Beyond eves and cracks: An interdisciplinary study of socio-spatial variation in urban malaria transmission in Ethiopia
Bibliographic record
Abstract
During the past century, the global trend of reduced malaria transmission has been concurrent with increasing urbanization. Although urbanization has traditionally been considered beneficial for vector control, the adaptation of malaria vectors to urban environments has created concerns among scientific communities and national vector control programs. Since urbanization rates in Ethiopia are among the highest in the world, the Ethiopian government developed an initiative focused on building multi-storied units organized in condominium housing. This study aimed to develop an interdisciplinary methodological approach that integrates architecture, landscape urbanism, medical anthropology, and entomology to characterize exposure to malaria vectors in this form of housing in three condominiums in Jimma Town. Mosquitoes were collected using light trap catches (LTCs) both indoor and outdoor during 2019's rainy season. Architectural drawings and ethnographic research were superposed to entomological data to detect critical interactions between uses of the space and settlement conditions potentially affecting malaria vector abundance and distribution. A total of 34 anopheline mosquitoes comprising three species (Anopheles gambiae s.l, An. pharoensis and An. coustani complex) were collected during the three months of mosquito collection. Anopheles gambiae s.l, the principal malaria vector in Ethiopia, was the predominant species of all the anophelines collected. Distribution of mosquito breeding sites across scales (household, settlement, urban landscape) is explained by environmental conditions, socio-cultural practices involving modification of existing spaces, and systemic misfits between built environment and territory. Variations in mosquito abundance and distribution in this study were mainly related to standard building practices that ignore the original logics of the territory, deficiency of water and waste disposal management systems, and adaptations of the space to fit heterogeneous lifestyles of residents. Our results indicate that contextualizing malaria control strategies in relation to vector ecology, social dynamics determining specific uses of the space, as well as building and territorial conditions could strengthen current elimination efforts. Although individual housing remains a critical unit of research for vector control interventions, this study demonstrates the importance of studying housing settlements at communal level to capture systemic interactions impacting transmission at the household level and in outdoor areas.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".