V-shaped recovery of tuberculosis notification trend amid COVID-19: Is it enough?
Bibliographic record
Abstract
Sir, The mandatory notification of tuberculosis (TB) in India has a pivotal role toward achieving the national target of TB elimination in India by 2025. However, COVID-19 pandemic led to a sharp decline in the notification of TB cases for the second consecutive year as evident from the Nikshay Dashboard [Figure 1] followed by a V-shaped recovery.[1]Figure 1: Timeline of tuberculosis notification for 2018–2021 till October 2021 in India (Source: Nikshay Dashboard), and till the third quarter of the year in the United Kingdom (UK) (Source: Public Health England)The fall in TB cases initially could have been because of decreased notification or actual decrease in incidence, with the former being more plausible. Similarly, the rise of notification in the latter part could have been due to the delayed reporting or an actual increase in incidence of TB. In fact, the sharp rise in TB notification in 2021 after the second wave of COVID-19 pandemic (in the month of June), created a national stir in India and fear regarding the increase in incidence of TB which was followed by national advisory for mandatory bidirectional screening for COVID-19 in TB and vice versa. Rampant use of steroids, immunosuppressants, and a weakened immunity due to the COVID-19 infection can be reasons behind the increase in incidence of TB.[2] COVID-19 and TB coinfection can have disastrous national health consequences with increased mortality and morbidity.[3] However, the lack of continued rise from July to August 2021 in India indicates the more likely factor being the delayed reporting of the TB cases of the previous months, and this “V-shaped recovery” can be attributed to the TB cases which we have missed during the second wave and were diagnosed later after the subsequent decrease in COVID cases. Thus, the national authorities in India subsequently issued a statement that there is not enough evidence to suggest an increase in TB cases due to COVID-19.[3] Such patterns of decline and recovery in TB notification were also seen in the United Kingdom [Figure 1] in 2020 during the COVID-19 peak. However, in 2021, the notification of TB did not show any fall despite recurrent COVID-19 peaks due to intensified administrative and medical efforts in the United Kingdom. It is also interesting to see from Figure 1 that even after this (episodic) V-shaped rise in the notification of TB cases over the past 2 years in India, we are still lagging far behind our target of detecting 3,00,000 cases/month, i.e., 3.6 million cases annually as laid out in the National Strategic Plan for TB Elimination (2017–2025).[4] The COVID-19 definitely caused major disruptions in TB notification, however, the annual curve is also showing a falling trend over the past 4 years which needs to be rapidly targeted. To conclude, it is a long journey toward the elimination of TB from the Indian subcontinent, especially amid COVID-led disruption of health services. However, with the intensified efforts to mitigate the impact of COVID-19 pandemic, the missing cases have been brought into notification, not once but twice. It is imperative that TB is not forgotten or ignored in these pandemic times and constant efforts are intensified in the diagnosis, notification, treatment, and cure of TB.[3] Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 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".