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Nature ; 584(7820): 262-267, 2020 08.
Artículo en Inglés | MEDLINE | ID: mdl-32512578

RESUMEN

Governments around the world are responding to the coronavirus disease 2019 (COVID-19) pandemic1, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with unprecedented policies designed to slow the growth rate of infections. Many policies, such as closing schools and restricting populations to their homes, impose large and visible costs on society; however, their benefits cannot be directly observed and are currently understood only through process-based simulations2-4. Here we compile data on 1,700 local, regional and national non-pharmaceutical interventions that were deployed in the ongoing pandemic across localities in China, South Korea, Italy, Iran, France and the United States. We then apply reduced-form econometric methods, commonly used to measure the effect of policies on economic growth5,6, to empirically evaluate the effect that these anti-contagion policies have had on the growth rate of infections. In the absence of policy actions, we estimate that early infections of COVID-19 exhibit exponential growth rates of approximately 38% per day. We find that anti-contagion policies have significantly and substantially slowed this growth. Some policies have different effects on different populations, but we obtain consistent evidence that the policy packages that were deployed to reduce the rate of transmission achieved large, beneficial and measurable health outcomes. We estimate that across these 6 countries, interventions prevented or delayed on the order of 61 million confirmed cases, corresponding to averting approximately 495 million total infections. These findings may help to inform decisions regarding whether or when these policies should be deployed, intensified or lifted, and they can support policy-making in the more than 180 other countries in which COVID-19 has been reported7.


Asunto(s)
Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/prevención & control , Pandemias/prevención & control , Neumonía Viral/epidemiología , Neumonía Viral/prevención & control , Cuarentena/métodos , Número Básico de Reproducción , COVID-19 , China/epidemiología , Infecciones por Coronavirus/mortalidad , Infecciones por Coronavirus/transmisión , Francia/epidemiología , Humanos , Irán/epidemiología , Italia/epidemiología , Neumonía Viral/mortalidad , Neumonía Viral/transmisión , República de Corea/epidemiología , Instituciones Académicas/organización & administración , Aislamiento Social , Estados Unidos/epidemiología
3.
Sci Data ; 9(1): 524, 2022 08 27.
Artículo en Inglés | MEDLINE | ID: mdl-36030259

RESUMEN

Water quality monitoring can inform policies that address pollution; however, inconsistent measurement and reporting practices render many observations incomparable across bodies of water, thereby impeding efforts to characterize spatial patterns and long-term trends in pollution. Here, we harmonized 9.2 million publicly available monitor readings from 226 distinct water monitoring authorities spanning the entirety of the Mississippi/Atchafalaya River Basin (MARB) in the United States. We created the Standardized Nitrogen and Phosphorus Dataset (SNAPD), a novel dataset of 4.8 million standardized observations for nitrogen- and phosphorus-containing compounds from 107 thousand sites during 1980-2018. To the best of our knowledge, this dataset represents the largest record of these pollutants in a single river network where measurements can be compared across time and space. We addressed numerous well-documented issues associated with the reporting and interpretation of these water quality data, heretofore unaddressed at this scale, and our approach to water quality data processing can be applied to other nutrient compounds and regions.

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