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1.
Am J Surg ; 2022 Oct 07.
Artículo en Inglés | MEDLINE | ID: covidwho-2274613

RESUMEN

INTRODUCTION: Natural disasters may lead to increases in community violence due to broad social disruption, economic hardship, and large-scale morbidity and mortality. The effect of the COVID-19 pandemic on community violence is unknown. METHODS: Using trauma registry data on all violence-related patient presentations in Connecticut from 2018 to 2021, we compared the pattern of violence-related trauma from pre-COVID and COVID pandemic using an interrupted time series linear regression model. RESULTS: There was a 55% increase in violence-related trauma in the COVID period compared with the pre-COVID period (IRR: 1.55; 95%CI: 1.34-1.80; p-value<0.001) driven largely by penetrating injuries. This increase disproportionately impacted Black/Latinx communities (IRR: 1.61; 95%CI: 1.36-1.90; p-value<0.001). CONCLUSION: Violence-related trauma increased during the COVID-19 pandemic. Increased community violence is a significant and underappreciated negative health and social consequence of the COVID-19 pandemic, and one that excessively burdens communities already at increased risk from systemic health and social inequities.

2.
Am J Disaster Med ; 16(3): 195-202, 2021.
Artículo en Inglés | MEDLINE | ID: covidwho-1572827

RESUMEN

Connecticut was impacted severely and early on by the COVID-19 pandemic due to the state's proximity to New York City. Hartford Healthcare (HHC), one of the largest healthcare systems in New England, became integral in the state's response with a robust emergency management system already in place. In this manuscript, we review HHC's prepandemic emergency operations as well as the response of the system-wide Office of Emergency Management to the initial news of the virus and throughout the evolving pandemic. Additionally, we discuss the unique acquisition of vital critical care resources and personal protective equipment, as well as the hospital personnel distribution in response to the shifting demands of the virus. The public testing and vaccination efforts, with early consideration for at risk populations, are described as well as ethical considerations of scarce resources. To date, the vaccination effort resulted in over 70 percent of the adult population being vaccinated and with 10 percent of the population having been infected, herd immunity is eminent. Finally, the preparation for reestablishing elective procedures while experiencing a second wave of the pandemic is discussed. These descriptions may be useful for other healthcare systems in both preparation and response for future catastrophic emergencies of all types.


Asunto(s)
COVID-19 , Pandemias , Adulto , Connecticut/epidemiología , Atención a la Salud , Humanos , SARS-CoV-2
3.
Accid Anal Prev ; 162: 106399, 2021 Nov.
Artículo en Inglés | MEDLINE | ID: covidwho-1437362

RESUMEN

INTRODUCTION: Recent research suggests that COVID-19 associated stay-at-home orders, or shelter-in-place orders, have impacted intra-and-interstate travel as well as motor vehicle crashes (crashes). We sought to further this research and to understand the impact of the stay-at-home order on crashes in the post order period in Connecticut. METHODS: We used a multiple-comparison group, interrupted time-series analysis design to compare crashes per 100 million vehicle miles traveled (VMT) per week in 2020 to the average of 2017-2019 from January 1-August 31. We stratified crash rate by severity and the number of vehicles involved. We modeled two interruption points reflecting the weeks Connecticut implemented (March 23rd, week 12) and rescinded (May 20th, week 20) its stay-at-home order. RESULTS: During the initial week of the stay-at-home order in Connecticut, there was an additional 28 single vehicle crashes compared to previous years (95% confidence interval (CI): [15.8, 36.8]). However, the increase at the order onset was not seen throughout the duration. Rescinding the stay-at-home order by and large did not result in an immediate increase in crash rates. Crash rates steadily returned to previous year averages during the post-stay-at-home period. Fatal crash rates were unaffected by the stay-at-home order and remained similar to previous year rates throughout the study duration. DISCUSSION: The initial onset of the stay-at-home order in Connecticut was associated with a sharp increase in the single vehicle crash rate but that increase was not sustained for the remainder of the stay-at-home order. Likely changes in driver characteristics during and after the order kept fatal crash rates similar to previous years.


Asunto(s)
Conducción de Automóvil , COVID-19 , Accidentes de Tránsito , Connecticut/epidemiología , Humanos , Vehículos a Motor , SARS-CoV-2
4.
Case Rep Surg ; 2021: 5531557, 2021.
Artículo en Inglés | MEDLINE | ID: covidwho-1354598

RESUMEN

The community spread of COVID-19 is well known and has been rigorously studied since the onset of the pandemic; however, little is known about the risk of transmission to hospitalized patients. Many practices have been adopted by healthcare facilities to protect patients and staff by attempting to mitigate internal spread of the disease; however, these practices are highly variable among institutions, and it is difficult to identify which interventions are both practical and impactful. Our institution, for example, adopted the most rigorous infection control methods in an effort to keep patients and staff as safe as possible throughout the pandemic. This case report details the hospital courses of two trauma patients, both of whom tested negative for the COVID-19 virus multiple times prior to producing positive tests late in their hospital courses. The two patients share many common features including history of psychiatric illness, significant injuries, ICU stays, one-to-one observers, multiple consulting services, and a prolonged hospital course prior to discharge to a rehabilitation facility. Analysis of these hospital courses can help provide a better understanding of potential risk factors for acquisition of a nosocomial COVID-19 infection and insight into which measures may be most effective in preventing future occurrences. This is important to consider not only for COVID-19 but also for future novel infectious diseases.

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