Restoration of dendritic cell homeostasis and Type I/Type III interferon levels in convalescent COVID-19 individuals.

BACKGROUND: Plasmacytoid and myeloid dendritic cells play a vital role in the protection against viral infections. In COVID-19, there is an impairment of dendritic cell (DC) function and interferon secretion which has been correlated with disease severity. RESULTS: In this study, we described the frequency of DC subsets and the plasma levels of Type I (IFNα, IFNß) and Type III Interferons (IFNλ1), IFNλ2) and IFNλ3) in seven groups of COVID-19 individuals, classified based on days since RT-PCR confirmation of SARS-CoV2 infection. Our data shows that the frequencies of pDC and mDC increase from Days 15-30 to Days 61-90 and plateau thereafter. Similarly, the levels of IFNα, IFNß, IFNλ1, IFNλ2 and IFNλ3 increase from Days 15-30 to Days 61-90 and plateau thereafter. COVID-19 patients with severe disease exhibit diminished frequencies of pDC and mDC and decreased levels of IFNα, IFNß, IFNλ1, IFNλ2 and IFNλ3. Finally, the percentages of DC subsets positively correlated with the levels of Type I and Type III IFNs. CONCLUSION: Thus, our study provides evidence of restoration of homeostatic levels in DC subset frequencies and circulating levels of Type I and Type III IFNs in convalescent COVID-19 individuals.

Population-Based Serosurvey for Severe Acute Respiratory Syndrome Coronavirus 2 Transmission, Chennai, India.

We conducted a cross-sectional survey to estimate the seroprevalence of IgG against severe acute respiratory syndrome coronavirus 2 in Chennai, India. Among 12,405 serum samples tested, weighted seroprevalence was 18.4% (95% CI 14.8%-22.6%). These findings indicate most of the population of Chennai is still susceptible to this virus.

Estimation of tuberculosis incidence at subnational level using three methods to monitor progress towards ending TB in India, 2015-2020.

OBJECTIVES: We verified subnational (state/union territory (UT)/district) claims of achievements in reducing tuberculosis (TB) incidence in 2020 compared with 2015, in India. DESIGN: A community-based survey, analysis of programme data and anti-TB drug sales and utilisation data. SETTING: National TB Elimination Program and private TB treatment settings in 73 districts that had filed a claim to the Central TB Division of India for progress towards TB-free status. PARTICIPANTS: Each district was divided into survey units (SU) and one village/ward was randomly selected from each SU. All household members in the selected village were interviewed. Sputum from participants with a history of anti-TB therapy (ATT), those currently experiencing chest symptoms or on ATT were tested using Xpert/Rif/TrueNat. The survey continued until 30 Mycobacterium tuberculosis cases were identified in a district. OUTCOME MEASURES: We calculated a direct estimate of TB incidence based on incident cases identified in the survey. We calculated an under-reporting factor by matching these cases within the TB notification system. The TB notification adjusted for this factor was the estimate by the indirect method. We also calculated TB incidence from drug sale data in the private sector and drug utilisation data in the public sector. We compared the three estimates of TB incidence in 2020 with TB incidence in 2015. RESULTS: The estimated direct incidence ranged from 19 (Purba Medinipur, West Bengal) to 1457 (Jaintia Hills, Meghalaya) per 100 000 population. Indirect estimates of incidence ranged between 19 (Diu, Dadra and Nagar Haveli) and 788 (Dumka, Jharkhand) per 100 000 population. The incidence using drug sale data ranged from 19 per 100 000 population in Diu, Dadra and Nagar Haveli to 651 per 100 000 population in Centenary, Maharashtra. CONCLUSION: TB incidence in 1 state, 2 UTs and 35 districts had declined by at least 20% since 2015. Two districts in India were declared TB free in 2020.

COVID-19 testing, timeliness and positivity from ICMR's laboratory surveillance network in India: Profile of 176 million individuals tested and 188 million tests, March 2020 to January 2021.

BACKGROUND: The Indian Council of Medical Research set up a pan-national laboratory network to diagnose and monitor Coronavirus disease 2019 (COVID-19). Based on these data, we describe the epidemiology of the pandemic at national and sub-national levels and the performance of the laboratory network. METHODS: We included surveillance data for individuals tested and the number of tests from March 2020 to January 2021. We calculated the incidence of COVID-19 by age, gender and state and tests per 100,000 population, the proportion of symptomatic individuals among those tested, the proportion of repeat tests and test positivity. We computed median (Interquartile range-IQR) days needed for selected surveillance activities to describe timeliness. RESULTS: The analysis included 176 million individuals and 188 million tests. The overall incidence of COVID-19 was 0.8%, and 12,584 persons per 100,000 population were tested. 6.1% of individuals tested returned a positive result. Ten of the 37 Indian States and Union Territories accounted for about 75.6% of the total cases. Daily testing scaled up from 40,000 initially to nearly one million in March 2021. The median duration between symptom onset and sample collection was two (IQR = 0,3) days, median duration between both sample collection and testing and between testing and data entry were less than or equal to one day. Missing or invalid entries ranged from 0.01% for age to 0.7% for test outcome. CONCLUSION: The laboratory network set-up by ICMR was scaled up massively over a short period, which enabled testing a large section of the population. Although all states and territories were affected, most cases were concentrated in a few large states. Timeliness between the various surveillance activities was acceptable, indicating good responsiveness of the surveillance system.

Immunity against diphtheria among children aged 5-17 years in India, 2017-18: a cross-sectional, population-based serosurvey.

BACKGROUND: Diphtheria is re-emerging as a public health problem in several Indian states. Most diphtheria cases are among children older than 5 years. In this study, we aimed to estimate age-specific immunity against diphtheria in children aged 5-17 years in India. METHODS: We used residual serum samples from a cross-sectional, population-based serosurvey for dengue infection done between June 19, 2017, and April 12, 2018, to estimate the age-group-specific seroprevalence of antibodies to diphtheria in children aged 5-17 years in India. 8309 serum samples collected from 240 clusters (122 urban and 118 rural) in 60 selected districts of 15 Indian states spread across all five geographical regions (north, northeast, east, west, and south) of India were tested for the presence of IgG antibodies against diphtheria toxoid using an ELISA. We considered children with antibody concentrations of 0·1 IU/mL or greater as immune, those with levels less than 0·01 IU/mL as non-immune (and hence susceptible to diphtheria), and those with levels in the range of 0·01 to less than 0·1 IU/mL as partially immune. We calculated the weighted proportion of children who were immune, partially immune, and non-immune, with 95% CIs, for each geographical region by age group, sex, and area of residence (urban vs rural). FINDINGS: 29·7% (95% CI 26·3-33·4) of 8309 children aged 5-17 years were immune to diphtheria, 10·5% (8·6-12·8) were non-immune, and 59·8% (56·3-63·1) were partially immune. The proportion of children aged 5-17 years who were non-immune to diphtheria ranged from 6·0% (4·2-8·3) in the south to 16·8% (11·2-24·4) in the northeast. Overall, 9·9% (7·7-12·5) of children residing in rural areas and 13·1% (10·2-16·6) residing in urban areas were non-immune to diphtheria. A higher proportion of girls than boys were non-immune to diphtheria in the northern (17·7% [12·6-24·2] vs 7·1% [4·1-11·9]; p=0·0007) and northeastern regions (20·0% [12·9-29·8] vs 12·9% [8·6-19·0]; p=0·0035). INTERPRETATION: The findings of our serosurvey indicate that a substantial proportion of children aged 5-17 years were non-immune or partially immune to diphtheria. Transmission of diphtheria is likely to continue in India until the immunity gap is bridged through adequate coverage of primary and booster doses of diphtheria vaccine. FUNDING: Indian Council of Medical Research.

Seroprevalence of chikungunya virus infection in India, 2017: a cross-sectional population-based serosurvey.

BACKGROUND: Since its re-emergence in 2005, chikungunya virus (CHIKV) transmission has been documented in most Indian states. Information is scarce regarding the seroprevalence of CHIKV in India. We aimed to estimate the age-specific seroprevalence, force of infection (FOI), and proportion of the population susceptible to CHIKV infection. METHODS: We did a nationally representative, cross-sectional serosurvey, in which we randomly selected individuals in three age groups (5-8, 9-17, and 18-45 years), covering 240 clusters from 60 selected districts of 15 Indian states spread across all five geographical regions of India (north, northeast, east, south, and west). Age was the only inclusion criterion. We tested serum samples for IgG antibodies against CHIKV. We estimated the weighted age-group-specific seroprevalence of CHIKV infection for each region using the design weight (ie, the inverse of the overall probability of selection of state, district, village or ward, census enumeration block, and individual), adjusting for non-response. We constructed catalytic models to estimate the FOI and the proportion of the population susceptible to CHIKV in each region. FINDINGS: From June 19, 2017, to April 12, 2018, we enumerated 117 675 individuals, of whom 77 640 were in the age group of 5-45 years. Of 17 930 randomly selected individuals, 12 300 individuals participated and their samples were used for estimation of CHIKV seroprevalence. The overall prevalence of IgG antibodies against CHIKV in the study population was 18·1% (95% CI 14·2-22·6). The overall seroprevalence was 9·2% (5·4-15·1) among individuals aged 5-8 years, 14·0% (8·8-21·4) among individuals aged 9-17 years, and 21·6% (15·9-28·5) among individuals aged 18-45 years. The seroprevalence was lowest in the northeast region (0·3% [95% CI 0·1-0·8]) and highest in the southern region (43·1% [34·3-52·3]). There was a significant difference in seroprevalence between rural (11·5% [8·8-15·0]) and urban (40·2% [31·7-49·3]) areas (p<0·0001). The seroprevalence did not differ by sex (male 18·8% [95% CI 15·2-23·0] vs female 17·6% [13·2-23·1]; p=0·50). Heterogeneous FOI models suggested that the FOI was higher during 2003-07 in the southern and western region and 2013-17 in the northern region. FOI was lowest in the eastern and northeastern regions. The estimated proportion of the population susceptible to CHIKV in 2017 was lowest in the southern region (56·3%) and highest in the northeastern region (98·0%). INTERPRETATION: CHIKV transmission was higher in the southern, western, and northern regions of India than in the eastern and northeastern regions. However, a higher proportion of the population susceptible to CHIKV in the eastern and northeastern regions suggests a susceptibility of these regions to outbreaks in the future. Our survey findings will be useful in identifying appropriate target age groups and sites for setting up surveillance and for future CHIKV vaccine trials. FUNDING: Indian Council of Medical Research.