Mumbai mayhem of COVID-19 pandemic reveals important factors that influence susceptibility to infection

Abstract

Background: COVID-19 severity is disproportionately high in the elderly and people with comorbidities. However, other factors that predispose individuals to increased chances of infection are unclear. Methods: Data from 18,600 people screened for COVID-19 in Mumbai during the outbreak's initial phase, March 7 to June 30, 2020, were used to assess risk factors associated with COVID-19 using the odds ratio analysis. Findings: Males aged 60 years having both diabetes and hypertension were at the highest risk of COVID-19 infection (M vs. F OR=2.5, 95% CI=1.34À4.67, p = 0.0049). People having both diabetes and hypertension in 20 years (OR=4.11, 95% CI=3.26À5.20, p <0.0001), diabetes and hypertension independently in 20À39 (OR=4.13, 95% CI=2.22À7.70, p <0.0001, OR=4.32, 95% CI=2.10À8.88, p = 0.0001) and 60 years (OR=2.69, 95% CI=1.87À3.87, p <0.0001, OR=2.03, 95% CI=1.46À2.82, p <0.0001), chronic renal disease in 20À39 years (OR=5.38, 95% CI=1.91À15.09, p = 0.0007) age groups had significantly higher risk of COVID-19 infection than those without comorbidity. Quarantined people had significantly lower positive odds (OR=0.59, 95% CI=0.53À0.66, p <0.001) than non-quarantined people. Interpretation: Our research indicates that the risk of getting COVID-19 disease is not equal. When considering sex, age, and comorbidity together, we found that males aged 60 years and having both diabetes and hypertension had a significantly high risk of COVID-19 infection. Therefore, remedial measures such as vaccination programs should be prioritized for at-risk individuals.

Risk Factors for SARS-CoV-2 Infection, Pneumonia, Intubation, and Death in Northeast Mexico

“…At this point, it is necessary to emphasise the role of these chronic diseases in susceptibility to contagion. Yadav et al had already pointed out this relationship in the Mumbai population and noted that the concurrence of these chronic diseases was strongly associated with COVID-19 infection (16). The biological explanation is that these comorbidities can lead to the overexpression of SARS-CoV-2 receptor molecules, such as angiotensin-converting enzyme 2 and CD147 (17).…”

“…In many cases, these circumstances prevented home office work, which could cause greater exposure to infected people and a greater spread of COVID-19 in this population ( 14 ). Moreover, this state has a high prevalence of chronic diseases such as obesity, diabetes and hypertension ( 15 ), which have consistently been associated with infection ( 16 , 17 ) and worse outcomes in the course of this disease ( 4 – 9 , 18 , 19 ).…”

SARS-CoV-2 Seroprevalence in Individuals With Type 1 and Type 2 Diabetes Compared With Controls

“…A community based seroprevalence study performed in rural Bangalore district of India found no association between diabetes and SARS-CoV-2 seropositivity [ 11 ]. On the other hand, a hospital based study from Mumbai, India which compared demographic factors and combordities between reverse transcriptase polymerase chain reaction (RT-PCR) positive and negative cases, found a significant association between diabetes and SARS-CoV-2 infection [ 12 ]. As many as seven undetected infected individuals may exist in community for every single RT-PCR confirmed case [ 11 ], and hence the findings of latter study may not be generalisable to SARS-CoV-2 infection, as a whole.…”

Impact of COVID-19 on tuberculosis services: an experience from a tertiary care hospital

“…Following a large increase in the global number of TB case notifications per year between 2017 and 2019, the reported data show a substantial fall of 18 % between 2019 and 2020, from 7.1 million to 5.8 million [8]. Also, a 62 % reduction in TB case notifications and a 70 % decline in childhood TB notifications during the nationwide lock down period led to an increased vulnerability to TB [8] Maharashtra was the worst-hit state during COVID-19 [9]. In particular, Mumbai, a city known for its massive population density, largest slum area, and a long list of foreign returnees, faced many difficulties in the management of TB patients and their access to healthcare during the lock down situations.…”

“…Maharashtra was the worst-hit state during COVID-19 [9]. In particular, Mumbai, a city known for its massive population density, largest slum area, and a long list of foreign returnees, faced many difficulties in the management of TB patients and their access to healthcare during the lock down situations.…”