Paying for hospital-based care of Kala-azar in Nepal: assessing catastrophic, impoverishment and economic consequences
Bibliographic record
Abstract
Households obtaining health care services in developing countries incur substantial costs, despite services generally being provided free of charge by public health institutions. This constitutes an economic burden on low-income households, and contributes to deepening their level of poverty. In addition to the economic burden of obtaining health care, the method of financing these payments has implications for the distribution of household assets. This effect on resource-poor households is amplified since they have decreased access to health insurance. Recent literature, however, ignores the importance of the method of financing health care payments. This paper looks at the case of Nepal and highlights the impact on households of paying for hospital-based care of Kala-azar (KA) by analysing the catastrophic, impoverishment and economic consequences of their coping strategies. The paper utilizes micro-data on a random selection of 50% of the KA-affected households of Siraha and Saptari districts of Nepal. The empirical results suggest that direct costs of hospital-based treatment of KA are catastrophic since they consume 17% of annual household income. This expenditure causes more than 20% of KA-affected households to fall below the poverty line, with the remaining households being pushed into the category of marginal poor; the poverty gap ratio is more than 90%. Further, KA incidence can have prolonged and severe economic consequences for the household economy due to the mechanisms of informal sector financing to which households resort. A heavy burden of loan repayments can lead households on a downward spiral that eventually becomes a poverty trap. In other words, the method of financing health care payments is an important ingredient in understanding the economic burden of disease.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".