| Literature DB >> 32362647 |
Nivedita Gupta1, Ira Praharaj1, Tarun Bhatnagar2, Jeromie Wesley Vivian Thangaraj2, Sidhartha Giri1, Himanshu Chauhan3, Sanket Kulkarni3, Manoj Murhekar2, Sujeet Singh3, Raman R Gangakhedkar1, Balram Bhargava4.
Abstract
Background & objectives: Sentinel surveillance among severe acute respiratory illness (SARI) patients can help identify the spread and extent of transmission of coronavirus disease 2019 (COVID-19). SARI surveillance was initiated in the early phase of the COVID-19 outbreak in India. We describe here the positivity for COVID-19 among SARI patients and their characteristics.Entities:
Keywords: COVID-19; SARI; sentinel; surveillance; Containment
Mesh:
Year: 2020 PMID: 32362647 PMCID: PMC7357403 DOI: 10.4103/ijmr.IJMR_1035_20
Source DB: PubMed Journal: Indian J Med Res ISSN: 0971-5916 Impact factor: 2.375
Distribution of coronavirus disease 2019 (COVID-19) cases among severe acute respiratory illness (SARI) patients by week, India, 2020
| Week | Number of laboratories testing SARI for COVID-19 | Number of SARI patients tested | Number of COVID-19 positive (%) |
|---|---|---|---|
| 8-9 (February 15 - 29) | 16 | 217 | 0 (0.0) |
| 10-11 (March 1 - 14) | 41 | 642 | 0 (0.0) |
| 12 (March 15 - 21) | 27 | 106 | 2 (1.9) |
| 13 (March 22 - 28) | 119 | 2877 | 48 (1.7) |
| 14 (March 29 - April 2) | 104 | 2069 | 54 (2.6) |
| Total | 5911 | 104 (1.8) |
Distribution of coronavirus disease 2019 (COVID-19) cases among severe acute respiratory illness (SARI) patients by age, gender and per cent positivity, India, 2020
| Characteristics | Number of COVID-19 cases (per cent of total) | Number of SARI patients (per cent of total) | Per cent positivity |
|---|---|---|---|
| Gender | n=102 | n=5723 | |
| Male | 85 (83.3) | 3676 (64.2) | 2.3 |
| Female | 17 (16.7) | 2047 (35.8) | 0.8 |
| Age groups (yr) | n=102 | n=5682 | |
| 0-9 | 2 (2.0) | 386 (6.8) | 0.5 |
| 10-19 | 0 | 371 (6.5) | 0 |
| 20-29 | 9 (8.8) | 1419 (25.0) | 0.6 |
| 30-39 | 8 (7.8) | 971 (17.1) | 0.8 |
| 40-49 | 16 (15.7) | 634 (11.2) | 2.5 |
| 50-59 | 31 (30.4) | 637 (11.2) | 4.9 |
| 60-69 | 26 (25.5) | 672 (11.8) | 3.9 |
| 70-79 | 8 (7.8) | 405 (7.1) | 2.0 |
| ≥80 | 2 (2.0) | 187 (3.3) | 1.1 |
Distribution of coronavirus disease 2019 (COVID-19) cases among severe acute respiratory illness (SARI) patients by State/Union Territory, India, 2020
| State/UT | Number of laboratories testing SARI patients | Number of SARI patients | Number of COVID-19 positive (%) | Number of districts with COVID-19 cases |
|---|---|---|---|---|
| Gujarat | 7 | 792 | 13 (1.6) | 4 |
| Tamil Nadu | 14 | 577 | 5 (0.9) | 5 |
| Maharashtra | 14 | 553 | 21 (3.8) | 8 |
| Kerala | 5 | 502 | 1 (0.2) | 1 |
| Karnataka | 8 | 320 | 2 (0.6) | 2 |
| Uttar Pradesh | 7 | 295 | 4 (1.4) | 2 |
| Delhi | 11 | 277 | 14 (5.1) | 5 |
| Assam | 5 | 276 | 1 (0.4) | 1 |
| Bihar | 2 | 263 | 3 (1.1) | 2 |
| West Bengal | 5 | 256 | 9 (3.5) | 6 |
| Madhya Pradesh | 4 | 249 | 5 (2.0) | 2 |
| Telangana | 4 | 190 | 8 (4.2) | 2 |
| Rajasthan | 4 | 179 | 0 (0.0) | 0 |
| Haryana | 3 | 161 | 4 (2.5) | 3 |
| Punjab | 2 | 158 | 1 (0.6) | 1 |
| Andhra Pradesh | 4 | 129 | 4 (3.1) | 2 |
| Himachal Pradesh | 2 | 110 | 0 (0.0) | 0 |
| Jharkhand | 1 | 110 | 1 (0.9) | 1 |
| Odisha | 3 | 107 | 2 (1.9) | 1 |
| Jammu and Kashmir | 4 | 79 | 1 (1.3) | 1 |
| Chhattisgarh | 1 | 74 | 0 (0.0) | 0 |
| Puducherry | 1 | 41 | 0 (0.0) | 0 |
| Arunachal Pradesh | 0 | 28 | 0 (0.0) | 0 |
| Chandigarh | 2 | 24 | 1 (4.2) | 1 |
| Meghalaya | 1 | 21 | 0 (0.0) | 0 |
| Manipur | 2 | 20 | 0 (0.0) | 0 |
| Tripura | 1 | 18 | 2 (11.1) | 1 |
| Nagaland | 0 | 18 | 0 (0.0) | 0 |
| Andaman and Nicobar Islands | 1 | 17 | 0 (0.0) | 0 |
| Mizoram | 0 | 11 | 0 (0.0) | 0 |
| Uttarakhand | 1 | 6 | 0 (0.0) | 0 |
| Sikkim | 0 | 3 | 0 (0.0) | 0 |
| Goa | 1 | 2 | 0 (0.0) | 0 |
| Dadra and Nagar Haveli | 0 | 1 | 0 (0.0) | 0 |
Coronavirus disease 2019 (COVID-19) cases among severe acute respiratory illness (SARI) patients by source of exposure, India, 2020 (n=102)
| Source of exposure | Number of cases (per cent of total) |
|---|---|
| No foreign travel/contact with known laboratory confirmed COVID-19 case | 40 (39.2) |
| Contact with a known laboratory confirmed COVID-19 case | 2 (2.0) |
| History of foreign travel | 1 (1.0) |
| Data not available | 59 (57.8) |