Genetic and epidemiological analysis of norovirus from children with gastroenteritis in Botswana, 2013–2015
Bibliographic record
Abstract
BACKGROUND: Norovirus is a leading cause of viral gastroenteritis worldwide with a peak of disease seen in children. The epidemiological analysis regarding the virus strains in Africa is limited. The first report of norovirus in Botswana was in 2010 and currently, the prevalence and circulating genotypes of norovirus are unknown, as the country has no systems to report the norovirus cases. This study investigated the prevalence, patterns and molecular characteristics of norovirus infections among children ≤5 years of age admitted with acute gastroenteritis at four hospitals in Botswana. METHODS: A total of 484 faecal samples were collected from children who were admitted with acute gastroenteritis during the rotavirus vaccine impact survey between July 2013 and December 2015. Norovirus was detected using real-time RT-PCR. Positive samples were genotyped using conventional RT-PCR followed by partial sequencing of the capsid and RdRp genes. Norovirus strains were determined by nucleotide sequence analysis using the online Norovirus Genotyping Tool Version 1.0, and confirmed using maximum likelihood tree construction as implemented in MEGA 6.0. RESULTS: The prevalence of norovirus was 9.3% (95% CI 6.7-11.9). The genotype diversity was dominated by the GII.4 strain at 69.7%. This was followed by GII.2, GII.12 each at 9.1%, GI.9 at 6.6% and GII.6, GII.10 each at 3.0%. The most common combined RdRp/Capsid genotype was the GII.Pe/GII.4 Sydney 2012. Norovirus was detected during most part of the year; however, there was a preponderance of cases in the wet season (December to March). CONCLUSION: The study showed a possible decline of norovirus infections in the last 10 years since the first report. An upward trend seen between 2013 and 2015 may be attributable to the success of rotavirus vaccine introductions in 2012. Knowledge of circulating genotypes, seasonal trends and overall prevalence is critical for prevention programming and possible future vaccine design implications.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".