BACKGROUND: With the increased availability of licensed vaccines for respiratory viruses such as severe acute respiratory syndrome coronavirus 2, respiratory syncytial virus (RSV), and influenza virus, a better understanding of the viral aetiology of severe acute respiratory infections (SARI) among children could help in optimising the use of these vaccines. We conducted a study among children aged <5 years hospitalised with SARI at a tertiary care children's hospital in north India and tested for common respiratory pathogens. METHODS: We randomly enrolled eligible SARI cases aged <5 years from August 2013 to July 2015. SARI cases were defined as either <7-day history of fever with cough or in children aged eight days to three months, a physician diagnosis of acute lower respiratory infection requiring hospitalisation. We also enrolled an age-group matched control without any acute illness in a 2:1 ratio from the outpatient clinic within 24 hours of case enrolment. Nasopharyngeal and/or oropharyngeal swabs were collected and tested using TaqMan Array Cards, a real-time reverse transcription polymerase chain reaction-based multi-pathogen testing platform for selected respiratory viruses among the enrolled cases and controls. We compared the prevalence of each pathogen among cases and controls using the χ(2) (χ(2)) or Fisher exact test (P < 0.05). We used logistic regression to estimate adjusted odds ratios (aORs) which were then used to calculate aetiologic fractions (EFs). RESULTS: We enrolled 840 cases and 419 outpatient controls. Almost half of the individuals in the whole sample were aged <6 months (n = 521, 41.4%). Females made up 33.7% of cases and 37.2% of controls. Viral detections were more common among cases (69%, 95% confidence interval (CI) = 66, 73) compared to controls (33%; 95% CI = 29, 38) (P < 0.01). RSV (n = 257, 31%; 95% CI = 28, 34%) was the most common virus detected among cases. Influenza A was detected among 24 (3%; 95% CI = 2, 4%), and influenza B among 5 (1%; 95% CI = 0, 1%) cases. The association between the virus and SARI was strongest for RSV (aOR = 23; 95% CI = 12, 47; EF = 96%). Antivirals were administered to 1% of SARI cases while 78% received antibiotics. CONCLUSIONS: Using a multi-pathogen molecular detection method, we detected respiratory viruses among more than two-thirds of children aged <5 years admitted with SARI in the Delhi tertiary care children's hospital. The guidelines for preventing and managing SARI cases among children could be optimised further with the improved availability of antivirals and vaccines.

BACKGROUND: We present post-vaccination nasal shedding findings from the phase IV, community-based, triple-blinded RCT conducted to assess efficacy of trivalent LAIV and inactivated influenza vaccines in rural north India. METHODS: Children aged 2-10 years received LAIV or intranasal placebo across 2015 and 2016, as per initial allocation. On days 2 and 4 post-vaccination, trained study nurses collected nasal swabs from randomly selected subset of trial participants based on operational feasibility, accounting for 10.0% and 11.4% of enrolled participants in 2015 and 2016, respectively. Swabs were collected in viral transport medium and transported under cold chain to laboratory for testing by reverse transcriptase real-time polymerase chain reaction. RESULTS: In year 1, on day 2 post-vaccination, 71.2% (74/104) of LAIV recipients shed at least one of vaccine virus strains compared to 42.3% (44/104) on day 4. During year 1, on day 2 post-vaccination, LAIV-A(H1N1)pdm09 was detected in nasal swabs of 12% LAIV recipients, LAIV-A(H3N2) in 41%, and LAIV-B in 59%. In year 2, virus shedding was substantially lower; 29.6% (32/108) of LAIV recipients shed one of the vaccine virus strains on day 2 compared to 21.3% on day 4 (23/108). CONCLUSION: At day 2 post-vaccination in year 1, two-thirds of LAIV recipients were shedding vaccine viruses. Shedding of vaccine viruses varied between strains and was lower in year 2. More research is needed to determine the reason for lower virus shedding and vaccine efficacy for LAIV-A(H1N1)pdm09.

BACKGROUND: Influenza is a cause of febrile acute respiratory infection (FARI) in India; however, few influenza vaccine trials have been conducted in India. We assessed absolute and relative efficacy of live attenuated influenza vaccine (LAIV) and inactivated influenza vaccine (IIV) among children aged 2 to 10 years in rural India through a randomized, triple-blind, placebo-controlled trial conducted over 2 years. METHODS AND FINDINGS: In June 2015, children were randomly allocated to LAIV, IIV, intranasal placebo, or inactivated polio vaccine (IPV) in a 2:2:1:1 ratio. In June 2016, vaccination was repeated per original allocation. Overall, 3,041 children received LAIV (n = 1,015), IIV (n = 1,010), nasal placebo (n = 507), or IPV (n = 509). Mean age of children was 6.5 years with 20% aged 9 to 10 years. Through weekly home visits, nasal and throat swabs were collected from children with FARI and tested for influenza virus by polymerase chain reaction. The primary outcome was laboratory-confirmed influenza-associated FARI; vaccine efficacy (VE) was calculated using modified intention-to-treat (mITT) analysis by Cox proportional hazards model (PH) for each year. In Year 1, VE was 40.0% (95% confidence interval (CI) 25.2 to 51.9) for LAIV and 59.0% (95% CI 47.8 to 67.9) for IIV compared with controls; relative efficacy of LAIV compared with IIV was -46.2% (95% CI -88.9 to -13.1). In Year 2, VE was 51.9% (95% CI 42.0 to 60.1) for LAIV and 49.9% (95% CI 39.2 to 58.7) for IIV; relative efficacy of LAIV compared with IIV was 4.2% (95% CI -19.9 to 23.5). No serious adverse vaccine-attributable events were reported. Study limitations include differing dosage requirements for children between nasal and injectable vaccines (single dose of LAIV versus 2 doses of IIV) in Year 1 and the fact that immunogenicity studies were not conducted. CONCLUSIONS: In this study, we found that LAIV and IIV vaccines were safe and moderately efficacious against influenza virus infection among Indian children. TRIAL REGISTRATION: Clinical Trials Registry of India CTRI/2015/06/005902.

BACKGROUND: There are limited data on incidence, risk factors and etiology of acute lower respiratory tract infection (LRTI) among older adults in low- and middle-income countries. METHODS: We established a cohort of community dwelling older adults ≥60 years and conducted weekly follow-up for acute respiratory infections (ARI) during 2015-2017. Nurses assessed ARI cases for LRTI, collecting combined nasal/throat swabs from all LRTI cases and an equal number of age- and sex-matched asymptomatic neighbourhood controls. Swabs were tested for influenza viruses, respiratory syncytial virus (RSV), human metapneumovirus (hMPV), and parainfluenza viruses (PIV) using polymerase chain reaction. LRTI and virus-specific LRTI incidence was calculated per 1000 person-years. We estimated adjusted incidence rate ratios (IRR) for risk factors using Poisson regression and calculated etiologic fractions (EF) using adjusted odds ratios for detection of viral pathogens in LRTI cases vs controls. RESULTS: We followed 1403 older adults for 2441 person-years. LRTI and LRTI-associated hospitalization incidences were 248.3 (95% confidence interval (CI) = 229.3-268.8) and 12.7 (95% CI = 8.9-18.1) per 1000 person-years. Persons with pre-existing chronic bronchitis as compared to those without (incidence rate ratio (IRR) = 4.7, 95% CI = 3.9-5.6); aged 65-74 years (IRR = 1.6, 95% CI = 1.3-2.0) and ≥75 years (IRR = 1.8, 95% CI = 1.4-2.4) as compared to 60-64 years; and persons in poorest wealth quintile (IRR = 1.4, 95% CI = 1.1-1.8); as compared to those in wealthiest quintile were at higher risk for LRTI. Virus was detected in 10.1% of LRTI cases, most commonly influenza (3.8%) and RSV (3.0%). EF for RSV and influenza virus was 83.9% and 83.6%, respectively. CONCLUSION: In this rural cohort of older adults, the incidence of LRTI was substantial. Chronic bronchitis was an important risk factor; influenza virus and RSV were major viral pathogens.

Background: Influenza causes substantial morbidity and mortality worldwide, however, reliable burden estimates from developing countries are limited, including India. We aimed to quantify influenza-associated mortality for India utilizing 2010-2013 nationally representative data sources for influenza virus circulation and deaths. Methods: Virological data were obtained from the influenza surveillance network of 10 laboratories led by National Institute of Virology, Pune covering eight states from 2010-2013. Death data were obtained from the nationally representative Sample Registration System for the same time period. Generalized linear regression with negative binomial distribution was used to model weekly respiratory and circulatory deaths by age group and proportion of specimens positive for influenza by subtype; excess deaths above the seasonal baseline were taken as an estimate of influenza-associated mortality counts and rates. Annual excess death rates and the 2011 India Census data were used to estimate national influenza-associated deaths. Results: Estimated annual influenza-associated respiratory mortality rates were highest for those >/=65 years (51.1, 95% confidence interval (CI) = 9.2-93.0 deaths/100 000 population) followed by those <5 years (9.8, 95% CI = 0-21.8/100 000). Influenza-associated circulatory death rates were also higher among those >/=65 years (71.8, 95% CI = 7.9-135.8/100 000) as compared to those aged <65 years (1.9, 95% CI = 0-4.6/100 000). Across all age groups, a mean of 127 092 (95% CI = 64 046-190,139) annual influenza-associated respiratory and circulatory deaths may occur in India. Conclusions: Estimated influenza-associated mortality in India was high among children <5 years and adults >/=65 years. These estimates may inform strategies for influenza prevention and control in India, such as possible vaccine introduction.

Background: In India, community-based acute lower respiratory infections (ALRI) burden studies are limited, hampering development of prevention and control strategies. Methods: We surveyed children <10 years old at home weekly from August 2012-August 2014, for cough, sore throat, rhinorrhoea, ear discharge, and shortness of breath. Symptomatic children were assessed for ALRI using World Health Organization definitions. Nasal and throat swabs were obtained from all ALRI cases and asymptomatic controls and tested using polymerase chain reaction for respiratory syncytial virus (RSV), human metapneumovirus (hMPV), parainfluenza viruses (PIV), and influenza viruses (IV). We estimated adjusted odds ratios (aOR) using logistic regression to calculate etiologic fractions (EF). We multiplied agent-specific ALRI incidence rates by EF to calculate the adjusted incidence as episodes per child-year. Results: ALRI incidence was 0.19 (95% confidence interval (CI) = 0.18-0.20) episode per child-year. Association between virus and ALRI was strongest for RSV (aOR = 15.9; 95% CI = 7.3-34.7; EF = 94%) and least for IV (aOR = 4.6; 95% CI = 2.0-10.6; EF = 78%). Adjusted agent-specific ALRI incidences were RSV (0.03, 95% CI = 0.02-0.03), hMPV (0.02, 95% CI = 0.01-0.02), PIV (0.02, 95% CI = 0.01-0.02), and IV (0.01, 95% CI = 0.01-0.01) episode per child-year. Conclusions: ALRI among children in rural India was high; RSV was a significant contributor.

Evidence on influenza vaccine effectiveness from low and middle countries (LMICs) is limited due to limited institutional capacities; lack of adequate resources; and lack of interest by ministries of health for influenza vaccine introduction. There are concerns that the highest ethical standards will be compromised during trials in LMICs leading to mistrust of clinical trials. These factors pose regulatory and operational challenges to researchers in these countries. We conducted a community-based vaccine trial to assess the efficacy of live attenuated influenza vaccine and inactivated influenza vaccine in rural north India. Key regulatory challenges included obtaining regulatory approvals, reporting of adverse events, and compensating subjects for trial-related injuries; all of which were required to be completed in a timely fashion. Key operational challenges included obtaining audio-visual consent; maintaining a low attrition rate; and administering vaccines during a narrow time period before the influenza season, and under extreme heat. We overcame these challenges through advanced planning, and sustaining community engagement. We adapted the trial procedures to cope with field conditions by conducting mock vaccine camps; and planned for early morning vaccination to mitigate threats to the cold chain. These lessons may help investigators to confront similar challenges in other LMICs.

BACKGROUND: No estimates of influenza-associated mortality exist for India. OBJECTIVE: To evaluate national mortality and viral surveillance data from India for assessing their appropriateness in estimating influenza-associated mortality using varied analytic approaches. METHODS: We reviewed influenza virus surveillance data from a national influenza surveillance network. We also reviewed national mortality data from Civil Registration System (CRS), Medical Certification of Cause of Death (MCCD) and the Sample Registration System (SRS). We compared and scored the different sources of mortality data using specific criteria, including the process of cause of death assignment, sample size, proportion of ill-defined deaths, representativeness and availability of time series data. Each of these 5 parameters was scored on a scale from 1 to 5. To evaluate how to generate an influenza-associated mortality estimate for India, we also reviewed 4 methodologic approaches to assess the appropriateness of their assumptions and requirements for these data sets. RESULTS: The influenza virus surveillance data included year-round sample testing for influenza virus and was found to be suitable for influenza mortality estimation modelling. Based on scoring for the 5 mortality data criteria, the SRS data had the highest score with 20 of 25 possible score, whereas MCCD and CRS scored 16 and 12, respectively. The SRS which used verbal autopsy survey methods was determined to be nationally representative and thus adequate for estimating influenza-associated mortality. Evaluation of the modelling methods demonstrated that Poisson regression, risk difference and mortality multiplier methods could be applied to the Indian setting. CONCLUSION: Despite significant challenges, it is possible to estimate influenza-associated mortality in India.