Icmr Covid Rt Pcr Report Download
Bulah Landaker
Results: A total of 104 (1.8%) of the 5,911 SARI patients tested were positive for COVID-19. These cases were reported from 52 districts in 20 States/Union Territories. The COVID-19 positivity was higher among males and patients aged above 50 years. In all, 40 (39.2%) COVID-19 cases did not report any history of contact with a known case or international travel.
Interpretation & conclusions: COVID-19 containment activities need to be targeted in districts reporting COVID-19 cases among SARI patients. Intensifying sentinel surveillance for COVID-19 among SARI patients may be an efficient tool to effectively use resources towards containment and mitigation efforts.
The researchers conducted the investigations after reports of sudden deaths among healthy adults in India started to emerge. These reports sparked concerns that these deaths may be linked to COVID-19 or the vaccine taken against it.
Earlier, Union Health Minister Mansukh Mandaviya had also quoted the ICMR to caution those with a past history of severe COVID-19 infection against overexertion. His comments came after a series of sudden deaths reported in October this year from Navaratri celebrations across Gujarat.
Sampling strategy: The districts will be categorized into four strata according to the reported COVID-19 cases per million population (zero, low: 0.1-4.7, medium: 4.8-10 and high: >10), as per data from the ICMR testing laboratory reporting portal ( ). Fifteen districts from each stratum will be selected randomly for a total of 60 districts. In addition, the top 10 cities reporting the highest number of cases in the country will be included, to be considered as hotspots. The proposed sampling strategy considers the operational feasibility of the survey.
Hotspot cities: With the assumption of five per cent seropositivity, relative precision of 20 per cent, confidence interval of 95 per cent and design effect of 2.5, there is a need to enrol 4,554 (rounded to 5000) individuals. For this purpose, 500 individuals will be allocated to each of the top 10 cities reporting the highest number of cases. Within each of these cities, 100 individuals will be included for the survey from five randomly selected clusters (containment zones within the city).
Analysis plan: The seroprevalence of SARS-CoV-2 infection will be estimated in different rounds of serosurveys. The trend of seropositivity will also be looked at to monitor the community-level transmission. Pooled seroprevalence from the group of districts for each of the four strata will be used to estimate the population prevalence of COVID-19 infection in the country after adjusting for population and antibody test characteristics. Similar analysis will be done separately for the hotspot cities. A sensitivity analysis will be done to determine the influence of antibody test kit performance on prevalence estimates7. Gaps in testing, missing convalescent cases on real-time reverse transcription (RT) PCR-based assay and undetected asymptomatic or mild symptomatic infections can influence the reported number of cases. The infection-to-case ratio will be calculated to account for the same.
Ethical considerations: Interviews will happen in a place as per the convenience of the participants to ensure privacy. All data will be stored securely under the investigator's responsibility, with a focus on ensuring the participant's confidentiality. The final report will be based on aggregate data without any identifying information. Electronic case report forms (eCRFs) will be used to collect data. A database with electronic tracking, password-restricted access and audit trail, with time and date stamps on data entry and edits, will be used.
The Indian Council of Medical Research (ICMR) has been leading India's laboratory surveillance testing for COVID-19. In the initial phase, testing for SARS-CoV-2 was conducted through 78 selected national reference laboratories3. Constrained by the international shortage of testing reagents, the ICMR testing strategy incorporated a risk-based approach alongside clinical symptoms. This approach balanced the need for immediate deployment of nation-wide surveillance and judicious use of resources. Subsequently, sentinel surveillance for severe acute respiratory infection (SARI) was started on February 15, 20204. The ICMR led the expansion of testing capacity by using its existing laboratory network, developing standard protocols and launching an online portal for reporting5.
Testing: The ICMR developed standard specimen collection, specimen transport and laboratory testing processes, including criteria for classifying results which are publicly available. The reported testing results are based on quantitative real-time-reverse-transcriptase polymerase chain reaction (qRT-PCR) tests.
The cumulative frequency of testing was 770 individuals per million population. The testing frequency by the States varied widely (Fig. 2). In all, 729 out of 736 districts (99.0%) reported any testing. Among the States and Union Territories (UTs) with more than first quartile of Indian population (660,000), the testing frequency ranged from 182/million in Manipur to 2149/million in Delhi. The States/UTs that reported higher than all India average of tests per million were Andhra Pradesh (1721), Tamil Nadu (1468), Jammu and Kashmir (1417), Rajasthan (1329), Haryana (1308), Tripura (1251), Gujarat (1133), Maharashtra (1070), Karnataka (1011), Himachal Pradesh (889) and Kerala (814) (Table I).
At the national level, the average number of contacts tested per laboratory-confirmed case was 6. At the State level, the average number of contacts tested per positive case ranged from 1.3 in Jharkhand to 328 in Tripura (Fig. 3). Among the top 10 States/UTs, based on the reported number of COVID-19 cases, the average number of contacts tested per positive case was more than the national average in Tamil Nadu (14.4), Uttar Pradesh (9.8), Telangana (8.1), Andhra Pradesh (7.7), Madhya Pradesh (7.6) and Rajasthan (6.3). Corrected for missing data from our sensitivity analysis, the average number of contacts tested per positive case was 20.4 at all-India level and ranged from 6.6 in Chandigarh to 1387 in Tripura (Table III).
Description of COVID-19 cases by time, place and person: In all, 3.9 per cent (n=40,184) cases were positive for SARS-CoV-2. Cases reported increased over time since March 30, 2020. The proportion of detected cases reporting any international travel decreased over time (Fig. 4). The seven-day moving average for the proportion of positive tests remained between 3 and 6 per cent after March 10, 2020 (Fig. 1). COVID-19 cases have been reported from 523 of 736 (71.1%) districts in the country. States with the highest proportion of districts reporting positive cases included Delhi, Maharashtra, Kerala, Punjab, Haryana, Tamil Nadu, Andhra Pradesh and Gujarat (Fig. 5). The States/UTs with the highest test positivity were Maharashtra (10.6%), Delhi (7.8%), Gujarat (6.3%), Madhya Pradesh (6.1%) and West Bengal (5.8%) (Table I).
Proportion of districts reporting any coronavirus disease 2019 case by State/Union Territory, India, January 22 - April 30, 2020. Source: Map outline reproduced with permission from Survey of India, Department of Science & Technology.
Positivity was highest among the symptomatic contacts (10.3%) and SARI patients (6.1%). Of the 40,184 positives, 25.3 per cent were asymptomatic family contacts, 10.6 per cent were symptomatic contacts and 10.5 per cent were SARI patients Table II. Among the 12,810 cases with reported symptoms at the time of specimen collection, cough and fever were the most commonly reported symptoms (64.5 and 60%, respectively). Around one-third of cases reported sore throat and breathlessness. Gastrointestinal symptoms such as abdominal pain, nausea, vomiting and diarrhoea were reported by less than 5 per cent of cases (Table IV).
The national COVID-19 testing strategy formulated and implemented by the ICMR evolved with the logistics and phase of the pandemic in India. The deployment of the testing sites was scaled up over time with guidance according to the control strategy. The coverage and testing frequency was improved since launch. Almost all Indian districts reported laboratory surveillance and scaled up their capacity to test. The timeliness of specimen testing is indicated by a few delays between the specimen collection and receipt at the laboratory. Because the testing criteria, except for SARI, require exposure to a positive case, we are uncertain about the transmission among unlinked individuals in the community. The surveillance data had a large proportion of tests with missing information on exposure history. States demonstrated wide variations in contacts tested per case. It represents the robustness of contact tracing. While exposure to different contacts could vary per case, the reason for this variation needs to be further explored to improve tracing and testing strategies.
The national laboratory surveillance data provided insights on the epidemiology of COVID-19 in India. Cases were reported from all over India, and travel was no longer the primary means of exposure. While cases continued to be reported, the rate of increase slowed, as demonstrated by the relatively stable test positivity over time. The change in the trend could be attributed to multiple public health measures implemented on a wider scale. A higher attack rate of COVID-19 among men and adults has been reported widely12. It is unclear whether this difference is due to susceptibility or exposure level or represents a higher selection probability for testing. Many cases were among contacts who were asymptomatic at the time of testing. It is reported that there is a pre-symptomatic period of about two days13. With the current data, it was not possible to determine if cases remained symptom free or were pre-symptomatic. The proportion of asymptomatic at the time of testing is also affected by the criteria used for case detection. As the staff responsible for contacts tracing varies across the country, this may also affect the quality of history taking. While the contacts traced and tested improved over a period of time, there were wide variations in terms of secondary attack rates by their known contact status. Our analysis of attack rate by including those with unknown contact status group was different from that of the analysis with known contact status. While the risk to contacts will vary per case, the reason for variation across the States can be further investigated to improve the quality of isolation and quarantine measures to reduce transmission.
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