Asymptomatic malaria in pregnancy and associated risk factors in Majang Zone, Gambella Region, Southwest Ethiopia: a hard-to-reach malaria hotspot
Bibliographic record
Abstract
BACKGROUND: Asymptomatic malaria in pregnancy (AMiP) is a daunting public health problem with multifaceted adverse outcomes for mothers, fetuses, newborns and beyond. This study aimed to assess the prevalence and risk factors of AMiP and anaemia in Majang Zone, Gambella, Southwest Ethiopia. METHODS: A facility-based cross-sectional study was conducted among 425 pregnant women attending the antenatal care (ANC) clinics of five health facilities in the Majang Zone from November 2022 to February 2023. Sociodemographic, obstetric, and anti-malarial intervention data were collected using an interviewer-administered questionnaire. A capillary blood specimen was collected to diagnose malaria and anaemia as well as determine the blood group. Malaria was diagnosed by rapid diagnostic test (RDT), microscopy, and quantitative polymerase chain reaction (qPCR). Statistical analyses were done by Statistical Package for Social Science (SPSS) version 26.0. The association between dependent and independent variables was assessed by multivariable binary logistic regression, considering P < 0.05 statistically significant. The magnitude of associations was quantified with the adjusted odds ratio (AOR) along with the corresponding 95% confidence interval (CI). RESULTS: The overall prevalence of AMiP was 15.3% (95% CI 12.1, 18.9). It was 11.3% (95% CI 8.4, 14.7) by RDT, 11.8% (95% CI 8.9, 15.2) by microscopy and 17.6% (95% CI 11.7, 24.9) by qPCR. Plasmodium falciparum, moderate parasitaemia and submicroscopic infection accounted for 55.4% of the AMiP prevalence, 50.8% of the parasite density, and 41.6% of the qPCR-positive AMiP, respectively. Nearly 32.3% of pregnant women with AMiP carried gametocytes. Risk factors of AMiP were: not utilizing insecticide-treated net (ITN) within the previous week (AOR: 9.43 95% CI 1.57, 56.62), having a history of malaria within the previous year (AOR: 2.26 95% CI 1.16, 4.42), lack of indoor residual spraying (IRS) within the previous year (AOR: 3.00 95% CI 1.50, 6.00), and ANC contact below two rounds (AOR: 4.28 95% CI 2.06, 8.87). The prevalence of anaemia was 27.7% (95% CI 23.6, 32.1), and it was higher among AMiP-positives (56.9%) than the negatives (22.5%) (P: 000). CONCLUSION: The prevalence of AMiP and anaemia was high, and remained as a critical public health problem in the study area. Focus on the identified risk factors and introduction of more sensitive diagnostic tools should be considered to mitigate AMiP in the study area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".