Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Background/Objectives 
Despite influenza vaccination programs in various jurisdictions, seasonal influenza vaccine (SIV) uptake remains suboptimal among older people (≥65years old), an important subpopulation for influenza vaccination. We sought to summarize determinants of SIV uptake (any vaccine receipt) and vaccination adherence (receipt of vaccine in two or more seasons in sequence) among older people.


Methods 
We searched for population-based studies conducted in community-dwelling older people (irrespective of their health status) from 2000–2019. Two reviewers independently selected publications for inclusion. One reviewer extracted data from the included studies; a second checked the extracted data for errors. Disagreements were resolved by discussion and consensus, or a third reviewer. We were interested in the determinants of SIV uptake and vaccination adherence. Where appropriate, we pooled adjusted results using the inverse variance, random-effects method and reported the odds ratios (OR) and their 95% confidence intervals (CI).


Results 
Out of 11,570 citations screened, we included 34 cross-sectional studies. The following were associated with increased SIV uptake: being older (OR 1.52, 95%CI 1.38–1.67 [21 studies]), white (1.30, 1.14–1.49 [10 studies]), married (1.23, 1.17–1.28 [9 studies]), non-smoker (1.28, 1.11–1.47 [7 studies]), of a higher social class (1.20, 1.06–1.36 [2 studies]), having a higher education (1.12, 1.04–1.21 [14 studies]), having a higher household income (1.11, 1.05–1.18 [8 studies]), having a chronic illness (1.53, 1.44–1.63 [16 studies]), having poor self-assessed health (1.23, 1.02–1.40 [9 studies]), having a family doctor (2.94, 1.79–4.76 [2 studies]), and having health insurance (1.58, 1.13–2.21 [6 studies]). The influence of these factors varied across geographical regions. Being older (1.26, 1.11–1.44 [2 studies]) was also associated with increased vaccination adherence.


Conclusions 
Several factors may determine SIV uptake and vaccination adherence among older people. More studies are needed to provide a stronger evidence base for planning more effective influenza vaccination programs.

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Seasonal influenza vaccination in older people: A systematic review and meta-analysis of the determining factors.

https://doi.org/10.1016/j.scitotenv.2022.158056

Effects of the built environment and human factors on the spread of COVID-19: A systematic literature review

Background Chronic conditions reduce the likelihood of physical functioning among older adults. However, the contribution of most prevalent diseases and multimorbidity to different measures of functional limitations is relatively underexplored among Indian older adults. The present study explores the prospective association between number of chronic conditions and limitations in activities of daily living (ADL) and instrumental activities of daily living (IADL) among older adults in India. Methods This study utilized data from the nationally representative Longitudinal Ageing Study in India (LASI-2017-18). The effective sample size was 31,464 older adults aged 60 years and above. Descriptive statistics along with cross-tabulation were presented in the study. Additionally, binary logistic regression analysis was used to fulfil the objectives. The outcome variables were dichotomized; high representing no difficulty in ADL/IADL and low representing a difficulty in at least one ADL/IADL. The chronic conditions included hypertension, diabetes, neurological/psychiatric disease, lung disease, heart diseases, stroke, and bone-related disease. The number of chronic diseases was categorized into no disease, single, two and three plus based on number of reported disease. Results 26.36% of older women and 20.87% of older men had low ADL and the figures for low IADL were 56.86 and 38.84% for older men and women respectively. The likelihood of low ADL (AOR: 1.698, CI:1.544, 1.868) and low IADL (AOR: 1.197; CI: 1.064, 1.346) was higher among womenthan men. With increasing age, the prevalence of low ADL increased among older adults. Respondents with pre-existing chronic conditions had higher likelihood of low ADL and IADL. Older adults with hypertension, psychiatric disease, heart disease, stroke and bone-related disease had significantly higher odds of reporting low IADL. The chances of low ADL and IADL were 2.156 (CI: 1.709, 2.719) and 2.892 (CI: 2.067, 4.047) times respectively higher among older adults with more than three chronic conditions. After controlling for socio-economic and health-related covariates, it was found that men with more than three pre-existing chronic conditions had higher odds of low ADL than women. On the other hand, low IADL were found higher among women with more than three pre-existing chronic conditions. Conclusions The present study demonstrates a significant burden of functional limitations among older individuals and that there is a strong association between pre-existing chronic conditions and functional disability. Those with hypertension, diabetes, psychiatric disorders, heart disease, stroke, lung disease or bone-related diseases should be effectively monitored to predict future functional limitations, which may lead to worsening health.

Number of chronic conditions and associated functional limitations among older adults: cross-sectional findings from the longitudinal aging study in India.

Variation in human growth and the genetic and environmental factors that are influencing it have been described worldwide. The objective of this study is to assess the geographical variance of under-five children nutritional status and its related covariates across Indian districts. We use the most recent fourth round of the Indian National Family Health Survey conducted in 2015-2016, which for the first time offers district level information. We employ principal component analysis (PCA) on the demographic and socio-economic determinants of childhood morbidity and conduct hierarchical clustering analysis to identify geographical patterns in nutritional status among children of age under five at the district level. Our results reveal strong geographical clustering among the districts of India. Throughout most of Southern India, children are provided with relatively better conditions for growth and improved nutritional status, as compared to districts in the central, particularly rural parts of India. Looking at average weight, as well as the proportion of children that suffer from underweight and wasting, northeastern Indian districts seem to be offering living conditions more conducive to healthy child development. The geographical clustering of malnutrition, as well as below-average child height and weight coincides with high poverty, low female education, lower BMI among mothers, higher prevalence of both parity 4+ and teenage pregnancies. The present study highlights the importance of combining PCA and cluster analysis methods in studying variation in under-five child growth and nutrition at the district level. We identify the geographical areas, where children are under severe risk of undernutrition, stunting and wasting and contribute to formulating policies to improve child nutrition in India.

Under-Five Child Growth and Nutrition Status:Spatial Clustering of Indian Districts. VID Working Paper 03/2019

The burden of disability and chronic morbidity among the elderly has been increasing substantially in India in recent years. Yet, the use of nationally representative data to investigate the relationship between chronic morbidity and reported disability in the country has been minimal. The objective of this study is twofold: i) to quantify the association between chronic morbidities and overall disabilities in the activities of daily living (ADLs) among elderly people in India, and ii) to understand how various chronic morbidities influence individual ADLs, specifically, walking, toileting and dressing. We used data from the India Human Development Survey-II (IHDS-II) as a basis for this study. We computed the Katz Index of independence in ADL to examine the burden of disability among the elderly. Ordered logistic regression was carried out to examine the effect of chronic morbidities on: i) the disability index (where 0 = no disability; 1 = disability in 1 or 2 ADLs; and 2 = disability in 3 ADLs), and ii) disabilities in three ADLs in the population over-60 years of age in India. The percentage of people scoring lower Katz index (indicating severe and mild disability) in at least one of the three ADLs is very high in India (17.91% for males and 26.21% for females). Irrespective of the type of ADL, the Katz score is lower in elderly females than in elderly males. Elderly people who are illiterate and belong to the poorest wealth quintile report lower Katz scores in ADL. Both bivariate and multivariate analyses confirm that all three types of chronic morbidities are positively and significantly associated with a disability condition in the ADLs. Yet, the effects of morbidities vary greatly according to the type of disability. For instance, while diabetes affect walking (OR: 2.56; 95% CI: 2.29–2.86), and toileting (OR: 2.63; 95% CI: 2.26–3.07), high blood pressure mainly affects walking (OR: 2.29, 95% CI: 2.09–2.5) and dressing disabilities (OR: 2.13, 95% CI: 1.84–2.46). Chronic morbidity is a decisive factor in old age disability. It is crucial to reduce chronic morbidity in a timely way to minimise the enormous associated burden of disability.

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Chronic morbidity and reported disability among older persons from the India Human Development Survey

Background The number of patients with coronavirus infection (COVID-19) has amplified in India. Understanding the district level correlates of the COVID-19 infection ratio (IR) is therefore essential for formulating policies and intervention. Objectives The present study examines the association between socio-economic and demographic characteristics of India’s population and the COVID-19 infection ratio at district level… Data and Methods Using crowdsourced data on the COVID-19 prevalence rate, we analyzed state and district level variation in India from March 14 to July 31 2020. We identified hotspot and cold spot districts for COVID-19 cases and infection ratio. We have also carried out a regression analysis to highlight the district level demographic, socio-economic, infrastructure, and health-related correlates of the COVID-19 infection ratio. Results The results showed that the IR is 42.38 per one hundred thousand population in India. The highest IR was observed in Andhra Pradesh (145.0), followed by Maharashtra (123.6), and was the lowest in Chhattisgarh (10.1). About 80 per cent of infected cases, and 90 per cent of deaths were observed in nine Indian states (Tamil Nadu, Andhra Pradesh, Telangana, Karnataka, Maharashtra, Delhi, Uttar Pradesh, West Bengal, and Gujarat). Moreover, we observed COVID-19 cold-spots in central, northern, western, and north-eastern regions of India. Out of 736 districts, six metropolitan cities (Mumbai, Chennai, Thane, Pune, Bengaluru, and Hyderabad) emerged as the major hotspots in India, containing around 30 per cent of confirmed total COVID-19 cases in the country. Simultaneously, parts of the Konkan coast in Maharashtra, parts of Delhi, the southern part of Tamil Nadu, the northern part of Jammu & Kashmir were identified as hotspots of COVID-19 infection. Moran’s-I value of 0.333showed a positive spatial clusteringlevel in the COVID-19 IR case over neighboring districts. Our regression analysis found that district-level population density (β: 0.05, CI:004-0.06), the percent of urban population (β:3.08, CI: 1.05-5.11), percent of Scheduled Caste Population (β: 3.92, CI: 0.12-7.72),and district-level testing ratio (β: 0.03, CI: 0.01-0.04) are positively associated with the prevalence of COVID-19. Conclusion COVID-19 cases were heavily concentrated in 9 states of India. Several demographic, socio-economic, and health-related variables are correlated with COVID-19 prevalence rate. However, after adjusting the role of socio-economic and health-related factors, the COVID-19 infection rate was found to be more rampant in districts with a higher population density, a higher percentage of the urban population, and a higher percentage of deprived castes and with a higher level of testing ratio. The identified hotspots and correlates in this study give crucial information for policy discourse.

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District level correlates of COVID-19 pandemic in India

Background COVID-19 is affecting the entire population of India. Understanding district level correlates of the COVID-19’s infection ratio (IR) is essential for formulating policies and interventions. Objective The present study aims to investigate the district level variation in COVID-19 during March-October 2020. The present study also examines the association between India’s socioeconomic and demographic characteristics and the COVID-19 infection ratio at the district level. Data and methods We used publicly available crowdsourced district-level data on COVID-19 from March 14, 2020, to October 31, 2020. We identified hotspot and cold spot districts for COVID-19 cases and infection ratio. We have also carried out two sets of regression analysis to highlight the district level demographic, socioeconomic, household infrastructure facilities, and health-related correlates of the COVID-19 infection ratio. Results The results showed on October 31, 2020, the IR in India was 42.85 per hundred thousand population, with the highest in Kerala (259.63) and the lowest in Bihar (6.58). About 80 percent infected cases and 61 percent deaths were observed in nine states (Delhi, Gujarat, West Bengal, Uttar Pradesh, Andhra Pradesh, Maharashtra, Karnataka, Tamil Nadu, and Telangana). Moran’s- I showed a positive yet poor spatial clustering in the COVID-19 IR over neighboring districts. Our regression analysis demonstrated that percent of 15–59 aged population, district population density, percent of the urban population, district-level testing ratio, and percent of stunted children were significantly and positively associated with the COVID-19 infection ratio. We also found that, with an increasing percentage of literacy, there is a lower infection ratio in Indian districts. Conclusion The COVID-19 infection ratio was found to be more rampant in districts with a higher working-age population, higher population density, a higher urban population, a higher testing ratio, and a higher level of stunted children. The study findings provide crucial information for policy discourse, emphasizing the vulnerability of the highly urbanized and densely populated areas.

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District level correlates of COVID-19 pandemic in India during March-October 2020.

Introduction: The burden of non-communicable diseases (NCDs) is a major public health concern across the world. Various initiatives have tried to address these with varying degrees of success. Objective: The objective is to assess and collate existing evidence in implementation research done in India on three broad domains of NCDs namely, cardiovascular diseases (CVD), diabetes mellitus (DM), and mental health (MH) in India. Materials and methods: Three systematic review protocols have been drafted to explore and collate extant evidence of implementation research on cardiovascular diseases, diabetes mellitus, and mental health in India, in accordance with the PRISMA-P statement. Academic databases including PubMed, Embase and Science Direct will be searched. Search strategies will be formulated in iterative processes and in accordance with the formats that are specific to the databases that will be searched. In addition, grey literature and non-academic databases will also be explored. Data extracted from the selected studies will be analysed and a narrative summary of the selected articles, using the SWiM (Synthesis without meta-analysis) guidelines will be produced. Intended Outcomes: The outputs of these systematic reviews could help in a better understanding of implementation research gaps and also how to address them. Apart from giving insights into how healthcare initiatives for CVDs, diabetes and mental health could be implemented in a better way, the study could also advocate the need to build and consolidate capacity for implementation research in the country.

https://f1000research.com/articles/12-100/pdf

Mukesh C. Parmar

Papers

Chronic morbidity and reported disability among older persons from the India Human Development Survey

District level correlates of COVID-19 pandemic in India

District level correlates of COVID-19 pandemic in India during March-October 2020.

Protocol of systematic reviews on implementation research on cardiovascular diseases, diabetes mellitus and mental ailments in India