Estimates of the case hospitalization rate and case fatality rate when hospital care is available for monkeypox (MPX) infections have not been well defined. This rapid systematic review and meta-analysis aimed to estimate the case hospitalisation rate and case fatality rate where hospital care is available. We systematically searched PubMed, Embase, the Lancet Preprints, and MedRxiv for studies published between Jan 1, 1950 and Aug 2, 2022. We included documents which contained both the number of cases and associated hospitalisations of MPX infections. From eligible studies we extracted the country, the year of the study, the study design type, the clade of MPX, the participant characteristics, transmission type, any treatments used, number of cases (including suspected, probable, or laboratory confirmed diagnosis), number of hospitalizations, hospitalized patient outcomes, and case definition. Case hospitalization rate (CHR) was defined as the proportion of cases that were admitted to hospital care while case fatality rate (CFR) was defined as the proportion of cases that died. CHR and CFR were analysed in a fully Bayesian meta-analytic framework using random effects models, including sub-group analysis with heterogeneity assessed using I². Of the 259 unique documents identified, 19 studies were eligible for inclusion. Included studies represented 7553 reported cases among which there were 555 hospitalizations. Of the 7540 cases for which outcomes were available, there were 15 recorded deaths. The median age of cases was 35 years (interquartile range 28–38, n = 2010) and primarily male (7339/7489, 98%) in studies where age or sex were available. Combined CHR was estimated to be 14.1% (95% credible interval, 7.5–25.0, I² 97.4%), with a high degree of heterogeneity. Further analysis by outbreak period indicates CHRs of 49.8% (28.2–74.0, I² 81.4%), 21.7% (7.2–52.1, I² 57.7%), and 5.8% (3.2–9.4, I² 92.4%) during the pre-2017, 2017–2021, and 2022 outbreaks, respectively, again with high levels of heterogeneity. CFR was estimated to be 0.03% (0.0–0.44, I² 99.9%), with evidence of large heterogeneity between the studies. There is limited data for MPX hospitalization rates in countries where MPX has been traditionally non-endemic until the current outbreak. Due to substantial heterogeneity, caution is needed when interpreting these findings. Health care organizations should be cognizant of the potential increase in healthcare utilization. Rapid identification of infection and use of appropriate therapies such as antivirals play a role reducing the CHR and associated CFR. None.

COVID-19 Symptoms by Variant, North Carolina

COVID-19 has disproportionately affected older adults. Frailty has been associated with impaired vaccine response in other vaccine types, but the impact of frailty on mRNA vaccine response is undefined. Observational study of adults aged 55 and older from 1 U.S. health care system between January 22, 2021 and September 16, 2021 with self-reported Moderna or Pfizer COVID-19 mRNA vaccine and an electronic frailty index (eFI) score from their medical record (n = 1 677). Participants’ frailty status was compared with positive antibody detection (seroconversion) following full vaccination and subsequent loss of positive antibody detection (seroreversion) using logistic regression models. Of 1 677 older adults with median (interquartile range) age, 67 (62 and 72) years, and frailty status (nonfrail: 879 [52%], prefrail: 678 [40%], and frail: 120 [7.2%]), seroconversion was not detected in 23 (1.4%) over 60 days following full vaccination. Frail individuals were less likely to seroconvert than nonfrail individuals, adjusted odds ratio (OR) 3.75, 95% confidence interval (CI; 1.04, 13.5). Seroreversion was detected in 50/1 631 individuals (3.1%) over 6 months of median follow-up antibody testing. Frail individuals were more likely to serorevert than nonfrail individuals, adjusted OR 3.02, 95% CI (1.17, 7.33). Overall antibody response to COVID-19 mRNA vaccination was high across age and frailty categories. While antibody detection is an incomplete descriptor of vaccine response, the high sensitivity of this antibody combined with health-system data reinforce our conclusions that frailty is an independent predictor of impaired antibody response to the COVID-19 mRNA vaccines. Frailty should be considered in vaccine studies and prevention strategies.

Objective: Emerging infectious diseases challenge healthcare systems to implement new models of care. We aim to evaluate the rapid implementation of a new care model for monkeypox in our health system. Design: This is a retrospective case series evaluation under the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework of implementation of a testing and care model for monkeypox in a large, integrated health system. Methods: Atrium Health implemented education of providers, testing protocols, and management of potential monkeypox cases using electronic health record (EHR) data capabilities, telehealth, and collaboration between multiple disciplines. The first 4 weeks of care model implementation were evaluated under the RE-AIM framework. Results: One hundred fifty-three patients were tested for monkeypox by 117 unique providers at urgent care, emergency departments, and infectious disease clinics in our healthcare system between 18 July 2022 and 14 August 2022. Fifty-eight monkeypox cases were identified, compared with 198 cases in the state during the time period, a disproportionate number compared with the health system service area, and 52 patients were assessed for need for tecovirimat treatment. The number of tests performed and providers sending tests increased during the study period. Conclusion: Implementation of a dedicated care model leveraging EHR data support, telehealth, and cross-disciplinary collaboration led to more effective identification and management of emerging infectious diseases and is important for public health. Plain Language Summary: Impact of care model implementation on monkeypox New infectious diseases challenge health systems to implement new care practices. Our health system responded to this challenge by implementing a care model for education, testing, and clinical care of monkeypox patients. We analyzed results from implementing the model. We were able to identify a disproportionate number of monkeypox cases compared with the rest of our state by using our model to educate medical providers, encourage testing, and ensure patients had access to best disease care. Implementation of care models for testing and management of new diseases will improve patient care and public health.

Background: The COVID-19 pandemic resulted in a massive disruption in access to care and thus passive, hospital- and clinic-based surveillance programs. In 2020, the reported cases of Lyme disease were the lowest both across the United States and North Carolina in recent years. During this period, human contact patterns began to shift with higher rates of greenspace utilization and outdoor activities, putting more people into contact with potential vectors and associated vector-borne diseases. Lyme disease reporting relies on passive surveillance systems, which were likely disrupted by changes in health care–seeking behavior during the pandemic. Objective: This study aimed to quantify the likely under-ascertainment of cases of Lyme disease during the COVID-19 pandemic in the United States and North Carolina. Methods: We fitted publicly available, reported Lyme disease cases for both the United States and North Carolina prior to the year 2020 to predict the number of anticipated Lyme disease cases in the absence of the pandemic using a Bayesian modeling approach. We then compared the ratio of reported cases divided by the predicted cases to quantify the number of likely under-ascertained cases. We then fitted geospatial models to further quantify the spatial distribution of the likely under-ascertained cases and characterize spatial dynamics at local scales. Results: Reported cases of Lyme Disease were lower in 2020 in both the United States and North Carolina than prior years. Our findings suggest that roughly 14,200 cases may have gone undetected given historical trends prior to the pandemic. Furthermore, we estimate that only 40% to 80% of Lyme diseases cases were detected in North Carolina between August 2020 and February 2021, the peak months of the COVID-19 pandemic in both the United States and North Carolina, with prior ascertainment rates returning to normal levels after this period. Our models suggest both strong temporal effects with higher numbers of cases reported in the summer months as well as strong geographic effects. Conclusions: Ascertainment rates of Lyme disease were highly variable during the pandemic period both at national and subnational scales. Our findings suggest that there may have been a substantial number of unreported Lyme disease cases despite an apparent increase in greenspace utilization. The use of counterfactual modeling using spatial and historical trends can provide insight into the likely numbers of missed cases. Variable ascertainment of cases has implications for passive surveillance programs, especially in the trending of disease morbidity and outbreak detection, suggesting that other methods may be appropriate for outbreak detection during disturbances to these passive surveillance systems.