Relationship between Telework Experience and Presenteeism during COVID-19 Pandemic,United States,March–November 2020

Persons with COVID-19–like illnesses are advised to stay home to reduce the spread of SARS-CoV-2. We assessed relationships between telework experience and COVID-19 illness with work attendance when ill. Adults experiencing fever, cough, or loss of taste or smell who sought healthcare or COVID-19 testing in the United States during March–November 2020 were enrolled. Adults with telework experience before illness were more likely to work at all (onsite or remotely) during illness (87.8%) than those with no telework experience (49.9%) (adjusted odds ratio 5.48, 95% CI 3.40–8.83). COVID-19 case-patients were less likely to work onsite (22.1%) than were persons with other acute respiratory illnesses (37.3%) (adjusted odds ratio 0.36, 95% CI 0.24–0.53). Among COVID-19 case-patients with telework experience, only 6.5% worked onsite during illness. Telework experience before illness gave mildly ill workers the option to work and improved compliance with public health recommendations to stay home during illness.     

The Impact of Funding Inpatient Treatments for COVID-19 on Health Equity in the United States: A Distributional Cost-Effectiveness Analysis

ObjectivesWe conducted a distributional cost-effectiveness analysis (DCEA) to evaluate how Medicare funding of inpatient COVID-19 treatments affected health equity in the United States.MethodsA DCEA, based on an existing cost-effectiveness analysis model, was conducted from the perspective of a single US payer, Medicare. The US population was divided based on race and ethnicity (Hispanic, non-Hispanic black, and non-Hispanic white) and county-level social vulnerability index (5 quintile groups) into 15 equity-relevant subgroups. The baseline distribution of quality-adjusted life expectancy was estimated across the equity subgroups. Opportunity costs were estimated by converting total spend on COVID-19 inpatient treatments into health losses, expressed as quality-adjusted life-years (QALYs), using base-case assumptions of an opportunity cost threshold of $150 000 per QALY gained and an equal distribution of opportunity costs across equity-relevant subgroups.ResultsMore socially vulnerable populations received larger per capita health benefits due to higher COVID-19 incidence and baseline in-hospital mortality. The total direct medical cost of inpatient COVID-19 interventions in the United States in 2020 was estimated at $25.83 billion with an estimated net benefit of 735 569 QALYs after adjusting for opportunity costs. Funding inpatient COVID-19 treatment reduced the population-level burden of health inequality by 0.234%. Conclusions remained robust across scenario and sensitivity analyses.ConclusionsTo the best of our knowledge, this is the first DCEA to quantify the equity implications of funding COVID-19 treatments in the United States. Medicare funding of COVID-19 treatments in the United States could improve overall health while reducing existing health inequalities.     

Coccidioidomycosis and COVID-19 Co-Infection,United States, 2020

We review the interaction between coronavirus disease (COVID-19) and coccidioidomycosis, a respiratory infection caused by inhalation of Coccidioides fungal spores in dust. We examine risk for co-infection among construction and agricultural workers, incarcerated persons, Black and Latino populations, and persons living in high dust areas. We further identify common risk factors for co-infection, including older age, diabetes, immunosuppression, racial or ethnic minority status, and smoking. Because these diseases cause similar symptoms, the COVID-19 pandemic might exacerbate delays in coccidioidomycosis diagnosis, potentially interfering with prompt administration of antifungal therapies. Finally, we examine the clinical implications of co-infection, including severe COVID-19 and reactivation of latent coccidioidomycosis. Physicians should consider coccidioidomycosis as a possible diagnosis when treating patients with respiratory symptoms. Preventive measures such as wearing face masks might mitigate exposure to dust and severe acute respiratory syndrome coronavirus 2, thereby protecting against both infections.     

A cross-sectional analysis of the association between social capital and willingness to get COVID-19 vaccine in Ontario,Canada

ObjectiveWe examine the role of social capital in intention to take the vaccine at the end of the first wave of the COVID-19 pandemic.MethodsThis study uses observational, cross-sectional data from the Ontario sample of the fall 2020 Canadian Community Health Survey (CCHS), a representative sample of the population with added questions relative to symptoms of COVID-19 and intentions to get vaccinated. Questions on social capital were asked to respondents from Ontario only, yielding a sample of 6516. Odds ratios (OR) and marginal effects at sample mean of an index of social capital (at the individual or aggregated level) on changes in intentions to get vaccinated are estimated from logistic regression models.ResultsIndividual-level social capital is associated with greater willingness to get vaccinated against COVID-19 (OR 1.09). Associations with aggregated-level social capital are less precisely estimated. Associations are the same for both males and females but vary across age categories: individual-level social capital is associated with higher willingness to get vaccinated among working-age respondents, but aggregate-level social capital is associated with higher willingness to get vaccinated among older adults.ConclusionVaccine hesitancy is not a random phenomenon, nor is it explained by individual characteristics such as education or income only. It also reflects the state of the social environment in which individuals live and public health messaging should take this into account if it is to be successful.Supplementary InformationThe online version contains supplementary material available at 10.17269/s41997-023-00746-9.     

Association between social vulnerability and COVID-19 vaccination hesitancy and vaccination in pregnant and postpartum individuals

ObjectiveTo evaluate the association of community-level social vulnerability with COVID-19 vaccine hesitancy and vaccination among pregnant and postpartum individuals.MethodsProspective cohort study assessing COVID-19 vaccine hesitancy among pregnant and postpartum individuals. We performed a baseline survey on COVID-19 vaccine hesitancy from 03/22/21 to 04/02/21, and a follow-up survey on COVD-19 vaccination status 3- to 6-months later. The primary exposure was the Centers for Disease Control and Prevention SVI (Social Vulnerability Index), measured in quartiles. Higher SVI quartiles indicated greater community-level social vulnerability with the lowest quartile (quartile 1) as the referent group. The primary outcome was COVID-19 vaccine hesitancy on the baseline survey (uncertainty or refusal of the vaccine), and the secondary outcome was self-report of not being vaccinated (unvaccinated) for COVID-19 on the follow-up survey.ResultsOf 456 assessed individuals, 46% reported COVID-19 vaccine hesitancy on the baseline survey; and of 290 individuals (290/456, 64%) who completed the follow-up survey, 48% (140/290) were unvaccinated. The frequency of baseline vaccine hesitancy ranged from 25% in quartile 1 (low SVI) to 68% in quartile 4 (high SVI), and being unvaccinated at follow-up ranged from 29% in quartile 1 to 77% in quartile 4. As social vulnerability increased, the risk of COVID-19 vaccine hesitancy at baseline increased (quartile 2 aRR (adjusted relative risk): 1.46; 95% CI:0.98 to 2.19; quartile 3 aRR: 1.86; 95% CI:1.28 to 2.71; and quartile 4 aRR: 2.24; 95% CI:1.56 to 3.21), as did the risk of being unvaccinated at follow-up (quartile 2 aRR: 1.00; 95% CI:0.66 to 1.51; quartile 3 aRR: 1.68; 95% CI:1.17 to 2.41; and quartile 4 aRR: 1.82; 95% CI:1.30 to 2.56).ConclusionsPregnant and postpartum individuals living in an area with higher community-level social vulnerability were more likely to report COVID-19 vaccine hesitancy and subsequently to be unvaccinated at follow-up.     

COVID-19 testing,case, and death rates and spatial socio-demographics in New York City: An ecological analysis as of June 2020

We assessed the geographic variation in socio-demographics, mobility, and built environmental factors in relation to COVID-19 testing, case, and death rates in New York City (NYC). COVID-19 rates (as of June 10, 2020), relevant socio-demographic information, and built environment characteristics were aggregated by ZIP Code Tabulation Area (ZCTA). Spatially adjusted multivariable regression models were fitted to account for spatial autocorrelation. The results show that different sets of neighborhood characteristics were independently associated with COVID-19 testing, case, and death rates. For example, the proportions of Blacks and Hispanics in a ZCTA were positively associated with COVID-19 case rate. Contrary to the conventional hypothesis, neighborhoods with low-density housing experienced higher COVID-19 case rates. In addition, demographic changes (e.g. out-migration) during the pandemic may bias the estimates of COVID-19 rates. Future research should further investigate these neighborhood-level factors and their interactions over time to better understand the mechanisms by which they affect COVID-19.     

COVID-19 vaccine intentions in the United States,a social-ecological framework

BackgroundCOVID-19 vaccine hesitancy is a major obstacle for pandemic mitigation. As vaccine hesitancy occurs along multiple dimensions, we used a social-ecological framework to guide the examination of COVID-19 vaccine intentions.MethodsUsing an online survey in the US conducted in July 2020, we examined intentions to obtain a COVID-19 vaccine, once available. 592 respondents provided data, including measures of demographics, vaccine history, social norms, perceived risk, and trust in sources of COVID-19 information. Bivariate and multivariate multinomial models were used to compare respondents who intended to be vaccinated against COVID-19 to respondents who did not intend or were ambivalent about COVID-19 vaccination.ResultsOnly 59.1% of the sample reported that they intended to obtain a COVID-19 vaccine. In the multivariate multinomial model, those respondents who did not intend to be vaccinated, as compared to those who did, had significantly lower levels of trust in the CDC as a source of COVID-19 information (aOR = 0.29, CI = 0.17–0.50), reported lower social norms of COVID-19 preventive behaviors (aOR = 0.67, CI 0.51–0.88), scored higher on COVID-19 Skepticism (aOR = 1.44, CI = 1.28–1.61), identified as more politically conservative (aOR = 1.23, CI = 1.05–1.45), were less likely to have obtained a flu vaccine in the prior year (aOR = 0.21, CI = 0.11–0.39), were less likely to be female (aOR = 0.51, CI = 0.29–0.87), and were much more likely to be Black compared to White (aOR = 10.70, CI = 4.09–28.1). A highly similar pattern was observed among those who were ambivalent about receiving a COVID-19 vaccine compared to those who intended to receive one.ConclusionThe results of this study suggest several avenues for COVID-19 vaccine promotion campaigns, including social network diffusion strategies and cross-partisan messaging, to promote vaccine trust. The racial and gender differences in vaccine intentions also suggest the need to tailor campaigns based on gender and race.     

Impact of reduced human papillomavirus vaccination coverage rates due to COVID-19 in the United States: A model based analysis

The coronavirus disease 2019 (COVID-19) pandemic has significantly affected utilization of preventative health care, including vaccines. We aimed to assess HPV vaccination rates during the pandemic, and conduct a simulation model-based analysis to estimate the impact of current coverage and future pandemic recovery scenarios on disease outcomes. The model population included females and males of all ages in the US. The model compares pre-COVID vaccine uptake to 3 reduced coverage scenarios with varying recovery speed. Vaccine coverage was obtained from Truven Marketscan™. Substantially reduced coverage between March-August 2020 was observed compared to 2018–2019. The model predicted that 130,853 to 213,926 additional cases of genital warts; 22,503 to 48,157 cases of CIN1; 48,682 to 110,192 cases of CIN2/3; and 2,882 to 6,487 cases of cervical cancer will occur over the next 100 years, compared to status quo. Providers should plan efforts to recover HPV vaccination and minimize potential long-term consequences.     

COVID-19 vaccine hesitancy cannot fully explain disparities in vaccination coverage across the contiguous United States

Vaccine hesitancy has been identified as a major obstacle preventing comprehensive coverage against the COVID-19 pandemic. However, few studies have analyzed the association between ex-ante vaccine hesitancy and ex-post vaccination coverage. This study leveraged one-year county-level data across the contiguous United States to examine whether the prospective vaccine hesitancy eventually translates into differential vaccination rates, and whether vaccine hesitancy can explain socioeconomic, racial, and partisan disparities in vaccine uptake. A set of structural equation modeling was fitted with vaccine hesitancy and vaccination rate as endogenous variables, controlling for various potential confounders. The results demonstrated a significant negative link between vaccine hesitancy and vaccination rate, with the difference between the two continuously widening over time. Counties with higher socioeconomic statuses, more Asian and Hispanic populations, more elderly residents, greater health insurance coverage, and more Democrats presented lower vaccine hesitancy and higher vaccination rates. However, underlying determinants of vaccination coverage and vaccine hesitancy were divergent regarding their different associations with exogenous variables. Mediation analysis further demonstrated that indirect effects from exogenous variables to vaccination coverage via vaccine hesitancy only partially explained corresponding total effects, challenging the popular narrative that portrays vaccine hesitancy as a root cause of disparities in vaccination. Our study highlights the need of well-funded, targeted, and ongoing initiatives to reduce persisting vaccination inequities.     

An exploratory study of COVID-19-related changes in abortion service availability and use in Washington,DC, Maryland,and Virginia

Objectives

This exploratory study aimed to assess COVID-19-related changes in abortion service availability and use in Washington, DC, Maryland, and Virginia.

Design

Data came from a convenience sample of eight abortion clinics in this region. We implemented a cross-sectional survey and collected retrospective aggregate monthly abortion data overall and by facility type, abortion type, and patient characteristics for March 2019–August 2020. We evaluated changes in the distribution of the total number of patients for March–August in 2019 compared to March–August 2020. We also conducted segmented regression analyses and produced scatter plots of monthly abortion patients overall and by facility type, abortion type, and patient characteristics, with separate fitted regression lines from the segmented regression models for the pre- and during-COVID-19 periods.

Results

Five clinics reported a reduced number of appointments early in the pandemic while four reported increased call volume. There were declines in the monthly abortion trend at hospital-based clinics at the outset of the pandemic. Monthly number of medication abortions increased from March 2020 through August 2020 compared to pre-COVID-19 trends while instrumentation abortions 11 up to 19 weeks decreased. The share of abortions to Black individuals increased during the early phase of the pandemic, as did the monthly trend in abortions among this group. We also saw changes in payment type, with declines in patients paying out-of-pocket.

Conclusions

Results revealed differences in abortion services, numbers, and types during the early stages of the COVID-19 pandemic in Washington, DC, Maryland, and Virginia.     

COVID-19 Symptoms and Deaths among Healthcare Workers,United States

We evaluated whether demographics and COVID-19 symptoms predicted COVID-19 deaths among healthcare workers (HCWs) in the United States by comparing COVID-19 deaths in HCWs with 3 control groups (HCW nondeaths, non-HCW deaths, and non-HCW nondeaths) using a case–control design. We obtained patient-level data of 33 variables reported during January 1, 2020–October 12, 2021, in all US states. We used logistic regression analysis while controlling for confounders. We found that persons who were >50 years of age, male, Black, or Asian experienced significantly more deaths than matched controls. In addition, HCWs who died had higher risks for the most severe clinical indicators. We also found that the most indicative symptoms were preexisting medical conditions, shortness of breath, fever, cough, and gastrointestinal symptoms. In summary, minority, male, and older HCWs had greater risk for COVID-19 death. Severe clinical indicators and specific symptoms may predict COVID-19–related deaths among HCWs.     

United States Influenza Search Patterns Since the Emergence of COVID-19: Infodemiology Study

BackgroundThe emergence and media coverage of COVID-19 may have affected influenza search patterns, possibly affecting influenza surveillance results using Google Trends.ObjectiveWe aimed to investigate if the emergence of COVID-19 was associated with modifications in influenza search patterns in the United States.MethodsWe retrieved US Google Trends data (relative number of searches for specified terms) for the topics influenza, Coronavirus disease 2019, and symptoms shared between influenza and COVID-19. We calculated the correlations between influenza and COVID-19 search data for a 1-year period after the first COVID-19 diagnosis in the United States (January 21, 2020 to January 20, 2021). We constructed a seasonal autoregressive integrated moving average model and compared predicted search volumes, using the 4 previous years, with Google Trends relative search volume data. We built a similar model for shared symptoms data. We also assessed correlations for the past 5 years between Google Trends influenza data, US Centers for Diseases Control and Prevention influenza-like illness data, and influenza media coverage data.ResultsWe observed a nonsignificant weak correlation (ρ= –0.171; P=0.23) between COVID-19 and influenza Google Trends data. Influenza search volumes for 2020-2021 distinctly deviated from values predicted by seasonal autoregressive integrated moving average models—for 6 weeks within the first 13 weeks after the first COVID-19 infection was confirmed in the United States, the observed volume of searches was higher than the upper bound of 95% confidence intervals for predicted values. Similar results were observed for shared symptoms with influenza and COVID-19 data. The correlation between Google Trends influenza data and CDC influenza-like-illness data decreased after the emergence of COVID-19 (2020-2021: ρ=0.643; 2019-2020: ρ=0.902), while the correlation between Google Trends influenza data and influenza media coverage volume remained stable (2020-2021: ρ=0.746; 2019-2020: ρ=0.707).ConclusionsRelevant differences were observed between predicted and observed influenza Google Trends data the year after the onset of the COVID-19 pandemic in the United States. Such differences are possibly due to media coverage, suggesting limitations to the use of Google Trends as a flu surveillance tool.     

COVID-19 Vaccination Coverage,Behaviors, and Intentions among Adults with Previous Diagnosis,United States

To determine the extent of gaps in coronavirus disease (COVID-19) vaccine coverage among those in the United States with and without previous COVID-19 diagnoses, we used July 21–August 2, 2021, data from a large, nationally representative survey (Household Pulse Survey). We analyzed vaccine receipt (≥1 dose and full vaccination) and intention to be vaccinated for 63,266 persons. Vaccination receipt was lower among those who had a prior diagnosis of COVID-19 compared to those without: >1 dose: 73% and 85%, respectively, p<0.001; full vaccination: 69% and 82%, respectively, p<0.001). Reluctance to be vaccinated was higher among those with a previous COVID-19 diagnosis (14%) than among those without (9%). These findings suggest the need to focus educational and confidence-building interventions on adults when they receive a COVID-19 diagnosis, during clinic visits, or at the time of discharge if hospitalized and to better educate the public about the value of being vaccinated, regardless of previous COVID-19 status.     

COVID-19 Response Strategies at Large Institutes of Higher Education in the United States: A Landscape Analysis,Fall 2020

PurposeTo examine the pandemic response plans of institutes of higher education (i.e., colleges and universities), including COVID-19 prevention, enforcement, and testing strategies.MethodData from the largest public (n = 50) and private (n = 50) US institutes of higher education were collected from October 30 to November 20, 2020.ResultsMost institutes of higher education (n = 93) offered some in-person teaching in the Fall 2020 semester; most adopted masking (100%) and physical distancing (99%) mandates. Other preventive strategies included on-campus housing de-densification (58%), classroom de-densification (61%), mandated COVID-19-related training (39%), and behavioral compacts (43%). Testing strategies included entry testing (65%), testing at regular intervals (32%), population sample testing (46%), and exit testing (15%). More private than public institutes implemented intercollegiate athletics bans, behavioral compacts, and suspension clauses for noncompliance.ConclusionsVariability in COVID-19 prevention and testing strategies highlights the need for national recommendations and the equitable distribution of sufficient pandemic response resources to institutes of higher education.     

福建省新型冠状病毒肺炎疫情趋势分析

目的  分析福建省新型冠状病毒肺炎(COVID-19)疫情趋势和预测时空聚集性, 为风险评估和防控提供参考。 方法  对福建省2020年1月2日―2020年2月18日COVID-19发病数进行时空趋势分析和预测。 结果  福建省2020年1月2日―2020年2月18日COVID-19报告发病数为293例, 无死亡。各时间点累计报告县(区)数(累计报告数)依次为:1月19日22个(35例)、1月26日53个(159例)、2月2日57个(244例)、2月18日61个(293例)。局部空间自相关分析提示, 截至2月18日, 鼓楼、仓山、闽侯、福清等福州县(区)热点性质为高聚集区。截至1月26日, 时空聚集区快速蔓延, 一级和二级聚集区多达7个, 分别以鲤城、涵江、思明、连江、沙县、古田和湄北为中心, 其中以鲤城和思明为中心预测发生于1月27日―2月18日, 期望发病数分别为54和24例。截至2月18日, 时空聚集区减少至2个, 分别以城厢和南安为中心。 结论  泉州、福州、莆田等市的部分县(区)COVID-19时空聚集风险较大, 应重点防控, 但低风险聚集区也不应忽视。     

Lack of association between vaccination rates and excess mortality in Cyprus during the COVID-19 pandemic

BackgroundIt has been claimed that COVID-19 vaccination is associated with excess mortality during the COVID-19 pandemic, a claim that contributes to vaccine hesitancy. We examined whether all-cause mortality has actually increased in Cyprus during the first two pandemic years, and whether any increases are associated with vaccination rates.MethodsWe calculated weekly excess mortality for Cyprus between January 2020 and June 2022, overall and by age group, using both a Distributed Lag Nonlinear Model (DLNM) adjusted for mean daily temperature, and the EuroMOMO algorithm. Excess deaths were regressed on the weekly number of confirmed COVID-19 deaths and on weekly first-dose vaccinations, also using a DLNM to explore the lag-response dimension.Results552 excess deaths were observed in Cyprus during the study period (95% CI: 508–597) as opposed to 1306 confirmed COVID-19 deaths. No association between excess deaths and vaccination rates was found overall and for any age group except 18–49 years, among whom 1.09 excess deaths (95% CI: 0.27–1.91) per 10,000 vaccinations were estimated during the first 8 weeks post-vaccination. However, detailed cause-of-death examination identified just two such deaths potentially linked to vaccination, therefore this association is spurious and attributable to random error.ConclusionsExcess mortality was moderately increased in Cyprus during the COVID-19 pandemic, primarily as a result of laboratory-confirmed COVID-19 deaths. No relationship was found between vaccination rates and all-cause mortality, demonstrating the excellent safety profile of COVID-19 vaccines.     

A retrospective analysis of social media posts pertaining to COVID-19 vaccination side effects

ObjectivesWith an uprising influence of social media platforms like Twitter and Instagram a multitude of worldwide accessible information is available. Since the beginning of COVID-19 pandemic the exchange of medical information about several topics related to this infectious disease and its vaccination has increased rapidly. The purpose of this investigation was to assess the content associated with COVID-19 vaccination and its side effects and evaluate its educational quality.MethodsWe conducted this retrospective study to investigate 600 Twitter and Instagram posts by #covidvaccinesideeffects due to number of ‘likes’, comments, type of post, language, its purpose and source. In addition, posts were evaluated due to educational quality by three examiners of different educational levels.ResultsThe majority of posts showed 0 to 50 “likes” and 0 to 5 comments in English language. A comparison between Twitter and Instagram by the influence of application showed significant differences in number of posts and “likes” or comments (p < 0.05). The major post type were texts for Twitter (251; 83.7%) and videos for Instagram (104; 34.7%). While a majority of posts by #covidvaccinesideeffects report about the occurrence of side effects, the majority of them were mild and general COVID-19 vaccination feedback during the first 4 months was positive. But, only 3 to 7% were rated by “excellent” educational and validatable content. Interrater reliability between all three examiners presented a high concordance with 89% (p = 0.001).ConclusionsThis study presents an analysis of quantity and quality of social media content according to COVID-19 vaccinations and its side effects. It supports the deduction that most of the content on Twitter and Instagram is shared by patients and unclear sources and thus is limited informative. Nevertheless, influence of social media on medical information especially during COVID-19 pandemic is increasing and practitioners have to face its effect on their patients.     

Ecological Analysis of the Decline in Incidence Rates of COVID-19 Among Nursing Home Residents Associated with Vaccination,United States,December 2020-January 2021

ObjectiveTo evaluate if facility-level vaccination after an initial vaccination clinic was independently associated with COVID-19 incidence adjusted for other factors in January 2021 among nursing home residents.DesignEcological analysis of data from the CDC's National Healthcare Safety Network (NHSN) and from the CDC's Pharmacy Partnership for Long-Term Care Program.Setting and ParticipantsCMS-certified nursing homes participating in both NHSN and the Pharmacy Partnership for Long-Term Care Program.MethodsA multivariable, random intercepts, negative binomial model was applied to contrast COVID-19 incidence rates among residents living in facilities with an initial vaccination clinic during the week ending January 3, 2021 (n = 2843), vs those living in facilities with no vaccination clinic reported up to and including the week ending January 10, 2021 (n = 3216). Model covariates included bed size, resident SARS-CoV-2 testing, staff with COVID-19, cumulative COVID-19 among residents, residents admitted with COVID-19, community county incidence, and county social vulnerability index (SVI).ResultsIn December 2020 and January 2021, incidence of COVID-19 among nursing home residents declined to the lowest point since reporting began in May, diverged from the pattern in community cases, and began dropping before vaccination occurred. Comparing week 3 following an initial vaccination clinic vs week 2, the adjusted reduction in COVID-19 rate in vaccinated facilities was 27% greater than the reduction in facilities where vaccination clinics had not yet occurred (95% confidence interval: 14%-38%, P < .05).Conclusions and ImplicationsVaccination of residents contributed to the decline in COVID-19 incidence in nursing homes; however, other factors also contributed. The decline in COVID-19 was evident prior to widespread vaccination, highlighting the benefit of a multifaced approach to prevention including continued use of recommended screening, testing, and infection prevention practices as well as vaccination to keep residents in nursing homes safe.