Trends for Diarrhea Morbidity in the Jasikan District of Ghana: Estimates from District Level Diarrhea Surveillance Data, 2012–2016
Bibliographic record
Abstract
About 22% of childhood deaths in developing countries are attributable to diarrhea. In poor resource settings, diarrhea morbidities are correlated with poverty and socio-contextual factors. Diarrhea rates in Ghana are reported to be high, with cases estimated at 113,786 among children under-five years in 2011. This study analyzed the trends of diarrhea morbidity outcomes in the Jasikan District of Ghana. A retrospective analysis of records on diarrhea data for a five years' period (January 2012 to December 2016) was undertaken. There was a total of 17740 diarrhea case reports extracted from District Health Information Management System (DHIMS) II database in an Excel format which was then exported to Stata version 14 for data cleaning, verification, and analysis. Excel version 2016 was used to plot the actual observed cases by years to assess trends and seasonality. There was a period incidence rate of 272.02 per 1000 persons with a decreasing annual growth rate of 1.85%. Declines for diarrhea generally occurred from November to December and increased from January upwards, evidence that most cases of diarrhea in this study were reported in the harmattan season. High incidence of diarrhea was found to be common among under-five children and among females. Decreasing trend of diarrhea incidence which was identified in this research within the five years' period understudied shows that, by the year 2020, there will be a sharp decline in the incidence rate of diarrhea reported cases in Jasikan District, given improvements in the external environmental conditions in the district, all things being equal.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".