Prevalence and associated risk factors of malaria in Amhara National Regional State: a systematic review and meta-analyses

Abstract

Background

Malaria is a major parasitic infectious disease caused by Plasmodium species and remains a significant public health challenge in sub-Saharan African, including Ethiopia. The Amhara National Regional State is among the most malaria-affected region in Ethiopia. However, comprehensive evidence on the pooled prevalence of malaria and its associated risks in the region has been limited. Therefore, this systematic review and meta-analysis aimed to estimate the pooled prevalence of malaria and identify its associated risk factors in Amhara National Regional State.

Methods

A systematic search of studies published between 2013 to March 3, 2023, was conducted using PubMed, Springer nature, Science Direct, and Google Scholar. Eligible studies were selected based on predefined inclusion criteria. Data were extracted using Microsoft Excel and analysed with Stata version 17. Heterogeneity among studies was assessed using the inverse variance (I²) statistic, while publication bias was evaluated using Egger’s regression test and funnel plot.

Results

Out of 2,743 records initially identified, 43 studies met the inclusion criteria. The pooled prevalence of malaria in the Amhara National Regional State was 14% (95% CI 12.0–17.0%). Subgroup analysis showed that the highest (17%, 95% CI 4.0–30.0%) pooled prevalence was from South and North Gonder Zones, whereas the lowest (8%, 95% CI 5.0–11.0%) prevalence was observed in East Gojjam Zone. Malaria prevalence estimate varied according to the diagnostic methods; with microscopy reporting a prevalence of 16%; 95% CI 13.0–18% and combination of microscopy with RDT reporting 9%; 95% CI 4.0–14.0%. The prevalence increased from 13% (95% CI 10.0–17%) before the onset of COVID-19 pandemic to 15% (95% CI 14.0–10.0%) after the onset. Plasmodium falciparum was the predominant species, accounting 9% (95% CI 6–11%) of the infection followed by P. vivax at 5% (95% CI 4–5%). Significant predictors of malarial infection included, the presence of stagnant water near residences (OR = 2.64; 95% CI 2.09–3.34), engagement in outdoor night activities (OR = 1.69; 95% CI 1.33–2.16), and lack of insecticide treated net (ITN) utilization (OR = 2.05; 95% CI 1.71–2.46).

Conclusion

This systematic review and meta-analysis revealed that malaria remained a considerable public health burden in the Amhara National Regional State with Plasmodium falciparum as the dominant species. Malaria prevalence varied across administrative zones, diagnostic methods, study seasons, and study periods. Environmental and behavioural factors significantly contributed to malaria transmission, highlighting the need for a strengthened and targeted malaria prevention and controlled interventions in the region.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12936-026-06034-4.

Introduction

Malaria is a vector-borne parasitic disease caused by protozoan parasites of the genus Plasmodium. Five Plasmodium species are known to infect humans: Plasmodium falciparum, P. vivax, P. ovale, P. malariae, and P. knowlesi [1]. Transmission occurs through the bite of an infected female Anopheles mosquito, which serves as the disease vector. Both the parasite and the vector thrive in warm environments that facilitate completion of their life cycles [2], which explains why malaria is predominantly distributed in tropical and subtropical regions, particularly in sub-Saharan African countries.

Malaria remains a leading cause of morbidity and mortality worldwide and poses a major global public health challenge. In 2022, the World Health Organization (WHO) estimated approximately 249 million cases and 608,000 globally [3]. The burden is disproportionately concentrated in Africa, which accounted for about 94% of all cases and 95% of all deaths in 2022. Notably, under five children represent approximately 80% of malaria-related deaths during the same year [3].

Ethiopia continues to face a substantial malaria burden. In 2022, 60% of the population was at risk of malaria [4], and 6.4% of Woredas (districts) experienced high transmission intensity. Among communicable diseases in the country, malaria accounts for about 30% of overall disability-adjusted life years lost [5] and contributes to 2.8% of mortality due to infectious and parasitic diseases [6]. Malaria transmission in Ethiopia is characteristically unstable and seasonal, largely influenced by altitude and climatic conditions. This instability limits the development of herd immunity, which leads to focal outbreaks and cyclic epidemics [7]. As a result, malaria epidemics often affect all age groups and may rapidly progress to severe disease, posing recurrent public health emergencies across the country, including the present study area.

A systematic review and meta-analysis conducted in 2021 identified the highest malaria prevalence in three regional states; the former Southern Nations, Nationalities, and People’s region (SNNPR) (16.17%), Oromia Regional State (13.11%), and Amhara National Regional State (ANRS) (12.41%) [8]. Thus, ANRS is among the-most malaria affected region in the country, with approximately 80% of its landmass classified as malarious and 68% of its population living at risk of malaria infection [9]. The average test positivity rate for malaria in the region has been reported as 21.9% by combination of microscopy and RDT. Although malaria prevention and control interventions have been implemented in line with the National Malaria Strategic Plan, the disease burden remains substantial.

Since 2019, malaria cases have increased in several parts of the region. This resurgence has been attributed to multiple factors, including inadequate larval source management, limited leadership commitment, security challenges and population displacement. In addition, the COVID-19 pandemic contributed to the resurgence by causing shortage of antimalarial drugs, disruptions in supply chain, and compromised quality of malaria diagnostic services [9–11]. Consequently, malaria remains a major public health concern in ANRS, disproportionately affecting vulnerable populations such as children and pregnant women [12].

Although numerous studies have assessed malaria prevalence and associated risk factors in different zones of ANRS, the available evidence has not been comprehensively synthesized at the regional level. Therefore, this systematic review and meta-analysis aimed to estimate the pooled prevalence of malaria, assess variations across administrative zones, and identify the major risk factors associated with malaria infection in the Amhara Regional State.

Material and methods

Study design and setting

A systematic review and meta-analysis were conducted in the Amhara National Regional State (ANRS), northwestern Ethiopia (9°–14° N, 36°–40° E). The region comprises 11 administrative zones and over 105 districts, with elevations ranging from 700 to 4,600 m above sea level. Malaria transmission in Ethiopia has traditionally been concentrated in lowland (< 1,500 m) and mid-altitude (1,500–2,500 m) areas, where temperatures are favourable for mosquito survival and parasite development. However, recent evidence indicates increasing malaria transmission in highland areas (> 2,500 m), which were previously considered low-risk. This expansion is likely driven by climatic changes, including rising temperatures and altered rainfall patterns, as well as environmental and demographic factors that create favourable conditions for malaria transmission. The study period (2013–2023) was selected to capture a decade of malaria transmission during a time of considerable climatic variability, providing sufficient temporal coverage to assess trends in malaria prevalence and associated risk factors.

Search strategies

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was used to conduct this review. Articles published in English were searched from public databases: PubMed, Springer Nature, Science Direct, and Google Scholar. Studies published between 2013 and March 3, 2023, that met the eligibility criteria were considered for inclusion. The core search terms and phrases were “malaria,” “prevalence,” “epidemiology,” “associated factors,” “risk factors” and “Amhara,” combined using Boolean operators (“AND” and “OR”). A typical search string was: (“malaria” OR “Malaria” [MeSH Terms]) AND (“prevalence” OR “Prevalence” [MeSH Terms]) AND (“associated factors” OR “risk factors” [MeSH Terms]) AND (“Amhara” [MeSH Terms]).

Inclusion and exclusion criteria

Inclusion criteria

Studies published in English between 2013 to March 3, 2023 were eligible for inclusion. Cross-sectional, prospective, and retrospective studies that reporting the prevalence of malaria and/or associated risk factors among populations in the Amhara National Regional State were included.

Exclusion criteria

Studies published before 2013, articles written in languages other than English, studies conducted outside Amhara region, and studies with inaccessible full texts were excluded.

Outcomes of the study

This systematic review and meta-analysis assessed two main outcomes. The primary outcome was the pooled prevalence of malaria, while the secondary outcome was the identification of factors associated with malaria infection. Malaria prevalence was defined as the proportion of individuals diagnosed with by microscopy, rapid diagnostic test (RDT), or combination of both methods at a given time point. Associated risk factors were defined as condition, behaviour, or exposures that increased the likelihood of malaria infection. The strength of association between malaria and these factors was quantified using odds ratios (OR).

Data extraction and quality assessment

Data extraction

Data extraction was performed independently by two reviewers (AT and TH) using a standardized Microsoft Excel spread sheet. The extracted information the author name, year of publication, area of study (zone), study design, sample size, study population, diagnostic method (microscopy and/or RDT), the prevalence of malaria, and total malaria cases, the number of attributed to each Plasmodium species. Any discrepancy between reviewers was resolved through discussion. When consensus could not be reached, a third reviewer (SM) was consulted to make the final decision.

Quality assessment for the studies

The methodological quality of the included studies was assessed using a modified version of the Newcastle–Ottawa Scale (NOS) [13, 14] adapted for cross sectional studies. Each item was scored as either “Yes” of “No”, and the overall quality score was obtained by summing the individual item scores. Studies scoring ≥ 7 points were classified as having low risk of bias, those scoring 3–6 points as having moderate risk of bias, and those scores below 3 points as having high risk of bias.

Data processing and analysis

Data extracted from eligible studies were analysed using STATA version 17. A random-effects model was used for estimating the pooled prevalence of malaria and pooled odds ratios for associated risk factors, since substantial heterogeneity anticipated among the included studies. Statistical heterogeneity among studies were assessed using I² statistics [15]. I² values below 25%, between 25 and 50%, and above 50% were considered to indicate low, moderate and high heterogeneity, respectively. To explore potential sources of heterogeneity, subgroup analysis and meta-regression were performed. Moreover, sensitivity test was conducted to evaluate the influence of individual study on the overall pooled estimates. The small study effect and publication bias were assessed using funnel plot and Egger's regression test.

Results

The initial search identifies 2,743 articles reporting the prevalence of malaria and its associated factors among different population groups in the Amhara National Regional State (ANRS), including children under five years of age, schoolchildren, adults, febrile patients, asymptomatic migrant laborers, pregnant women, and delivering mothers. These records were retrieved from PubMed, Google Scholar, and other sources described previously. Of the identified records, 757 articles were excluded due to duplications. The titles of the remaining 1,986 articles were screened, leading to the exclusion of 1,871 articles. Subsequently, 60 articles were excluded after abstract review because they were not relevant to this review and full texts were not accessible. Following full-text assessment, 12 additional articles were excluded based on the predefined eligibility criteria. Consequently, 43 studies met the inclusion criteria and were included in the final systematic review and meta-analysis (Fig. 1).

Fig. 1.

PRISMA flow diagram showing the selection of studies included in the systematic review and meta-analysis of the prevalence and associated risk factors of malaria in Amhara region

Characteristics of the eligible studies

The 43 eligible studies [16–58], published between 2013 to March 3, 2023, included a total of 693,175 participants and were used to estimate the pooled prevalence of malaria and its associated risk factors in the ANRS. The studies were conducted across 10 administrative zones of the Amhara region. The reported malaria prevalence ranged from 2.8% in West Gojjam Zone to 61.6% in North Gondar Zone. The sample sizes varied considerably, ranging from 149 to 212, 952 participants. The characteristic of the included studies included in this systematic review and meta-analysis are presented in Table 1.

Table 1.

Characteristics of the eligible studies included in this systematic review and meta-analysis in Amhara National Regional State

Author (Year of publication)	Study period	Study areas	Study setting	Study season	Clinical status	Age category	Diagnostic test	Sample size	No- of cases	Prevalence (%)	Quality score (10%)
Abate et al. 2014 [16]	2011	Shewa Robit	Community based	Spring	Mixed	All age	Microscopy	425	12	2.8	8
Abebaw et al. 2022 [17]	2018	Debre Elias	Community based	Autumn	Mixed	All age	Microscopy & RDT	440	22	5	9
Adugna et al. 2022 [18]	2021	Around Lake Tana	Institution-based	Year round	Symptomatic	All age	Microscopy	513	131	25.5	8
Alelign et al. 2018 [19]	2013	Woreta town	Institution-based	Winter	Symptomatic	All age	Microscopy	102,520	33,431	32.6	8
Alemu et al. 2014 [17]	2013	Metema, Enfranz, & Makisegnit	Institution-based	Autumn	Symptomatic	All age	Microscopy & PCR	297	183	61.6	5
Almaw et al. 2022 [21]	2019	Tis Abay, Zenzelma & Hamusit	Institution-based	Autumn	Symptomatic	Pregnant women	Microscopy	312	65	20.8	9
Aschale et al. 2018 [22]	2016	West Armachiho	Institution-based	Spring	Asymptomatic	≥ 15 years	Microscopy	385	71	18.4	7
Ayalew et al. 2016 [23]	2013	Jiga town	Community based	Spring	Mixed	All age	RDT	392	11	2.8	6
Belay et al. 2020 [24]	2018	Chagni Town	Institution-based	Spring	Symptomatic	All age	Microscopy	4077	296	7.3	6
Daba et al. 2023 [25]	2020	Jile tumuga, Aruma fursi, & Dawachefa	Institution-based	Winter	Symptomatic	All age	Microscopy	212,952	33,005	15.5	9
Daba et al. 2021 [26]	2020	Bati hospital	Institution-based	Year round	Symptomatic	All age	Microscopy & RDT	84,269	12,032	14.3	6
Debash et al. 2022 [27]	2022	Zequala	Institution-based	Winter	Symptomatic	Under 5 years	Microscopy	633	156	24.6	6
Dejazmach et al. 2021 [28]	2020	Bahir Dar Zuria	Institution-based	Winter	Symptomatic	All age	Microscopy& RDT	149	22	14.8	6
Derbie et al. 2017 [29]	2016	Woreta town	Institution-based	Year round	Symptomatic	All age	Microscopy	8057	434	5.4	7
Eshetu et al. 2022 [30]	2020	Makisegnit	Institution-based	Year round	Symptomatic	All age	Microscopy	28,217	4641	16.4	9
Fekadu et al. 2018 [31]	2017	Dembia district	Community based	Spring	Asymptomatic	≥ 15 years	RDT	832	56	6.7	7
Feleke et al. 2020 [32]	2019	Karakore, Ataye and Senbete towns	Institution-based	Spring	Asymptomatic	Pregnant women	Microscopy & RDT	263	15	5.7	8
Feleke et al. 2018 [33]	2017	Ataye town	Institution-based	Year round	Symptomatic	All age	Microscopy	31,810	2670	8.4	7
Ferede et al. 2013 [34]	2013	Metema town	Institution-based	Year round	Symptomatic	All age	Microscopy	55,833	9486	17	7
Gebretseadik et al. 2018 [35]	2016	Kombolcha	Institution-based	Year round	Symptomatic	All age	Microscopy	27,492	2066	7.52	8
Gethun et al. 2018 [36]	2020	Bahir Dar Zuria	Institution-based	Summer	Symptomatic	All age	Microscopy	391	111	28.4	9
Haile et al. 2020 [37]	2018	Dembecha town	Institution-based	Year round	Symptomatic	All age	Microscopy	12,766	2086	16.34	7
Kassie et al. 2014 [38]	2013	Dejen district	Community based	Spring	Asymptomatic	All age	Microscopy	403	53	13.2	5
Limenih et al. 2021 [39]	2021	Kuch town	Institution-based	Autumn	Mixed	Pregnant women	Microscopy	218	14	6.4	6
Melese et al. 2022 [40]	2019	Raya Kobo	Community based	Winter	Asymptomatic	All age	Microscopy, PCR & RDT	270	19	7	7
Minwuyelet et al. 2021 [41]	2019	Bichena	Institution-based	Year round	Symptomatic	All age	Microscopy	9182	852	9.3	8
Minwuyelet et al. 2020 [42]	2019	Gondar Zuria	Community based	Autumn	Asymptomatic	All age	Microscopy	251	30	11.9	8
Mulugeta et al. 2022 [43]	2019	Gonder town	Institution-based	Year round	Symptomatic	All age	Microscopy	17,500	1341	7.7	4
Negatu et al. 2022 [45]	2020	Hamusit town	Institution-based	Winter	Symptomatic	All age	Microscopy	210	61	29	7
Shiferawu et al. 2021 [45]	2017	Shewa Robit	Institution-based	Year round	Symptomatic	All age	Microscopy	33,932	4705	13.9	9
Tarekegn et al. 2021 [46]	2018	Dembeya district	Institution-based	Spring	Symptomatic	All age	Microscopy	735	26	3.5	7
Tazebew et al. 2021 [47]	2018	Estie District	Institution-based	Year round	Symptomatic	All age	Microscopy	390	33	8.5	8
Tesfa et al. 2018 [48]	2013	Ady Arkay	Institution-based	Year round	Symptomatic	All age	Microscopy	20,483	7382	36.1	7
Tesfaye et al. 2022 [49]	2018	Shewa Robit	Institution-based	Year round	Symptomatic	All age	Microscopy	422	81	19.2	8
Tilahun et al. 2020 [50]	2019	Fendka town	Institution-based	Winter	Asymptomatic	Pregnant women	Microscopy, PCR & RDT	331	37	11.2	8
Tilaye et al. 2021 [51]	2018	Metema district	Community based	Year round	Mixed	≥ 15 years	Microscopy	2201	354	16.1	8
Tilaye et al. 2022 [52]	2019	Metema district	Community based	Year round	Asymptomatic	≥ 15 years	Microscopy	1208	212	17.5	8
Tsega et al. 2020 [53]	2018	Bibugn district	Institution-based	Year round	Mixed	All age	Microscopy	822	46	5.6	7
Tsegaye et al. 2021 [54]	2019	Wegera district	Institution-based	Spring	Symptomatic	< 5 years	Microscopy	585	51	8.7	8
Workineh et al. 2021a [55]	2020	Addis Zemen &Woreta	Institution-based	Year round	Symptomatic	≤ 15 years	Microscopy	422	62	14.7	10
Workineh et al. 2021b [56]	2020	Libokemkem district	Institution-based	Year round	Symptomatic	All age	Microscopy	15,452	1688	10.9	7
Worku et al. 2014 [57]	2013	Sanja town	Institution-based	Winter	Asymptomatic	6–15 years	Microscopy	383	26	6.8	9
Yimer et al. 2017 [58]	2014	Bahir Dar City	Institution-based	Year round	Symptomatic	All age	Microscopy	14,750	740	5	6

Mixed: studies include symptomatic and asymptomatic study subjects

Publication bias across studies

Publication bias was assessed visually using a funnel plot, which showed a symmetrical distribution of studies, suggesting the absence of publication bias (Fig. 2). This finding was further supported by Egger’s regression test, which showed no statistically significant evidence of publication bias across the included studies (p > 0.9999). These results indicate that the observed variation among studies was unlikely to be influenced by publication bias.

Fig. 2.

Funnel plots indicate absence of publication bias across the eligible studies included in systematic review and Meta-analysis

Prevalence of malaria in Amhara National Regional State

Based on the analysis of 43 studies conducted over a ten-year period among different population groups, the pooled prevalence of malaria in the ANRS was 14% (95% CI 12.0–17.0). Considerable heterogeneity was observed across the included studies (I² = 99.93% and P < 0.001) (Fig. 3).

Fig. 3.

Forest plot showed the pooled prevalence of malaria in Amhara National Regional State

Plasmodium species detected in the study participants

The present systematic review and meta-analysis identified two malaria parasite species in the region: P. falciparum and P. vivax. The pooled prevalence of P. falciparum, P. vivax, and mixed infections was 9% (95% CI 6–11%), 5% (95% CI 4–5%), and 1% (95% CI 0–1%), respectively. Thus, P. falciparum was the predominant malarial parasite species in Amhara National Regional State (Fig. 4).

Fig. 4.

Pie chart for the pooled prevalence of Plasmodium species causing malaria in Amhara National Regional State (n = 43)

Subgroup analysis

Subgroup analyses were conducted to explore variations in malaria prevalence according to administrative zone, diagnostic method, study setting, study population, study period, study season, and clinical status of participant (Figs. 5, 6, 7, 8, 9, 10 and Table 2). Zone-based subgroup analysis showed that the highest pooled prevalence was observed in North and South Gonder Zones (17%), whereas the lowest pooled prevalence was recorded in East Gojjam Zone (8%). The pooled prevalence estimates and the number of studies included from each administrative zone were presented in Table 2 and Supplementary Fig. 1.

Fig. 5.

Forest plot showed the pooled prevalence of malaria based on year of studies in Amhara National Regional State (n = 43)

Fig. 6.

Forest plot showed the pooled prevalence of malaria based on clinical status of the participant in Amhara National Regional State (n = 43)

Fig. 7.

Forest plot showed the pooled prevalence of malaria based on study settings in Amhara National Regional State (n = 43)

Fig. 8.

Forest plot showed the pooled prevalence of malaria based on nature of study participants in Amhara National Regional State (n = 43)

Fig. 9.

Forest plot showed the pooled prevalence of malaria based on diagnostic methods in Amhara National Regional State (n = 43)

Fig. 10.

Forest plot showed the pooled prevalence of malaria across study season in Amhara National Regional State (n = 43)

Table 2.

The pooled prevalence of malaria across administrative Zones in Amhara National Regional State (n = 43)

Zones	No. of studies included	Prevalence (95% CI)
East Gojam	4	8 (5–11)
West Gojam	8	15 (8–22)
North Gondar	13	17 (12–22)
South Gondar	6	17 (4–30)
North Shoa	5	10 (4–14)
Agew Awi	2	9 (5–13)
Oromo Special Zone	2	15 (14–16)
North Wello	1	7 (4.3–10.7
South Wello	1	7.5 (7.2–7.8)
Wag hemra	1	24.6 (21.3–28.3)
Total	43	14 (12.0–17.0)

The subgroup analysis by study period revealed a higher pooled prevalence of malaria among studies conducted between 2019 and 2022 (15%; 95% CI 135–17%) than among studies conducted before 2019 (13%; 95% CI 10–17%) (Fig. 5). The year 2019 was selected as a cut-off point to assess the potential influence of COVID-19 pandemic on malaria transmission and control activities.

The pooled prevalence of malaria was higher among symptomatic individuals (17%; 95% CI 14–20%) than among asymptomatic individuals (11.0%; 95% CI 8–14%) (Fig. 6). Similarly, studies conducted in health facilities reported a higher prevalence (16%; 95% CI 13–18%) compared with community-based studies 9%; 95% CI 5–13%) (Fig. 7). The pooled prevalence of malaria was comparable in all age categories while slightly lower among pregnant women (Fig. 8).

The pooled prevalence of malaria detected using microscopy alone was 16% (95% CI 13–18%) compared with 9%; 95% CI 4–11% among studies using a combination of microscopy and RDT (Fig. 9). Seasonal analysis showed that malaria prevalence was highest during autumn (21%; 95% CI 5–37%) and the lowest during spring (7%; 95% CI 5–9%) (Fig. 10).

Meta-regression and sensitivity analysis

Substantial heterogeneity was observed among studies included in this systematic review and meta-analysis. Therefore, meta-regression analysis was conducted to identify potential sources of heterogeneity. The results suggested that the clinical status of study participants contributed to the observed heterogeneity (regression coefficient = 0.650, 95% CI 0.496–0.852, p = 0.003). Study season also marginally contributed to heterogeneity (regression coefficient = 1.309, 95% CI 1.089–1.575, p = 0.05). In contrast, year of period (regression coefficient = 0.1.459, 95% CI 0.930–2.290, p = 0.098), diagnostic method (regression coefficient = 0.909, 95% CI 0.730–1.132, p = 0.386), age of category of participants (regression coefficient = 0.982, 95% CI 0.836–1.152, p = 0.819), and study setting (regression coefficient = 0.616, 95% CI 0.369–1.031, p = 0.065) did not significantly explain the observed heterogeneity. Furthermore, sensitivity analysis was performed by sequentially excluding one study at a time and recalculating the pooled prevalence estimate. The overall pooled prevalence remained largely unchanged, indicating that no single study had a disproportionate influence on the pooled estimate.

Factors associated with malaria parasite infection in Amhara National Regional State

Eleven potential risk factors for malaria infection were evaluated, including sex, residence, family size, educational status, outdoor activity at night, use of insecticide treated net (ITN), indoor residual spraying (IRS), previous history of malaria, malaria-related health education, presence of holes in house walls, and stagnant water near the household (Figs. 11, 12, 13).

Fig. 11.

Forest plot showed the strength of association between the prevalence of malaria with socio-demographic variables (n = 43)

Fig. 12.

Forest plot showed the strength of association between the prevalence of malaria with possible risk factors (n = 43)

Fig. 13.

Forest plot showed the strength of association between the prevalence of malaria with ITN and IRS usage (n = 43)

The association between sex and malaria infection was assessed from 24 studies, which quantify the association in odd ratio in individual papers. The pooled analysis showed that males were significantly more likely to be infected with malaria than females (OR = 1.24; 95% CI 1.20–1.27, p < 0.001), indicating males were about 1.24 times higher chance of infection than females. Similarly, 6 studies examined the association between family size and malaria infection. Individual living in households with five or more members had significantly higher odds of malaria infection than those living in smaller households (OR = 1.40; 95% CI 1.00–1.83, p = 0.021) (Fig. 11).

Place of residence was evaluated in 15 studies. Individuals living in rural areas were more likely to be infected with malaria than urban residents (OR = 1.43; 95% CI 1.32, 1.56; p = 0.031). Similarly, pooled analysis of 13 studies showed that illiterate individuals had higher odds of malaria infection than literate individuals (OR = 1.19; 95% CI 0.89, 1.71, p = 0.012) (Fig. 11).

Eight studies assessed the association of night outdoor activities and malarial infection. Participants engaged outdoor activities during the night had significantly higher odds of malaria infection than those who did not (OR = 1.69; 95% CI 1.33–2.16, p < 0.001). Similarly, nine studies examined the relationship between previous malaria infections and current infection status. Participants with a history of malaria infection were more likely to experience subsequent infection than those without such history (OR = 1.37; 95% CI 1.07, 1.75, p < 0.001) (Fig. 12).

Eight studies investigate the relationship between proximity to stagnant water and malarial infection. Individuals living near stagnant water bodies had significantly higher odds of malaria infection than those living farther away (OR = 2.64; 95% CI 2.09, 3.34; p < 0.001). Similarly, housing conditions were assessed in seven studies. Individuals living in houses with holes in the walls had significantly higher odds of malarial infection than those living in houses without wall openings (OR = 1.36; 95% CI 1.09, 1.69; p < 0.001) (Fig. 12).

The association between ITN utilization and malarial infection was evaluated in 22 studies. Individuals who did not regularly use ITN had approximately twice the odds of malaria infection compared with regular users (OR = 2.05; 95% CI 1.72–2.42, p < 0.001). Similarly, ten studies assessed the association between IRS and malaria infection. Although individuals who did not use IRS had higher odds of malaria infection than those who did (OR = 1.44; 95% CI 1.07–1.94), the association was not statistically significant (p = 0.106) (Fig. 13).

Discussion

Synthesizing existing evidence is essential for informing malaria prevention and control strategies and guiding policy decisions. In this systematic review and meta-analysis, the pooled prevalence of malaria in the Amhara National Regional State (ANRS) was 14%. This estimate is comparable to that reported in a systematic review conducted in Mauritania, 14.9% [59]. However, it is higher than the pooled prevalence reported among children (9.07%) [60] and pregnant women (12.7%) in Ethiopia [61]. Conversely, the prevalence observed in the present review was substantially lower than the pooled estimate reported from sub-Saharan Africa (32%) [62]. These differences may be attributed to ecological conditions, transmission intensity, intervention coverage, sensitivity of diagnostic techniques used, study periods, and sampling approaches across studies [43, 63].

The present review showed that P. falciparum was the predominant malaria parasite in the region, followed by P. vivax. This findings is consistent with previous systematic review conducted in Ethiopia [64], although it differs from studies conducted elsewhere [65, 66]. Such discrepancies may be explained by differences in study population, climatic conditions, sample sizes, and diagnosis methods [67]. The predominance of P. falciparum is of particular concern because it is associated with severe malaria, higher mortality, and the emergence of antimalarial drug resistance.

Malaria prevalence varied considerable across administrative zones. The highest prevalence was observed in North and South Gonder Zones, whereas the lowest prevalence was reported in East Gojjam Zone. These variations may reflect differences in malaria endemicity, climatic and environmental conditions, rainfall patterns, irrigation practice, proximity to mosquitoes breeding sites, and the coverage of malaria control interventions [8]. North Gonder Zone includes malaria hotspot areas such as Humera and Metam, which have historically experienced high malaria transmission. These findings highlight the need for geographically targeted malaria control strategies, particularly in high-transmission zones.

The prevalence of malaria was higher among symptomatic individuals. This difference may be explained by the development of herd immunity among asymptomatic carriers, which can suppress parasite densities below the detection threshold of conventional diagnostic method [17, 59]. Similarly, studies conducted in health facilities reported higher malaria prevalence than community based studies. This is expected because health facility attendees are more likely to seek care for malaria-related symptoms, whereas community based studies include both symptomatic and asymptomatic individuals [17].

Migrant workers and children were identifies as particularly vulnerable groups. Migrant workers are frequently engaged in outdoor activities during peak mosquitoes biting hours and often move from low-transmission areas, increasing their exposure to malaria vectors [68–70]. Children are also have at increased risk because of their relatively underdeveloped immunity to malaria infection [71]. These findings underscore the need for targeted interventions for vulnerable populations, including migrant laboreres and children.

A higher prevalence of malaria was observed in studies conducted during autumn than in other seasons. This pattern is consistent with the seasonal epidemiology of malaria in Ethiopia, where transmission is strongly influenced by rainfall. Autumn (September to December) corresponds to peak malaria transmission season, while spring (April to June), represent a secondary transmission period [72]. Nevertheless, malaria transmission may occur throughout the year in some areas where environmental conditions remains favourable for vector breeding and parasite development [73, 74].

The pooled prevalence of malaria was higher in studies conducted between 2019 and 2022 than in those conducted before 2019. This increase may be associated with disruptions caused by the COVID-19 pandemic, which diverted resources and attention away from malaria prevention and control activities [9]. Furthermore, the armed conflict in the region may have disrupted healthcare services, displaced populations, and reduced access to malaria prevention measures thereby contributing to increased malaria transmission.

This review also examined several factors associated with malaria infection, including sex, place of residence, family size, educational status, outdoor activity, ITN usage, IRS, previous history of malaria, malaria-related knowledge, housing conditions, and the presence of stagnant water near the household. Accordingly, male participants were more likely to be infected with malaria than females, consistent with findings from previous studies [75, 76]. This difference may be attributed to greater outdoor exposure among males during farming and other occupational activities, particularly during the evening and night time when mosquito biting activities is highest. In addition, men may spend extended periods away from home without adequate malaria protection [75]. These findings suggest that malaria prevention programs should give particular attention to males engaged in outdoor occupations.

Rural residence was significantly associated with malaria infection, consistent with previous studies [77–79]. Similarly, individuals living in houses with holes in the wall also had a higher risk of malaria infection than those living in better-constructed houses [80]. Poor housing conditions, closer proximity to mosquitoes breading sites, and limited access to malaria prevention measures may contribute to the elevated risk observed among rural population [81]. Improved housing quality and strengthening malaria prevention efforts in rural communities may therefore reduce malaria transmission.

Individuals from households with five or more family member had higher odds of malaria infection than those from smaller households, a finding that agrees with previous studies [79, 82, 83]. Larger family size may attract more mosquitoes because of stronger olfactory cues and may have insufficient ITNs to adequately protect all family members [75] Ensuring equitable distribution of ITNs according to household size may help reduce this risk.

Educational status was significantly associated with malaria infection. Illiterate individuals were more likely to be infected with malaria than literate individuals, consistent with previous studies [77, 82, 84]. Similarly, lack of knowledge regarding malaria prevention and control was associated with a higher risk of infection, which is consistent with other reports of [82, 85]. These findings highlight the importance of education and community awareness in the successful implementation of malarias prevention strategies. Strengthening malaria-related health education, particularly among populations with limited literacy, may contribute to reducing malaria transmission.

The presence of stagnant water near their home was strongly associated with malaria infection. Individuals living near stagnant water bodies were more than twice as likely to be infected with malaria as those living farther away. This finding is consistent with reports from elsewhere [82, 84–87]. Stagnant water provides favorable breeding habitats for mosquitoes, thereby increasing human-vector contact and the risk of infection [88]. Environmental management strategies aimed at reducing mosquitoes breeding sites should therefore be strengthened.

Engagement in outdoor activities at night was also associated with increased malaria risk. Individuals involved in night time outdoor activities had significantly higher odds of infection than those who were not, which is consistent with others studies [82, 85]. This may be due to increase exposure to mosquito bite during peak vector activity period [89]. Promoting personal protective measures for individuals engaged in nigh time is therefore essential.

Regular use of ITN remains one of the most effective malaria prevention measures. Individuals who did not regularly use ITN had approximately twice the odds of malaria infection compared with regular users, a finding consistent with previous studies conducted in Ethiopia and elsewhere [82–85, 87]. Likewise, the absence of indoor residual spraying was associated with an increased risk of malaria infection, which is in line with other reports [82, 84, 85, 87]. This finding emphasize the importance of maintain adequate ITN coverage and ensuring regular IRS implementation in malaria-endemic areas.

Finally, a pervious history of malaria infection was also associated with an increased the risk of subsequent infection, which is consistent with previous studies [80, 82]. This finding may particularly relevant for P. vivax infection, which can cause relapse due to dormant-liver stage hypnozoites if radical cure is not achieved with appropriate treatment, such as primaquine.

Overall, the identified risk factors have important implications for malaria prevention and measures in the region. Government agencies and other stakeholders should incorporate targeted strategies to address these risk factors and reduce malaria transmission. Particular emphasis should be placed on high-risk populations through seasonal indoor residual spraying, expanded distribution and proper utilization of insecticide treated nets, environmental management, and strengthened community health education programs.

Limitation of the study

Although this study presents important findings, it has also several limitations. First, the included studies were unevenly distributed across the administrative zones of the ANRS, which may have affected the regional representativeness of the pooled estimates. Second, only published articles were included, and therefore relevant unpublished studies may have been missed. Third, the review was restricted to studies published between 2013 and March 2023; consequently, more recent evidence was not captured. Fourth, variations in sampling approaches across studies, including community-based random sampling and health facility-based non-random sampling of symptomatic individuals, may have influenced the pooled prevalence estimates. Fifth, the diagnostic methods used were not uniform. Three studies used polymerase chain reaction (PCR), seven used rapid diagnostic tests (RDTs), and the remaining studies relied on microscopy. Differences in the sensitivity and specificity of these diagnostic techniques may have affected the estimated prevalence of malaria. In addition, due to inconsistencies in the definition and classification of risk factors across studies, not all identified factors could be quantitatively synthesized in the meta-analysis. Finally, although subgroup and meta-regression analyses were conducted, residual heterogeneity remained unexplained, indicating that other unmeasured factors may have contributed to the observed variability among studies.

Conclusion

This systematic review and meta-analysis estimated the pooled prevalence of malaria in the Amhara National Regional State at 14.2%, indicating that malaria remains a significant public health concern in the region. Plasmodium falciparum was the predominant malaria parasite species, followed by P. vivax. Given the greater potential of P. falciparum to cause severe disease, mortality, and the emergence of antimalarial drug resistance, its predominance has important implications for malaria control and elimination efforts in the region.

Malaria prevalence varied across administrative zones, diagnostic methods, study settings, study populations, study periods, and the clinical status of participants. Several socio-demographic, environmental, and behavioral factors were significantly associated with malaria infection, highlighting the multifactorial nature of malaria transmission.

These findings underscore the need for strengthened and targeted malaria prevention and control interventions, particularly in high-burden areas and among vulnerable populations. Enhanced community health education, especially in rural settings, improved utilization of insecticide-treated nets and indoor residual spraying, environmental management, and strengthened surveillance systems are essential to reduce malaria transmission. Continued technical, financial, and logistical support from the Ministry of Health and other stakeholders will be critical for accelerating progress toward malaria control and eventual elimination in the region.

Abbreviations

IRS

Indoor residual spraying

ITNs

Insecticide-treated nets

LSM

Larval source management

OR

Odds ratio

SNNP

Southern Nations, Nationalities, and Peoples’ Region

SSA

Sub-Saharan Africa

WHO

World Health Organization

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

CI

Confident interval

FDREMH

Federal democratic Republic of Ethiopia Ministry of Health

Author contributions

AT is involved in the design, data collection, data analysis, interpretation of the finding and drafting the manuscript. TH and SM were involved data analysis, interpretation, drafting and reviewing the manuscript.

Funding

The author’s received no financial support for the review authorship, and/or publication of this manuscript.

Data availability

All data generated or analysed during this study are included in this published article and its supplementary information files.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.