Model training periods impact estimation of COVID-19 incidence from wastewater viral loads.

Wastewater-based epidemiology (WBE) has been deployed broadly as an early warning tool for emerging COVID-19 outbreaks. WBE can inform targeted interventions and identify communities with high transmission, enabling quick and effective responses. As the wastewater (WW) becomes an increasingly important indicator for COVID-19 transmission, more robust methods and metrics are needed to guide public health decision-making. This research aimed to develop and implement a mathematical framework to infer incident cases of COVID-19 from SARS-CoV-2 levels measured in WW. We propose a classification scheme to assess the adequacy of model training periods based on clinical testing rates and assess the sensitivity of model predictions to training periods. A testing period is classified as adequate when the rate of change in testing is greater than the rate of change in cases. We present a Bayesian deconvolution and linear regression model to estimate COVID-19 cases from WW data. The effective reproductive number is estimated from reconstructed cases using WW. The proposed modeling framework was applied to three Northern California communities served by distinct WW treatment plants. The results showed that training periods with adequate testing are essential to provide accurate projections of COVID-19 incidence.

Testing and vaccination to reduce the impact of COVID-19 in nursing homes: an agent-based approach.

BACKGROUND: Efforts to protect residents in nursing homes involve non-pharmaceutical interventions, testing, and vaccine. We sought to quantify the effect of testing and vaccine strategies on the attack rate, length of the epidemic, and hospitalization. METHODS: We developed an agent-based model to simulate the dynamics of SARS-CoV-2 transmission among resident and staff agents in a nursing home. Interactions between 172 residents and 170 staff based on data from a nursing home in Los Angeles, CA. Scenarios were simulated assuming different levels of non-pharmaceutical interventions, testing frequencies, and vaccine efficacy to reduce transmission. RESULTS: Under the hypothetical scenario of widespread SARS-CoV-2 in the community, 3-day testing frequency minimized the attack rate and the time to eradicate an outbreak. Prioritization of vaccine among staff or staff and residents minimized the cumulative number of infections and hospitalization, particularly in the scenario of high probability of an introduction. Reducing the probability of a viral introduction eased the demand on testing and vaccination rate to decrease infections and hospitalizations. CONCLUSIONS: Improving frequency of testing from 7-days to 3-days minimized the number of infections and hospitalizations, despite widespread community transmission. Vaccine prioritization of staff provides the best protection strategy when the risk of viral introduction is high.

Healthy Davis Together: Creating a Model for Community Control of COVID-19.

While many higher-education institutions dramatically altered their operations and helped mitigate COVID-19 transmission on campuses, these efforts were rarely fully extended to surrounding communities. A community pandemic-response program was launched in a college town that deployed epidemiological infection-control measures and health behavior change interventions. An increase in self-reported preventive health behaviors and a lower relative case positivity proportion were observed. The program identified scalable approaches that may generalize to other college towns and community types. Building public health infrastructure with such programs may be pivotal in promoting health in the postpandemic era. (Am J Public Health. 2022;112(8):1142-1146. https://doi.org/10.2105/AJPH.2022.306880).

The impact of COVID-19 vaccination on California's return to normalcy.

SARS-CoV-2 has infected nearly 3.7 million and killed 61,722 Californians, as of May 22, 2021. Non-pharmaceutical interventions have been instrumental in mitigating the spread of the coronavirus. However, as we ease restrictions, widespread implementation of COVID-19 vaccines is essential to prevent its resurgence. In this work, we addressed the adequacy and deficiency of vaccine uptake within California and the possibility and severity of resurgence of COVID-19 as restrictions are lifted given the current vaccination rates. We implemented a real-time Bayesian data assimilation approach to provide projections of incident cases and deaths in California following the reopening of its economy on June 15, 2021. We implemented scenarios that vary vaccine uptake prior to reopening, and transmission rates and effective population sizes following the reopening. For comparison purposes, we adopted a baseline scenario using the current vaccination rates, which projects a total 11,429 cases and 429 deaths in a 15-day period after reopening. We used posterior estimates based on CA historical data to provide realistic model parameters after reopening. When the transmission rate is increased after reopening, we projected an increase in cases by 21.8% and deaths by 4.4% above the baseline after reopening. When the effective population is increased after reopening, we observed an increase in cases by 51.8% and deaths by 12.3% above baseline. A 30% reduction in vaccine uptake alone has the potential to increase cases and deaths by 35% and 21.6%, respectively. Conversely, increasing vaccine uptake by 30% could decrease cases and deaths by 26.1% and 17.9%, respectively. As California unfolds its plan to reopen its economy on June 15, 2021, it is critical that social distancing and public behavior changes continue to be promoted, particularly in communities with low vaccine uptake. The Centers for Disease Control and Prevention (CDC) recommendation to ease mask-wearing for fully vaccinated individuals despite major inequities in vaccine uptake in counties across the state highlights some of the logistical challenges that society faces as we enthusiastically phase out of this pandemic.

Parameter identifiability and optimal control of an SARS-CoV-2 model early in the pandemic.

We fit an SARS-CoV-2 model to US data of COVID-19 cases and deaths. We conclude that the model is not structurally identifiable. We make the model identifiable by prefixing some of the parameters from external information. Practical identifiability of the model through Monte Carlo simulations reveals that two of the parameters may not be practically identifiable. With thus identified parameters, we set up an optimal control problem with social distancing and isolation as control variables. We investigate two scenarios: the controls are applied for the entire duration and the controls are applied only for the period of time. Our results show that if the controls are applied early in the epidemic, the reduction in the infected classes is at least an order of magnitude higher compared to when controls are applied with 2-week delay. Further, removing the controls before the pandemic ends leads to rebound of the infected classes.

Using Non-Pharmaceutical Interventions and High Isolation of Asymptomatic Carriers to Contain the Spread of SARS-CoV-2 in Nursing Homes.

More than 40% of the deaths recorded in the first wave of the SARS-CoV-2 pandemic were linked to nursing homes. Not only are the residents of long-term care facilities (LTCFs) typically older and more susceptible to endemic infections, the facilities' high degree of connection to wider communities makes them especially vulnerable to local COVID-19 outbreaks. In 2008, in the wake of the SARS-CoV-1 and MERS epidemics and anticipating an influenza pandemic, we created a stochastic compartmental model to evaluate the deployment of non-pharmaceutical interventions (NPIs) in LTCFs during influenza epidemics. In that model, the most effective NPI by far was a staff schedule consisting of 5-day duty periods with onsite residence, followed by an 4-to-5 day off-duty period with a 3-day quarantine period just prior to the return to work. Unlike influenza, COVID-19 appears to have significant rates of pre-symptomatic transmission. In this study, we modified our prior modeling framework to include new parameters and a set of NPIs to identify and control the degree of pre-symptomatic transmission. We found that infections, deaths, hospitalizations, and ICU utilization were projected to be high and largely irreducible, even with rigorous application of all defined NPIs, unless pre-symptomatic carriers can be identified and isolated at high rates. We found that increasingly rigorous application of NPIs is likely to significantly decrease the peak of infections; but even with complete isolation of symptomatic persons, and a 50% reduction in silent transmission, the attack rate is projected to be nearly 95%.

Anxiety During the COVID-19 Pandemic: A Web-Based Survey of Thyroid Cancer Survivors.

OBJECTIVE: Cancer patients and survivors may be disproportionately affected by COVID-19. We sought to determine the effects of the pandemic on thyroid cancer survivors' health care interactions and quality of life. METHODS: An anonymous survey including questions about COVID-19 and the Patient-Reported Outcomes Measurement Information System profile (PROMIS-29, version 2.0) was hosted on the Thyroid Cancer Survivors' Association, Inc website. PROMIS scores were compared to previously published data. Factors associated with greater anxiety were evaluated with univariable and multivariable logistic regression. RESULTS: From May 6, 2020, to October 8, 2020, 413 participants consented to take the survey; 378 (92%) met the inclusion criteria: diagnosed with thyroid cancer or noninvasive follicular neoplasm with papillary-like nuclear features, located within the United States, and completed all sections of the survey. The mean age was 53 years, 89% were women, and 74% had papillary thyroid cancer. Most respondents agreed/strongly agreed (83%) that their lives were very different during the COVID-19 pandemic, as were their interactions with doctors (79%). A minority (43%) were satisfied with the information from their doctor regarding COVID-19 changes. Compared to pre-COVID-19, PROMIS scores were higher for anxiety (57.8 vs 56.5; P < .05) and lower for the ability to participate in social activities (46.2 vs 48.1; P < .01), fatigue (55.8 vs 57.9; P < .01), and sleep disturbance (54.7 vs 56.1; P < .01). After adjusting for confounders, higher anxiety was associated with younger age (P < .01) and change in treatment plan (P = .04). CONCLUSION: During the COVID-19 pandemic, thyroid cancer survivors reported increased anxiety compared to a pre-COVID cohort. To deliver comprehensive care, providers must better understand patient concerns and improve communication about potential changes to treatment plans.

The Role of SARS-CoV-2 Testing on Hospitalizations in California.

The rapid spread of the new SARS-CoV-2 virus triggered a global health crisis, disproportionately impacting people with pre-existing health conditions and particular demographic and socioeconomic characteristics. One of the main concerns of governments has been to avoid health systems becoming overwhelmed. For this reason, they have implemented a series of non-pharmaceutical measures to control the spread of the virus, with mass tests being one of the most effective controls. To date, public health officials continue to promote some of these measures, mainly due to delays in mass vaccination and the emergence of new virus strains. In this research, we studied the association between COVID-19 positivity rate and hospitalization rates at the county level in California using a mixed linear model. The analysis was performed in the three waves of confirmed COVID-19 cases registered in the state to September 2021. Our findings suggest that test positivity rate is consistently associated with hospitalization rates at the county level for all study waves. Demographic factors that seem to be related to higher hospitalization rates changed over time, as the profile of the pandemic impacted different fractions of the population in counties across California.

COVID-19 hospitalizations in five California hospitals: a retrospective cohort study.

BACKGROUND: The novel coronavirus pandemic has had a differential impact on communities of color across the US. The University of California hospital system serves a large population of people who are often underrepresented elsewhere. Data from hospital stays can provide much-needed localized information on risk factors for severe cases and/or death. METHODS: Patient-level retrospective case series of laboratory-confirmed COVID-19 hospital admissions at five UC hospitals (N = 4730). Odds ratios of ICU admission, death, and a composite of both outcomes were calculated with univariate and multivariate logistic regression based on patient characteristics, including sex, race/ethnicity, and select comorbidities. Associations between comorbidities were quantified and visualized with a correlation network. RESULTS: Overall mortality rate was 7.0% (329/4,730). ICU mortality rate was 18.8% (225/1,194). The rate of the composite outcome (ICU admission and/or death) was 27.4% (1298/4730). Comorbidity-controlled odds of a composite outcome were increased for age 75-84 (OR 1.47, 95% CI 1.11-1.93) and 85-59 (OR 1.39, 95% CI 1.04-1.87) compared to 18-34 year-olds, males (OR 1.39, 95% CI 1.21-1.59) vs. females, and patients identifying as Hispanic/Latino (OR 1.35, 95% CI 1.14-1.61) or Asian (OR 1.43, 95% CI 1.23-1.82) compared to White. Patients with 5 or more comorbidities were exceedingly likely to experience a composite outcome (OR 2.74, 95% CI 2.32-3.25). CONCLUSIONS: Males, older patients, those with multiple pre-existing comorbidities, and those identifying as Hispanic/Latino or Asian experienced an increased risk of ICU admission and/or death. These results are consistent with reported risks among the Hispanic/Latino population elsewhere in the United States, and confirm multiple concerns about heightened risk among the Asian population in California.

Anxiety and Fear During the Covid-19 Pandemic: A Web-Based Survey of Thyroid Cancer Survivors

Background: The coronavirus (COVID-19) pandemic has led to rapid changes in our society and healthcare system. Cancer patients and survivors may be disproportionately affected by these changes, including decreased access to healthcare, increased infection risk, and economic challenges. We sought to determine the effects of the pandemic on thyroid cancer survivors’ quality of life. Methods: An anonymous web-based survey was administered in collaboration with ThyCa: Thyroid Cancer Survivors’ Association, consisting of questions about (1) demographics, (2) thyroid cancer clinical characteristics, (3) attitudes toward and impact of COVID-19, and (4) the Patient-Reported Outcomes Measurement Information System (PROMIS) 29-item profile. The survey was linked on the ThyCa homepage. PROMIS measures were scored using item response theory models with a T-score metric relative to U.S. reference data via the HealthMeasures Scoring Service (https://www.healthmeasures.net). T-scores were analyzed using Mann-Whitney U, Wilcoxon signed-rank, Kruskal-Wallis, and Spearman’s rank correlation tests. Results: From 5/6/2020 - 10/8/2020, 505 participants accessed the survey, and all completed surveys by U.S.-based thyroid cancer survivors were analyzed (n=378, 75%). Mean age was 53 years, 89% were female, 90% were white, 74% had papillary thyroid cancer, 97% had surgery, and 70% received radioactive iodine. The vast majority agreed or strongly agreed (83%) that their lives were very different during COVID-19, as was the way they interacted with their doctors (79%). Less than half (43%) agreed or strongly agreed that they were satisfied with the amount of information from their doctor’s office regarding COVID-19 changes. Compared to previously-published PROMIS data for this population, T-scores were significantly higher in the domain of anxiety/fear (57.8 vs. 56.5, p&lt;0.01) and lower for ability to participate in social roles and activities (46.2 vs. 48.1, p&lt;0.01). Younger age was weakly correlated with greater anxiety/fear (Spearman’s rho=-0.38, p&lt;0.01), and greater anxiety/fear was associated with pending treatment (p&lt;0.01), lower cancer stage (p=0.01), and female sex (p=0.02). Conclusions: During the COVID-19 pandemic, thyroid cancer survivors reported increased anxiety/fear and decreased social participation. In our efforts to care for patients both physically and mentally as the pandemic continues, we must better understand their fears and concerns and improve communication about potential changes to their care.

Identification of Functional Limitations and Discharge Destination in Patients With COVID-19.

OBJECTIVES: The objectives of this study were to identify functional limitations in patients with coronavirus 2019 (COVID-19) admitted to acute care hospitals; to evaluate functional limitations by demographic, medical, and encounter characteristics; and to examine functional limitations in relation to discharge destination. DESIGN: and Setting:This is a cross-sectional, retrospective study of adult patients with COVID-19 who were discharged from 2 different types of hospitals (academic medical center and a community hospital) within 1 health care system from January 1 to April 30, 2020. PARTICIPANTS: Patients were identified from the Cedars-Sinai COVID-19 data registry who had a new-onset positive test for severe acute respiratory syndrome coronavirus 2. A total of 273 patients were identified, which included 230 patients who were discharged alive and 43 patients who died and were excluded from the study sample. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Functional limitations in patients with COVID-19 in acute care hospitals and the predictors for discharge disposition. RESULTS: A total of 230 records were analyzed including demographic, encounter, medical, and functional variables. In a propensity score-matched cohort based on age and comorbidity, 88.2% had functional physical health deficits, 72.5% had functional mental health deficits, and 17.6% experienced sensory deficits. In the matched cohort, individuals discharged to an institution experienced greater physical (62.7% vs 25.5%, P<.001) and mental health (49.0% vs 23.5%, P=.006) deficits than patients discharged home. Marital status (odds ratio, 3.17; P=.011) and physical function deficits (odds ratio, 3.63; P=.025) were associated with an increase odds ratio of discharge to an institution. CONCLUSIONS: This research highlights that functional status is a strong predictor for discharge destination to an institution for patients with COVID-19. Patients who were older, in the acute care hospital longer, and with comorbidities were more likely to be discharged to an institution. Rehabilitation is a significant aspect of the health care system for these vulnerable patients. The challenges of adjusting the role of rehabilitation providers and systems during the pandemic needs further exploration. Moreover, additional research is needed to look more closely at the many facets and timing of functional status needs, to shed light in use of interdisciplinary rehabilitation services, and to guide providers and health care systems in facilitating optimal recovery and patient outcomes.