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1.
Am J Trop Med Hyg ; 107(1): 218, 2022 06 13.
Article in English | MEDLINE | ID: covidwho-2072014
2.
Am J Trop Med Hyg ; 2022 Apr 04.
Article in English | MEDLINE | ID: covidwho-1776512

ABSTRACT

We studied all-cause mortality during the COVID-19 pandemic in 19 Indian states (population 1.27 billion). Excess mortality was calculated by comparison with years 2015 to 2019. The known COVID-19 deaths reported for a state were assumed to be accurate, unless excess mortality data suggested a higher toll. Data from one state were excluded due to anomalies. In several regions, fewer deaths were reported in 2020 than expected. Areas in Andhra Pradesh, Delhi, Haryana, Karnataka, Madhya Pradesh, Tamil Nadu, and West Bengal saw spikes in mortality in Spring 2021. The pandemic-related mortality through August 31, 2021, in 18 Indian states was estimated to be 198.7 per 100,000 population (range 146.1-263.8 per 100,000). If these rates apply nationally, then 2.69 million people (range 1.98 to 3.57 million) may have perished in India as a result of the pandemic by August 31, 2021.

3.
Am J Trop Med Hyg ; 103(6): 2400-2411, 2020 12.
Article in English | MEDLINE | ID: covidwho-895570

ABSTRACT

We studied sources of variation between countries in per-capita mortality from COVID-19 (caused by the SARS-CoV-2 virus). Potential predictors of per-capita coronavirus-related mortality in 200 countries by May 9, 2020 were examined, including age, gender, obesity prevalence, temperature, urbanization, smoking, duration of the outbreak, lockdowns, viral testing, contact-tracing policies, and public mask-wearing norms and policies. Multivariable linear regression analysis was performed. In univariate analysis, the prevalence of smoking, per-capita gross domestic product, urbanization, and colder average country temperature were positively associated with coronavirus-related mortality. In a multivariable analysis of 196 countries, the duration of the outbreak in the country, and the proportion of the population aged 60 years or older were positively associated with per-capita mortality, whereas duration of mask-wearing by the public was negatively associated with mortality (all P < 0.001). Obesity and less stringent international travel restrictions were independently associated with mortality in a model which controlled for testing policy. Viral testing policies and levels were not associated with mortality. Internal lockdown was associated with a nonsignificant 2.4% reduction in mortality each week (P = 0.83). The association of contact-tracing policy with mortality was not statistically significant (P = 0.06). In countries with cultural norms or government policies supporting public mask-wearing, per-capita coronavirus mortality increased on average by just 16.2% each week, as compared with 61.9% each week in remaining countries. Societal norms and government policies supporting the wearing of masks by the public, as well as international travel controls, are independently associated with lower per-capita mortality from COVID-19.


Subject(s)
COVID-19/epidemiology , COVID-19/mortality , Masks/supply & distribution , Pandemics , Quarantine/organization & administration , SARS-CoV-2/pathogenicity , Age Factors , COVID-19/diagnosis , COVID-19 Testing/methods , Cold Temperature , Comorbidity , Contact Tracing/legislation & jurisprudence , Global Health/statistics & numerical data , Hospitalization/statistics & numerical data , Humans , Linear Models , Multivariate Analysis , Obesity , Physical Distancing , Severity of Illness Index , Sex Factors , Smoking/physiopathology , Survival Analysis , Urbanization
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