Consanguineous marriages and endemic malaria: can inbreeding increase population fitness?
Bibliographic record
Abstract
BACKGROUND: The practice of consanguineous marriages is widespread in countries with endemic malaria. In these regions, consanguinity increases the prevalence of alpha+-thalassemia, which is protective against malaria. However, it also causes an excessive mortality amongst the offspring due to an increase in homozygosis of recessive lethal alleles. The aim of this study was to explore the overall effects of inbreeding on the fitness of a population infested with malaria. METHODS: In a stochastic computer model of population growth, the sizes of inbred and outbred populations were compared. The model has been previously validated producing results for inbred populations that have agreed with analytical predictions. Survival likelihoods for different alpha+-thalassemia genotypes were obtained from the odds of severe forms of disease from a field study. Survivals were further estimated for different values of mortality from malaria. RESULTS: Inbreeding increases the frequency of alpha+-thalassemia allele and the loss of life due to homozygosis of recessive lethal alleles; both are proportional to the coefficient of inbreeding and the frequency of alleles in population. Inbreeding-mediated decrease in mortality from malaria (produced via enhanced alpha+-thalassemia frequency) mitigates inbreeding-related increases in fatality (produced via increased homozygosity of recessive lethals). When the death rate due to malaria is high, the net effect of inbreeding is a reduction in the overall mortality of the population. CONCLUSION: Consanguineous marriages may increase the overall fitness of populations with endemic malaria.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".