array}{l} n= \frac{{(Z - α / 2)}^{2} P(1-P)}{{(d)}^{2}} \\ n= \frac{{(1.96)}^{2} (0.281) (1 - 0.281)}{{(0.05)}^{2}} \\ n=310+15%(46)=356 \end{array}

Thus, 356 individuals were included in the study. At all 12 health facilities (two hospitals, two health centers, and eight medium private clinics) in the town, patients who were suspected of having malaria were selected randomly to undergo a parasitological examination.

Blood collection and processing

Blood collection was performed in accordance with the standard operating procedure developed by the World Health Organization.²³ Briefly, before blood collection, the tip of the finger was cleaned using a cotton pad that was moistened with alcohol. Using a disposable blood lancet, two drops of blood was placed onto the slide. Thick and thin blood smears were prepared on the same slide side by side. After the slides were air-dried in a horizontal position, the thin blood smears were fixed with methanol for about 30 s. The thick blood smears were stained with 10% Giemsa solution for 20 minutes. Blood slides were observed under oil emersion objectives by experienced laboratory technologists. Parasite positivity was detected using the thick blood smears, while Plasmodium species identification was performed using the thin smears. The blood slides were observed by two technicians at each health facility for quality control. Slides were considered to be negative after 100 fields were carefully examined.

Questionnaire survey

A structured questionnaire including socio-demographic information and commonly known risk factors such as age, sex, occupation, education status, use of insecticide-treated nets, indoor residual spray, and stagnant water for mosquito breeding were included in our study. The questionnaire was translated from English into the local language (Afan Oromo) by an Afan Oromo expert. At each health facility, the fluent-speaking Afan Oromo laboratory technicians received an orientation on how to collect the data. After the purpose of the study was explained to the study participants or the children’s parents, the questionnaire was completed by data collectors before collecting the blood film. The principal investigator and a malaria expert from the Batu town health office supervised and doubled-checked the questionnaire responses for completeness.

Data analysis

Collected data were entered into a Microsoft Excel (Microsoft, Redmond, WA, USA) spreadsheet. The data were analyzed using SPSS version 25 (IBM Corp., Armonk, NY, USA). The Chi-square test was used to determine the association between malaria and age, sex, and season. Descriptive statistics were used to calculate the frequencies and percentages. Tables and graphs were also used to present the results. The association of different risk factors with malaria infection was analyzed using logistic regression analysis together with their corresponding 95% CI and odds ratio (OR). A P-value <0.05 was considered to be statistically significant.

Ethics approval and consent to participate

Ethics approval for this research was obtained from Adama Science and Technology University Research September 2019, Adama, Ethiopia. The aims, risks, and benefits of the study were explained to the study participants. Written informed consent was provided by the study participants, but for children less than 18 years of age, consent was provided by their parents. Confidentiality of participant information was maintained using a code number instead of their name to protect the participants’ identity. Patients with positive P. falciparum and mixed infection test results were treated with AL, while those infected with P. vivax were treated with CQ, in accordance with the national malaria treatment guideline.²⁴

Results

Socio-demographic characteristics of the study participants

All 356 individuals who were included in the study provided responses to the questionnaire. Among study participants, 216 (60.7%) were male, and most of the participants were over 14 years of age (46.90%). Educational status for most of the study respondents (24.72%) were above grade 12, and most of them (41.57%) were private workers (day laborers) (Table 1).

Table 1.

Socio-demographic characteristics of the study participants (N = 356).

Variables	Frequency	Percentage
Sex
Male	216	60.7
Female	140	39.3
Age (years)
0–4	86	24.16
5–14	103	28.93
>14	167	46.91
Education status
Illiterate	41	11.52
Grade 1–4	53	14.89
Grade 5–8	71	19.94
Grade 9–10	55	15.45
Grade 11–2	48	13.48
>Grade 12	88	24.72
Occupation*
Merchant	95	26.69
Government employer	62	17.42
Farmer	51	14.32
Private (day laborers)	148	41.57

*For children less than 18 years of age, their parents occupation was considered.

Magnitude of malaria and its associated risk factors

The overall slide positivity rate in the study area was 17.13%, and P. vivax accounted for 50.8% of infections while P. falciparum and mixed (both P. falciparum and P. vivax) infections accounted for 45.9% and 3.3% of infections, respectively. We observed mixed infections only in female. For malaria infections distributed by sex, among the 17.13% of positive slides, we observed 9% and 8.13% of cases in male and female, respectively (Table 2). Sex had no significant association with malaria infection (χ² = 2.026). Malaria infection occurred among all age groups. We observed a higher association with malaria infection in older (>14 years) age groups followed by an association in the 5- to 14-year-old age group (Table 2).

Table 2.

Magnitude of malaria related to study participant sex and age groups.

Risk factors	Number examined	Number infected	Percentage*	P-value
Sex
Male	216	32	9
Female	140	29	8.1	0.156
Total	356	61	17.1
Age groups
0–4 years	86	9	2.5	0.001
5–14 years	103	10	2.8
>14 years	167	42	11.8
Total	356	61	17.1

*The percentage is out of the total population (N = 356).

The average monthly trend of malaria infection was 16.9%. However, the number of patients visiting health facilities fluctuated during the months when the study was conducted. A greater number of malaria cases (36; 59.0%) were treated during June and July (wet season) while fewer malaria cases (25; 41.0%) were treated during April and May (dry season) (Figure 2). However, there was no statistically significant difference in malaria cases between seasons (χ² = 3.118) (Table 3). Among patients treated for malaria at health facilities, 82% of them were treated at private health facilities while 18% were treated at a government health facilities.

Figure 2.

Malaria infection positivity rate in the infected population at Batu town health facilities from April to July 2018.

Table 3.

Seasonal pattern of malaria by Plasmodium species in Batu town health facilities.

Season	Month	No. examined	Slide positive n, (%)	Pf, n	Pv, n	Mixed, n P-value
Dry season	April	93	14 (15.05)	7	7	0
	May	89	11 (12.36)	6	4	1
Wet season	June	99	21 (21.21)	7	14	0	0.077
	July	75	15 (20.27)	8	6	1
	Total	356	61 (17.13)	28	31	2

Logistic regression analysis showed that individuals who use insecticide-treated nets were less likely to become infected with malaria (OR = 0.38, 95% CI [0.194, 0.743], P = 0.005). Individuals who lived closer to stagnant water were more likely to become infected with malaria than those who lived a greater distance from reservoir water (OR = 0.34, 95% CI [0.19, 0.59], P < 0.001). Similarly, individuals with a house where insecticides were sprayed were approximately 0.2-times less likely to become infected with malaria compared with those with a house that was not sprayed with insecticides (OR = 0.18, 95% CI [0.097, 0.34], P < 0.001) (Table 4).

Table 4.

Logistic regression analysis for the association of other risk factors with malaria infections.

Variable	Category	Total population examined (N= 356)		OR (95% CI)	P-value
Variable	Category	Malaria cases (n = 61)	Malaria negative results (n = 294)	OR (95% CI)	P-value
Sex	Male	32	184	1.49 (0.86, 2.60)	0.156
Sex	Female	29	111
ITN use	Yes	16	38	0.38 (0.194, 0.743)	0.005
ITN use	No	45	257
Presence of stagnant water	Yes	38	106	0.34 (0.19, 0.59)	<0.001
Presence of stagnant water	No	23	189
Insecticide spray	Yes	26	39	0.18 (0.097, 0.34)	<0.001
Insecticide spray	No	35	256

OR, odds ratio; CI, confidence interval; ITN, insecticide-treated net.

Discussion

The findings of this current 4-month study (April–July 2018) revealed that 61 participants (17.13%) had malaria infection. This positivity rate (17.13%) is greater than that reported in other parts of Ethiopia such as Butajira,²⁵ Arba Minch hospital,⁵ and Arsi Negele,²⁶ which had a positivity rate of 0.93%, 7%, and 11.45%, respectively. However, our study positivity rate was less than that of patients attending Wonago health centers (28.1%),²² Hadiya (25.8%),²⁷ Kersa Woreda (43.8%),²⁸ and Hallaba (82.8%).⁹ The observed differences might result from altitude, seasonal, or other climate variations that contribute to Anopheles mosquito breeding as well as the malaria control measures implemented in the study areas.²⁵

For Plasmodium species, P. vivax accounted for most of the cases. This finding is in agreement with the study conducted at the Hallaba health center, with 70.41% of infections caused by P. vivax and 23.08% caused by P. falciparum, while the rest (6.51%) were mixed infections.⁹ Our results are also similar to the study conducted at Aleta Wondo that showed 66% P. vivax and 34% P. falciparum infections.²⁹ The results of the study conducted at health centers in Dilla town⁶ also showed that P. vivax accounted for 62.5% of infections, followed by P. falciparum at 26.8%, and mixed infections with both P. vivax and P. falciparum at 10.7%, which is in agreement with the present findings. An 85% prevalence of P. vivax was also reported in the area surrounding Dilla town.³⁰ A study conducted by Ketema et al.³¹ on the therapeutic efficacy of CQ treatment for P. vivax showed a two-fold increase in the prevalence of CQ-resistant P. vivax in South Ethiopia. This dominance of P. vivax in the area may require implementation of unique interventions to control vivax malaria in addition to conventional control measures such as insecticide-treated nets and indoor residual spraying.

In the present study, male showed a higher prevalence of malaria infection compared with female, but the difference was not statistically significant; this is in agreement with the results of a retrospective study that was conducted at Batu town health facilities.¹¹ This result is also in agreement with the findings of Regasa⁹ at Arba Minch hospital and Alemu et al.¹⁷ from Jimma town who reported higher malaria infection rates among male compared with female. The higher positivity rate of malaria among male might be because male engage in outdoor activities and recreation at night outside the home, which makes them more likely to be near Anopheles mosquitoes breeding sites.

Malaria infection also occurred among all age groups. However, the highest malaria infection occurred in participants who were older than 14 years, and the difference was statistically significant. This result is in agreement with the findings of Regessa⁵ and Molla and Ayele.⁶ The highest malaria positivity rate in this age group might be because these participants are away from home during the time when Anopheles mosquitoes bite. A study conducted by Kenea et al.³² at Adami-Tulu Jido Kombolcha (which is close to our study area) showed that a greater proportion (76.6%) of human biting activity by the Anopheles mosquito occurs outdoors compared with indoors during the early part of the night. The peak biting time for An. arabiensis (the major vector in the area)¹⁸ begins in the early evening.³³ Similarly, a study conducted on Bioko Island, Equatorial Guinea, showed that a high level of outdoor biting by An. gambiae (s.s) occurred throughout the night.³⁴ In the current study area, more malaria cases were detected during June and July compared with in April and May, but there was no statistically significant difference. This might be because in April and May, it was the dry season, but rain occurred during June and July, which might create a conducive breeding ground for Anopheles mosquitoes. Generally, seasonal variations in malaria transmission are a well-established feature of unstable malaria, where in Ethiopia,³⁵ 2.6% of malaria cases were reported in the dry season (April and May) and 5.8% of malaria cases were reported during the wet season (September–November).

In government health facilities (hospital and health centers), there was a tendency to treat patients who were clinically suspected of having malaria in addition to those patients with laboratory parasitology-confirmed cases. However, private health facilities have a strict policy not to treat patients with only clinically suspected malaria. They treat malaria patients only once the infection has been confirmed microscopically. This might be why the large difference in treatment frequency was observed between government and private health facilities. To eliminate malaria, involving the private health sector is essential for complete and timely reporting of malaria cases.³⁶ Investigating the role of private health facilities in the town in diagnosing and treating patients who are infected with malaria showed that more patients were attending these facilities. A survey study that was conducted by Jerene et al.³⁷ showed that 86% of private health facilities in Oromia Regional State in Ethiopia were providing malaria diagnostic and treatment services.

In the present study, living near stagnant water was identified as a risk factor for malaria infection. Among those infected with malaria, more cases occurred in patients who lived near stagnant water compared with those who did not live near stagnant water. This may be because stagnant water is a suitable breeding ground for Anopheles mosquitoes. Additionally, participants whose houses were not sprayed with insecticide were more likely to have a malaria infection than those whose houses were sprayed with insecticide. Participants who had and used insecticide-treated nets were less likely to become infected with malaria than those who did not have bed nets, which is in agreement the findings of Molla and Ayele⁶ and Belete and Roro.²²

Limitations

This study had some limitations. First, this study was facility-based, and it involved only symptomatic patients who were seeking treatment from a health facility. Asymptomatic malaria carriers from the community who do not visit a health facility and seek treatment were not enrolled due to a lack of logistics and financial constraints. Second, a malaria diagnosis was made only using the gold standard microscopy; some malaria-negative patients could have malaria parasites that can only be detected using robust molecular diagnostic techniques such as polymerase chain reaction and loop-mediated isothermal amplifications. This might underestimate the true magnitude of malaria during the study period.

Conclusion

The results of the present study suggest that both P. falciparum and P. vivax were the dominant species in the study area. However, the P. vivax positivity rate was higher than that of P. falciparum. There was also a strong association between several risk factors and the occurrence of malaria. Malaria remains a public health problem in Batu town, and this might be true for other towns located in malaria areas throughout the country. Therefore, appropriate control measures should be scaled-up to minimize malaria-related morbidity and mortality.

Footnotes

Acknowledgements

We would like to thank the Batu Health Office Department of Infectious Disease Prevention and Control unit for its assistance with coordinating with the town’s health facilities. We are also grateful to the laboratory technicians who collected the blood films and completed the questionnaires. Additionally, we thank the study participants for their cooperation with providing the required information and blood films.

Author contributions

JH and DH conceived and designed the study. JH performed data collection and statistical analysis, wrote the final draft, and reviewed and edited the final draft of the manuscript. DH supervised the study and edited and reviewed the final draft of the manuscript. Both authors read and approved the final version of the manuscript.

Consent for publication

The participants or their parents/legal guardians provided informed consent before participating in this study.

Declaration of conflicting interests

The authors declare that there are no conflicts of interest.

Funding

This study received no specific grant from any funding agencies in the public, commercial, or not-for-profit-sectors. It was fully funded by the authors.

ORCID iD

Hunduma Dinka

References

World Health Organization. World malaria report 2017; 2017. Geneva, Switzerland.

World Health Organization. World malaria report 2014; 2014. Geneva, Switzerland.

FMOH. National Strategic plan for malaria prevention, control and elimination in Ethiopia, 2010–2015, Addis Ababa: Federal Ministry of Health, 2010.

The Carter Centre. Summary proceedings 4th annual malaria control program review Ethiopia and Nigeria. Atlanta, Georgia, 2013.

Regasa

Magnitude of malaria infection in Ethiopia. Glob J Medi Res 2014; 14: 19–21.

Molla

Ayele

Prevalence of malaria and associated factors in Dilla town and the surrounding rural areas, Gedeo Zone, Southern Ethiopia. J Bacterio Parasit 2015; 6: 5.

FMOH. Malaria diagnosis and treatment guidelines for health workers, Addis Ababa, Ethiopia: Federal Ministry of Health of Ethiopia 2004.

Gebretsadik

Feleke

Fiseha

Eight-year trend analysis of malaria prevalence in Kombolcha, South Wollo, North-central Ethiopia: a retrospective study. Parasit Vectors 2018; 11: 15.

Tefera

Prevalence of malaria and associated factors among patients attending at Hallaba Health Center, Southern Ethiopia. Immun Infect Dis 2014; 2: 25–29.

10.

File

Dinka

Golassa

A retrospective analysis on the transmission of Plasmodium falciparum and Plasmodium vivax: the case of Adama City, East Shoa Zone. Ethiopia. Mal J 2019; 18: 193.

11.

Hassen

Dinka

Retrospective analysis of urban malaria cases due to Plasmodium falciparum and Plasmodium vivax: the case of Batu town, Oromia, Ethiopia.

Heliyon 2020; e03616.

12.

Taye

Hadis

Adugna

, et al. Biting behavior and Plasmodium infection rates of Anopheles arabiensis from Sille, Ethiopia. Act Trop 2006; 97: 50–54.

13.

Massebo

, Balkew

, Gebre-Michael

,et al. Blood meal origins and insecticide susceptibility of Anopheles arabiensis from Chano in South-West Ethiopia. Parasit Vectors 2013; 6: 44.

14.

Carter

Yared

Gebresilassie

, et al. First detection of Anopheles stephensi Liston, 1901 (Diptera: culicidae) in Ethiopia using molecular and morphological approaches. Act Trop 2018; 188: 180–186.

15.

Wilson

Krogstad

Arinaitwe

, et al. Urban malaria: understanding its epidemiology, ecology and transmission across seven diverse ICEMR National Sites. Am J Trop Med Hyg 2015; 93: 110–123.

16.

Mathanga

Tembo

Mzilahowa

, et al. Patterns and determinants of malaria risk in urban and periurban areas of Blantyre, Malawi. Mal J 2016; 15: 590.

17.

Alemu

Tsegaye

Golassa

, et al. Urban malaria and associated risk factors in Jimma town, south-west Ethiopia. Malar J 2011; 10: 173.

18.

Abose

Ye-ebiyo

Olana

, et al. Reorientation and definition of the role of malaria vector control in Ethiopia; the epidemiology and control of malaria with special emphasis to the distribution, behavior and susceptibility to insecticides of anopheline vectors and chloroquine resistance in Ziway, Central Ethiopia and other areas 1998; Addis Ababa: Ethiopia.

19.

Kenea

Balkew

, and Gebre-Michael

. Environmental factors associated with larval habitats of anopheline mosquitoes (Diptera: Culicidae) in irrigated and major drainage areas in the middle course of the Rift Valley, central Ethiopia. J Vector Borne Dis 2011; 48: 85–92.

20.

Von Elm

Altman

Egger

, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med 2007; 147: 573–577.

21.

Daniel

, and Cross

CL.

Determination of sample size: a foundation of analysis in the health sciences, Biostatistics, 10th edition, John Wiley & Sons, Inc., Hoboken, NJ, (2013), pp. 190–192.

22.

Belete

Roro

AB.

Malaria prevalence and associated risk factors among patients attending Chichu and Wonago health centers, South Ethiopia. J Res H lth Sci 2016; 16: 185–189.

23.

World Health Organization. Malaria microscopy quality assurance 2009; 2009. Geneva, Switzerland.

24.

FMOH. National malaria guidelines, 3rd ed. Addis Ababa: Federal Ministry of Health 2012.

25.

Woyessa

Deressa

Ali

, et al. Prevalence of malaria infection in Butajira area, South-central Ethiopia. Malar J 2012; 11: 84.

26.

Mengistu

, and Solomon

Trend analysis of malaria prevalence in Arsi Negelle Health Center, Southern Ethiopia. J Infect Dis Immun 2015; 1–6.

27.

Delil

Dileba

Habtu

, et al. Magnitude of malaria and factors among febrile cases in low transmission areas of Hadiya Zone, Ethiopia: a facility based cross sectional study. PLoS One 2016; 11(5): e0154277.

28.

Karunamoorthi

Bekele

Prevalence of malaria from peripheral blood smears examination: a 1-year retrospective study from the Serbo Health Center, Kersa Woreda, Ethiopia.

J Infect Pub Hlth 2009; 2: 171–176.

29.

Milikit

Worede

Molargi

, et al. Prevalence of malaria among patients attending in Aleta Wondo Health Center, Southern Ethiopia. Immun Infect Dis 2007; 13–26.

30.

Gari

Kenea

Loha

, et al. Malaria incidence and entomological findings in an area targeted for a cluster randomized controlled trial to prevent malaria in Ethiopia: results from a pilot study. Malar J 2016; 15: 145.

31.

Ketema

Getahun

, and Bacha

Therapeutic efficacy of chloroquine for treatment of P. vivax malaria cases in Halaba district. South Ethiopia. Parasit Vectors 2011; 4: 46.

32.

Kenea

Balkew

Tekie

, et al. Human-biting activities of Anopheles species in south central Ethiopia. Parasit Vectors 2016; 9: 527.

33.

FMOH. An epidemiological profile of malaria in Ethiopia, Addis Ababa, Ethiopia. Federal Ministry of Health 2014.

34.

Overgaard

Saebo

Reddy

, et al. Light traps fail to estimate reliable malaria mosquito biting rates on Bioko Island, Equatorial Guinea. Malar J 2012; 11: 56.

35.

Yewhalaw

Kassahun

Woldemichael

, et al. The influence of the Gilgel-Gibe hydroelectric dam in Ethiopia on caregivers’ knowledge, perceptions and health-seeking behavior towards childhood malaria. Malar J 2010; 9: 47.

36.

World Health Organization. Global malaria programme, World malaria report 2015; 2015. Geneva, Switzerland.

37.

Jerene

Fentie

Teka

, et al. The role of private health facilities in the provision of malaria case management and prevention services in four zones of Oromia Regional State, Ethiopia. Int Health 2012; 4: 70–73.