Risk assessment for COVID-19 transmission at household level in sub-Saharan Africa: evidence from DHS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Household habitat conditions matter for diseases transmission and control, especially in the case of the novel coronavirus (COVID-19). These conditions include availability and adequacy of sanitation facilities, and number of persons per room. Despite this, little attention is being paid to these conditions as a pathway to understanding the transmission and prevention of COVID-19, especially in Africa, where household habitat conditions are largely suboptimal. This study assesses household sanitation and isolation capacities to understand the COVID-19 transmission risk at household level across Africa. We conducted a secondary analysis of the Demographic and Health Surveys of 16 African countries implemented between 2015 and 2018 to understand the status of households for prevention of COVID-19 transmission in home. We assessed handwashing capacity and self-isolation capacity using multiple parameters, and identified households with elderly persons, who are most at risk of the disease. We fitted two-level random intercept logit models to explore independent relationships among the three indicators, while controlling for the selected explanatory variables. Handwashing capacity was highest in Tanzania (48.2%), and lowest in Chad (4.2%), varying by household location (urban or rural), as well as household wealth. Isolation capacity was highest in South Africa (77.4%), and lowest in Ethiopia (30.9%). Senegal had the largest proportion of households with an elderly person (42.1%), while Angola (16.4%) had the lowest. There were strong, independent relationships between handwashing and isolation capacities in a majority of countries. Also, strong associations were found between isolation capacity and presence of older persons in households. Household capacity for COVID-19 prevention varied significantly across countries, with those having elderly household members not necessarily having the best handwashing or isolation capacity. In view of the age risk factors of COVID-19 transmission, and its dependence on handwashing and isolation capacities of households, each country needs to use the extant information on its risk status to shape communication and intervention strategies that will help limit the impact of the disease in its population across Africa. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41118-021-00130-w.
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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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it