Corrigendum to "PRAK-03202: A triple antigen virus-like particle vaccine candidate against SARS CoV-2"[Heliyon 7 (10) (October 2021) e08124].

[This corrects the article DOI: 10.1016/j.heliyon.2021.e08124.].

PRAK-03202: A triple antigen virus-like particle vaccine candidate against SARS CoV-2.

The rapid development of safe and effective vaccines against severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) is a necessary response to coronavirus outbreak. Here, we developed PRAK-03202, the world's first triple antigen virus-like particle vaccine candidate, by cloning and transforming SARS-CoV-2 gene segments into a highly characterized S. cerevisiae-based D-Crypt™ platform, which induced SARS CoV-2 specific neutralizing antibodies in BALB/c mice. Immunization using three different doses of PRAK-03202 induced an antigen-specific (spike, envelope, and membrane proteins) humoral response and neutralizing potential. Peripheral blood mononuclear cells from convalescent patients showed lymphocyte proliferation and elevated interferon levels suggestive of epitope conservation and induction of T helper 1-biased cellular immune response when exposed to PRAK-03202. These data support further clinical development and testing of PRAK-03202 for use in humans.

SIBLING- AND FAMILY-LEVEL CLUSTERING OF UNDERWEIGHT CHILDREN IN NORTHERN INDIA.

Child undernutrition remains a major child health and developmental issue in low- and middle-income countries. The concentration (clustering) of underweight children among siblings at the family level is known to exist in India. This study examined the extent and covariates of clustering of underweight children at the sibling and family level in Uttar Pradesh, the largest state of northern India. Clustering of underweight (low weight-for-age) children was assessed using data on 7533 under-five children from the National Family Health Survey (NFHS) conducted in 2005-06, analysed using binary logistic and binomial regression models. Related bio-demographic, socioeconomic and health care variables were used as covariates in the models. The odds of being underweight for the index child were about two times higher (OR=2.34, p<0.001) if any of the siblings within the household was malnourished or underweight. A longer birth interval increased the odds of a child being underweight. The odds of underweight were significantly lower (OR=0.69, p<0.001) for children born to normal-weight mothers compared with those born to underweight mothers. Similarly, the odds of underweight were significantly lower (OR=0.49, p=0.01) for children born to educated mothers (high school and above) compared with those born to illiterate mothers. The results of the binomial regression model suggested that the deviations between observed and expected number of children were positive (3.09, 3.78 and 2.71) for 1, 2 and 2+ underweight children within the households of underweight women, indicating the concentration of underweight children among underweight/malnourished mothers. Underweight children were found to be clustered among underweight mothers with multiple underweight siblings. The findings suggest that policy interventions need to focus on underweight mothers with multiple underweight children.

The impact of multimorbidity on adult physical and mental health in low- and middle-income countries: what does the study on global ageing and adult health (SAGE) reveal?

BACKGROUND: Chronic diseases contribute a large share of disease burden in low- and middle-income countries (LMICs). Chronic diseases have a tendency to occur simultaneously and where there are two or more such conditions, this is termed as 'multimorbidity'. Multimorbidity is associated with adverse health outcomes, but limited research has been undertaken in LMICs. Therefore, this study examines the prevalence and correlates of multimorbidity as well as the associations between multimorbidity and self-rated health, activities of daily living (ADLs), quality of life, and depression across six LMICs. METHODS: Data was obtained from the WHO's Study on global AGEing and adult health (SAGE) Wave-1 (2007/10). This was a cross-sectional population based survey performed in LMICs, namely China, Ghana, India, Mexico, Russia, and South Africa, including 42,236 adults aged 18 years and older. Multimorbidity was measured as the simultaneous presence of two or more of eight chronic conditions including angina pectoris, arthritis, asthma, chronic lung disease, diabetes mellitus, hypertension, stroke, and vision impairment. Associations with four health outcomes were examined, namely ADL limitation, self-rated health, depression, and a quality of life index. Random-intercept multilevel regression models were used on pooled data from the six countries. RESULTS: The prevalence of morbidity and multimorbidity was 54.2 % and 21.9 %, respectively, in the pooled sample of six countries. Russia had the highest prevalence of multimorbidity (34.7 %) whereas China had the lowest (20.3 %). The likelihood of multimorbidity was higher in older age groups and was lower in those with higher socioeconomic status. In the pooled sample, the prevalence of 1+ ADL limitation was 14 %, depression 5.7 %, self-rated poor health 11.6 %, and mean quality of life score was 54.4. Substantial cross-country variations were seen in the four health outcome measures. The prevalence of 1+ ADL limitation, poor self-rated health, and depression increased whereas quality of life declined markedly with an increase in number of diseases. CONCLUSIONS: Findings highlight the challenge of multimorbidity in LMICs, particularly among the lower socioeconomic groups, and the pressing need for reorientation of health care resources considering the distribution of multimorbidity and its adverse effect on health outcomes.

Socioeconomic determinants of health inequalities among the older population in India: a decomposition analysis.

This study quantified and decomposed health inequalities among the older population in India and analyzes how health status varies for populations between 60 to 69 years and 70 years and above. Data from the 60th round of the National Sample Survey (NSS) was used for the analyses. Socioeconomic inequalities in health status were measured by using Concentration Index (CI) and further decomposed to find critical determinants and their relative contributions to total health inequality. Overall, CI estimates were negative for the older population as a whole (CI = -0.1156), as well as for two disaggregated groups, 60 to 69 years (CI = -0.0943) and 70 years and above (CI = -0.08198). This suggests that poor health status is more concentrated among the socioeconomically disadvantaged older population. Decomposition analyses revealed that poor economic status (54 %) is the dominant contributor to total health inequalities in the older population, followed by illiteracy (24 %) and rural place of residence (20 %). Other indicators, such as religion, gender and marital status were positive, while Caste was negatively associated with health inequality in the older populations. Finally, a comparative assessment of decomposition results suggest that critical contributors for health inequality vary for the older population of 60 to 69 years and 70 years and above. These findings provide important insights on health inequalities among the older population in India. Implications are advanced.

Health inequalities among urban children in India: a comparative assessment of Empowered Action Group (EAG) and South Indian states.

As India rapidly urbanizes, within urban areas socioeconomic disparities are rising and health inequality among urban children is an emerging challenge. This paper assesses the relative contribution of socioeconomic factors to child health inequalities between the less developed Empowered Action Group (EAG) states and more developed South Indian states in urban India using data from the 2005-06 National Family Health Survey. Focusing on urban health from varying regional and developmental contexts, socioeconomic inequalities in child health are examined first using Concentration Indices (CIs) and then the contributions of socioeconomic factors to the CIs of health variables are derived. The results reveal, in order of importance, pronounced contributions of household economic status, parent's illiteracy and caste to urban child health inequalities in the South Indian states. In contrast, parent's illiteracy, poor economic status, being Muslim and child birth order 3 or more are major contributors to health inequalities among urban children in the EAG states. The results suggest the need to adopt different health policy interventions in accordance with the pattern of varying contributions of socioeconomic factors to child health inequalities between the more developed South Indian states and less developed EAG states.

Are self reported morbidities deceptive in measuring socio-economic inequalities.

BACKGROUND & OBJECTIVES: The ambiguity and variability in existing literature on the magnitude of socio-economic inequality in self-reported morbidities makes it difficult to set priorities in health policy. This study examined three critical research questions: first, how far self-reporting affects measuring socio-economic inequalities in case of obstetric morbidities. Second, does using simple bivariate variations mislead in estimating socio-economic differentials in prevalence of obstetric morbidities? Finally, whether use of sophisticated regression based decomposition results can overcome such problems. METHODS: The data from National Family Health Survey (NFHS-3; 2005-06) were used, and analyzed by statistical tools such as bivariate estimates and regression based decomposition analysis. RESULTS: Bivariate results revealed that self-reported obstetric morbidity data were misleading in measurement of socio-economic differentials, as these failed to show existing socio-economic variations in obstetric morbidities by socio-economic standing of women. However, decomposition analysis showed that the prevalence of obstetric complications was greater among socioeconomically disadvantaged groups. INTERPRETATION & CONCLUSIONS: Based on our findings on measurement of socio-economic inequality in self-reported obstetric morbidity, we conclude that the use of regression based inequality decomposition estimates not only overcomes the problems of measuring socio-economic inequality based on self-reported morbidities, but also increases the validity of such measures.