Abstract
Monocytes are thought to play an important role in host defence and pathogenesis of COVID-19. However, a comprehensive examination of monocyte numbers and function has not been performed ...longitudinally in acute and convalescent COVID-19. We examined the absolute counts of monocytes, the frequency of monocyte subsets, the plasma levels of monocyte activation markers using flowcytometry and ELISA in seven groups of COVID-19 individuals, classified based on days since RT-PCR confirmation of SARS-CoV2 infection. Our data shows that the absolute counts of total monocytes and the frequencies of intermediate and non-classical monocytes increases from Days 15–30 to Days 61–90 and plateau thereafter. In contrast, the frequency of classical monocytes decreases from Days 15–30 till Days 121–150. The plasma levels of sCD14, CRP, sCD163 and sTissue Factor (sTF)—all decrease from Days 15–30 till Days 151–180. COVID-19 patients with severe disease exhibit higher levels of monocyte counts and higher frequencies of classical monocytes and lower frequencies of intermediate and non-classical monocytes and elevated plasma levels of sCD14, CRP, sCD163 and sTF in comparison with mild disease. Thus, our study provides evidence of dynamic alterations in monocyte counts, subset frequencies and activation status in acute and convalescent COVID-19 individuals.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Structural and individual level factors in prisons create challenges towards detection and management of HIV/tuberculosis. WHO and India's HIV/tuberculosis control programs recommend intensified case ...finding in prisons. Low HIV and tuberculosis detection rates suggest poor implementation of existing surveillance strategies within the prison healthcare system in Mizoram's capital city of Aizawl. We explored the operational feasibility of implementing the intensified case finding strategy in Aizawl central prison. We implemented the intensified screening through entry screening of new inmates, mass screening of resident inmates and exit screening at release. We set up digital chest radiography, sputum smear microscopy and HIV testing facilities within the prison and referral to external facility for Cartridge Based Nucleic Acid Amplification Test (CBNAAT). We screened 738 inmates (Male: 626; Female: 112). Of 53% inmates having presumptive tuberculosis symptoms, 37% underwent sputum microscopy. We detected 14 new tuberculosis cases; overall tuberculosis positivity 1.9%. We tested 65% of 657 inmates for HIV, of which 41 new cases were detected; overall HIV positivity 16.5%. Three male inmates had HIV-tuberculosis co-infection. It is feasible to implement intensified case detection for tuberculosis/HIV in the prison with inter-departmental coordination, albeit with certain challenges.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•We reviewed and synthesized the seroprevalence of SARS-CoV-2 from 53 studies in India.•Overall pooled seroprevalence was 20.7% and 69.2% in the first and second wave.•In both waves, seroprevalence ...was higher in urban than in rural areas.•Studies showed inadequacy in reporting methodology.•We recommend designing and reporting studies using standard protocols.
Introduction: India experienced 2 waves of COVID-19 pandemic caused by SARS-CoV-2 and reported the second highest caseload globally. Seroepidemiologic studies were done to track the course of the pandemic. We systematically reviewed and synthesized the seroprevalence of SARS-CoV-2 in the Indian population.
Methods: We included studies reporting seroprevalence of IgG antibodies against SARS-CoV-2 from March 1, 2020 to August 11, 2021 and excluded studies done only among patients with COVID-19 and vaccinated individuals. We searched published databases, preprint servers, and government documents using a combination of keywords and medical subheading (MeSH) terms of “Seroprevalence AND SARS-CoV-2 AND India”. We assessed risk of bias using the Newcastle-Ottawa scale, the appraisal tool for cross-sectional studies (AXIS), the Joanna Briggs Institute (JBI) critical appraisal tool, and WHO's statement on the Reporting of Seroepidemiological Studies for SARS-CoV-2 (ROSES-S). We calculated pooled seroprevalence along with 95% Confidence Intervals (CI) during the first (March 2020 to February 2021) and second wave (March to August 2021). We also estimated seroprevalence by selected demographic characteristics.
Results: We identified 3821 studies and included 53 studies with 905379 participants after excluding duplicates, screening of titles and abstracts and full-text screening. Of the 53, 20 studies were of good quality. Some of the reviewed studies did not report adequate information on study methods (sampling = 24% (13/53); laboratory = 83% 44/53). Studies of ‘poor’ quality had more than one of the following issues: unjustified sample size, nonrepresentative sample, nonclassification of nonrespondents, results unadjusted for demographics and methods insufficiently explained to enable replication. Overall pooled seroprevalence was 20.7% in the first (95% CI = 16.1 to 25.3) and 69.2% (95% CI = 64.5 to 73.8) in the second wave. Seroprevalence did not differ by age in first wave, whereas in the second, it increased with age. Seroprevalence was slightly higher among women in the second wave. In both the waves, the estimate was higher in urban than in rural areas.
Conclusion: Seroprevalence increased by 3-fold between the 2 waves of the pandemic in India. Our review highlights the need for designing and reporting studies using standard protocols.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Since the recent introduction of several viable vaccines for SARS-CoV-2, vaccination uptake has become the key factor that will determine our success in containing the COVID-19 pandemic. We argue ...that game theory and social network models should be used to guide decisions pertaining to vaccination programmes for the best possible results. In the months following the introduction of vaccines, their availability and the human resources needed to run the vaccination programmes have been scarce in many countries. Vaccine hesitancy is also being encountered from some sections of the general public. We emphasize that decision-making under uncertainty and imperfect information, and with only conditionally optimal outcomes, is a unique forte of established game-theoretic modelling. Therefore, we can use this approach to obtain the best framework for modelling and simulating vaccination prioritization and uptake that will be readily available to inform important policy decisions for the optimal control of the COVID-19 pandemic.
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.
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DOBA, IZUM, KILJ, NUK, ODKLJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Wastewater-based epidemiology (WBE) has emerged as an effective environmental surveillance tool for predicting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease outbreaks in ...high-income countries (HICs) with centralized sewage infrastructure. However, few studies have applied WBE alongside epidemic disease modelling to estimate the prevalence of SARS-CoV-2 in low-resource settings. This study aimed to explore the feasibility of collecting untreated wastewater samples from rural and urban catchment areas of Nagpur district, to detect and quantify SARS-CoV-2 using real-time qPCR, to compare geographic differences in viral loads, and to integrate the wastewater data into a modified Susceptible-Exposed-Infectious-Confirmed Positives-Recovered (SEIPR) model. Of the 983 wastewater samples analyzed for SARS-CoV-2 RNA, we detected significantly higher sample positivity rates, 43.7% (95% confidence interval (CI) 40.1, 47.4) and 30.4% (95% CI 24.66, 36.66), and higher viral loads for the urban compared with rural samples, respectively. The Basic reproductive number, R0, positively correlated with population density and negatively correlated with humidity, a proxy for rainfall and dilution of waste in the sewers. The SEIPR model estimated the rate of unreported coronavirus disease 2019 (COVID-19) cases at the start of the wave as 13.97 95% CI (10.17, 17.0) times that of confirmed cases, representing a material difference in cases and healthcare resource burden. Wastewater surveillance might prove to be a more reliable way to prepare for surges in COVID-19 cases during future waves for authorities.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
India has experienced the second largest outbreak of COVID-19 globally, yet there is a paucity of studies analysing contact tracing data in the region which can optimise public health interventions ...(PHI's).
We analysed contact tracing data from Karnataka, India between 9 March and 21 July 2020. We estimated metrics of transmission including the reproduction number (R), overdispersion (k), secondary attack rate (SAR), and serial interval. R and k were jointly estimated using a Bayesian Markov Chain Monte Carlo approach. We studied determinants of risk of further transmission and risk of being symptomatic using Poisson regression models.
Up to 21 July 2020, we found 111 index cases that crossed the super-spreading threshold of ≥8 secondary cases. Among 956 confirmed traced cases, 8.7% of index cases had 14.4% of contacts but caused 80% of all secondary cases. Among 16715 contacts, overall SAR was 3.6% 95% CI, 3.4-3.9 and symptomatic cases were more infectious than asymptomatic cases (SAR 7.7% vs 2.0%; aRR 3.63 3.04-4.34). As compared to infectors aged 19-44 years, children were less infectious (aRR 0.21 0.07-0.66 for 0-5 years and 0.47 0.32-0.68 for 6-18 years). Infectors who were confirmed ≥4 days after symptom onset were associated with higher infectiousness (aRR 3.01 2.11-4.31). As compared to asymptomatic cases, symptomatic cases were 8.16 3.29-20.24 times more likely to cause symptomatic infection in their secondary cases. Serial interval had a mean of 5.4 4.4-6.4 days, and case fatality rate was 2.5% 2.4-2.7 which increased with age.
We found significant heterogeneity in the individual-level transmissibility of SARS-CoV-2 which could not be explained by the degree of heterogeneity in the underlying number of contacts. To strengthen contact tracing in over-dispersed outbreaks, testing and tracing delays should be minimised and retrospective contact tracing should be implemented. Targeted measures to reduce potential superspreading events should be implemented. Interventions aimed at children might have a relatively small impact on reducing transmission owing to their low symptomaticity and infectivity. We propose that symptomatic cases could cause a snowballing effect on clinical severity and infectiousness across transmission generations; further studies are needed to confirm this finding.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
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.
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.
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.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Risk factors for the development of severe COVID-19 disease and death have been widely reported across several studies. Knowledge about the determinants of severe disease and mortality in the Indian ...context can guide early clinical management.
We conducted a hospital-based case control study across nine sites in India to identify the determinants of severe and critical COVID-19 disease.
We identified age above 60 years, duration before admission >5 days, chronic kidney disease, leucocytosis, prothrombin time > 14 sec, serum ferritin >250 ng/mL, d-dimer >0.5 ng/mL, pro-calcitonin >0.15 μg/L, fibrin degradation products >5 μg/mL, C-reactive protein >5 mg/L, lactate dehydrogenase >150 U/L, interleukin-6 >25 pg/mL, NLR ≥3, and deranged liver function, renal function and serum electrolytes as significant factors associated with severe COVID-19 disease.
We have identified a set of parameters that can help in characterising severe COVID-19 cases in India. These parameters are part of routinely available investigations within Indian hospital settings, both public and private. Study findings have the potential to inform clinical management protocols and identify patients at high risk of severe outcomes at an early stage.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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