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COVID 19 mortality: Probable role of microbiome to explain disparity.

ABSTRACT: There is a significant difference between COVID 19 associated mortality between different countries. Generally the number of deaths per million population are higher in the developed countries despite better health care efficiency, drinking water quality and expected healthy life span (HALE) at the time of birth. Developing and underdeveloped countries on the other hand have lower mortality even with higher rural and slum populations along with incidence of diarrhea because of lack of sanitation. We analyzed data from 122 countries out of which 80 were high or upper middle income and 42 were low or low middle income countries. There was statistically significant positive correlation between COVID 19 deaths /million population and water current score, health efficiency, and HALE. Statistically significant negative correlation was observed with % rural population and fraction of diarrhea because of inadequate sanitation for all ages. Moreover analysis of 51 countries showed that there is significant negative correlation between COVID 19 deaths /million population and proportion of total population living in slums. We propose that high microbial exposure particularly gram negative bacteria can possibly induce interferon type I which might have a protective effect against COVID 19 since the countries with less mortality also tend to have lack of sanitation and high incidence of attendant diseases. So, far none of the predictive models have taken into account immune status of populations engendered by environmental microbial exposure or microbiome. There might be a need to look at dynamics of COVID 19 pandemic using immune perspective. The approach can potentially inform better policies including interventions.

SUBMITTER: Kumar P

PROVIDER: S-EPMC7444648 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe impact of the COVID-19 pandemic on paediatric populations varied between high-income countries (HICs) versus low-income to middle-income countries (LMICs). We sought to investigate differences in paediatric clinical outcomes and identify factors contributing to disparity between countries.MethodsThe International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) COVID-19 database was queried to include children under 19 years of age admitted to hospital from January 2020 to April 2021 with suspected or confirmed COVID-19 diagnosis. Univariate and multivariable analysis of contributing factors for mortality were assessed by country group (HICs vs LMICs) as defined by the World Bank criteria.ResultsA total of 12 860 children (3819 from 21 HICs and 9041 from 15 LMICs) participated in this study. Of these, 8961 were laboratory-confirmed and 3899 suspected COVID-19 cases. About 52% of LMICs children were black, and more than 40% were infants and adolescent. Overall in-hospital mortality rate (95% CI) was 3.3% [=(3.0% to 3.6%), higher in LMICs than HICs (4.0% (3.6% to 4.4%) and 1.7% (1.3% to 2.1%), respectively). There were significant differences between country income groups in intervention profile, with higher use of antibiotics, antivirals, corticosteroids, prone positioning, high flow nasal cannula, non-invasive and invasive mechanical ventilation in HICs. Out of the 439 mechanically ventilated children, mortality occurred in 106 (24.1%) subjects, which was higher in LMICs than HICs (89 (43.6%) vs 17 (7.2%) respectively). Pre-existing infectious comorbidities (tuberculosis and HIV) and some complications (bacterial pneumonia, acute respiratory distress syndrome and myocarditis) were significantly higher in LMICs compared with HICs. On multivariable analysis, LMIC as country income group was associated with increased risk of mortality (adjusted HR 4.73 (3.16 to 7.10)).ConclusionMortality and morbidities were higher in LMICs than HICs, and it may be attributable to differences in patient demographics, complications and access to supportive and treatment modalities.

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COVID 19 mortality: Probable role of microbiome to explain disparity.

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