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Why India Cannot Rise With Weak State Capacity

TIME - Tech

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The Fight Over Who Counts in India

TIME - Tech

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Epidemiology and transmission dynamics of COVID-19 in two Indian states

Science

By August 2020, India had reported several million cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with cases tending to show a younger age distribution than has been reported in higher-income countries. Laxminarayan et al. analyzed data from the Indian states of Tamil Nadu and Andhra Pradesh, which have developed rigorous contact tracing and testing systems (see the Perspective by John and Kang). Superspreading predominated, with 5% of infected individuals accounting for 80% of cases. Enhanced transmission risk was apparent among children and young adults, who accounted for one-third of cases. Deaths were concentrated in 50- to 64-year-olds. Incidence did not change in older age groups, possibly because of effective stay-at-home orders and social welfare programs or socioeconomic status. As in other settings, however, mortality rates were associated with older age, comorbidities, and being male. Science , this issue p. [691][1]; see also p. [663][2] Although most cases of coronavirus disease 2019 (COVID-19) have occurred in low-resource countries, little is known about the epidemiology of the disease in such contexts. Data from the Indian states of Tamil Nadu and Andhra Pradesh provide a detailed view into severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission pathways and mortality in a high-incidence setting. Reported cases and deaths have been concentrated in younger cohorts than would be expected from observations in higher-income countries, even after accounting for demographic differences across settings. Among 575,071 individuals exposed to 84,965 confirmed cases, infection probabilities ranged from 4.7 to 10.7% for low-risk and high-risk contact types, respectively. Same-age contacts were associated with the greatest infection risk. Case fatality ratios spanned 0.05% at ages of 5 to 17 years to 16.6% at ages of 85 years or more. Primary data from low-resource countries are urgently needed to guide control measures. [1]: /lookup/doi/10.1126/science.abd7672 [2]: /lookup/doi/10.1126/science.abe9707


Can technology help in dealing with natural disasters? - Express Computer

#artificialintelligence

Every year during the monsoon period, India faces a deluge of floods. Almost every year, it is common to see one or two Indian states being badly affected by floods. Most recently, in Bihar, more than 1,400 villages in 15 districts were marooned due to flooding. In 2019 alone, more than 13 Indian states (Kerala, Gujarat, Karnataka, Maharashtra, Madhya Pradesh, Andhra Pradesh, Odisha) have been affected due to floods. Government reports state that this year has been witness to the heaviest monsoon rains to wreck havoc in India in the last 25 years.


Can technology help in dealing with natural disasters? - Express Computer

#artificialintelligence

Every year during the monsoon period, India faces a deluge of floods. Almost every year, it is common to see one or two Indian states being badly affected by floods. Most recently, in Bihar, more than 1,400 villages in 15 districts were marooned due to flooding. In 2019 alone, more than 13 Indian states (Kerala, Gujarat, Karnataka, Maharashtra, Madhya Pradesh, Andhra Pradesh, Odisha) have been affected due to floods. Government reports state that this year has been witness to the heaviest monsoon rains to wreck havoc in India in the last 25 years.