Handwashing and Household Health Expenditures Under COVID-19: Evidence from Cameroon
Bibliographic record
Abstract
Handwashing is one of the recommended measures during the COVID-19 period to limit the spread of the disease and also contributes to the prevention of WASH-related illnesses. The objective of this study is to analyze the impact of using a handwashing device on household healthcare expenditures in Cameroon, particularly during the period of strict COVID-19 strict restrictions. The data used were collected in September 2021 from 604 Cameroonian households in the Centre and Littoral regions as part of a study funded by the International Development Research Centre (IDRC). To account for unobserved heterogeneity affecting both the decision to use a handwashing device and household healthcare expenditures, an Endogenous Switching Regression (ESR) model was employed. The results highlight that the main determinants of a household’s decision to use handwashing devices include environmental factors such as the region, given its importance in the implementation of communication strategies, as well as specific characteristics of the household head. Furthermore, the use of this device leads to a reduction of approximately 52% in healthcare expenditures for households that used it, which corresponds to an average amount of 12,900 CFA francs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".