DOI: https://doi.org/10.21203/rs.3.rs-2020761/v1
Background: Malaria is a serious disease that leads to severe adverse effects on mothers and the fetus during pregnancy. Approximately 25 million pregnant women in sub-Saharan Africa live at risk of malaria. This study aims to address the prevalence of malaria and its associated factors among pregnant women in Bossaso, Somalia.
Objective: To determine the prevalence of malaria and its associated factors among pregnant women in Bossaso city, Somalia.
Methods: A health institution-based cross-sectional study was conducted among 422 pregnant women in Bossaso General Hospital (BGH) using an interview-administered questionnaire and malaria diagnosis confirmation, which was done on microscope-based laboratory techniques. The collected data were analyzed using Statistical Package for the Social Sciences (SPSS) version 25. Bivariate and multivariate logistic regression models were employed to identify factors associated with malaria. The level of statistical significance was declared at a p-value less than or equal to 0.05.
Results: The overall prevalence of malaria was found 20.9% [95%CI (15.9%, 25.9%)]. Of these, 64 (75.3%), 19 (22.4%), and 2 (2.4%) were caused by Plasmodium falciparum, Plasmodium vivax, and mixed infection, respectively. The factors like the presence of water pond sites around the house or vicinity [AOR= 6.5, 95% CI (1.6, 20.5)] and always using insecticide-treated bed nets (ITNs) [AOR=0.1, 95%CI (0.01, 0.88)] were found to be significantly associated with malaria during pregnancy.
Conclusion and Recommendation: Malaria is still a health problem among pregnant women in Bossaso city. The overall prevalence of malaria among pregnant women in the study area was found to be high. This study emphasized the need to provide health education and consultation to pregnant women on the appropriate malaria preventive methods and continued strengthening other interventions.
Malaria is a protozoan caused parasitic infection of the genus Plasmodium. Plasmodium falciparum, Plasmodium vivax, Plasmodium Ovale, and Plasmodium malariae cause human malaria. It is naturally spread to humans through a bite by an infected female Anopheles mosquito. Among the four parasite species, plasmodium falciparum is the most prevalent malaria parasite in the World Health Organization (WHO) African Region, accounting for 99.7% of estimated malaria cases in 2017 (WHO, 2011).
Malaria disease is categorized as uncomplicated or with severe complications. Individuals infected with uncomplicated malaria commonly experience a combination of flue like symptoms and other simple symptoms. If left untreated, these may proceed to complicated malaria, which presents as organ failures, impairment of consciousness, and even death (CDC, 2019).
Approximately 228 million cases of malaria occurred worldwide in 2018 compared to 231 million patients in 2017. The WHO African Region still bears the most significant burden of malaria morbidity in 33 moderate to high transmission countries in the WHO African Region. There were an estimated 33.2 million pregnancies, of which 35% (11.6 million) were exposed to malaria infection. By WHO subregion, East Africa had a high prevalence of exposure to malaria during pregnancy by 2.4 million (24%) (WHO, 2020).
Malaria remains life-threatening and one of the most significant public health challenges worldwide, and it is amongst the top killers in sub-Saharan Africa. The WHO African Region continues to carry a disproportionately high share of the global malaria burden. In 2018 alone, the region was home to 93% of malaria cases and 94% malaria deaths (WHO, 2019).
Since malaria has significant public health problems, pregnant women are more likely to become infected with malaria than non-pregnant women. Once infected, there is a tendency toward increased severity of the disease. In high-transmission settings, it is associated with maternal illness and low birth weight, while in low transmission areas, malaria usually presents as an acute illness with detectable peripheral parasitemia (WHO, 2018, 2019). In addition to this, malaria susceptibility increases during pregnancy, making these women an important parasite reservoir in the community. Meanwhile, the biology and clinical presentations of Plasmodium falciparum in semi-immune women interfere with diagnosis during pregnancy, rendering targeted interventions ineffective for control. Furthermore, concerns for teratogenicity and embryotoxicity complicate the proposed application of any drugs, vaccines, or anti-vector measures among pregnant women (Fried & Duffy, 2017)
In Somalia, although the prevalence of malaria had dropped dramatically since 2009 when more than a quarter of Somalis (27.3%) were infected to fewer than two percent of the population in 2014, yet malaria endemicity remains in most parts of the central and Southern regions and some areas in the north with other areas being prone to epidemics (UNICEF, 2018).
One out of every 20 women dies due to pregnancy-related causes (Maternal Mortality Ratio is 692 deaths of mothers for 100,000 live births). Maternal health services are low, with 44 and 38 percent of births in Somaliland and Puntland attended by skilled birth attendants (F. R. O. SOMALIA, 2020; U. Somalia, 2015). Additionally, an estimated 11% of neonatal deaths are attributable to LBW due to malaria in sub-Saharan Africa (Singh et al.).
Moreover, no study has been conducted to address the prevalence and associated factors of malaria among pregnant women in the region. Therefore, this study was designed to assess the prevalence of malaria and the factors associated with its infection among pregnant women in the urban area of north-eastern Somalia.
The study was conducted in Bossaso city in the north-eastern Bari province, Somalia. It extends over an area of 28 km2 and is populated by approximately 700,000 residents, its characterized by a hot temperature and a mean annual relative humidity of around 60% (Municipality, 2015). The study was carried out in Bossaso General Hospital, the hospital provides health services to over one million people with six primary departments (Bossaso, G.H., 2019 unpublished raw data). Among these is the maternity department that this research was conducted among pregnant women attending there.
Health institution-based cross-sectional study design was employed from June 7th to September 7th, 2020, where all pregnant women who visited the MCH department in BGH during the study period were illegible to be included however, the pregnant women who visited the MCH in BGH and had a severe illness during the study period were excluded from this study.
The sample size was determined using a single proportion formula using, 95% confidence level, 5% margin of error, and a 50% prevalence of malaria among pregnant women was considered since no previous studies that clearly show the prevalence of malaria among pregnant women has been done in the area. To compensate for the non-response rate, 10% of the determined sample size was added, which resulted in a total sample size of 422
The required number of pregnant women were taken by systematic sampling technique where participants were selected according to a random starting point with a fixed number, whereas the sampling intervals were based on every interval adjusted, the required sample was recruited from the pregnant women who were visiting and willing to give blood for microscopic blood film examination in BGH until the required sample size was achieved.
The study subjects were interviewed using a pre-tested and structured interviewer-administered questionnaire, which was developed in both English and (af-Somali) languages and which was pre-tested on 5% of the sample. The questionnaire contents included socio-demographic factors, maternal, environmental, and other factors, and laboratory results.
Malaria diagnosis was confirmed using microscopic blood films prepared from finger-prick blood samples results collected from selected pregnant women. Experienced laboratory technicians from BGH prepared thick and thin blood films labeled and air-dried horizontally in a slide tray. Thin films were fixed with methanol for about 30 seconds, and both thick and thin films were stained with 3% Giemsa for 20–30 minutes at the study health facilities by using the WHO 2015 standard malaria laboratory procedures guideline (WHO, 2015)
After collecting all the necessary data was coded on the principal investigators’ coding sheet, the collected data were entered and cleaned using Epi INFO version 7. After cleaning, the data was transported to the SPSS version 25 (Chicago, IL, USA) for analysis.
Both descriptive and inferential statistics were performed. In descriptive statistics, tables and graphs were used to depict frequencies, proportions, and summary statistics to describe the study population in relation to relevant variables.
During analysis, both bivariate and multivariable logistic regression techniques were used to determine the extent of association between the different variables related to malaria. Covariates with a p-value less than 0.25 in the bivariate logistic regression analysis were entered into the multivariable logistic regression analysis to control potential confounders and identify malaria-associated factors. A significant association of variables with the outcome was determined using adjusted odds ratios and a 95% confidence interval in multivariable analysis. Variables with a p-value of less than 0.05 were declared as statistically significant.
Attention was given to questionnaire designing, objective-based, logically sequenced, free of scientific terms, and a non-leading structured questionnaire was prepared. Data collectors and supervisors were provided with two days of intensive training on the study’s objective, contents of the questionnaires, and how to maintain confidentiality and privacy of the study subject.
Before the actual data collection began at BGH, pre-testing was conducted on 21 pregnant women visiting a local private health facility. The necessary correction was made on the questionnaires translated into the local languages. The questionnaire was thoroughly checked for errors, impossible values, and inconsistencies due to coding, entry, typing, and other errors. The data collection tools were checked daily for completeness, accuracy, clarity and consistency by investigators.
Stained quality control slides were used to check the quality and performance of the Giemsa stain. Before the examination, the stained patient slides, stained quality control slides were checked for the quality of blood components from malaria-positive blood then, if the quality control slides were satisfactory, the patient slides were cross-checked.
An ethical clearance letter was obtained from Haramaya University, College of Health and Medical Sciences school of public health. The letter was communicated, and permission was obtained from the administrative organization of the hospital and the MCH sub-department. The participants were informed about the purpose of the study and the importance of their participation in the study. Also, there was informed, voluntary, written, and signed consent obtained from the participants. Only the volunteer individuals were involved, and study participants had the right to withdraw from the study at any time. Personal data was kept confidential.
A total of 406 pregnant women participated in the study, with a response rate of 96.2%. The participant’s age ranges from 18 to 45 years, with a mean age of 28.68 (SD ± 5.6) years. The majority of pregnant women belonged to the age group of 25–34 years 216 (53.2%).
Nearly all the respondents were Muslim religion followers 402 (99%). The majority ethnicity component of the participants was Somalis 331 (81.5%). The vast majority of respondents had a family size of fewer than eight individuals, 276 (68%).
Close to half of the pregnant women were housewives 195 (48%), regarding the educational status of pregnant women, close to half of the pregnant women were educated until primary school 192 (47.3%). In comparison, 132 (32.5%) had no formal education. The majority of the participants’ families earn a monthly income of < 100 USD 172 (42.4%) (Table-1).
The largest part of the pregnant women was married 351 (86.5%), multigravidas 237 (67.2%), and slightly more than half of them were in the 3rd trimester of their gestational age 213 (52.5%). The foremost part of participants, 158 (38.9%), had only one ANC visit during the current pregnancy, while 69 (17%) had no ANC visits before. Of those who visited ANC clinics, only a tiny portion of them had health education during their ANC visits, 20 (7.7%).
Of the pregnant women, 94 out of 337 (23.2%) had taken malaria drugs during ANC visits, and from these, 34 (36.2%) of them named SP (Fansidar) the medication that they had taken during their ANC visits.
Slightly more than half of the pregnant women expressed that malaria can be prevented by sleeping under insecticide-treated bed net 196 (48.3%). In comparison, 63 (15.5%) of them did not know that, and half of the participants suggested that they would get treatment within three days (Table 2).
|
Variable |
categories |
frequency |
percent (%) |
|---|---|---|---|
|
Age |
15–24 |
118 |
29.1 |
|
25–34 |
216 |
53.2 |
|
|
≥ 35 |
72 |
17.7 |
|
|
Residence |
Urban |
370 |
91.1 |
|
Rural |
36 |
8.9 |
|
|
Religion |
Muslim |
402 |
99.0 |
|
Christian |
4 |
1.0 |
|
|
Ethnicity |
Somalis |
331 |
81.5 |
|
Somali Bantus |
60 |
14.8 |
|
|
Arab |
3 |
.7 |
|
|
Oromo |
12 |
3.0 |
|
|
Family size |
≤ 7 |
276 |
68.0 |
|
≥ 8 |
130 |
32 |
|
|
Occupation |
Government employed |
3 |
.7 |
|
Private organizational employee |
16 |
3.9 |
|
|
Merchant |
82 |
20.2 |
|
|
Daily laborer |
65 |
16 |
|
|
Farmer |
8 |
2.0 |
|
|
Pastoralist |
37 |
9.1 |
|
|
Housewife |
195 |
48.0 |
|
|
Educational status |
Had no formal education |
132 |
32.5 |
|
Primary school (1-8th) |
192 |
47.3 |
|
|
secondary school (9-12th) and above |
82 |
20.2 |
|
|
Husband’s educational status (n = 351) |
Had no formal education |
3 |
0.9 |
|
Primary school (1-8th) |
116 |
33.0 |
|
|
secondary school (9-12th) and above |
114 |
32.5 |
|
|
Monthly income |
0–99 USD |
172 |
42.4 |
|
100–199 USD |
119 |
29.3 |
|
|
200–299 USD |
70 |
17.2 |
|
|
≥ 300 USD |
45 |
11.1 |
|
Characteristics |
Category |
Frequency |
percentage |
|
|---|---|---|---|---|
|
Current marital status |
Married |
351 |
86.5 |
|
|
Widowed |
23 |
5.7 |
||
|
Divorced |
32 |
7.9 |
||
|
Gravidity |
Primigravida |
49 |
12.1 |
|
|
Secundigravida |
84 |
20.7 |
||
|
Multigravida |
237 |
67.2 |
||
|
Trimester |
1st trimester |
77 |
19 |
|
|
2nd trimester |
116 |
28.6 |
||
|
3rd trimester |
213 |
52.5 |
||
|
Number of ANC visits |
Not visited before |
69 |
17.0 |
|
|
Once |
158 |
38.9 |
||
|
Twice |
110 |
27.1 |
||
|
Three times or more |
69 |
17.0 |
||
|
Had health education during ANC visits (n = 337) |
Yes |
26 |
7.7 |
|
|
No |
311 |
92.3 |
||
|
Taken malaria drugs during ANC visits (n = 337) |
Yes |
94 |
23.2 |
|
|
No |
243 |
59.9 |
||
|
Types of malaria drugs taken (n = 94) |
SP (fansidar) |
34 |
36.2 |
|
|
Do not know |
60 |
63.8 |
||
|
How is malaria transmitted |
Through mosquito bites |
160 |
54.9 |
|
|
By eating tainted food |
79 |
19.5 |
||
|
By drinking contaminated water |
41 |
10.1 |
||
|
Do not know |
63 |
15.5 |
||
|
How is malaria prevented |
Washing fruit and vegetables before eating them |
64 |
15.8 |
|
|
Sleeping under an ITN |
196 |
48.3 |
||
|
Allowing inside the home to be sprayed with insecticides |
146 |
36 |
||
|
If you think you are infected with malaria, how soon should you get tested? |
Within one week |
65 |
16.1 |
|
|
Within three days |
200 |
50 |
||
|
Within 24 hours |
136 |
33.9 |
||
Nearly half of the participants, 194 (47.8%), live in cement-made types of houses. The other housing means include Emergency and transitional shelter 70 (17.2%) and Traditional Somali house 43 (10.6%). Of the participants, 120 (29.6%) have water pond sites around their home or vicinity. A significant proportion of the respondents, 252 (62.5%), stay outside overnight while more than half 257 (63.3%) usually sleep outside their houses.
The majority of the pregnant women’s households had ITNS 256 (63.1%); from these, only 45 (17.6%) mentioned that they always used it, while 68 (26.6%) stated that they never used it. 98 (24.1%) use mosquito repellants from pregnant women, and 49 (12.1%) had at least one indoor residual spraying for the last 12 months (Table 3).
|
Characteristics |
categories |
frequency |
percent (%) |
|---|---|---|---|
|
Type of house |
Mad and Thatch |
6 |
1.5 |
|
cement |
194 |
47.8 |
|
|
stone |
93 |
22.9 |
|
|
Emergency and transitional shelter |
70 |
17.2 |
|
|
Traditional Somali house |
43 |
10.6 |
|
|
Are there any water pond sites around your house or vicinity? |
yes |
120 |
29.6 |
|
no |
286 |
70.4 |
|
|
Do you stay outside overnight after (6:00 pm)? |
yes |
252 |
62.1 |
|
no |
154 |
37.9 |
|
|
Where do you usually sleep? |
inside the house |
149 |
36.7 |
|
outside the house |
257 |
63.3 |
|
|
Does your household have any Insecticide-treated bed nets that can be used while sleeping? |
yes |
256 |
63.1 |
|
no |
150 |
36.9 |
|
|
If yes, how often do you use it? (n = 256) |
Always |
45 |
17.6 |
|
Sometimes |
143 |
55.9 |
|
|
Never |
68 |
26.6 |
|
|
If yes, do mothers and children given priority of using bed nets? (n = 256) |
yes |
126 |
49.2 |
|
no |
130 |
50.8 |
|
|
Do you use mosquito repellants? |
yes |
98 |
24.1 |
|
no |
308 |
75.9 |
|
|
Do you use protective clothing at night (long close cover hands and legs)? |
yes |
129 |
31.8 |
|
no |
277 |
68.2 |
|
|
Was there indoor residual spraying in the last 12 months? |
yes |
49 |
12.1 |
|
no |
357 |
87.9 |
|
|
If yes, how often? (n = 49) |
once |
43 |
87.6 |
|
twice |
6 |
12.2 |
The overall prevalence of malaria among pregnant women in this study was 20.9% [95% CI (15.9%, 25.9%)] of whom 64(75.3%), 19(22.4%), and 2(2.4%) had plasmodium falciparum, plasmodium vivax, and mixed infection respectively.
Factors Associated with Malaria Among Pregnant Women.
To determine the association between malaria and explanatory variables, bivariate and multivariable analyses were performed using binary logistic regression. As shown in (Table 5), there are 12 factors associated with malaria in the bivariate analysis at a p-value of < 0.25, and these include age, gravidity, number of ANC visits, health education during ANC visits, how malaria is transmitted, presence of water pond sites around the house or vicinity, staying outside overnight after (6:00 pm), usually sleeping outside or inside the house, how often ITNS being used, utilization of mosquito repellants, usage of protective clothing at night (long close cover hands and legs), presence of indoor residual sprayed this year.
Then all of these factors listed above were further analyzed and entered into the final model for adjusting confounding factors. After adjusted in multivariable logistic regression, only two factors remained significantly associated with malaria.
Pregnant women who had water pond sites around their house or vicinity had 6.5 times increased odds of malaria infection compared to their counterparts [AOR = 6.5, 95% CI (1.6, 20.5)]. The odds of malaria infection among pregnant women were decreased by 90% for those who always used ITNs compared to those who used it less frequently [AOR = 0.1, 95%CI (0.01, 0.88)] (Table 4).
|
Covariant |
Category |
Malaria status |
COR (95%CL) |
AOR (95%CL) |
|
|
Positive N (%) |
Negative N (%) |
||||
|
Age |
15–24 |
19 (16.1%) |
99 (83.9%) |
1.04 (0.47, 2.3) |
2.25 (0.14, 35.38) |
|
25–34 |
54 (25%) |
162 (75%) |
0.6 (0.3, 1.2) |
2.67 (0.5, 14.32) |
|
|
≥ 35 |
12 (16.7%) |
60 (83.3%) |
1 |
1 |
|
|
Gravidity |
Primigravida |
21 (42.9%) |
28 (57.1%) |
0.31 (0.16, 0.58) |
2.23 (0.14, 35.5) |
|
Secundigravida |
13 (15.5%) |
71 (84.5%) |
1.26 (0.65, 2.44) |
0.7 (0.1, 5.05) |
|
|
multigravida |
51 (18.7%) |
222 (81.3%) |
1 |
1 |
|
|
Number of ANC visits |
Never visited |
33 (47.8%) |
36 (52.2%) |
0.2 (0.88, 0.43) |
2.43 (0.42, 14.12) |
|
Once |
30 (19%) |
128 (81%) |
0.8 (0.38, 1.73) |
0.37 (0.08, 1.7) |
|
|
Twice |
11 (10.0%) |
99 (90.0%) |
1.9 (0.76, 4.74) |
0.19 (0.04, 1.01) |
|
|
Three times or more |
11 (15.9%) |
58 (84.1%) |
1 |
1 |
|
|
Had health education during ANC visits (n = 337) |
Yes |
6 (23.1%) |
20 (76.9%) |
0.56 (0.2, 1.48) |
5.9 (0.7, 46.3) |
|
No |
45 (14.5) |
266 (85.5%) |
1 |
1 |
|
|
How is malaria transmitted |
Through mosquito bites |
50 (22.4) |
173 (77.6%) |
0.58 (0.27, 1.25) |
5.6 (0.94, 33.7) |
|
By eating tainted food |
18 (22.8%) |
61 (77.2%) |
0.57 (0.23, 1.36) |
3.8 (0.55, 26.9) |
|
|
By drinking contaminated water |
8 (19.5%) |
33 (80.5) |
0.69 (0.24, 1.96) |
3.9 (0.43, 36.0) |
|
|
Do not know |
9 (14.3%) |
54 (85.7) |
1 |
1 |
|
|
Presence of water pond sites around your house or vicinity |
yes |
42 (35%) |
78 (65%) |
3.04 (0.2, 0.54) |
6.5 (1.6, 20.53) * |
|
no |
43 (15%) |
243 (85%) |
1 |
1 |
|
|
staying outside overnight after (6:00 pm) |
yes |
63 (25%) |
189 (75%) |
0.5 (0.29, 0.85) |
1.8 (0.6, 5.35) |
|
no |
22 (14.3%) |
132 (85.7%) |
1 |
1 |
|
|
Usually sleep |
Inside the house |
25 (16.8%) |
124 (83.2%) |
1 |
1 |
|
Outside the house |
60 (23.3%) |
197 (76.7%) |
0.66 (0.39, 1.11) |
1.1 (0.33, 3.04) |
|
|
How often ITNS being used (n = 256) |
Always |
6 (13.3%) |
39 (86.7%) |
1.38 (0.53, 3.6) |
0.1 (0.01, 0.88) * |
|
Sometimes |
19 (27.9%) |
49 (72.1) |
0.55 (0.28, 1.08) |
0.9 (0.2, 4.2) |
|
|
Never |
25 (17.5%) |
118 (82.5%) |
1 |
1 |
|
|
Utilization of mosquito repellants |
yes |
12 (12.2%) |
86 (87.8%) |
1 |
1 |
|
no |
73 (23.7%) |
235 (76.3%) |
0.45 (0.23, 0.87) |
2.6 (0.8, 8.42) |
|
|
Usage of protective clothing at night (long close cover hands and legs) |
yes |
20 (15.5%) |
199 (84.5%) |
1 |
1 |
|
no |
65 (23.5%) |
212 (76.9%) |
0.6 (0.35, 1.04) |
1.4 (0.4, 4.7) |
|
|
Presence of IRS this year |
yes |
7 (14.3%) |
42 (85.7%) |
1.68 (0.73, 3.88) |
0.2 (0.02, 1.7) |
|
no |
78 (21.8) |
279 (78.2%) |
1 |
1 |
|
This study assessed the prevalence of malaria infection and associated factors among pregnant women in Bossaso city, Somalia. This study resulted in a prevalence of 20.9%. In addition to these various potential factors assessed in this study, the factors like the presence of water bond sites around the house and always using ITNs were associated with malaria among pregnant women. However, different studies reported different factors that influence the rate of malaria infection among pregnant women.
The prevalence in this study (20.9%) was much closer to a prevalence of a study done in Benin (20.8%) (Accrombessi et al., 2018). However, this finding is more outstanding from the studies conducted in western Ethiopia (10.2%) (Gontie et al., 2020), Salavan province, Laos (5.9%) (Briand et al., 2016), Burkina Faso (18.1%) (Cisse et al., 2014) Nigeria (3.1%) (Isah, Amanabo, & Ekele, 2011) & in Nigeria as well 7.7% (Agomo, Oyibo, Anorlu, & Agomo, 2009). The reason for this discrepancy might be attributed to the difference in geographical location among the study areas. For instance, our study was conducted in a malaria-endemic area with a high rate of transmission. Therefore, individuals living in malaria-endemic areas have a greater chance of developing asymptomatic malaria. In contrast, those living in low transmission areas have a low probability of being infected, leading to a low prevalence of the diseases in such areas. Another reason for the difference could be methodology, including sampling techniques among these studies.
When this figure is compared with the results from Nigeria (41.6%) (Fana et al., 2015), Zambia 31.8% (Chaponda et al., 2015), the findings were found to be lower. The difference in the prevalence might be due to, study period, study design, and economic differences between the study areas and better implementation of improved malaria interventions, including increased coverage in the distribution of ITNS and IRS in our study area. Based on personal communication of the regional health office, this difference might be due to better availability of ITNs in Bossaso, good health awareness of the community, and expanded health service coverage and utilization in Bossaso.
In this study, Plasmodium falciparum and vivax species caused the majority of the cases, 75.3%, and 22.4%, respectively, while the remaining were caused by mixed infection (2.4%). This result is in line with the 2016 screening survey conducted in the Bossaso regional hospital, which showed 73.7%, 25.4% of malaria infections were caused by Plasmodium falciparum and vivax correspondingly (NMCPs/MoH, 2016). However, our result was lower than the WHO Somalia prevalence reports of the species, which was > 95% of malaria species in the country was due to plasmodium falciparum (WHO, 2010a). On the other hand, the proportion of malaria cases caused by Plasmodium falciparum in our study was lower than the WHO malaria 2018 report, which revealed over 99% of malaria cases in the Africa region were due to Plasmodium falciparum (WHO, 2019b). The possible reason for these variations might be due to marked seasonal, inter-annual, and spatial variability. It may also be due to significant differences in climate (temperature, rainfall, and relative humidity), human settlement, and population movement patterns.
Our study also assessed socio-demographic, obstetric, environmental, and ITN ownership and utilization factors. As a result, the presence of water pond sites around the house or vicinity, how often ITNs being used were significantly associated with malaria.
In this study, always using malaria preventive ITNS significantly associated decreased the odds of developing malaria infection during pregnancy [AOR = 0.1, 95%CI (0.01, 0.88)]. A similar association was found in a study conducted in Lagos, Nigeria (Agomo & Oyibo, 2013). The possible explanation could be due to UNICEF’s recent provision of ITNS and community awareness campaigns by the MOH. The use of ITNs reduces malaria transmission, and it is one of the proven, cost-effective components of malaria prevention through the vector control approach.
In the present study, having water pond sites around the house or vicinity was significantly associated with the occurrence of malaria in pregnant women [AOR = 6.5, 95% CI (1.6, 20.5)]. This finding is in line with a study conducted in Uganda (Musoke et al., 2018) and other studies done in east India, which described it as a potential source of transmission (Sabin et al., 2018). The presence of stagnant water could explain which is an environmental risk factor that increases the breeding of mosquitoes near homes. The relatively inexpensive measures of removing pools of water have been shown to significantly reduce mosquito abundance and malaria incidence. Such interventions can be used with core malaria prevention methods, such as the utilization of ITNs as a strategy to minimize the occurrence of the disease.
Overall, a timely intervention strategy is mandatory and should focus on the WHO recommended three-pronged approach for malaria in pregnancy, which includes ITNS, IPT and case management. In this study, although the majority of the pregnant women had ITNs, yet only a few of them were regularly using it, so the health care providers in the region and stakeholders should create health awareness campaigns on the importance of using ITNs and specifically target pregnant women during routine care visits. In addition to this, a small portion of pregnant women had Sulfadoxine-pyrimethamine during ANC visits. This is also another area that the health care providers should work on since the administration of SP to the pregnant women has already demonstrated significant reductions in the morbidity and mortality of malaria in pregnancy.
The time of data collection may affect the prevalence due to seasonal variation of malaria transmission. The study did not include a qualitative method, particularly observation of housing conditions. The low prevalence of some of the associated factors created a wide confidence interval reducing the precision of the findings.
This study was conducted in the COVID-19 era, where health systems have become overwhelmed with the efforts required to stop the coronavirus transmission, and hospitals have struggled to cope with increasing numbers of COVID-19 cases. This led to comprehensive concerns about the potential consequences of the pandemic, including disruptions of essential health services including malaria services.
The study found that the overall prevalence of malaria among pregnant women in the study area was found to be high. The high proportion of these malaria species in our study clearly implies that there is a need for aggressive prevention and control of the diseases, especially among pregnant women. Because Plasmodium falciparum causes the most severe form of the disease, and it can cause devastating complications not only for the mother but also for the fetus. Factors significantly associated with malaria were only two factors; the presence of water pond sites and how often ITNs were being used.
The study recommends district health offices to provide broad-scale health education and awareness-building projects to the pregnant women communities regarding cleaning their surroundings and removing stagnant water pools as to prevent mosquito abundance and hence decrease malaria incidence.
The health care providers should deliver health education sessions to pregnant women during routine care visits and teach them different malaria prevention methods, especially the importance of ITNs.
The study encourages MOH and other stakeholders to do further studies on the specific types and other causes of malaria. Using more advanced equipment could motivate more focused clinical management of selected pregnant women and result in essential improvements in their overall health and survival.
Above all, we would like to express our heart complete gratitude to Haramaya University, notably the college of health science and medical science, for providing us for this opportunity. We would also like to thank the Bossaso General Hospital administration and directors for their cooperation. Furthermore, we would also like to extend our acknowledgment to our beloved family members, friends, data collectors, and study participants for their unreserved efforts in delivering their professional support technique and helping us in preparing the research
Conflict Of Interest
The authors declared no competing of interest
Authors’ Contributions
AJ has contributed substantially from the idea's inception, proposal development, data collection, analysis, interpretation, final write-up, and manuscript drafting. TA and AA designed the work, edited the proposal, revised it, and facilitated the publication process. After reading and approving the submitted paper in its final form, the authors agreed to be responsible for all aspects of the work.
Data Availability
The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.
Funding Statement
Haramaya university's postgraduate directorate funded this study. The funding body had no role in designing the study, data collection, analysis, interpretation, and manuscript writing.