Post COVID sequelae among COVID-19 survivors: insights from the Indian National Clinical Registry for COVID-19.

INTRODUCTION: The effects of COVID-19 infection persist beyond the active phase. Comprehensive description and analysis of the post COVID sequelae in various population groups are critical to minimise the long-term morbidity and mortality associated with COVID-19. This analysis was conducted with an objective to estimate the frequency of post COVID sequelae and subsequently, design a framework for holistic management of post COVID morbidities. METHODS: Follow-up data collected as part of a registry-based observational study in 31 hospitals across India since September 2020-October 2022 were used for analysis. All consenting hospitalised patients with COVID-19 are telephonically followed up for up to 1 year post-discharge, using a prestructured form focused on symptom reporting. RESULTS: Dyspnoea, fatigue and mental health issues were reported among 18.6%, 10.5% and 9.3% of the 8042 participants at first follow-up of 30-60 days post-discharge, respectively, which reduced to 11.9%, 6.6% and 9%, respectively, at 1-year follow-up in 2192 participants. Patients who died within 90 days post-discharge were significantly older (adjusted OR (aOR): 1.02, 95% CI: 1.01, 1.03), with at least one comorbidity (aOR: 1.76, 95% CI: 1.31, 2.35), and a higher proportion had required intensive care unit admission during the initial hospitalisation due to COVID-19 (aOR: 1.49, 95% CI: 1.08, 2.06) and were discharged at WHO ordinal scale 6-7 (aOR: 49.13 95% CI: 25.43, 94.92). Anti-SARS-CoV-2 vaccination (at least one dose) was protective against such post-discharge mortality (aOR: 0.19, 95% CI: 0.01, 0.03). CONCLUSION: Hospitalised patients with COVID-19 experience a variety of long-term sequelae after discharge from hospitals which persists although in reduced proportions until 12 months post-discharge. Developing a holistic management framework with engagement of care outreach workers as well as teleconsultation is a way forward in effective management of post COVID morbidities as well as reducing mortality.

Challenges in Accessing and Delivering Maternal and Child Health Services during the COVID-19 Pandemic: A Cross-Sectional Rapid Survey from Six States of India.

BACKGROUND/OBJECTIVES: Globally, the COVID-19 pandemic and its prevention and control policies have impacted maternal and child health (MCH) services. This study documents the challenges faced by patients in accessing MCH services, and the experiences of health care providers in delivering those services during the COVID-19 outbreak, explicitly focusing on the lockdown period in India. METHODS: A cross-sectional study (rapid survey) was conducted in 18 districts from 6 states of India during March to June, 2020. The sample size included 540 MCH patients, 18 gynaecologists, 18 paediatricians, 18 district immunisation officers and 108 frontline health workers. Bivariate analysis and multivariable analysis were used to assess the association between sociodemographic characteristics, and challenges faced by the patients. RESULTS: More than one-third of patients (n = 212; 39%) reported that accessing MCH services was a challenge during the lockdown period, with major challenges being transportation-related difficulties (n = 99; 46%) unavailability of hospital-based services (n = 54; 23%) and interrupted outreach health services (n = 39; 18.4%). The supply-side challenges mainly included lack of infrastructural preparedness for outbreak situations, and a shortage of human resources. CONCLUSIONS/RECOMMENDATIONS: A holistic approach is required that focuses on both preparedness and response to the outbreak, as well reassignment and reinforcement of health care professionals to continue catering to and maintaining essential MCH services during the pandemic.

Quality of anthropometric data in India's National Family Health Survey: Disentangling interviewer and area effect using a cross-classified multilevel model.

India has adopted a target-based approach to reduce the scourge of child malnourishment. Because the monitoring and evaluation required by this approach relies primarily on large-scale data, a data quality assessment is essential. As field teams are the primary mode of data collection in large-scale surveys, this study attempts to understand their contribution to variations in child anthropometric measures. This research can help disentangle the confounding effects of regions/districts and field teams on the quality of child anthropometric data. The anthropometric z-scores of 2,25,002 children below five years were obtained from the fourth round of India's National Family and Health Survey (NFHS-4), 2015-16. Unadjusted and adjusted standard deviations (SD) of the anthropometric measures were estimated to assess the variations in measurements. In addition, a cross-classified multilevel model (CCMM) approach was adopted to estimate the contribution of geographical regions/districts and teams to variations in anthropometric measures. The unadjusted SDs of the measures of stunting, wasting, and underweight were 1.7, 1.4, and 1.2, respectively. The SD of stunting was above the World Health Organisation threshold (0.8-1.2), as well as the Demographic and Health Survey mark. After adjusting for team-level characteristics, the SDs of all three measures reduced marginally, indicating that team-level workload had a marginal but significant role in explaining the variations in anthropometric z-scores. The CCMM showed that the maximum contribution to variations in anthropometric z-scores came from community-level (Primary Sampling Unit (PSU)) characteristics. Team-level characteristics had a higher contribution to variations in anthropometric z-scores than district-level attributes. Variations in measurement were higher for child height than weight. The present study decomposes the effects of district- and team-level factors and highlights the nuances of introducing teams as a level of analysis in multilevel modelling. Population size, density, and terrain variations between PSUs should be considered when allocating field teams in large-scale surveys.