Seroprevalence of anti SARS-CoV-2 IgG antibodies among adults in Jammu district, India: A community-based study

Background & objectives: Serology testing is essential for immunological surveillance in the population. This serosurvey was conducted to ascertain the cumulative population immunity against SARS-CoV-2 among adults in Jammu district and to understand the association of seropositivity with sociodemographic and clinical correlates. Methods: On September 30 and October 1, 2020, a household survey was done in 20 villages/wards chosen from 10 health blocks in district Jammu, India. Demographic, clinical and exposure information was collected from 2000 adults. Serum samples were screened for IgG antibodies using COVID Kavach MERILISA kit. Tests of association were used to identify risk factors associated with IgG positivity. Crude odds ratio with 95 per cent confidence intervals (CIs) was calculated during univariate analysis followed by logistic regression. Results: Overall adjusted seroprevalence for SARS-CoV-2 was 8.8 per cent (95% CI: 8.78-8.82); it varied from 4.1 per cent in Chauki choura to 16.7 per cent Pallanwalla across 10 blocks in the district. Seropositivity was observed to be comparatively higher in 41-50 and 61-70 yr age groups, among males and in rural areas. Fever, sore throat, cough, dyspnoea, myalgias, anosmia, ageusia, fatigue, seizures, history of exposure, medical consultation, hospitalization and missing work showed significant association with seropositivity on univariate analysis. On logistic regression, only sore throat, myalgia and missing work showed significant adjusted odds of IgG positivity. Extrapolation to adult population suggested that exposure to SARS-CoV-2 was 14.4 times higher than reported cases, translating into Infection fatality rate of 0.08 per cent. Interpretation & conclusions: Since a major part of population was immunologically naive, all efforts to contain COVID-19 need to be vigorously followed while these baseline results provide an important yardstick to monitor the trends of COVID-19 and guide locally appropriate control strategies in the region

VacPred: Sequence-based prediction of plant vacuole proteins using machine-learning techniques

Subcellular localization prediction of the proteome is one of major goals of large-scale genome or proteomesequencing projects to define the gene functions that could be possible with the help of computationalmodeling techniques. Previously, different methods have been developed for this purpose using multi-labelclassification system and achieved a high level of accuracy. However, during the validation of our blind datasetof plant vacuole proteins, we observed that they have poor performance with accuracy value range from*1.3% to 48.5%. The results showed that the previously developed methods are not very accurate for the plantvacuole protein prediction and thus emphasize the need to develop a more accurate and reliable algorithm. Inthis study, we have developed various compositions as well as PSSM-based models and achieved a highaccuracy than previously developed methods. We have shown that our best model achieved *63% accuracyon blind dataset, which is far better than currently available tools. Furthermore, we have implemented our bestmodels in the form of GUI-based free software called ‘VacPred’ which is compatible with both Linux andWindow platform. This software is freely available for download at www.deepaklab.com/vacpred.

Effect of blood culture reports on antibiotics use by physicians in septic patients of intensive care unit.

Background: To limit the emergence and spread of antibiotic resistance, adjustments in the antibiotic regimen should be done according to the results of blood cultures as soon as they are available. This study was planned to determine the effect of blood culture and sensitivity tests on the antibiotics use in ICU patients of a tertiary care teaching hospital. Methods: This chart review retrospective study was carried out in ICU patients of a tertiary care teaching hospital. The data was collected from patients’ medical record file in a case record form which included patient’s demographic details, provisional diagnosis/or diagnosis, blood culture reports, and antimicrobial treatment (both the empiric treatment as well as the change made after the release of the blood culture results). The effect of blood culture results on antibiotic treatment was analysed. Results: A total of 245 patients were subjected to blood culture during the period of 6 months with an average of 40.8/month. 86 (35.1%) patients showed positive blood culture results, while 159 (64.9%) patients showed negative blood culture results. 55 patients discharged after the release of blood culture and sensitivity results. Antibiotic regimens were modified or changed in 26 (47.27%), and in 29 (52.72%) there was no modification. Most commonly used antibiotic after blood culture reports were meropenem (34.62%) followed by 11.54% of each teicoplanin, piperacillin+ tazobactum and tigecyclin. Conclusions: Blood culture reports help in management of critically ill patients if bacteria are resistant to previously used antibiotic, but do not help in narrowing the therapy in ICU patients.

An observational comparative study of cost between branded medicines and generic medicines.

Background: Same drug can be sold for different prices under different brand names due to various reasons. Branded medicine is the original product that has been developed by a pharmaceutical company and generic medicine is a copy of the original branded product, marketed after the expiry date of the patent and hence supposed to be of low cost as compared to their branded versions. The objective was to compare the costs of various branded and generic medicine and to ascertain the rationality of emphasizing generic versus branded prescription. Methods: Prices of 50 commonly used branded and generic medicines available as both branded and generic forms and in same concentration, dosage form and combination were selected and the percentage difference in the mean cost of generic and branded medicines was calculated. Results: The mean cost of 26 generic medicines out of the selected 50 medicines was higher than their branded versions. Mean cost of 20 branded medicines was higher than generic ones, and cost of 4 medicines was approximately same. Percentage difference in the mean costs of branded and generic medicines varied from <10% to >70%. Conclusions: Most of the drugs available in the market have brand names whether they are branded or generic medicines. Hence, doctor should write a cheapest known brand with the name of the generic salt in bracket so that the patient can buy another if that brand is not available. Furthermore, the Drug Controller of India should release a website where every doctor should be able to fi nd the cheapest and approved drugs in the market.