Average Household Size and the Eradication of Malaria
Bibliographic record
Abstract
Efforts to eradicate malaria during the 20th century succeeded in some parts of the world but failed in others. Malaria also disappeared spontaneously in several countries for reasons that remain an enigma. The connection between malaria and poverty has long been noted. Here we focus on a specific aspect: household size, which has hitherto received little attention. We find strong evidence that when average household size drops below four persons, the probability of malaria eradication jumps dramatically and its incidence in the population drops significantly. This effect is independent of all commonly-studied explanatory variables and was globally valid across all climate zones irrespective of counter measures, vector species, or Plasmodium species. We propose an explanation based on the dispersal mechanism of the parasite. Malaria is transmitted at night by mosquito bite. The mosquito typically spreads the Plasmodium only locally over short distances to new human victims. To survive, the Plasmodium depends on infected humans making social contacts over longer distances. When household size decreases sufficiently, these contacts cross a threshold value that changes the balance between extinctions and replacements and the Plasmodium disappears on its own. We test this interpretation by contrasting our malaria model with dengue fever, which is also poverty-related and mosquito-borne but transmitted differently, namely through daytime exposure. Household size is uncorrelated with dengue incidence, whereas an indicator of outdoor work that is insignificant in the malaria model is highly significant for dengue. We conclude that poverty-induced malaria infection risks are likely to persist, but a focus on reducing effective household size can be a feasible and promising means of its eradication.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".