Anopheles stephensi bionomics and epidemiology in Ethiopia: A systematic review and meta-analysis with implications for urban malaria control

Anopheles stephensi bionomics and epidemiology in Ethiopia: A systematic review and meta-analysis with implications for urban malaria control | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Anopheles stephensi bionomics and epidemiology in Ethiopia: A systematic review and meta-analysis with implications for urban malaria control Teresa Beyena, Kidane Lelisa, Abdissa Deberssa, Lemma Regesa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8849944/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background An. stephensi , an invasive malaria vector originally endemic to South Asia, has rapidly expanded across East Africa. Its emergence in Ethiopia threatens malaria elimination progress, particularly in urban areas where populations were previously considered at lower risk. We conducted a systematic review to synthesise evidence on its bionomics and epidemiological role in Ethiopia, with implications for urban malaria control strategies. Methods We conducted a PRISMA 2020-compliant systematic review and meta-analysis registered with PROSPERO (CRD420251176953). Searches of PubMed, Scopus, Web of Science, and regional repositories (2016–February 2026) identified studies reporting An. stephensi bionomics and epidemiological role in Ethiopia. Eligible studies required ≥ 50% quality score on JBI appraisal tools. Random-effects meta-analysis estimated pooled proportions of An. stephensi among total Anopheles , with subgroup analyses by geography, habitat, and behavioural traits. Publication bias was assessed using Egger’s and Begg’s tests. Results Eighteen studies (9 epidemiological, 11 bionomical) met inclusion criteria. The pooled proportion of An. stephensi was 0.51 (95% CI: 0.28–0.75) in epidemiological studies and 0.46 (95% CI: 0.26–0.66) in bionomics studies, with extreme heterogeneity (I² > 99%). Geographic variation was marked: South-eastern Ethiopia showed near-total dominance (0.73), while Central Ethiopia reported lower proportions (0.13). Extreme heterogeneity reflected genuine ecological variation across Ethiopia. No evidence of publication bias was detected. Conclusion An. stephensi has very rapidly emerged as a major malaria vector in Ethiopia, utilising urban environments and showing behavioural adaptability. The presence of this vector poses a threat to malaria elimination efforts and highlights the importance of integrated urban vector management, which includes reducing larval sources, using targeted insecticides, and engaging in community-based interventions. Future research should prioritise longitudinal surveillance and insecticide resistance management to inform evidence-based control. Entomology Anopheles stephensi bionomics Ethiopia meta-analysis urban malaria vector surveillance Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Introduction Malaria remains a significant economic and public health challenge in Ethiopia, which puts millions of people at risk of infection every year [ 1 – 4 ]. Malaria transmission in the country has historically been dominated by the vector An. arabiensis , with secondary vectors such as An. funestus, An. pharoensis , and An. nili , as well as An. coustani [ 5 – 6 ]. The recent invasion of An. stephensi , a vector previously confined to South Asia and the Middle East, has complicated to the Ethiopian malaria epidemiology [ 7 , 8 ]. Unlike traditional rural vectors, An. stephensi exhibits ecological adaptive, thriving in urban settings using artificial water sources including overhead tanks, construction sites, and waste containers [ 9 , 10 ]. This adaptability allows it to colonise densely populated areas, challenging the long-held assumption that urbanisation reduces malaria risk [ 11 , 12 ]. Its capacity to transmit both P. falciparum and P. vivax complicates the challenge, as Ethiopia is currently dealing with a dual burden of these two parasites. This indicates that the first invasive malaria vector has established itself in urban Africa, suggesting a paradigm shift in transmission dynamics [ 8 , 12 ]. An. stephensi' historical distribution was mostly limited to South Asia, particularly India, Pakistan, and parts of the Arabian Peninsula [ 8 – 14 ]. Its detection in Djibouti in 2012 marked the beginning of its rapid expansion across East Africa [ 15 , 16 ]. Subsequent reports confirmed its presence in Ethiopia in 2016, first in Dire Dawa and later expanding to several regions, including Somali, Afar, and, most recently southern Ethiopia [ 17 , 18 , 21 , 25 ]. Its expansion correlates with growing urbanisation, which produces favourable breeding conditions. Alarmingly, modelling studies suggest that the spread of An. stephensi might put over 126 million Africans at risk for malaria [ 19 ]. Its invasion represents not only geographical expansion but also a shift in malaria transmission, particularly in previously low-prevalence urban areas. An. stephensi role in urban malaria is becoming increasingly evident, with its prevalence associated with increased malaria incidence in Ethiopian urban areas. Unlike rural vectors, An. stephensi bites early in the evening, reducing the effectiveness of long-lasting insecticidal nets (LLINs) [ 21 , 27 ]. This behavioural shift requires a re-evaluation of current control strategies, including LLINs and IRS [ 27 ]. The adaptability across ecological niches, as well as the increasing resistance to widely used insecticides, highlights its importance in changing the epidemiology of malaria in Ethiopia [ 22 , 23 ]. Because the species preferentially uses human-made habitats, traditional vector management strategies based on rural transmission may not be sufficient to address the challenges posed by this invasive vector. Failure to adapt policies could reverse two decades of malaria control progress [ 24 ]. The emerging evidence shows that An. stephensi may influence the seasonal malaria transmission patterns, potentially extending transmission periods in urban centres [ 23 ]. Ethiopia has made significant achievements in decreasing malaria incidence during the last two decades, but the An. stephensi invasion threatens to undermine these successes [ 25 ]. The World Health Organization (WHO) has identified An. stephensi as a significant new vector in Africa and warns that its spread might threaten malaria control efforts across the continent [ 13 ]. Ethiopia's growing urbanisation, which provides ideal habitats, makes resolving this issue even more urgent. This challenge is not confined to Ethiopia; neighbouring East African countries face similar risks, showing the continental implications of An. stephensi spread [ 13 , 25 ]. Despite increasing indications of An. stephensi spreading, significant gaps remain in the understanding of its biology, epidemiology, and resistance patterns in Ethiopia. Studies have documented its spatiotemporal distribution and seasonal dynamics, as well as its establishment in various ecological zones [ 22 , 25 ], but a comprehensive review is required. Resistance to pyrethroids and carbamates affects the efficacy of LLINs and indoor residual spraying (IRS) [ 26 , 27 ]. Without a complete synthesis, control programmes risk depending on fragmented evidence. This review therefore presents the first pooled quantitative synthesis of An. stephensi bionomics and epidemiology in Ethiopia. Historically, Ethiopia's urban malaria control strategies have focused on reducing habitats and promoting the use of LLINs as a control method. However, An. stephensi ecology, including its preference for artificial containers and biting behaviour, makes these measures ineffective [ 25 , 28 , 20 ]. Insecticide resistance complicates control, demanding new approaches including larval source management, integrated vector control, and community-based interventions [ 26 ]. Findings will directly inform Ethiopia’s National Malaria Elimination Program and WHO regional vector control frameworks. This systematic review addresses this gap by synthesising all available quantitative data to provide policymakers and control programmes with an evidence-based understanding of An. stephensi establishment and invasive potential in Ethiopia. It aims to determine the distribution and proportion of An. stephensi within Ethiopian Anopheles populations, evaluate its epidemiological importance across various geographic and ecological settings, and characterise the bionomic traits. The seasonal variations, evidence quality, and research gaps were examined with contrasts to other East African countries where An. stephensi has been identified. By combining various findings, this review gives a foundation for designing context-specific, evidence-based interventions against An. stephensi in Ethiopia and beyond. Method Design and Protocol This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA-P 2020) guidelines (29). The study selection process was documented with a four-stage PRISMA flow diagram, which depicts the steps taken from the initial collection of identified records to the final set of studies included in the analysis. The review protocol was developed in advance to ensure methodological transparency, and it was formally registered with the International Prospective Register of Systematic Reviews (PROSPERO) under the registration number CRD420251176953. Database and Search Strategy This systematic review and meta-analysis began on November 30, 2025, and included eligible studies conducted in Ethiopia and published in English until February 10, 2026. To ensure complete coverage, electronic databases and grey literature sources were thoroughly investigated. We searched PubMed, Scopus, Science Direct, Web of Science, and Google Scholar, as well as regional repositories and grey literature. Search terms were combined with Boolean operators ("AND" and "OR") and adapted for each platform's syntax. The primary search string used across databases was ('Anopheles stephensi' OR 'urban mosquito') AND (Ethiopia OR 'Eastern' OR 'Southern' OR 'Central' OR 'South-western') AND ('bionomics' OR 'epidemiology' OR 'host preference' OR 'resting behaviour' OR 'breeding habitat' OR 'distribution' OR 'malaria'). Search filters were applied for publication date (2016–February 2026) and language (English). Reference lists of included studies were screened using a snowballing approach for additional relevant studies. Eligibility Criteria Records were imported into EndNote X7 for organization and duplicate removal. Inclusion criteria were: studies conducted in Ethiopia; entomological data on Anopheles (any life stage); outcomes reporting the proportion of An. stephensi or bionomic traits (habitat, feeding, resting, behaviour); and study designs including cross-sectional, case-control, cohort/prospective, modelling studies, and systematic reviews with primary data. Exclusion criteria were: studies outside Ethiopia; human-only clinical studies without entomological data; case reports, editorials, opinion pieces, and conference abstracts without full text; non-English publications; and studies published before 2016. Studies were eligible only if they scored ≥ 50% on the JBI quality appraisal. The eligibility criteria for the studies were shown in Table 1 . Table 1 summary inclusion and exclusion criteria Criterion Inclusion Exclusion Geographic Location Studies conducted in Ethiopia Studies outside Ethiopia Study Population Anopheles mosquitoes (any stage) in Ethiopia Human populations only; vector studies from other countries Outcomes Proportion of An. stephensi; bionomics data (habitat, feeding, resting, behaviour) Clinical malaria outcomes without entomological data Study Design Cross-sectional, case-control, prospective, modelled data; systematic reviews Case reports, editorials, opinion pieces, conference abstracts without full text Publication Status Peer-reviewed articles; grey literature with full text Non-English publications; partial data Publication Date 2016–February, 2026 Prior to 2016 Data Quality Studies with ≥ 50% JBI quality score Studies with < 50% JBI quality score Outcome of Interest The primary outcome was the proportion of An. stephensi among all Anopheles collected in each study, expressed as n/N. Secondary outcomes included bionomic characteristics (breeding habitat type, host preference, resting location, and feeding time), seasonal patterns, surveillance method, and ecological zone. Study Selection and quality Assessment Two reviewers (T.B. and K.L.) independently reviewed titles and abstracts. Then, three reviewers (T.B., K.L., and A.D.) assessed full-text publications for eligibility criteria. Disagreements were resolved by discussion and, where necessary, adjudicated by a fourth reviewer (L.R.). Study quality was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Prevalence Studies for cross-sectional designs and the JBI Checklist for Cohort Studies for prospective designs. Each item was scored as “yes” (1), “no” (0), or “unclear” (0), yielding a maximum score of 9. Studies scoring ≥ 4.5 (50%) were included (30). Data Extraction A standardised data extraction form was tested on three studies and then applied to all included studies. Extracted items included first author, year, study location and ecological zone, study design, sampling method, sample frame, collection period and season, total Anopheles collected (N), number of An. stephensi (n), method of species identification (morphological and/or molecular), and bionomic variables (breeding habitat, host preference, resting behaviour, and feeding time). Funding sources and declared conflicts of interest were also recorded. Two reviewers independently extracted data; discrepancies were resolved by consensus. Data Synthesis and Analysis All extracted data was organised in Excel and then imported into STATA version 19.5 (StataCorp, College Station, Texas, USA) for statistical analysis. A random-effects meta-analysis approach was used to obtain pooled estimates of An. stephensi proportions, taking into account study heterogeneity. The subgroup analyses were established to investigate potential sources of heterogeneity based on ecological factors (geographic zone, habitat type), vector behaviour (host preference, resting patterns, feeding time), and study design factors (epidemiological domain, surveillance method, collection season). Significant subgroup differences were found using interaction testing (Q statistic) at p < 0.05. The point estimates were reported with 95% confidence intervals. The I² statistic was used to quantify heterogeneity, with the following interpretations: I² 75% = extreme heterogeneity. Random-effects models were used throughout, with the expectation of significant heterogeneity due to regional and ecological variation. Tau² estimations are presented alongside I² to measure the variance between studies. Publication bias was evaluated using (1) visual assessment of the funnel plot; (2) Egger's weighted regression test (p < 0.05 showing bias); (3) Begg's rank correlation test (p < 0.05 indicating bias); and (4) trim-and-fill analysis to estimate the number and size of potentially missing studies. Stata's metabias and metatrim commands were used. Results Search Results A total of 4,410 records were identified from electronic databases, including PubMed (2,892 records), Science Direct (365 records), and Scopus (218 records), as well as an additional 752 records from Google Scholar. After eliminating 2,832 duplicate records, 2,393 records remained for screening. During the screening stage, 2,017 records were excluded after a review of their titles and abstracts. A full-text screening of 107 publications showed 49 articles that were potentially relevant based on title and abstract review. During the full-text review, 33 papers were removed for the following reasons: lack of outcome of interest (n = 24), the study location being outside Ethiopia (n = 4), non-English publishing (n = 3), and insufficient methodological transparency (n = 2). This identified 18 eligible studies for inclusion in the systematic review. As shown in Fig. 1 , the PRISMA 2020 flow diagram summarizes the study selection process and reasons for exclusion. Characteristics of the Included Studies A total of 18 studies published between 2016 and 2025 were analysed [ 20 , 25 , 28 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. Most of the studies were conducted in Eastern Ethiopia (n = 12), with additional studies from Central Ethiopia (n = 2), Southern Ethiopia (n = 1), and South-eastern Ethiopia (n = 2), along with one multi-site study. Sample sizes varied significantly, from a low of 34 specimens [ 31 ] to a high of 49,482 specimens [ 32 ], with reported proportions of An. stephensi values ranging from 0.07 to 1.0. Several studies [ 33 – 36 ] reported very high proportions (≥ 0.8), particularly in Eastern Ethiopia. Quality appraisal scores ranged from 7 to 9, with most of the studies scoring 8 or 9, strengthening confidence in pooled estimates. Detailed summary of included studies were shown in below Table 2 . Table 2 Characteristics of included studies on An. stephensi in Ethiopia 2016–2025 Study Year of Publication Zone Total Anopheles Proportion Research Focus Quality Score/9 Abiy et al. (37) 2021 Central Ethiopia 1900 0.13 Bionomics 7 Ashine et al. (25) 2024 Central Ethiopia 8121 0.09 Both 7 Balkew et al. (38) 2021 Eastern Ethiopia 3217 0.32 Bionomics 8 Balkew et al. (39) 2020 Eastern Ethiopia 3417 0.65 Bionomics 9 Carter et al. (33) 2018 Eastern Ethiopia 535 0.99 Bionomics 9 Carter et al. (40) 2021 Eastern Ethiopia 565 0.33 Bionomics 8 Degefa et al. (35) 2025 Eastern Ethiopia 16135 0.89 Bionomics 9 Emiru et al. (34) 2023 Eastern Ethiopia 1267 0.93 Epidemiology 9 Hamlet et al. (31) 2022 Eastern Ethiopia 34 0.79 Epidemiology 9 Hawaria et al. (41) 2025 Multi-sites 738 0.07 Epidemiology 7 Hawaria et al. (42) 2023 Southern Ethiopia 548 0.43 Bionomics 9 Merga et al. (28) 2024 Eastern Ethiopia 1715 0.13 Bionomics 7 Merga et al. (20) 2025 Eastern Ethiopia 5159 0.43 Both 9 Tadesse et al. (32) 2021 South-eastern 49482 1 Epidemiology 9 Waymire et al. (43) 2025 South-eastern 599 0.27 Epidemiology 8 Yared et al. (36) 2025 Eastern Ethiopia 15560 0.88 Bionomics 9 Yared et al. (44) 2023 Eastern Ethiopia 561 0.33 Epidemiology 8 Zhou et al. (45) 2024 Eastern Ethiopia 2212 0.37 Epidemiology 9 Both = studies reporting both epidemiological and bionomic outcomes. Epidemiological proportion of Anopheles stephensi The meta-analysis included nine studies focusing on the epidemiological proportion of An. stephensi among Anopheles mosquitoes in diverse ecological and urban contexts in Ethiopia. The reported proportions varied widely, from 0.07 in [ 41 ] and 0.08 in [ 46 ] to near-total dominance of 1.00 [ 32 ]. Very high proportions of An. stephensi have been documented with proportions of 0.93 [ 34 ], 0.79 [ 31 ], and 0.79[ 47 ]. Moderate proportions of ecological variables were observed [ 45 ] with a reported estimate of 0.37 [ 44 ] at 0.33 and [ 43 ] at 0.27, indicative of mixed-species habitats or transitional ecological zones. The overall pooled proportion was 0.51 (95% CI: 0.28–0.75; z = 4.24, p < 0.001). Heterogeneity was extreme (τ² = 0.13, I² = 99.98%, H² = 4393.96), reflecting genuine ecological and epidemiological variability across Ethiopia. This underscores the importance of stratified analyses by ecological zone. Results are summarised in Fig. 2 . Subgroup Analysis by Geographic Zone and Epidemiological Domain Subgroup analysis by geographic zone showed significant variation in the proportion of An. stephensi among all Anopheles mosquitoes across Ethiopia. In Eastern Ethiopia, the pooled proportion was 0.57 (95% CI: 0.32–0.82), with extreme heterogeneity (τ² = 0.06, I² = 99.69%). Estimates ranged from 0.33 [ 44 ] to 0.79 [ 31 , 20 ]. In multi-site studies, the pooled proportion was much lower at 0.08 (95% CI: 0.07–0.08), with negligible heterogeneity (I² = 0.07%), suggesting consistent results across ecological zones [ 25 , 41 ]. In South-eastern Ethiopia, the pooled proportion reached 0.73 (95% CI: 0.28–1.18), with marked heterogeneity (τ² = 0.16, I² = 99.97%), largely driven by differences between [ 32 ] and [ 43 ]. Overall, the pooled proportion across all zones was 0.51 (95% CI: 0.28–0.75), and subgroup differences were statistically significant (Q(2) = 22.89, p < 0.001; Fig. 3 ). Similarly, subgroup meta-analysis across epidemiological domains showed distinct trends. In the entomological + molecular category, proportions ranged from 0.07 [ 41 ] to 1.00 [ 32 ], with a pooled estimate of 0.35 (95% CI: 0.08–0.78; z = 1.62, p = 0.11) and high heterogeneity (τ² = 0.19, I² = 99.99%). The epidemiology group included two studies, with proportions ranging from 0.37 [ 45 ] to 0.93 [ 46 ]; the pooled estimate was 0.65 (95% CI: 0.11–1.19; z = 2.34, p = 0.02), with marked heterogeneity (τ² = 0.15, I² = 99.95%). The modelling group reported proportions from 0.33 [ 44 ] to 0.79 [ 31 , 20 ], yielding a pooled estimate of 0.64 (95% CI: 0.33–0.94; z = 4.12, p < 0.001) with high heterogeneity (τ² = 0.07, I² = 99.39%). The overall pooled proportion across all domains was 0.51 (95% CI: 0.28–0.75), and subgroup differences were not statistically significant (Q(2) = 1.23, p = 0.54; Fig. 4 ). Subgroup analysis by study design Subgroup meta-analysis across epidemiological study designs showed distinct trends in the proportion of An. stephensi among total Anopheles mosquitoes. The cross-sectional studies reported proportions ranging from 0.07 [ 41 ] to 1.00 [ 32 ], with a pooled estimate of 0.35 (95% CI: 0.08–0.78; z = 1.62, p = 0.11). Heterogeneity was extreme (τ² = 0.19, I² = 99.99%). The modelling group included studies [ 8 , 20 , 44 ] with proportions ranging from 0.33 to 0.79, with a pooled estimate of 0.64 (95% CI: 0.33–0.94; z = 4.12, p < 0.001) and high heterogeneity (τ² = 0.07, I² = 99.39%). Prospective case–control studies [ 34 , 45 ] reported proportions of 0.93 and 0.37 and a pooled estimate of 0.65 (95% CI: 0.11–1.19; z = 2.34, p = 0.02) and marked heterogeneity (τ² = 0.15, I² = 99.95%). The overall pooled proportion across all study designs was 0.51 (95% CI: 0.28–0.75), with extreme heterogeneity (I² = 99.98%). Subgroup differences were not statistically significant (Q(2) = 1.23, p = 0.54; Fig. 5 ). Funnel Plot and Publication Bias Assessment The funnel plot analysis showed no evidence of publication bias in the epidemiological dataset. The inverse-variance weighted estimate (θ_IV) indicated central alignment and symmetrical distribution of studies within the pseudo 95% confidence limits (Fig. 6 ). Egger’s regression test (β₁ = 2.67, p = 0.685) and Begg’s test (Kendall’s score = 2.00, p = 0.917) were non-significant. Trim-and-fill analysis confirmed symmetry, with no imputed studies and a stable pooled estimate (0.989, 95% CI: 0.988–0.989). This suggests robustness of the pooled results despite high heterogeneity. Proportion of Anopheles stephensi Bionomics The forest plot meta-analysis of bionomics studies revealed substantial variation in the proportion of An. stephensi across ecological and behavioural contexts. Estimates ranged from a low of 0.13 [ 46 , 28 , 37 ] to a high of 0.99 [ 48 ]. Intermediate proportions were reported at 0.32 [ 38 ], 0.33 [ 40 ], and 0.43 [ 18 ]. Degefa et al. [ 35 ] reported a proportion of 0.89, closely followed by Yared et al. [ 36 ] with 0.88, both supported by large sample sizes. The random-effects model yielded a pooled proportion of 0.46 (95% CI: 0.26–0.66; z = 4.46, p < 0.001). Heterogeneity was extreme (τ² = 0.11, I² = 99.98%, H² = 4,120.87), reflecting ecological diversity and methodological variability across studies. This confirms the significant presence of An. stephensi in diverse bionomic contexts. Results are summarised in Fig. 7 . Subgroup analysis by Ecological Zone and Habitat type of the bionomics studies Subgroup analysis of bionomics studies revealed significant geographical differences in the proportion of An. stephensi among total Anopheles mosquitoes. In Eastern Ethiopia, individual studies reported moderate estimates of 0.32 [ 22 ] and 0.33 [ 40 ], with an overall pooled proportion of 0.60 (95% CI: 0.35–0.85). In Southern Ethiopia, An. stephensi was less dominant, with a proportion of 0.43 reported by Hawaria et al. [ 18 ]. Studies from Central Ethiopia indicated a lower proportion of approximately 0.13, as reported by Merga et al. [ 28 ], Abiy et al. [ 37 ], and Ashine et al. [ 25 ], with a pooled proportion of 0.13 (95% CI: 0.12–0.14). The overall pooled proportion across ecological zones was 0.46 (95% CI: 0.26–0.66), with significant heterogeneity (τ² = 0.11, I² = 99.98%; Fig. 8 ). Similarly, subgroup meta-analysis by habitat type showed variation in the proportion of An. stephensi . In artificial habitats, pooled estimates ranged from 0.13 [ 25 , 28 ] to 0.89 [ 35 ], with a pooled proportion of 0.45 (95% CI: 0.22–0.67; z = 3.88, p < 0.001). In mixed natural and artificial habitats, estimates varied from 0.13 [ 37 ] to 0.99 [ 33 ], with a pooled proportion of 0.48 (95% CI: 0.03–0.99; z = 1.85, p = 0.06). Heterogeneity was substantial (τ² = 0.20, I² = 99.98%). The overall pooled proportion across all habitat types was 0.46 (95% CI: 0.26–0.66), with no statistically significant subgroup differences (Q(1) = 0.02, p = 0.90; Fig. 9 ). Subgroup Feeding Preference Subgroup meta-analysis by feeding preference showed significant variation in the proportion of An. stephensi . In the human-associated habitat subgroup, proportions ranged from 0.13 [ 28 , 20 ] to 0.89 [ 35 ], with a pooled estimate of 0.34 (95% CI: 0.07–0.61; z = 2.48, p = 0.01). Heterogeneity was substantial (τ² = 0.11, I² = 99.97%). In the mixed habitat subgroup, proportions ranged from 0.32 [ 38 ] to 0.99 [ 33 ], with a pooled estimate of 0.59 (95% CI: 0.31–0.87; z = 4.14, p < 0.001). Heterogeneity was high (τ² = 0.10, I² = 99.96%). The overall pooled proportion was 0.46 (95% CI: 0.26–0.66), with no statistically significant subgroup differences (Q(1) = 1.53, p = 0.22; Fig. 10 ). Subgroup by resting preference Subgroup meta-analysis by resting preference revealed distinct patterns of the proportion of An. stephensi among total Anopheles mosquitoes. Indoor studies reported proportions ranging from 0.13 [ 25 , 20 , 37 ] to 0.89 [ 2 ], with a pooled estimate of 0.42 (95% CI: 0.15–0.69; z = 3.01, p < 0.001). Heterogeneity was marked (τ² = 0.14, I² = 99.98%). Indoor and outdoor studies reported proportions from 0.32 [ 38 ] to 0.99 [ 33 ], with a pooled estimate of 0.52 (95% CI: 0.21–0.83; z = 3.25, p < 0.001). Heterogeneity remained high (τ² = 0.10, I² = 99.90%). The overall pooled proportion across resting preferences was 0.46 (95% CI: 0.26–0.66), with no statistically significant subgroup differences (Q(1) = 0.21, p = 0.64; Fig. 11 ). Seasonal design A subgroup meta-analysis of seasonal collection periods identified significant variations in the proportion of An. stephensi mosquitoes among total Anopheles populations. Seasonal studies reported proportions from 0.13 [ 25 , 28 , 20 ] to 0.99 [ 33 ], with a pooled estimate of 0.43 (95% CI: 0.16–0.70; z = 3.12, p < 0.001). Heterogeneity was extreme (τ² = 0.13, I² = 99.98%). Year-round studies reported proportions from 0.13 [ 37 ] to 0.88 [ 36 ], with a pooled estimate of 0.50 (95% CI: 0.17–0.82; z = 3.00, p < 0.001). Heterogeneity remained high (τ² = 0.11, I² = 99.95%). The overall pooled proportion across seasonal designs was 0.46 (95% CI: 0.26–0.66), with no statistically significant subgroup differences (Q(1) = 0.10, p = 0.76; Fig. 12 ). Publication Bias and Funnel plot The funnel plot for the An. stephensi bionomics dataset showed no evidence of publication bias, with symmetrical distribution of studies around the pooled estimate (Fig. 13). Egger’s regression (β₁ = − 18.94, z = − 1.11, p = 0.27) and Begg’s test (Kendall’s score = − 7.00, z = − 0.62, p = 0.64) were non-significant. Trim-and-fill analysis indicated no missing studies, with a stable pooled estimate of 0.455 (95% CI: 0.255–0.655). Discussions The rapid spread of An. stephensi in African urban areas poses a significant threat to malaria prevention efforts, potentially reversing decades of progress [ 49 , 50 , 51 ]. Its spread in Ethiopia poses a particular challenge to malaria control, allowing for year-round urban outbreaks that are becoming increasingly resistant to standard insecticides and diagnostic techniques [ 17 , 52 ]. This systematic review and meta-analysis revealed that An. stephensi has quickly emerged as the dominant malaria vector in Ethiopia and the Horn of Africa. The overall pooled epidemiological proportion was 0.51 (95% CI: 0.28–0.75), while the overall pooled bionomics proportion was 0.46 (95% CI: 0.26–0.66). These findings suggest that the species has swiftly evolved in urban and peri-urban habitats, with reported proportions ranging from a low presence of 0.07–0.08 [ 41 , 46 ] to near-total domination of 1.00 [ 32 ]. Emiru et al. [ 34 ], Hamlet et al. [ 31 ], and Merga et al. [ 20 ] all reported high proportions (≥ 0.8), showing their epidemiological relevance. Moderate proportions (0.27–0.37) in transitional zones [ 43 , 45 ] indicate coexistence with other Anopheles species. Geographic heterogeneity implies that south-eastern Ethiopia has nearly complete dominance [ 32 , 43 ]. On the other hand, Eastern Ethiopia frequently reported high proportion rates when compared to [ 34 , 35 , 36 ], but Central Ethiopia had low proportions of 0.13 [ 25 , 37 ]. These findings highlight how An. stephensi thrives in urbanised ecosystems modified by human activity, notably water storage and peri-domestic habitats showed comparable variability over the Horn of Africa [ 52 ]. Ethiopia's trajectory reflects invasion tendencies in surrounding East African countries and throughout the world. In Djibouti, native vectors were displaced within 5–8 years after identification, with An. stephensi accounting for 0.80–0.95 [ 53 , 54 ]. Similar patterns have been seen in Sudan [ 55 ] and Somalia [ 56 ]. In India, the species thrives in artificial environments like water storage tanks and building sites, with proportions of around 0.80 [ 57 ]. Reports from Iran and Saudi Arabia demonstrate its adaptation to peridomestic habitats and seasonal persistence (14). Climate suitability models forecast increasing spread throughout Africa, exposing millions to urban malaria risk [ 19 ]. The bionomics analysis highlights An. stephensi ecological adaptability. The species prefers artificial breeding sites [ 33 , 35 ], is adaptable to both human-only and mixed-host habitats [ 40 , 42 ], may be found in both indoor and outdoor resting locations [ 20 , 36 ], and is most active in the evening and night [ 34 , 45 ]. Seasonal persistence has been shown in both seasonal and year-round samples [ 25 – 37 ]. This behavioural variability challenges traditional management strategies established for rural vectors like An. arabiensis and An. funestus [ 25 , 58 ]. The spread of An. stephensi in urban environments creates serious public health concerns. Standard interventions like long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are ineffective due to the mosquito's exophagic and exophagic behaviour [ 21 , 27 ]. Rapid urbanisation accelerates its growth, but resistance to pyrethroids and carbamates complicates control efforts. To address these challenges, urgent policy action is essential. Priority actions include improving urban entomological surveillance to monitor An. stephensi populations, managing artificial breeding sites through larval source management, implementing integrated vector management with environmental modification, biological control, and insecticide use, and promoting community-based interventions to reduce breeding habitats. Strengths and Limitations This review's methodological rigorousness is a significant strength: it follows the PRISMA 2020 recommendations, is registered with PROSPERO, and includes both epidemiological and bionomic research. The results were completely evaluated for publication bias using symmetrical funnel plots and non-significant Egger's and Begg's tests. However, extreme heterogeneity (I² = 99.98%) restricts the generalizability of pooled values, demonstrating ecological diversity and methodological variability. Evidence gaps remain, including a lack of data from Central Ethiopia, insecticide susceptibility studies, and longitudinal parasitological surveys, Conclusion This meta-analysis demonstrates that An. stephensi is widely distributed throughout Ethiopia and the Horn of Africa, with pooled proportions indicating high proportions across epidemiological and ecological settings. Its adaptability to various ecological zones, habitats, host preferences, resting areas, feeding periods, and seasons demonstrates its invasive ability. Ethiopia's trajectory is consistent with worldwide invasion patterns, especially in Djibouti and India, where An. stephensi has shifted malaria transmission dynamics. Integrated monitoring and customised vector control strategies, focusing on artificial breeding sites and urban areas, are urgently needed. Without immediate action, An. stephensi threatens to undercut Ethiopia's malaria eradication efforts and increase urban malaria spread throughout Africa. Abbreviations CI Confidence Interval CRD Centre for Reviews and Dissemination (used in PROSPERO registration number) IRS Indoor Residual Spraying I² I-squared statistic (measure of heterogeneity) JBI Joanna Briggs Institute LLINs Long-Lasting Insecticidal Nets N Total number of Anopheles collected n Number of An. stephensi collected PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analyses PRISMA-P Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol PROSPERO International Prospective Register of Systematic Reviews Q statistic Test for subgroup differences in meta-analysis τ² (Tau-squared) Between study variance in meta-analysis θ_IV Inverse-variance weighted estimate WHO World Health Organization Z z-score (test statistic in meta-analysis) Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Clinical trial Not applicable. Funding This systematic review and meta-analysis was not funded by any organisation or individual. Authors’ Contributions T.B. directed the systematic review and meta-analysis, designed the study, selected the articles, developed the protocol, registered it with PROSPERO, extracted the data, performed the statistical analysis, and prepared the manuscript. Database searches and study selection were conducted by T.B., K.L., and A.D. Data extraction and quality appraisal using JBI tools, as well as statistical analysis and meta-analysis in STATA, were performed by T.B., K.L., A.D., and L.R. The initial manuscript draft was prepared by T.B., while K.L. and A.D. provided critical revisions. All authors read and approved the final version of the manuscript. Acknowledgements We want to thank our colleagues who had a great contribution to the preparation of this manuscript. Data availability The data that support the findings of this study are found in the manuscript. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8849944","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":589505382,"identity":"c7ec9e69-4d8e-4691-a904-308e45e6aeca","order_by":0,"name":"Teresa 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of subgroup meta‑analysis of \u003cem\u003eAn. stephensi\u003c/em\u003e proportions by habitat type (artificial vs. mixed habitats).\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-8849944/v1/e45b779b864684a40435409f.png"},{"id":102484857,"identity":"cedae7ee-c549-418b-9c42-90b23fd74a41","added_by":"auto","created_at":"2026-02-12 07:30:24","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":199146,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of subgroup meta‑analysis of \u003cem\u003eAn. stephensi\u003c/em\u003e proportions by feeding preference (human‑associated vs. mixed habitats) in Ethiopia\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-8849944/v1/c9dc6897274924ad8e0f0a3a.png"},{"id":102484859,"identity":"0fcba54f-e147-44f3-97b6-723c367bb469","added_by":"auto","created_at":"2026-02-12 07:30:24","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":194215,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of subgroup meta‑analysis of \u003cem\u003eAn. stephensi\u003c/em\u003e proportions by resting preference (indoor vs. indoor + outdoor)\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-8849944/v1/9d1efbfbed1652fda2727260.png"},{"id":102484861,"identity":"36d8432e-1f0b-414c-b715-025a8de6df52","added_by":"auto","created_at":"2026-02-12 07:30:24","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":183878,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of subgroup meta‑analysis of \u003cem\u003eAn. stephensi\u003c/em\u003e proportions by seasonal collection design (seasonal vs. year‑round)\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-8849944/v1/12196efcc423d1182f852d38.png"},{"id":102484863,"identity":"ef58ddd7-5c4e-4217-8069-d90bd8a6d231","added_by":"auto","created_at":"2026-02-12 07:30:24","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":62388,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plot assessing publication bias in bionomic studies of \u003cem\u003eAn. stephensi\u003c/em\u003e in Ethiopia.\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-8849944/v1/c32e6f06e8c750b0ed6c2fc9.png"},{"id":102750633,"identity":"846bbc70-9f0d-480d-85e8-b0dee116e3a4","added_by":"auto","created_at":"2026-02-16 09:21:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4202833,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8849944/v1/4820b6dc-46e3-4208-95e7-511e7422fc38.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cem\u003eAnopheles stephensi\u003c/em\u003e bionomics and epidemiology in Ethiopia: A systematic review and meta-analysis with implications for urban malaria control\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMalaria remains a significant economic and public health challenge in Ethiopia, which puts millions of people at risk of infection every year [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Malaria transmission in the country has historically been dominated by the vector \u003cem\u003eAn. arabiensis\u003c/em\u003e, with secondary vectors such as \u003cem\u003eAn. funestus, An. pharoensis\u003c/em\u003e, and \u003cem\u003eAn. nili\u003c/em\u003e, as well as \u003cem\u003eAn. coustani\u003c/em\u003e [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The recent invasion of \u003cem\u003eAn. stephensi\u003c/em\u003e, a vector previously confined to South Asia and the Middle East, has complicated to the Ethiopian malaria epidemiology [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Unlike traditional rural vectors, \u003cem\u003eAn. stephensi\u003c/em\u003e exhibits ecological adaptive, thriving in urban settings using artificial water sources including overhead tanks, construction sites, and waste containers [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This adaptability allows it to colonise densely populated areas, challenging the long-held assumption that urbanisation reduces malaria risk [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Its capacity to transmit both \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. vivax\u003c/em\u003e complicates the challenge, as Ethiopia is currently dealing with a dual burden of these two parasites. This indicates that the first invasive malaria vector has established itself in urban Africa, suggesting a paradigm shift in transmission dynamics [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eAn. stephensi'\u003c/em\u003e historical distribution was mostly limited to South Asia, particularly India, Pakistan, and parts of the Arabian Peninsula [\u003cspan additionalcitationids=\"CR9 CR10 CR11 CR12 CR13\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Its detection in Djibouti in 2012 marked the beginning of its rapid expansion across East Africa [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Subsequent reports confirmed its presence in Ethiopia in 2016, first in Dire Dawa and later expanding to several regions, including Somali, Afar, and, most recently southern Ethiopia [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Its expansion correlates with growing urbanisation, which produces favourable breeding conditions. Alarmingly, modelling studies suggest that the spread of \u003cem\u003eAn. stephensi\u003c/em\u003e might put over 126\u0026nbsp;million Africans at risk for malaria [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Its invasion represents not only geographical expansion but also a shift in malaria transmission, particularly in previously low-prevalence urban areas. \u003cem\u003eAn. stephensi\u003c/em\u003e role in urban malaria is becoming increasingly evident, with its prevalence associated with increased malaria incidence in Ethiopian urban areas. Unlike rural vectors, \u003cem\u003eAn. stephensi\u003c/em\u003e bites early in the evening, reducing the effectiveness of long-lasting insecticidal nets (LLINs) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This behavioural shift requires a re-evaluation of current control strategies, including LLINs and IRS [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe adaptability across ecological niches, as well as the increasing resistance to widely used insecticides, highlights its importance in changing the epidemiology of malaria in Ethiopia [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Because the species preferentially uses human-made habitats, traditional vector management strategies based on rural transmission may not be sufficient to address the challenges posed by this invasive vector. Failure to adapt policies could reverse two decades of malaria control progress [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The emerging evidence shows that \u003cem\u003eAn. stephensi\u003c/em\u003e may influence the seasonal malaria transmission patterns, potentially extending transmission periods in urban centres [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEthiopia has made significant achievements in decreasing malaria incidence during the last two decades, but \u003cem\u003ethe An. stephensi\u003c/em\u003e invasion threatens to undermine these successes [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The World Health Organization (WHO) has identified \u003cem\u003eAn. stephensi\u003c/em\u003e as a significant new vector in Africa and warns that its spread might threaten malaria control efforts across the continent [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Ethiopia's growing urbanisation, which provides ideal habitats, makes resolving this issue even more urgent. This challenge is not confined to Ethiopia; neighbouring East African countries face similar risks, showing the continental implications of \u003cem\u003eAn. stephensi\u003c/em\u003e spread [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite increasing indications of \u003cem\u003eAn. stephensi\u003c/em\u003e spreading, significant gaps remain in the understanding of its biology, epidemiology, and resistance patterns in Ethiopia. Studies have documented its spatiotemporal distribution and seasonal dynamics, as well as its establishment in various ecological zones [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], but a comprehensive review is required. Resistance to pyrethroids and carbamates affects the efficacy of LLINs and indoor residual spraying (IRS) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Without a complete synthesis, control programmes risk depending on fragmented evidence. This review therefore presents the first pooled quantitative synthesis of \u003cem\u003eAn. stephensi\u003c/em\u003e bionomics and epidemiology in Ethiopia.\u003c/p\u003e \u003cp\u003eHistorically, Ethiopia's urban malaria control strategies have focused on reducing habitats and promoting the use of LLINs as a control method. However, \u003cem\u003eAn. stephensi\u003c/em\u003e ecology, including its preference for artificial containers and biting behaviour, makes these measures ineffective [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Insecticide resistance complicates control, demanding new approaches including larval source management, integrated vector control, and community-based interventions [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Findings will directly inform Ethiopia\u0026rsquo;s National Malaria Elimination Program and WHO regional vector control frameworks.\u003c/p\u003e \u003cp\u003eThis systematic review addresses this gap by synthesising all available quantitative data to provide policymakers and control programmes with an evidence-based understanding of \u003cem\u003eAn. stephensi\u003c/em\u003e establishment and invasive potential in Ethiopia. It aims to determine the distribution and proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e within Ethiopian Anopheles populations, evaluate its epidemiological importance across various geographic and ecological settings, and characterise the bionomic traits. The seasonal variations, evidence quality, and research gaps were examined with contrasts to other East African countries where \u003cem\u003eAn. stephensi\u003c/em\u003e has been identified. By combining various findings, this review gives a foundation for designing context-specific, evidence-based interventions against \u003cem\u003eAn. stephensi\u003c/em\u003e in Ethiopia and beyond.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDesign and Protocol\u003c/h2\u003e \u003cp\u003eThis systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA-P 2020) guidelines (29). The study selection process was documented with a four-stage PRISMA flow diagram, which depicts the steps taken from the initial collection of identified records to the final set of studies included in the analysis. The review protocol was developed in advance to ensure methodological transparency, and it was formally registered with the International Prospective Register of Systematic Reviews (PROSPERO) under the registration number CRD420251176953.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDatabase and Search Strategy\u003c/h3\u003e\n\u003cp\u003eThis systematic review and meta-analysis began on November 30, 2025, and included eligible studies conducted in Ethiopia and published in English until February 10, 2026. To ensure complete coverage, electronic databases and grey literature sources were thoroughly investigated. We searched PubMed, Scopus, Science Direct, Web of Science, and Google Scholar, as well as regional repositories and grey literature. Search terms were combined with Boolean operators (\"AND\" and \"OR\") and adapted for each platform's syntax. The primary search string used across databases was ('Anopheles stephensi' OR 'urban mosquito') AND (Ethiopia OR 'Eastern' OR 'Southern' OR 'Central' OR 'South-western') AND ('bionomics' OR 'epidemiology' OR 'host preference' OR 'resting behaviour' OR 'breeding habitat' OR 'distribution' OR 'malaria'). Search filters were applied for publication date (2016\u0026ndash;February 2026) and language (English). Reference lists of included studies were screened using a snowballing approach for additional relevant studies.\u003c/p\u003e\n\u003ch3\u003eEligibility Criteria\u003c/h3\u003e\n\u003cp\u003eRecords were imported into EndNote X7 for organization and duplicate removal. Inclusion criteria were: studies conducted in Ethiopia; entomological data on Anopheles (any life stage); outcomes reporting the proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e or bionomic traits (habitat, feeding, resting, behaviour); and study designs including cross-sectional, case-control, cohort/prospective, modelling studies, and systematic reviews with primary data. Exclusion criteria were: studies outside Ethiopia; human-only clinical studies without entomological data; case reports, editorials, opinion pieces, and conference abstracts without full text; non-English publications; and studies published before 2016. Studies were eligible only if they scored\u0026thinsp;\u0026ge;\u0026thinsp;50% on the JBI quality appraisal. The eligibility criteria for the studies were shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003esummary inclusion and exclusion criteria\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCriterion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInclusion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExclusion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeographic Location\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudies conducted in Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudies outside Ethiopia\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy Population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnopheles mosquitoes (any stage) in Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHuman populations only; vector studies from other countries\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProportion of An. stephensi; bionomics data (habitat, feeding, resting, behaviour)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eClinical malaria outcomes without entomological data\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy Design\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional, case-control, prospective, modelled data; systematic reviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase reports, editorials, opinion pieces, conference abstracts without full text\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublication Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeer-reviewed articles; grey literature with full text\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-English publications; partial data\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublication Date\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2016\u0026ndash;February, 2026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrior to 2016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eData Quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudies with \u0026ge;\u0026thinsp;50% JBI quality score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudies with \u0026lt;\u0026thinsp;50% JBI quality score\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eOutcome of Interest\u003c/h3\u003e\n\u003cp\u003eThe primary outcome was the proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e among all Anopheles collected in each study, expressed as n/N. Secondary outcomes included bionomic characteristics (breeding habitat type, host preference, resting location, and feeding time), seasonal patterns, surveillance method, and ecological zone.\u003c/p\u003e\n\u003ch3\u003eStudy Selection and quality Assessment\u003c/h3\u003e\n\u003cp\u003eTwo reviewers (T.B. and K.L.) independently reviewed titles and abstracts. Then, three reviewers (T.B., K.L., and A.D.) assessed full-text publications for eligibility criteria. Disagreements were resolved by discussion and, where necessary, adjudicated by a fourth reviewer (L.R.). Study quality was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Prevalence Studies for cross-sectional designs and the JBI Checklist for Cohort Studies for prospective designs. Each item was scored as \u0026ldquo;yes\u0026rdquo; (1), \u0026ldquo;no\u0026rdquo; (0), or \u0026ldquo;unclear\u0026rdquo; (0), yielding a maximum score of 9. Studies scoring\u0026thinsp;\u0026ge;\u0026thinsp;4.5 (50%) were included (30).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Extraction\u003c/h2\u003e \u003cp\u003eA standardised data extraction form was tested on three studies and then applied to all included studies. Extracted items included first author, year, study location and ecological zone, study design, sampling method, sample frame, collection period and season, total Anopheles collected (N), number of \u003cem\u003eAn. stephensi\u003c/em\u003e (n), method of species identification (morphological and/or molecular), and bionomic variables (breeding habitat, host preference, resting behaviour, and feeding time). Funding sources and declared conflicts of interest were also recorded. Two reviewers independently extracted data; discrepancies were resolved by consensus.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Synthesis and Analysis\u003c/h3\u003e\n\u003cp\u003eAll extracted data was organised in Excel and then imported into STATA version 19.5 (StataCorp, College Station, Texas, USA) for statistical analysis. A random-effects meta-analysis approach was used to obtain pooled estimates of \u003cem\u003eAn. stephensi\u003c/em\u003e proportions, taking into account study heterogeneity. The subgroup analyses were established to investigate potential sources of heterogeneity based on ecological factors (geographic zone, habitat type), vector behaviour (host preference, resting patterns, feeding time), and study design factors (epidemiological domain, surveillance method, collection season). Significant subgroup differences were found using interaction testing (Q statistic) at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The point estimates were reported with 95% confidence intervals. The I\u0026sup2; statistic was used to quantify heterogeneity, with the following interpretations: I\u0026sup2; \u0026lt; 25% = low, 25\u0026ndash;50% = moderate, 50\u0026ndash;75% = large, and \u0026gt;\u0026thinsp;75% = extreme heterogeneity. Random-effects models were used throughout, with the expectation of significant heterogeneity due to regional and ecological variation. Tau\u0026sup2; estimations are presented alongside I\u0026sup2; to measure the variance between studies. Publication bias was evaluated using (1) visual assessment of the funnel plot; (2) Egger's weighted regression test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 showing bias); (3) Begg's rank correlation test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicating bias); and (4) trim-and-fill analysis to estimate the number and size of potentially missing studies. Stata's metabias and metatrim commands were used.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSearch Results\u003c/h2\u003e \u003cp\u003eA total of 4,410 records were identified from electronic databases, including PubMed (2,892 records), Science Direct (365 records), and Scopus (218 records), as well as an additional 752 records from Google Scholar. After eliminating 2,832 duplicate records, 2,393 records remained for screening. During the screening stage, 2,017 records were excluded after a review of their titles and abstracts. A full-text screening of 107 publications showed 49 articles that were potentially relevant based on title and abstract review. During the full-text review, 33 papers were removed for the following reasons: lack of outcome of interest (n\u0026thinsp;=\u0026thinsp;24), the study location being outside Ethiopia (n\u0026thinsp;=\u0026thinsp;4), non-English publishing (n\u0026thinsp;=\u0026thinsp;3), and insufficient methodological transparency (n\u0026thinsp;=\u0026thinsp;2). This identified 18 eligible studies for inclusion in the systematic review. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the PRISMA 2020 flow diagram summarizes the study selection process and reasons for exclusion.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of the Included Studies\u003c/h2\u003e \u003cp\u003eA total of 18 studies published between 2016 and 2025 were analysed [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Most of the studies were conducted in Eastern Ethiopia (n\u0026thinsp;=\u0026thinsp;12), with additional studies from Central Ethiopia (n\u0026thinsp;=\u0026thinsp;2), Southern Ethiopia (n\u0026thinsp;=\u0026thinsp;1), and South-eastern Ethiopia (n\u0026thinsp;=\u0026thinsp;2), along with one multi-site study. Sample sizes varied significantly, from a low of 34 specimens [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] to a high of 49,482 specimens [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], with reported proportions of \u003cem\u003eAn. stephensi\u003c/em\u003e values ranging from 0.07 to 1.0. Several studies [\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] reported very high proportions (\u0026ge;\u0026thinsp;0.8), particularly in Eastern Ethiopia. Quality appraisal scores ranged from 7 to 9, with most of the studies scoring 8 or 9, strengthening confidence in pooled estimates. Detailed summary of included studies were shown in below Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of included studies on \u003cem\u003eAn. stephensi\u003c/em\u003e in Ethiopia 2016\u0026ndash;2025\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYear of Publication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eZone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal Anopheles\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProportion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eResearch Focus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQuality Score/9\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAbiy et al.\u003c/b\u003e (37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentral Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBionomics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAshine et al.\u003c/b\u003e (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentral Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBalkew et al.\u003c/b\u003e (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBionomics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBalkew et al.\u003c/b\u003e(39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBionomics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCarter et al.\u003c/b\u003e(33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBionomics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCarter et al.\u003c/b\u003e (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBionomics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDegefa et al.\u003c/b\u003e (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBionomics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmiru et al.\u003c/b\u003e (34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEpidemiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHamlet et al.\u003c/b\u003e (31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEpidemiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHawaria et al.\u003c/b\u003e (41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMulti-sites\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEpidemiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHawaria et al.\u003c/b\u003e(42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSouthern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBionomics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMerga et al.\u003c/b\u003e(28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBionomics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMerga et al.\u003c/b\u003e (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTadesse et al.\u003c/b\u003e (32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSouth-eastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEpidemiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWaymire et al.\u003c/b\u003e (43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSouth-eastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEpidemiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYared et al.\u003c/b\u003e(36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15560\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBionomics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYared et al.\u003c/b\u003e(44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEpidemiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eZhou et al.\u003c/b\u003e (45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEastern Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEpidemiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBoth =\u0026thinsp;studies reporting both epidemiological and bionomic outcomes.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEpidemiological proportion of\u003c/b\u003e \u003cb\u003eAnopheles stephensi\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe meta-analysis included nine studies focusing on the epidemiological proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e among Anopheles mosquitoes in diverse ecological and urban contexts in Ethiopia. The reported proportions varied widely, from 0.07 in [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] and 0.08 in [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] to near-total dominance of 1.00 [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Very high proportions of \u003cem\u003eAn. stephensi\u003c/em\u003e have been documented with proportions of 0.93 [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], 0.79 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], and 0.79[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Moderate proportions of ecological variables were observed [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] with a reported estimate of 0.37 [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] at 0.33 and [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] at 0.27, indicative of mixed-species habitats or transitional ecological zones. The overall pooled proportion was 0.51 (95% CI: 0.28\u0026ndash;0.75; z\u0026thinsp;=\u0026thinsp;4.24, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Heterogeneity was extreme (τ\u0026sup2; = 0.13, I\u0026sup2; = 99.98%, H\u0026sup2; = 4393.96), reflecting genuine ecological and epidemiological variability across Ethiopia. This underscores the importance of stratified analyses by ecological zone. Results are summarised in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup Analysis by Geographic Zone and Epidemiological Domain\u003c/h2\u003e \u003cp\u003eSubgroup analysis by geographic zone showed significant variation in the proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e among all \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes across Ethiopia. In Eastern Ethiopia, the pooled proportion was 0.57 (95% CI: 0.32\u0026ndash;0.82), with extreme heterogeneity (τ\u0026sup2; = 0.06, I\u0026sup2; = 99.69%). Estimates ranged from 0.33 [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] to 0.79 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In multi-site studies, the pooled proportion was much lower at 0.08 (95% CI: 0.07\u0026ndash;0.08), with negligible heterogeneity (I\u0026sup2; = 0.07%), suggesting consistent results across ecological zones [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. In South-eastern Ethiopia, the pooled proportion reached 0.73 (95% CI: 0.28\u0026ndash;1.18), with marked heterogeneity (τ\u0026sup2; = 0.16, I\u0026sup2; = 99.97%), largely driven by differences between [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Overall, the pooled proportion across all zones was 0.51 (95% CI: 0.28\u0026ndash;0.75), and subgroup differences were statistically significant (Q(2)\u0026thinsp;=\u0026thinsp;22.89, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSimilarly, subgroup meta-analysis across epidemiological domains showed distinct trends. In the entomological\u0026thinsp;+\u0026thinsp;molecular category, proportions ranged from 0.07 [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] to 1.00 [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], with a pooled estimate of 0.35 (95% CI: 0.08\u0026ndash;0.78; z\u0026thinsp;=\u0026thinsp;1.62, p\u0026thinsp;=\u0026thinsp;0.11) and high heterogeneity (τ\u0026sup2; = 0.19, I\u0026sup2; = 99.99%). The epidemiology group included two studies, with proportions ranging from 0.37 [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] to 0.93 [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]; the pooled estimate was 0.65 (95% CI: 0.11\u0026ndash;1.19; z\u0026thinsp;=\u0026thinsp;2.34, p\u0026thinsp;=\u0026thinsp;0.02), with marked heterogeneity (τ\u0026sup2; = 0.15, I\u0026sup2; = 99.95%). The modelling group reported proportions from 0.33 [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] to 0.79 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], yielding a pooled estimate of 0.64 (95% CI: 0.33\u0026ndash;0.94; z\u0026thinsp;=\u0026thinsp;4.12, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with high heterogeneity (τ\u0026sup2; = 0.07, I\u0026sup2; = 99.39%). The overall pooled proportion across all domains was 0.51 (95% CI: 0.28\u0026ndash;0.75), and subgroup differences were not statistically significant (Q(2)\u0026thinsp;=\u0026thinsp;1.23, p\u0026thinsp;=\u0026thinsp;0.54; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis by study design\u003c/h2\u003e \u003cp\u003eSubgroup meta-analysis across epidemiological study designs showed distinct trends in the proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e among total \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes. The cross-sectional studies reported proportions ranging from 0.07 [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] to 1.00 [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], with a pooled estimate of 0.35 (95% CI: 0.08\u0026ndash;0.78; z\u0026thinsp;=\u0026thinsp;1.62, p\u0026thinsp;=\u0026thinsp;0.11). Heterogeneity was extreme (τ\u0026sup2; = 0.19, I\u0026sup2; = 99.99%). The modelling group included studies [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] with proportions ranging from 0.33 to 0.79, with a pooled estimate of 0.64 (95% CI: 0.33\u0026ndash;0.94; z\u0026thinsp;=\u0026thinsp;4.12, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and high heterogeneity (τ\u0026sup2; = 0.07, I\u0026sup2; = 99.39%). Prospective case\u0026ndash;control studies [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] reported proportions of 0.93 and 0.37 and a pooled estimate of 0.65 (95% CI: 0.11\u0026ndash;1.19; z\u0026thinsp;=\u0026thinsp;2.34, p\u0026thinsp;=\u0026thinsp;0.02) and marked heterogeneity (τ\u0026sup2; = 0.15, I\u0026sup2; = 99.95%). The overall pooled proportion across all study designs was 0.51 (95% CI: 0.28\u0026ndash;0.75), with extreme heterogeneity (I\u0026sup2; = 99.98%). Subgroup differences were not statistically significant (Q(2)\u0026thinsp;=\u0026thinsp;1.23, p\u0026thinsp;=\u0026thinsp;0.54; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFunnel Plot and Publication Bias Assessment\u003c/h2\u003e \u003cp\u003eThe funnel plot analysis showed no evidence of publication bias in the epidemiological dataset. The inverse-variance weighted estimate (θ_IV) indicated central alignment and symmetrical distribution of studies within the pseudo 95% confidence limits (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Egger\u0026rsquo;s regression test (β₁ = 2.67, p\u0026thinsp;=\u0026thinsp;0.685) and Begg\u0026rsquo;s test (Kendall\u0026rsquo;s score\u0026thinsp;=\u0026thinsp;2.00, p\u0026thinsp;=\u0026thinsp;0.917) were non-significant. Trim-and-fill analysis confirmed symmetry, with no imputed studies and a stable pooled estimate (0.989, 95% CI: 0.988\u0026ndash;0.989). This suggests robustness of the pooled results despite high heterogeneity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eProportion of\u003c/b\u003e \u003cb\u003eAnopheles stephensi\u003c/b\u003e \u003cb\u003eBionomics\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe forest plot meta-analysis of bionomics studies revealed substantial variation in the proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e across ecological and behavioural contexts. Estimates ranged from a low of 0.13 [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] to a high of 0.99 [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Intermediate proportions were reported at 0.32 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], 0.33 [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], and 0.43 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Degefa et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] reported a proportion of 0.89, closely followed by Yared et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] with 0.88, both supported by large sample sizes. The random-effects model yielded a pooled proportion of 0.46 (95% CI: 0.26\u0026ndash;0.66; z\u0026thinsp;=\u0026thinsp;4.46, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Heterogeneity was extreme (τ\u0026sup2; = 0.11, I\u0026sup2; = 99.98%, H\u0026sup2; = 4,120.87), reflecting ecological diversity and methodological variability across studies. This confirms the significant presence of \u003cem\u003eAn. stephensi\u003c/em\u003e in diverse bionomic contexts. Results are summarised in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis by Ecological Zone and Habitat type of the bionomics studies\u003c/h2\u003e \u003cp\u003eSubgroup analysis of bionomics studies revealed significant geographical differences in the proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e among total \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes. In Eastern Ethiopia, individual studies reported moderate estimates of 0.32 [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and 0.33 [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], with an overall pooled proportion of 0.60 (95% CI: 0.35\u0026ndash;0.85). In Southern Ethiopia, \u003cem\u003eAn. stephensi\u003c/em\u003e was less dominant, with a proportion of 0.43 reported by Hawaria et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Studies from Central Ethiopia indicated a lower proportion of approximately 0.13, as reported by Merga et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], Abiy et al. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], and Ashine et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], with a pooled proportion of 0.13 (95% CI: 0.12\u0026ndash;0.14). The overall pooled proportion across ecological zones was 0.46 (95% CI: 0.26\u0026ndash;0.66), with significant heterogeneity (τ\u0026sup2; = 0.11, I\u0026sup2; = 99.98%; Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSimilarly, subgroup meta-analysis by habitat type showed variation in the proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e. In artificial habitats, pooled estimates ranged from 0.13 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] to 0.89 [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], with a pooled proportion of 0.45 (95% CI: 0.22\u0026ndash;0.67; z\u0026thinsp;=\u0026thinsp;3.88, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In mixed natural and artificial habitats, estimates varied from 0.13 [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] to 0.99 [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], with a pooled proportion of 0.48 (95% CI: 0.03\u0026ndash;0.99; z\u0026thinsp;=\u0026thinsp;1.85, p\u0026thinsp;=\u0026thinsp;0.06). Heterogeneity was substantial (τ\u0026sup2; = 0.20, I\u0026sup2; = 99.98%). The overall pooled proportion across all habitat types was 0.46 (95% CI: 0.26\u0026ndash;0.66), with no statistically significant subgroup differences (Q(1)\u0026thinsp;=\u0026thinsp;0.02, p\u0026thinsp;=\u0026thinsp;0.90; Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup Feeding Preference\u003c/h2\u003e \u003cp\u003eSubgroup meta-analysis by feeding preference showed significant variation in the proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e. In the human-associated habitat subgroup, proportions ranged from 0.13 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] to 0.89 [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], with a pooled estimate of 0.34 (95% CI: 0.07\u0026ndash;0.61; z\u0026thinsp;=\u0026thinsp;2.48, p\u0026thinsp;=\u0026thinsp;0.01). Heterogeneity was substantial (τ\u0026sup2; = 0.11, I\u0026sup2; = 99.97%). In the mixed habitat subgroup, proportions ranged from 0.32 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] to 0.99 [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], with a pooled estimate of 0.59 (95% CI: 0.31\u0026ndash;0.87; z\u0026thinsp;=\u0026thinsp;4.14, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Heterogeneity was high (τ\u0026sup2; = 0.10, I\u0026sup2; = 99.96%). The overall pooled proportion was 0.46 (95% CI: 0.26\u0026ndash;0.66), with no statistically significant subgroup differences (Q(1)\u0026thinsp;=\u0026thinsp;1.53, p\u0026thinsp;=\u0026thinsp;0.22; Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup by resting preference\u003c/h2\u003e \u003cp\u003eSubgroup meta-analysis by resting preference revealed distinct patterns of the proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e among total \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes. Indoor studies reported proportions ranging from 0.13 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] to 0.89 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], with a pooled estimate of 0.42 (95% CI: 0.15\u0026ndash;0.69; z\u0026thinsp;=\u0026thinsp;3.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Heterogeneity was marked (τ\u0026sup2; = 0.14, I\u0026sup2; = 99.98%). Indoor and outdoor studies reported proportions from 0.32 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] to 0.99 [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], with a pooled estimate of 0.52 (95% CI: 0.21\u0026ndash;0.83; z\u0026thinsp;=\u0026thinsp;3.25, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Heterogeneity remained high (τ\u0026sup2; = 0.10, I\u0026sup2; = 99.90%). The overall pooled proportion across resting preferences was 0.46 (95% CI: 0.26\u0026ndash;0.66), with no statistically significant subgroup differences (Q(1)\u0026thinsp;=\u0026thinsp;0.21, p\u0026thinsp;=\u0026thinsp;0.64; Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eSeasonal design\u003c/h2\u003e \u003cp\u003eA subgroup meta-analysis of seasonal collection periods identified significant variations in the proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e mosquitoes among total Anopheles populations. Seasonal studies reported proportions from 0.13 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] to 0.99 [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], with a pooled estimate of 0.43 (95% CI: 0.16\u0026ndash;0.70; z\u0026thinsp;=\u0026thinsp;3.12, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Heterogeneity was extreme (τ\u0026sup2; = 0.13, I\u0026sup2; = 99.98%). Year-round studies reported proportions from 0.13 [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] to 0.88 [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], with a pooled estimate of 0.50 (95% CI: 0.17\u0026ndash;0.82; z\u0026thinsp;=\u0026thinsp;3.00, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Heterogeneity remained high (τ\u0026sup2; = 0.11, I\u0026sup2; = 99.95%). The overall pooled proportion across seasonal designs was 0.46 (95% CI: 0.26\u0026ndash;0.66), with no statistically significant subgroup differences (Q(1)\u0026thinsp;=\u0026thinsp;0.10, p\u0026thinsp;=\u0026thinsp;0.76; Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003ePublication Bias and Funnel plot\u003c/h2\u003e \u003cp\u003eThe funnel plot for the \u003cem\u003eAn. stephensi\u003c/em\u003e bionomics dataset showed no evidence of publication bias, with symmetrical distribution of studies around the pooled estimate (Fig.\u0026nbsp;13). Egger\u0026rsquo;s regression (β₁ = \u0026minus;\u0026thinsp;18.94, z = \u0026minus;\u0026thinsp;1.11, p\u0026thinsp;=\u0026thinsp;0.27) and Begg\u0026rsquo;s test (Kendall\u0026rsquo;s score = \u0026minus;\u0026thinsp;7.00, z = \u0026minus;\u0026thinsp;0.62, p\u0026thinsp;=\u0026thinsp;0.64) were non-significant. Trim-and-fill analysis indicated no missing studies, with a stable pooled estimate of 0.455 (95% CI: 0.255\u0026ndash;0.655).\u003c/p\u003e \u003c/div\u003e "},{"header":"Discussions","content":"\u003cp\u003eThe rapid spread of \u003cem\u003eAn. stephensi\u003c/em\u003e in African urban areas poses a significant threat to malaria prevention efforts, potentially reversing decades of progress [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Its spread in Ethiopia poses a particular challenge to malaria control, allowing for year-round urban outbreaks that are becoming increasingly resistant to standard insecticides and diagnostic techniques [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis systematic review and meta-analysis revealed that \u003cem\u003eAn. stephensi\u003c/em\u003e has quickly emerged as the dominant malaria vector in Ethiopia and the Horn of Africa. The overall pooled epidemiological proportion was 0.51 (95% CI: 0.28\u0026ndash;0.75), while the overall pooled bionomics proportion was 0.46 (95% CI: 0.26\u0026ndash;0.66). These findings suggest that the species has swiftly evolved in urban and peri-urban habitats, with reported proportions ranging from a low presence of 0.07\u0026ndash;0.08 [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] to near-total domination of 1.00 [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Emiru et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], Hamlet et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], and Merga et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] all reported high proportions (\u0026ge;\u0026thinsp;0.8), showing their epidemiological relevance. Moderate proportions (0.27\u0026ndash;0.37) in transitional zones [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] indicate coexistence with other Anopheles species.\u003c/p\u003e \u003cp\u003eGeographic heterogeneity implies that south-eastern Ethiopia has nearly complete dominance [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. On the other hand, Eastern Ethiopia frequently reported high proportion rates when compared to [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], but Central Ethiopia had low proportions of 0.13 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. These findings highlight how \u003cem\u003eAn. stephensi\u003c/em\u003e thrives in urbanised ecosystems modified by human activity, notably water storage and peri-domestic habitats showed comparable variability over the Horn of Africa [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEthiopia's trajectory reflects invasion tendencies in surrounding East African countries and throughout the world. In Djibouti, native vectors were displaced within 5\u0026ndash;8 years after identification, with \u003cem\u003eAn. stephensi\u003c/em\u003e accounting for 0.80\u0026ndash;0.95 [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Similar patterns have been seen in Sudan [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] and Somalia [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In India, the species thrives in artificial environments like water storage tanks and building sites, with proportions of around 0.80 [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Reports from Iran and Saudi Arabia demonstrate its adaptation to peridomestic habitats and seasonal persistence (14). Climate suitability models forecast increasing spread throughout Africa, exposing millions to urban malaria risk [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe bionomics analysis highlights \u003cem\u003eAn. stephensi\u003c/em\u003e ecological adaptability. The species prefers artificial breeding sites [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], is adaptable to both human-only and mixed-host habitats [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], may be found in both indoor and outdoor resting locations [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], and is most active in the evening and night [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Seasonal persistence has been shown in both seasonal and year-round samples [\u003cspan additionalcitationids=\"CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33 CR34 CR35 CR36\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. This behavioural variability challenges traditional management strategies established for rural vectors like \u003cem\u003eAn. arabiensis\u003c/em\u003e and \u003cem\u003eAn. funestus\u003c/em\u003e [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. The spread of \u003cem\u003eAn. stephensi\u003c/em\u003e in urban environments creates serious public health concerns. Standard interventions like long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are ineffective due to the mosquito's exophagic and exophagic behaviour [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Rapid urbanisation accelerates its growth, but resistance to pyrethroids and carbamates complicates control efforts.\u003c/p\u003e \u003cp\u003eTo address these challenges, urgent policy action is essential. Priority actions include improving urban entomological surveillance to monitor \u003cem\u003eAn. stephensi\u003c/em\u003e populations, managing artificial breeding sites through larval source management, implementing integrated vector management with environmental modification, biological control, and insecticide use, and promoting community-based interventions to reduce breeding habitats.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThis review's methodological rigorousness is a significant strength: it follows the PRISMA 2020 recommendations, is registered with PROSPERO, and includes both epidemiological and bionomic research. The results were completely evaluated for publication bias using symmetrical funnel plots and non-significant Egger's and Begg's tests. However, extreme heterogeneity (I\u0026sup2; = 99.98%) restricts the generalizability of pooled values, demonstrating ecological diversity and methodological variability. Evidence gaps remain, including a lack of data from Central Ethiopia, insecticide susceptibility studies, and longitudinal parasitological surveys,\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis meta-analysis demonstrates that \u003cem\u003eAn. stephensi\u003c/em\u003e is widely distributed throughout Ethiopia and the Horn of Africa, with pooled proportions indicating high proportions across epidemiological and ecological settings. Its adaptability to various ecological zones, habitats, host preferences, resting areas, feeding periods, and seasons demonstrates its invasive ability. Ethiopia's trajectory is consistent with worldwide invasion patterns, especially in Djibouti and India, where \u003cem\u003eAn. stephensi\u003c/em\u003e has shifted malaria transmission dynamics. Integrated monitoring and customised vector control strategies, focusing on artificial breeding sites and urban areas, are urgently needed. Without immediate action, \u003cem\u003eAn. stephensi\u003c/em\u003e threatens to undercut Ethiopia's malaria eradication efforts and increase urban malaria spread throughout Africa.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cb\u003eCI\u003c/b\u003e Confidence Interval\u003c/p\u003e\u003cp\u003e\u003cb\u003eCRD\u003c/b\u003e Centre for Reviews and Dissemination (used in PROSPERO registration number)\u003c/p\u003e\u003cp\u003e\u003cb\u003eIRS\u003c/b\u003e Indoor Residual Spraying\u003c/p\u003e\u003cp\u003e\u003cb\u003eI\u0026sup2;\u003c/b\u003e I-squared statistic (measure of heterogeneity)\u003c/p\u003e\u003cp\u003e\u003cb\u003eJBI\u003c/b\u003e Joanna Briggs Institute\u003c/p\u003e\u003cp\u003e\u003cb\u003eLLINs\u003c/b\u003e Long-Lasting Insecticidal Nets\u003c/p\u003e\u003cp\u003e\u003cb\u003eN\u003c/b\u003e Total number of \u003cem\u003eAnopheles\u003c/em\u003e collected\u003c/p\u003e\u003cp\u003e\u003cb\u003en\u003c/b\u003e Number of \u003cem\u003eAn. stephensi\u003c/em\u003e collected\u003c/p\u003e\u003cp\u003e\u003cb\u003ePRISMA\u003c/b\u003e Preferred Reporting Items for Systematic Reviews and Meta-Analyses\u003c/p\u003e\u003cp\u003e\u003cb\u003ePRISMA-P\u003c/b\u003e Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol\u003c/p\u003e\u003cp\u003e\u003cb\u003ePROSPERO\u003c/b\u003e International Prospective Register of Systematic Reviews\u003c/p\u003e\u003cp\u003e\u003cb\u003eQ statistic\u003c/b\u003e Test for subgroup differences in meta-analysis\u003c/p\u003e\u003cp\u003e\u003cb\u003eτ\u0026sup2; (Tau-squared)\u003c/b\u003e Between study variance in meta-analysis\u003c/p\u003e\u003cp\u003e\u003cb\u003eθ_IV\u003c/b\u003e Inverse-variance weighted estimate\u003c/p\u003e\u003cp\u003eWHO World Health Organization\u003c/p\u003e\u003cp\u003e\u003cb\u003eZ\u003c/b\u003e z-score (test statistic in meta-analysis)\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eClinical trial\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis systematic review and meta-analysis was not funded by any organisation or individual.\u003c/p\u003e\u003ch2\u003eAuthors\u0026rsquo; Contributions\u003c/h2\u003e \u003cp\u003eT.B. directed the systematic review and meta-analysis, designed the study, selected the articles, developed the protocol, registered it with PROSPERO, extracted the data, performed the statistical analysis, and prepared the manuscript. Database searches and study selection were conducted by T.B., K.L., and A.D. Data extraction and quality appraisal using JBI tools, as well as statistical analysis and meta-analysis in STATA, were performed by T.B., K.L., A.D., and L.R. The initial manuscript draft was prepared by T.B., while K.L. and A.D. provided critical revisions. All authors read and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe want to thank our colleagues who had a great contribution to the preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eThe data that support the findings of this study are found in the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. WHO Malaria Policy Advisory Group: meeting report, 8\u0026ndash;10 April 2025. 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Parasit Vectors 15(1):247\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThomas S, Ravishankaran S, Justin NAJA, Asokan A, Mathai MT, Valecha N et al (2017) Resting and feeding preferences of \u003cem\u003eAnopheles stephensi\u003c/em\u003e in an urban setting, perennial for malaria. Malar J 16(1):111\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGebresilassie A, Aklilu E, Yared S et al (2025) Habitat heterogeneity and green filamentous algae influence the larval ecology of \u003cem\u003eAnopheles stephensi\u003c/em\u003e during the dry season in Eastern Ethiopia. Parasit Vectors 18:461\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Armauer Hansen Research Institute","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Anopheles stephensi, bionomics, Ethiopia, meta-analysis, urban malaria, vector surveillance","lastPublishedDoi":"10.21203/rs.3.rs-8849944/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8849944/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003e \u003cem\u003eAn. stephensi\u003c/em\u003e, an invasive malaria vector originally endemic to South Asia, has rapidly expanded across East Africa. Its emergence in Ethiopia threatens malaria elimination progress, particularly in urban areas where populations were previously considered at lower risk. We conducted a systematic review to synthesise evidence on its bionomics and epidemiological role in Ethiopia, with implications for urban malaria control strategies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a PRISMA 2020-compliant systematic review and meta-analysis registered with PROSPERO (CRD420251176953). Searches of PubMed, Scopus, Web of Science, and regional repositories (2016\u0026ndash;February 2026) identified studies reporting \u003cem\u003eAn. stephensi\u003c/em\u003e bionomics and epidemiological role in Ethiopia. Eligible studies required\u0026thinsp;\u0026ge;\u0026thinsp;50% quality score on JBI appraisal tools. Random-effects meta-analysis estimated pooled proportions of \u003cem\u003eAn. stephensi\u003c/em\u003e among total \u003cem\u003eAnopheles\u003c/em\u003e, with subgroup analyses by geography, habitat, and behavioural traits. Publication bias was assessed using Egger\u0026rsquo;s and Begg\u0026rsquo;s tests.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eEighteen studies (9 epidemiological, 11 bionomical) met inclusion criteria. The pooled proportion of \u003cem\u003eAn. stephensi\u003c/em\u003e was 0.51 (95% CI: 0.28\u0026ndash;0.75) in epidemiological studies and 0.46 (95% CI: 0.26\u0026ndash;0.66) in bionomics studies, with extreme heterogeneity (I\u0026sup2; \u0026gt; 99%). Geographic variation was marked: South-eastern Ethiopia showed near-total dominance (0.73), while Central Ethiopia reported lower proportions (0.13). Extreme heterogeneity reflected genuine ecological variation across Ethiopia. No evidence of publication bias was detected.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003e \u003cem\u003eAn. stephensi\u003c/em\u003e has very rapidly emerged as a major malaria vector in Ethiopia, utilising urban environments and showing behavioural adaptability. The presence of this vector poses a threat to malaria elimination efforts and highlights the importance of integrated urban vector management, which includes reducing larval sources, using targeted insecticides, and engaging in community-based interventions. Future research should prioritise longitudinal surveillance and insecticide resistance management to inform evidence-based control.\u003c/p\u003e","manuscriptTitle":"Anopheles stephensi bionomics and epidemiology in Ethiopia: A systematic review and meta-analysis with implications for urban malaria control","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-12 07:30:19","doi":"10.21203/rs.3.rs-8849944/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"110ddce1-8e7c-411f-91e8-7c73ca43ba7f","owner":[],"postedDate":"February 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":62721639,"name":"Entomology"}],"tags":[],"updatedAt":"2026-02-20T18:28:24+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-12 07:30:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8849944","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8849944","identity":"rs-8849944","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}