Impact of COVID-19 pandemic on tuberculosis notifications in India
Notice bibliographique
Résumé
Sir, India contributes nearly a quarter of the global tuberculosis burden.[1] Currently, this silent epidemic has been overshadowed by the ongoing coronavirus 2019 disease (COVID-19) pandemic. Once tuberculosis dropped off the radar of public health and political priority, several gaps have emerged that have caused a huge setback to our National Tuberculosis Elimination Program (NTEP). In particular, reduced and delayed notification of newly detected cases has remained a problem. In India, all tuberculosis notifications are electronically communicated through the NIKSHAY platform maintained by the Government of India. We queried the NIKSHAY database for monthly case notifications across India from 2018 onward, to ascertain the impact of COVID-19 on tuberculosis notification rates.[2] We built a forecast model for 2020 and 2021 from the information obtained for 2018 and 2019, using Winters additive time series modeling. This forecast model provided anticipated monthly notification figures, along with a 95% confidence range, had our NTEP continued to perform as previously without being hindered by the COVID-19 pandemic. We compared the actual monthly notification data from 2020 onward against this predicted “target” for each month, and correlated it with the fluctuations in daily national caseload of new COVID-19 patients. The monthly tuberculosis notification showed a gradual upslope over time, which was reflected in the forecast model as well [Figure 1]. In general, the notification rates had hovered around 200,000 patients every month in 2019, and started deviating from the forecasted rates in March 2020 due to social and travel restrictions. In view of the continued detection of fresh COVID-19 patients, India enforced a strict nationwide lockdown from March 25, 2020, onward. By April 2020, monthly tuberculosis notification rates plummeted to below 84,000 [Figure 1]. These improved marginally over the next few months, but remained much lower than usual numbers during previous years. This suggested a large number of patients were being “missed” by the NTEP, due to widespread disruptions in general and tuberculosis-related health services, but were still able to spread tuberculosis in the community.[3] As a mitigation measure, the NTEP proposed and implemented a rapid response plan to augment tuberculosis services in September 2020.[4] This further improved case notification, and monthly tuberculosis notification had touched pre-COVID-19 levels by March 2021, though it was still slightly below forecasted targets [Figure 1]. Unfortunately, India experienced a much more devastating second COVID wave between April and June 2021. Strict lockdowns and restrictions were once again imposed, and simultaneously tuberculosis notification declined to just over 92,000 cases during May 2021 [Figure 1]. There has been some recovery as the COVID-19 restrictions were eased out, but notifications still remain less than targeted.Figure 1: The solid red line in the top panel depicts countrywide monthly notifications rates for new tuberculosis patients from January 2018 to September 2021. The green line represents the notification forecast from 2020 onward, along with its 95% confidence zone (green-shaded area). The bottom panel summarizes total number of new COVID-19 patients diagnosed each day throughout India till end of September 2021Tuberculosis notification in other high-burden countries has also been adversely affected by disruptions due to COVID-19 pandemic. Globally, tuberculosis notifications fell by 21% in 2020 compared to 2019 data.[5] The reduction in detection of new cases can lead to long-term increase in tuberculosis incidence and mortality. However, these negative effects can be mitigated with rapid restoration of tuberculosis services, and implementation of focused interventions guided by notification targets, immediately after lifting restrictions.[6] We need to further improve case detection and notification to avoid major setbacks to the gains made by NTEP in recent years. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».