Background & objectives: COVID-19 cases have been rising rapidly in countries where the SARS-CoV-2 variant of concern (VOC), Omicron (B.1.1.529) has been reported. We conducted a study to describe ...the epidemiological and clinical characteristics and outcomes of COVID-19 patients with 'S' gene target failure (SGTF, suspected Omicron). Furthermore, their clinical outcomes with COVID-19 patients with non-SGTF (non-Omicron) were also compared.
Methods: This study was conducted in Tamil Nadu, India, between December 14, 2021 and January 7, 2022 among patients who underwent reverse transcription-PCR testing for SARS-CoV-2 in four laboratories with facilities for S gene screening. Consecutively selected COVID-19 patients with SGTF were telephonically contacted, seven and 14 days respectively after their date of positive result to collect information on the socio-demographic characteristics, previous history of COVID-19, vaccination status and clinical course of illness along with treatment details. To compare their outcomes with non-SGTF patients, one randomly suspected non-Omicron case for every two suspected Omicron cases from the line-list were selected, matching for the date of sample collection and the testing laboratory.
Results: A total of 1175 SGTF COVID-19 patients were enrolled for this study. Almost 6 per cent (n=72) reported a history of previous infection. 141 (13.5%) suspected Omicron cases were non-vaccinated, while 148 (14.2%) and 703 (67.4%) had received valid one and two doses of COVID-19 vaccines, respectively. Predominant symptoms reported included fever (n=508, 43.2%), body pain (n=275, 23.4%), running nose (n=261, 22.2%) and cough (n=249, 21.2%). Five (0.4%) of the 1175 suspected Omicron cases required oxygen supplementation as compared to ten (1.6%) of the 634 suspected non-Omicron cases. No deaths were reported among omicron suspects, whereas there were four deaths among suspected non-Omicron cases.
Interpretation & conclusions: Majority of the suspected Omicron cases had a mild course of illness. The overall severity of these cases was less compared to the suspected non-Omicron cases.
Noncommunicable diseases (NCDs) account for nearly 75% of all deaths in Tamil Nadu. The government of Tamil Nadu has initiated several strategies to control NCDs under the Tamil Nadu Health Systems ...Reform Program (TNHSRP). We aimed to estimate the prevalence of NCD risk factors and determine the predictors of diabetes and hypertension, which will be helpful for planning and serve as a baseline for evaluating the impact of interventions.
A state-wide representative cross-sectional study was conducted among 18-69-year-old adults in Tamil Nadu in 2020. The study used a multi-stage sampling method to select the calculated sample size of 5780. We adapted the study tools based on WHO's STEPS surveillance methodology. We collected information about sociodemographic factors, NCD risk factors and measured blood pressure and fasting capillary blood glucose. The predictors of diabetes and hypertension were calculated using generalised linear models with 95% confidence intervals (95% CI).
Due to the COVID-19 pandemic lockdown, we could cover 68% (n = 3800) of the intended sample size. Among the eligible individuals surveyed (n = 4128), we had a response rate of 92%. The mean age of the study participants was 42.8 years, and 51% were women. Current tobacco use was prevalent in 40% (95% CI: 33.7-40.0) of men and 7.9% (95% CI: 6.4-9.8) of women. Current consumption of alcohol was prevalent among 39.1% (95% CI: 36.4-42.0) of men. Nearly 28.5% (95% CI: 26.7-30.4) of the study participants were overweight, and 11.4% (95% CI: 10.1-12.7) were obese. The prevalence of hypertension was 33.9% (95% CI: 32.0-35.8), and that of diabetes was 17.6% (95% CI: 16.1-19.2). Older age, men, and obesity were independently associated with diabetes and hypertension.
The burden of NCD risk factors like tobacco use, and alcohol use were high among men in the state of Tamil Nadu. The prevalence of other risk factors like physical inactivity, raised blood pressure and raised blood glucose were also high in the state. The state should further emphasise measures that reduce the burden of NCD risk factors. Policy-based and health system-based interventions to control NCDs must be a high priority for the state.
Introduction: Viral hepatitis is a crucial public health problem in India. Hepatitis C virus (HCV) elimination is a national priority and a key strategy has been adopted to strengthen the HCV ...diagnostics services to ensure early and accurate diagnosis. Methods: To conduct an economic evaluation of implementing a rapid point-of-care screening test for the identification of HCV among the selected key population under the National Viral Hepatitis Control Programme in Tamil Nadu, South India. Economic evaluation of a point-of-care screening test for HCV diagnosis among the key population attending the primary health care centers. A combination of decision tree and Markov model was developed to estimate cost-effectiveness of point-of-care screening test for HCV diagnosis at the primary health care centers. Total costs, quality-adjusted life years (QALYs) of the intervention and comparator, and incremental cost-effectiveness ratio (ICER) were calculated. The model parameter uncertainties which would influence the cost-effectiveness outcome has been evaluated by one-way sensitivity analysis and probabilistic sensitivity analysis. Results: When compared to the tertiary level diagnostic strategy for HCV, the point-of-care screening for selected key population at primary health care level results in a gain of 57 undiscounted QALYs and 38 discounted QALYs, four undiscounted life years and two discounted life years. The negative ICER of the new strategy indicates that it is less expensive and more effective compared with the current HCV diagnosis strategy. Conclusions: The proposed strategy for HCV diagnosis in the selected key population in Tamil Nadu is dominant and cost-saving compared to the current strategy.
This study employs repeated, large panels of serological surveys to document rapid and substantial waning of SARS-CoV-2 antibodies at the population level and to calculate the extent to which ...infection and vaccination separately contribute to seroprevalence estimates. Four rounds of serological surveys were conducted, spanning two COVID waves (October 2020 and April-May 2021), in Tamil Nadu (population 72 million) state in India. Each round included representative populations in each district of the state, totaling ≥ 20,000 persons per round. State-level seroprevalence was 31.5% in round 1 (October-November 2020), after India's first COVID wave. Seroprevalence fell to 22.9% in round 2 (April 2021), a roughly one-third decline in 6 months, consistent with dramatic waning of SARS-Cov-2 antibodies from natural infection. Seroprevalence rose to 67.1% by round 3 (June-July 2021), with infections from the Delta-variant induced second COVID wave accounting for 74% of the increase. Seroprevalence rose to 93.1% by round 4 (December 2021-January 2022), with vaccinations accounting for 63% of the increase. Antibodies also appear to wane after vaccination. Seroprevalence in urban areas was higher than in rural areas, but the gap shrunk over time (35.7 v. 25.7% in round 1, 89.8% v. 91.4% in round 4) as the epidemic spread even in low-density rural areas.
Tamil Nadu's Chief Minister's Comprehensive Health Insurance Scheme (CMCHIS) aims at reducing inequity by making the health service affordable and available by roping in both the public and private ...providers.
This study aims to find if there exist any inter-district disparity in the distribution of hospitals empaneled and utilization of services under the CMCHIS scheme.
A secondary data analysis was done using the CMCHIS data on hospitals empanelled and number of claims made in the scheme for the year 2018.
The districts were classified into high-developed district (HDD), middle-developed district (MDD), and low-developed district (LDD) based on the Human Development Index. Availability of hospital services was calculated as the number of empanelled hospitals/100,000 families enrolled. Utilization was calculated as the number of claims made by people living in the district per one lakh families enrolled and number of claims made by hospitals under CMCHIS/100,000 enrolled.
The relationship between enrolment ratio, hospital availability, number of claims made, and Human Development Index across districts was examined using the Pearson's Correlation analysis.
Enrolment was highest in the LDDs (22.8%), followed by MDDs (21.9%) and HDDs (18.7%). The number of hospitals per 100,000 families enrolled was the highest in HDDs (8.0) and lowest in LDDs (4.6). The utilization was the highest in HDD followed by MDD and lowest in LDD.
The disparity in the hospitals availability and utilization between districts should be addressed by adopting a targeting approach giving priorities to empanelling hospitals in the less-developed districts.
Background: A screening program for cervical cancer was established in 2011 in Tamil Nadu. Since the inception of the program, coverage, and dropout of screening has not been analyzed. We conducted a ...study to describe the referral mechanism in the cervical cancer screening program implemented in Tamil Nadu, to estimate the level of adherence to the referral process by the beneficiaries, and to identify strengths and weaknesses related to the referral mechanism in the program.
Methods: This descriptive study was conducted during 2015-2016 in the Tiruchirappalli administrative district of Tamil Nadu. All women aged 30 years and above, who were screened in public health facilities, were the participants. Using a structured form, we collected the data maintained in the registers at the district health administration. We estimated the screening coverage, follow-up evaluation, and dropout rates at different stages of the referral mechanism. We used SPSS and Epi Info software for analysis.
Results: Coverage of cervical cancer screening was 4,838(41.6%). We estimated 4,838(41.6%) of screened positives were lost to follow-up for a colposcopy examination. Biopsy samples were obtained from 3425(84%) of those who required a biopsy. Cervical cancer was diagnosed in 159(4.6%) and precancerous lesions in 528(15.4%) women.
Conclusion: More than half of the target population was screened in public health facilities. The dropout rate was less than half of those screened at the colposcopy evaluation level. Major pitfalls of the program were human resource issues at referral centers and poor maintenance of meaningful data.
India has been severely affected by the ongoing COVID-19 pandemic. However, due to shortcomings in disease surveillance, the burden of mortality associated with COVID-19 remains poorly understood. We ...aimed to assess changes in mortality during the pandemic in Chennai, Tamil Nadu, using data on all-cause mortality within the district.
For this observational study, we analysed comprehensive death registrations in Chennai, from Jan 1, 2016, to June 30, 2021. We estimated expected mortality without the effects of the COVID-19 pandemic by fitting models to observed mortality time series during the pre-pandemic period, with stratification by age and sex. Additionally, we considered three periods of interest: the first 4 weeks of India's first lockdown (March 24 to April 20, 2020), the 4-month period including the first wave of the pandemic in Chennai (May 1 to Aug 31, 2020), and the 4-month period including the second wave of the pandemic in Chennai (March 1 to June 30, 2021). We computed the difference between observed and expected mortality from March 1, 2020, to June 30, 2021, and compared pandemic-associated mortality across socioeconomically distinct communities (measured with use of 2011 census of India data) with regression analyses.
Between March 1, 2020, and June 30, 2021, 87 870 deaths were registered in areas of Chennai district represented by the 2011 census, exceeding expected deaths by 25 990 (95% uncertainty interval 25 640–26 360) or 5·18 (5·11–5·25) excess deaths per 1000 people. Stratified by age, excess deaths numbered 21·02 (20·54–21·49) excess deaths per 1000 people for individuals aged 60–69 years, 39·74 (38·73–40·69) for those aged 70–79 years, and 96·90 (93·35–100·16) for those aged 80 years or older. Neighbourhoods with lower socioeconomic status had 0·7% to 2·8% increases in pandemic-associated mortality per 1 SD increase in each measure of community disadvantage, due largely to a disproportionate increase in mortality within these neighbourhoods during the second wave. Conversely, differences in excess mortality across communities were not clearly associated with socioeconomic status measures during the first wave. For each increase by 1 SD in measures of community disadvantage, neighbourhoods had 3·6% to 8·6% lower pandemic-associated mortality during the first 4 weeks of India's country-wide lockdown, before widespread SARS-CoV-2 circulation was underway in Chennai. The greatest reductions in mortality during this early lockdown period were observed among men aged 20–29 years, with 58% (54–62) fewer deaths than expected from pre-pandemic trends.
Mortality in Chennai increased substantially but heterogeneously during the COVID-19 pandemic, with the greatest burden concentrated in disadvantaged communities. Reported COVID-19 deaths greatly underestimated pandemic-associated mortality.
National Institute of General Medical Sciences, Bill & Melinda Gates Foundation, National Science Foundation.
For the Hindi translation of the abstract see Supplementary Materials section.
ObjectiveTo describe the characteristics of contacts of patients with COVID-19 case in terms of time, place and person, to calculate the secondary attack rate (SAR) and factors associated with ...COVID-19 infection among contacts.DesignA retrospective cohort studySetting and participantsContacts of cases identified by the health department from 14 March 2020to 30 May 2020, in 9 of 38 administrative districts of Tamil Nadu. Significant proportion of cases attended a religious congregation.Outcome measureAttack rate among the contacts and factors associated with COVID-19 positivity.ResultsWe listed 15 702 contacts of 931 primary cases. Of the contacts, 89% (n: 14 002) were tested for COVID-19. The overall SAR was 4% (599/14 002), with higher among the household contacts (13%) than the community contacts (1%). SAR among the contacts of primary cases with congregation exposure were 5 times higher than the contacts of non-congregation primary cases (10% vs 2%). Being a household contact of a primary case with congregation exposure had a fourfold increased risk of getting COVID-19 (relative risk (RR): 16.4; 95% CI: 13 to 20) than contact of primary case without congregation exposure. Among the symptomatic primary cases, household contacts of congregation primaries had higher RR than household contacts of other cases ((RR: 25.3; 95% CI: 10.2 to 63) vs (RR: 14.6; 95% CI: 5.7 to 37.7)). Among asymptomatic primary case, RR was increased among household contacts (RR: 16.5; 95% CI: 13.2 to 20.7) of congregation primaries compared with others.ConclusionOur study showed an increase in disease transmission among household contacts than community contacts. Also, symptomatic primary cases and primary cases with exposure to the congregation had more secondary cases than others.
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