Barriers of Visceral Leishmaniasis reporting and surveillance in Nepal: comparison of governmental <scp>VL</scp>‐program districts with non‐program districts
Bibliographic record
Abstract
OBJECTIVES: At the time when Nepal is on the verge of reaching the maintenance phase of the Visceral Leishmaniasis (VL) elimination program, the country is facing new challenges. The disease has expanded to 61 of the country's 75 districts including previously non-endemic areas where there is no control or patient management program in place. This study aimed to assess which elements of the surveillance and reporting systems need strengthening to identify cases at an early stage, prevent further transmission and ensure sustained VL elimination. METHODS: In a cross-sectional mixed-method study, we collected data from two study populations in VL program and non-program districts. From February to May 2016, structured interviews were conducted with 40 VL patients, and 14 in-depth and semi-structured interviews were conducted with health managers. RESULTS: The median total delay from onset of symptoms to successful reporting to the Ministry of Health was 68.5 days in the VL-program and 83 days in non-program districts. The difference in patient's delay from the onset of symptoms to seeking health care was 3 days in VL-program and 20 days in non-program districts. The diagnostic delay (38.5 days and 36 days, respectively), treatment delay (1 vs. 1 days) and reporting delay (45 vs. 36 days) were similar in program and non-program districts. The diagnostic delay increased three-fold from 2012, while treatment and reporting delay remained unchanged. The main barriers to surveillance were: (i) lack of access and awareness in non-program districts; (ii) growing private sector not included in and not participating to referral, treatment and reporting; (iii) lack of cooperation and coordination among stakeholders for training and deployment of interventions; (iv) insufficient validation, outreach and process optimisation of the reporting system. CONCLUSIONS: Corrective measures are needed to maintain the achievements of the VL elimination campaign and prevent resurgence of the disease in Nepal. A clear patient referral structure, reinforcement of report notification and validation and direct relay of data by local hospitals and the private sector to the district health offices are needed to ensure prompt treatment and timely and reliable information to facilitate a responsive system of interventions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".