Demographic Determinants and Geographical Variability of COVID-19 Vaccine Hesitancy in Underserved Communities: Cross-sectional Study.

BACKGROUND: COVID-19 hospitalizations and deaths disproportionately affect underserved and minority populations, emphasizing that vaccine hesitancy can be an especially important public health risk factor in these populations. OBJECTIVE: This study aims to characterize COVID-19 vaccine hesitancy in underserved diverse populations. METHODS: The Minority and Rural Coronavirus Insights Study (MRCIS) recruited a convenience sample of adults (age≥18, N=3735) from federally qualified health centers (FQHCs) in California, the Midwest (Illinois/Ohio), Florida, and Louisiana and collected baseline data in November 2020-April 2021. Vaccine hesitancy status was defined as a response of "no" or "undecided" to the question "Would you get a coronavirus vaccine if it was available?" ("yes" categorized as not hesitant). Cross-sectional descriptive analyses and logistic regression models examined vaccine hesitancy prevalence by age, gender, race/ethnicity, and geography. The expected vaccine hesitancy estimates for the general population were calculated for the study counties using published county-level data. Crude associations with demographic characteristics within each region were assessed using the chi-square test. The main effect model included age, gender, race/ethnicity, and geographical region to estimate adjusted odds ratios (ORs) and 95% CIs. Interactions between geography and each demographic characteristic were evaluated in separate models. RESULTS: The strongest vaccine hesitancy variability was by geographic region: California, 27.8% (range 25.0%-30.6%); the Midwest, 31.4% (range 27.3%-35.4%); Louisiana, 59.1% (range 56.1%-62.1%); and Florida, 67.3% (range 64.3%-70.2%). The expected estimates for the general population were lower: 9.7% (California), 15.3% (Midwest), 18.2% (Florida), and 27.0% (Louisiana). The demographic patterns also varied by geography. An inverted U-shaped age pattern was found, with the highest prevalence among ages 25-34 years in Florida (n=88, 80.0%,) and Louisiana (n=54, 79.4%; P<.05). Females were more hesitant than males in the Midwest (n= 110, 36.4% vs n= 48, 23.5%), Florida (n=458, 71.6% vs n=195, 59.3%), and Louisiana (n= 425, 66.5% vs. n=172, 46.5%; P<.05). Racial/ethnic differences were found in California, with the highest prevalence among non-Hispanic Black participants (n=86, 45.5%), and in Florida, with the highest among Hispanic (n=567, 69.3%) participants (P<.05), but not in the Midwest and Louisiana. The main effect model confirmed the U-shaped association with age: strongest association with age 25-34 years (OR 2.29, 95% CI 1.74-3.01). Statistical interactions of gender and race/ethnicity with the region were significant, following the pattern found by the crude analysis. Compared to males in California, the associations with the female gender were strongest in Florida (OR=7.88, 95% CI 5.96-10.41) and Louisiana (OR=6.09, 95% CI 4.55-8.14). Compared to non-Hispanic White participants in California, the strongest associations were found with being Hispanic in Florida (OR=11.18, 95% CI 7.01-17.85) and Black in Louisiana (OR=8.94, 95% CI 5.53-14.47). However, the strongest race/ethnicity variability was observed within California and Florida: the ORs varied 4.6- and 2-fold between racial/ethnic groups in these regions, respectively. CONCLUSIONS: These findings highlight the role of local contextual factors in driving vaccine hesitancy and its demographic patterns.

Ten Years of the Nepal Ambulance Service: Successful and Sustainable Efforts.

We describe the evolution of the nonprofit Nepal Ambulance Service (NAS) in a narrative of its 10-y history, presenting geographical, social, cultural, and financial considerations that permeated the development of NAS. We gathered narrative information from the NAS leadership and partners to detail key organizational considerations regarding the implementation and maintenance of the prehospital system in Nepal. We describe the response of NAS to the 2015 earthquake and summarize transport data for 6 mo before and 6 mo after the event. The data collected included the date and time of calls received, time to ambulance dispatch, on-scene time, time to arrival at the hospital, time until the ambulance crew was back in service, patient age and sex, chief complaints, and work shift time of the ambulance crew. To characterize the time to response and transport after the 2015 earthquake, we present the means and standard deviations of the time intervals. There was an overall increase in calls and, specifically, trauma-related calls after the 2015 earthquake. The time from a call placed to dispatch was stable, approximately 2 min, throughout the period, whereas the time from dispatch to the scene and arrival at the scene varied widely. We discuss the response to coronavirus disease 2019 (COVID-19). The NAS provided care to 1230 patients with COVID-19. The descriptive data show how well NAS responded to a major national disaster and the recent pandemic.

Acceleration of opioid-related EMS runs in the spring of 2020: The National Emergency Medical Services Information System data for 2018-2020.

BACKGROUND: State- and county-level reports suggest that the COVID-19 pandemic exacerbated the opioid crisis. We examined US national trends of nonfatal opioid overdose in 2020 in comparison to pre-COVID years 2018-2019. METHODS: We used National Emergency Medical Services Information System (NEMSIS) data to conduct a temporal analysis from 2018 to 2020. Opioid-related EMS run was defined using five scenarios of naloxone administration. To determine annual patterns and slope inflection points, we used the Prophet model of the time series analysis. Linear slopes and their 95% confidence intervals (CIs) were calculated for pre-stay-at-home (pre-SaH) and SaH periods in 2020 and compared to the slopes during the same time in 2018-2019. Three cut-points for SaH start were considered: March 19, 24, and 29. RESULTS: We identified 91,065, 144,802, and 242,904 opioid-related EMS runs in 2018-2020, respectively. In 2020, opioid-related runs increased in January-June, with a pronounced acceleration in March, which coincides with the stay-at-home (SaH) orders. In both 2018 and 2019, opioid-related runs increased in January-August without the spring acceleration. In 2020, weekly increases (95% CI) during SaH for all examined cut-points were significantly greater than in pre-SaH: 18.09 (16.03-20.16) vs. 6.44 (3.42-9.47) for March 19, 17.77 (15.57-19.98) vs. 4.85 (2.07-7.64) for March 24, 18.03 (15.68-20.39) vs. 4.97(2.4-7.54) for March 29. No significant difference was found between these periods in 2018-2019. CONCLUSIONS: The acceleration of opioid-related EMS runs during the SaH period of 2020 suggests that EMS data may serve as an early warning system for local health jurisdictions to deploy harm reduction/prevention resources.