Descriptive Epidemiology of Acute Flaccid Paralysis Cases in Afghanistan, 2015-2018
Bibliographic record
Abstract
Background Polio is on the verge of eradication, while Afghanistan and Pakistan are the only endemic countries remaining where polio is still prevalent. Surveillance for acute flaccid paralysis (AFP) is one of the four cornerstone strategies of the Polio Eradication Initiative. Objective This study aims to describe the epidemiology of AFP cases in terms of time, place, and person. Methods It is a descriptive study whereby we analyzed the secondary data reported by AFP surveillance in Afghanistan. We accessed and used line lists from 2015 to 2018 to describe the epidemiological status of AFP cases in the country. With the use of Epi Info 7 and Microsoft Excel, we calculated descriptive measures, including frequencies, mean, median, SD, generated proportions, tables, and graphs. Results Overall, 11,513 cases were reported in the last 4 years (2015-2018) by AFP surveillance at the Ministry of Public Health. The majority of the cases (29%) were reported in 2018, while 2088 (18%) cases were reported in 2015. The trend of oral polio vaccination has increased from 2015 to 2018 (57%, 64%, 63%, and 68%, respectively). Most of the cases were reported from southern and western regions, and 57% were male cases. The highest (38%) proportions of cases were in those less than 30 months in age. Guillain-Barre syndrome was 38% of all categories. The samples were collected using appropriate procedures. However, the numbers of confirmed cases increased from 13 in 2016 to 14 in 2017, 20 in 2018, and 22 in 2019. Conclusions The AFP surveillance system is well established in the country. Nevertheless, with the increase in the trend of oral polio vaccine coverage, there is also an increase in the number of confirmed polio cases. Hence, the system should be sustained, and strategies should be strengthened to focus on the southern region as being the main engine of polio in the country.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".