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1.
Health Aff (Millwood) ; 41(3): 445-453, 2022 03.
Artigo em Inglês | MEDLINE | ID: covidwho-1690679

RESUMO

Evidence for the effectiveness of masking on SARS-CoV-2 transmission at the individual level has accumulated, but the additional benefit of community-level mandates is less certain. In this observational study of matched cohorts from 394 US counties between March 21 and October 20, 2020, we estimated the association between county-level public masking mandates and daily COVID-19 case incidence. On average, the daily case incidence per 100,000 people in masked counties compared with unmasked counties declined by 23 percent at four weeks, 33 percent at six weeks, and 16 percent across six weeks postintervention. The beneficial effect varied across regions of different population densities and political leanings. The most concentrated effects of masking mandates were seen in urban counties; the benefit of the mandates was potentially stronger within Republican-leaning counties. Although benefits were not equally distributed in all regions, masking mandates conferred benefit in reducing community case incidence during an early period of the COVID-19 pandemic.


Assuntos
COVID-19 , COVID-19/epidemiologia , COVID-19/prevenção & controle , Governo , Humanos , Incidência , Pandemias/prevenção & controle , SARS-CoV-2 , Estados Unidos/epidemiologia
2.
Front Public Health ; 9: 593417, 2021.
Artigo em Inglês | MEDLINE | ID: covidwho-1110365

RESUMO

Interest in the mathematical modeling of infectious diseases has increased due to the COVID-19 pandemic. However, many medical students do not have the required background in coding or mathematics to engage optimally in this approach. System dynamics is a methodology for implementing mathematical models as easy-to-understand stock-flow diagrams. Remarkably, creating stock-flow diagrams is the same process as creating the equivalent differential equations. Yet, its visual nature makes the process simple and intuitive. We demonstrate the simplicity of system dynamics by applying it to epidemic models including a model of COVID-19 mutation. We then discuss the ease with which far more complex models can be produced by implementing a model comprising eight differential equations of a Chikungunya epidemic from the literature. Finally, we discuss the learning environment in which the teaching of the epidemic modeling occurs. We advocate the widespread use of system dynamics to empower those who are engaged in infectious disease epidemiology, regardless of their mathematical background.


Assuntos
COVID-19 , Doenças Transmissíveis , Simulação por Computador , Modelos Teóricos , Pandemias , Algoritmos , Humanos , SARS-CoV-2
3.
J Healthc Eng ; 2020: 8862645, 2020.
Artigo em Inglês | MEDLINE | ID: covidwho-1066956

RESUMO

The COVID-19 pandemic has highlighted resource constraints in respiratory support. The oxygen transfer characteristics of a specific hollow fiber membrane dialyser was investigated with a view to repurposing the device as a low-cost, readily available blood oxygenator. Oxygen transfer in a low-flux hollow fiber dialyser with a polysulfone membrane was studied by passing first water and then blood through the dialyser in countercurrent to high-purity oxygen. Oxygen transfer rates of about 15% of the nominal 250 ml (STP)/min of a typical adult oxygen consumption rate were achieved for blood flow rates of 500 ml/min. Using two such dialysis devices in parallel could provide up to 30% of the nominal oxygen consumption. Specific hollow fiber dialysis devices operating with suitable pumps in a veno-venous access configuration could provide a cost-effective and readily available supplementation of respiratory support in the face of severe resource constraints.


Assuntos
COVID-19/terapia , Oxigenadores , Diálise Renal/instrumentação , Fenômenos Fisiológicos Sanguíneos , Estado Terminal/terapia , Desenho de Equipamento , Reutilização de Equipamento , Humanos , Modelos Biológicos , Oxigênio/metabolismo , Pandemias , SARS-CoV-2
4.
JAMA Health Forum ; 1(8): e200970, 2020 Aug 03.
Artigo em Inglês | MEDLINE | ID: covidwho-734227
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