Modeling and Predicting Epidemic Spread: A Gaussian Process Regression Approach (preprint)

Modeling and prediction of epidemic spread are critical to assist in policy-making for mitigation. Therefore, we present a new method based on Gaussian Process Regression to model and predict epidemics, and it quantifies prediction confidence through variance and high probability error bounds. Gaussian Process Regression excels in using small datasets and providing uncertainty bounds, and both of these properties are critical in modeling and predicting epidemic spreading processes with limited data. However, the derivation of formal uncertainty bounds remains lacking when using Gaussian Process Regression in the setting of epidemics, which limits its usefulness in guiding mitigation efforts. Therefore, in this work, we develop a novel bound on the variance of the prediction that quantifies the impact of the epidemic data on the predictions we make. Further, we develop a high probability error bound on the prediction, and we quantify how the epidemic spread, the infection data, and the length of the prediction horizon all affect this error bound. We also show that the error stays below a certain threshold based on the length of the prediction horizon. To illustrate this framework, we leverage Gaussian Process Regression to model and predict COVID-19 using real-world infection data from the United Kingdom.

Reverse Engineering the Reproduction Number: A Framework for Data-Driven Counterfactual Analysis, Strategy Evaluation, and Feedback Control of Epidemics (preprint)

During the COVID-19 pandemic, different countries, regions, and communities constructed various epidemic models to evaluate spreading behaviors and assist in making mitigation policies. Model uncertainties, introduced by complex transmission behaviors, contact-tracing networks, time-varying spreading parameters, and human factors, as well as insufficient data, have posed arduous challenges for model-based approaches. To address these challenges, we propose a novel framework for data-driven counterfactual analysis, strategy evaluation, and feedback control of epidemics, which leverages statistical information from epidemic testing data instead of constructing a specific model. Through reverse engineering the reproduction number by quantifying the impact of the intervention strategy, this framework tackles three primary problems: 1) How severe would an outbreak have been without the implemented intervention strategies? 2) What impact would varying the intervention strength have had on an outbreak? 3) How can we adjust the intervention intensity based on the current state of an outbreak? Specifically, we consider the epidemic intervention policies such as the testing-for-isolation strategy as an example, which was successfully implemented by the University of Illinois Urbana-Champaign (UIUC) and Purdue University (Purdue) during the COVID-19 pandemic. By leveraging data collected by UIUC and Purdue, we validate the effectiveness of the proposed data-driven framework.

Differentially Private Computation of Basic Reproduction Numbers in Networked Epidemic Models (preprint)

The basic reproduction number of a networked epidemic model, denoted $R_0$, can be computed from a network's topology to quantify epidemic spread. However, disclosure of $R_0$ risks revealing sensitive information about the underlying network, such as an individual's relationships within a social network. Therefore, we propose a framework to compute and release $R_0$ in a differentially private way. First, we provide a new result that shows how $R_0$ can be used to bound the level of penetration of an epidemic within a single community as a motivation for the need of privacy, which may also be of independent interest. We next develop a privacy mechanism to formally safeguard the edge weights in the underlying network when computing $R_0$. Then we formalize tradeoffs between the level of privacy and the accuracy of values of the privatized $R_0$. To show the utility of the private $R_0$ in practice, we use it to bound this level of penetration under privacy, and concentration bounds on these analyses show they remain accurate with privacy implemented. We apply our results to real travel data gathered during the spread of COVID-19, and we show that, under real-world conditions, we can compute $R_0$ in a differentially private way while incurring errors as low as $7.6\%$ on average.

Analysis and Applications of Population Flows in a Networked SEIRS Epidemic Process (preprint)

Transportation networks play a critical part in the spread of infectious diseases between populations. In this work, we define a networked susceptible-exposed-infected-recovered epidemic process with loss of immunity over time (SEIRS) that explicitly models the flow of individuals between sub-populations, which serves as the propagating mechanism for infection. We provide sufficient conditions for local stability and instability of the healthy state of the system and show that no perturbation of population flows can change the local stability of any healthy state. We also provide sufficient conditions for the existence and uniqueness of an endemic state. We then develop tools and methods for applying our model to real-world data, including spreading parameter estimation and disease arrival time prediction, and apply them in a case study using both travel and infection data from counties in Minnesota during the first year of the COVID-19 pandemic.

Change time estimation uncertainty in nonlinear dynamical systems with applications to COVID‐19

The impact that each individual non‐pharmaceutical intervention (NPI) had on the spread rate of COVID‐19 is difficult to estimate, since several NPIs were implemented in rapid succession in most countries. In this article, we analyze the detectability of sudden changes in a parameter of nonlinear dynamical systems, which could be used to represent NPIs or mutations of the virus, in the presence of measurement noise. Specifically, by taking an agnostic approach, we provide necessary conditions for when the best possible unbiased estimator is able to isolate the effect of a sudden change in a model parameter, by using the Hammersley–Chapman–Robbins (HCR) lower bound. Several simplifications to the calculation of the HCR lower bound are given, which depend on the amplitude of the sudden change and the dynamics of the system. We further define the concept of the most informative sample based on the largest ℓ2 distance between two output trajectories, which is a good indicator of when the HCR lower bound converges. These results are thereafter used to analyze the susceptible‐infected‐removed model. For instance, we show that performing analysis using the number of recovered/deceased, as opposed to the cumulative number of infected, may be an inferior signal to use since sudden changes are fundamentally more difficult to estimate and seem to require more samples. Finally, these results are verified by simulations and applied to real data from the spread of COVID‐19 in France. [ FROM AUTHOR] Copyright of International Journal of Robust & Nonlinear Control is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Acceptability of serosurveys in southern Zambia: data collector and caregiver perspectives.

Background: Factors associated with whether individuals choose to participate in serosurveys are not well understood. Understanding perceptions from multiple perspectives, including the perspectives of both data collectors and participants, through a holistic model such as the socio-ecological model contextualizes individual, interpersonal, and structural level influences on survey research participation. We used a multiple methods approach to characterize reasons for serosurvey participation in communities in Southern Province, Zambia where a serosurvey was conducted in 2016. Methods: The first phase conducted focus group discussions and in-depth interviews with 24 data collectors who participated in a measles-rubella serosurvey in 2016. The second phase surveyed 34 caregivers at health facilities to identify barriers and facilitators to serosurvey participation. Emergent themes were then classified into a socio-ecological model using individual, interpersonal, and structural level constructs. Results: Common themes emerged from data collectors as well as caregivers surveyed. At the individual level, providing incentives was a facilitator, and some religious beliefs were described as a barrier to serosurvey participation. At the interpersonal level, family dynamics and community peer influences could help or hinder serosurvey participation. Community health workers were consistently named as facilitators of participation. At the structural level, concerns about specimen collection, who was selected for serosurveys, and not receiving test results arose as potential barriers. The most frequently reported facilitator was provision of information about the purpose of the serosurvey (85% of respondents). The most frequently reported barrier was lack of clarity regarding use of their blood specimen (53% of respondents). For specimen collection type, caregivers consistently preferred finger prick blood collection over both venous blood draw and oral swabs. Conclusion: Serosurvey participation was deemed acceptable to most study participants. The socio-ecological model revealed barriers and facilitators for participation to guide strategies to improve participation which can be applied to ongoing serosurveys for SARS-CoV-2. Serosurveys should continue to develop engagement plans to provide information about blood collection ahead of the serosurvey and communicate the objectives of such studies through trusted sources such as community health workers and traditional leaders.

Clinical Characteristics, Racial Inequities, and Outcomes in Patients with Breast Cancer and COVID-19: A COVID-19 and Cancer Consortium (CCC19) Cohort Study (preprint)

Title: Clinical Characteristics, Racial Inequities, and Outcomes in Patients with Breast Cancer and COVID-19: A COVID-19 and Cancer Consortium (CCC19) Cohort Study Background: Limited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations. Methods: This is a COVID-19 and Cancer Consortium (CCC19) registry-based retrospective cohort study of females with active or history of BC and laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection diagnosed between March 2020 and June 2021 in the US. Primary outcome was COVID-19 severity measured on a five-level ordinal scale, including none of the following complications, hospitalization, intensive care unit admission, mechanical ventilation, and all-cause mortality. Multivariable ordinal logistic regression model identified characteristics associated with COVID-19 severity. Results: 1,383 female patient records with BC and COVID-19 were included in the analysis, the median age was 61 years, and median follow-up was 90 days. Multivariable analysis revealed higher odds of COVID-19 severity for older age (aOR per decade, 1.48 [95% CI, 1.32 - 1.67]); Black patients (aOR 1.74; 95 CI 1.24-2.45), Asian Americans and Pacific Islander patients (aOR 3.40; 95 CI 1.70 - 6.79) and Other (aOR 2.97; 95 CI 1.71-5.17) racial/ethnic groups; worse ECOG performance status (ECOG PS [≥]2: aOR, 7.78 [95% CI, 4.83 - 12.5]); pre-existing cardiovascular (aOR, 2.26 [95% CI, 1.63 - 3.15])/pulmonary comorbidities (aOR, 1.65 [95% CI, 1.20 - 2.29]); diabetes mellitus (aOR, 2.25 [95% CI, 1.66 - 3.04]); and active and progressing cancer (aOR, 12.5 [95% CI, 6.89 - 22.6]). Hispanic ethnicity, timing and type of anti-cancer therapy modalities were not significantly associated with worse COVID-19 outcomes. The total all-cause mortality and hospitalization rate for the entire cohort was 9% and 37%, respectively however, it varied according to the BC disease status. Conclusions: Using one of the largest registries on cancer and COVID-19, we identified patient and BC related factors associated with worse COVID-19 outcomes. After adjusting for baseline characteristics, underrepresented racial/ethnic patients experienced worse outcomes compared to Non-Hispanic White patients. Funding: This study was partly supported by National Cancer Institute grant number P30 CA068485 to Tianyi Sun, Sanjay Mishra, Benjamin French, Jeremy L. Warner; P30-CA046592 to Christopher R. Friese; P30 CA023100 for Rana R McKay; P30-CA054174 for Pankil K. Shah and Dimpy P. Shah; and the American Cancer Society and Hope Foundation for Cancer Research (MRSG-16-152-01 -CCE) and P30-CA054174 for Dimpy P. Shah. REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research grant support (UL1 TR000445 from NCATS/NIH). The funding sources had no role in the writing of the manuscript or the decision to submit it for publication. Clinical trial number: CCC19 registry is registered on ClinicalTrials.gov, NCT04354701.

Social Media Use by Residents and Faculty in Otolaryngology Training Programs.

OBJECTIVES: Despite the growth of social media in healthcare, the appropriateness of online friendships between otolaryngological residents and attendings is poorly defined in the current literature. This issue is of growing importance, particularly as residency programs increasingly utilize social media as a means of connecting with and evaluating applicants due to limited in-person experiences during the COVID-19 pandemic. Our objective was to better understand the prevalence of and concerns surrounding social media use between residents and faculty. METHODS: This study sent out 2 surveys in 2017 to all United States Otolaryngology residency program directors to disperse to their residents and attendings, respectively. RESULTS: We received a response from 72 residents and 98 attendings. Our findings show that social media is commonly used by both residents and attendings, and most residents have at least 1 online friendship with an attending. Resident and attending opinions diverge on topics such as appropriateness of use, privacy settings, and professionalism. CONCLUSIONS: We call on residency programs to delineate a transparent social media policy so applicant expectations on social media are clear.

Simulation Method for Testing Aerosol Mitigation Strategies: An Observational Study.

BACKGROUND: Frontline health care workers who perform potentially aerosol-generating procedures, such as endotracheal intubations, in patients with coronavirus disease 2019 may be at an increased risk of exposure to severe acute respiratory syndrome coronavirus 2. To continue to care for patients with coronavirus disease 2019, minimizing exposure is paramount. Using simulation, we devised a testing method to evaluate devices that may mitigate the spread of aerosol and droplet-sized particles. METHODS: In this prospective single-center study, participants intubated a manikin 3 times using standard personal protective equipment, once with no barrier device, once with an acrylic box, and once with a modified horizontal drape. The micrometer-sized particle count, generated by a nebulization model, was recorded before and after each intubation. The first-pass intubation rate and time to intubation were recorded. Each operator completed a postsimulation survey about their experience using the barrier devices. RESULTS: Thirty airway proceduralists completed the simulation and survey. There was no significant difference in particle counts (aerosols or droplets) or first-pass intubation, but the horizontal drape was found to significantly increase intubation time (P = 0.01). Most participants preferred the drape over the acrylic box or no barrier device. CONCLUSIONS: The acrylic box and plastic drape did not mitigate particle spread. However, our testing method can be used to test barrier designs using negative pressure or other mitigation strategies for particle spread.

The Modified and Extended Hospital Elder Life Program: A remote model of care to expand delirium prevention.

BACKGROUND: Delirium is a common complication of hospitalization and is associated with poor outcomes. Multicomponent delirium prevention strategies such as the Hospital Elder Life Program (HELP) have proven effective but rely on face-to-face intervention protocols and volunteer staff, which was not possible due to restrictions during the COVID-19 pandemic. We developed the Modified and Extended Hospital Elder Life Program (HELP-ME), an innovative adaptation of HELP for remote and/or physically distanced applications. METHODS: HELP-ME protocols were adapted from well-established multicomponent delirium prevention strategies and were implemented at four expert HELP sites. Each site contributed to the protocol modifications and compilation of a HELP-ME Operations Manual with standardized protocols and training instructions during three expert panel working groups. Implementation was overseen and monitored during seven learning sessions plus four coaching sessions from January 8, 2021, through September 24, 2021. Feasibility of implementing HELP-ME was measured by protocol adherence rates. Focus groups were conducted to evaluate the acceptability, provide feedback, and identify facilitators and barriers to implementation. RESULTS: A total of 106 patients were enrolled across four sites, and data were collected for 214 patient-days. Overall adherence was 82% (1473 completed protocols/1798 patient-days), achieving our feasibility target of >75% overall adherence. Individual adherence rates ranged from 55% to 96% across sites for the individual protocols. Protocols with high adherence rates included the nursing delirium protocol (96%), nursing medication review (96%), vision (89%), hearing (87%), and orientation (88%), whereas lower adherence occurred with fluid repletion (64%) and range-of-motion exercises (55%). Focus group feedback was generally positive for acceptability, with recommendations that an optimal approach would be hybrid, balancing in-person and remote interventions for potency and long-term sustainability. CONCLUSIONS: HELP-ME was fully implemented at four HELP sites, demonstrating feasibility and acceptability. Testing hybrid approaches and evaluating effectiveness is recommended for future work.

Uptake of public health measures and vaccine acceptance during the COVID-19 pandemic in rural Zambia.

Vaccines are effective tools to prevent COVID-19-related morbidity. However, coverage is low throughout sub-Saharan Africa. Uptake of public health measures, perceptions of COVID-19 illness and vaccines, and intention to vaccinate were evaluated in 2021-2022 in rural Zambia. Adherence to public health measures, perceptions of COVID-19 risk and severity, and vaccine acceptance increased significantly over time, particularly in December 2021, coinciding with the fourth pandemic wave and relaunch of the national vaccine campaign. Vaccine acceptance was associated with perceptions of vaccine safety and effectiveness, but not disease severity. These findings highlight the importance of strong pandemic response and public communication for increased uptake of mitigatory measures, including vaccine acceptance.

Acceptability of serosurveys in southern Zambia: surveyor and community perspectives (preprint)

Background: Factors associated with whether individuals choose to participate in serosurveys  are not well understood. Understanding perceptions from multiple perspectives, including the perspectives of both data collectors and participants through a holistic model such as the socio-ecological model contextualizes individual, interpersonal, and structural level influences on survey research participation. We used a multiple methods approach to characterize reasons for serosurvey participation in communities in Southern Province, Zambia where a serosurvey was conducted in 2016. Methods: The first phase conducted focus group discussions and in-depth interviews with 24 data collectors who participated in a measles-rubella serosurvey in 2016. The second phase surveyed 34 caregivers at health facilities to identify barriers and facilitators to serosurvey participation. Emergent themes were then classified into a socio-ecological model using individual, interpersonal, and structural level constructs. Results: Common themes emerged from data collectors as well as caregivers surveyed. At the individual level, providing incentives was a motivator, and some religious beliefs were described as a barrier to serosurvey participation. At the interpersonal level, family dynamics and community influences could help or hinder serosurvey participation.  Community health workers were consistently named as facilitators of participation. At the structural level, concerns about specimen collection, who was selected for serosurveys, and not receiving test results arose as potential barriers. The most frequently reported facilitator was provision of information about the purpose of the serosurvey (85% of respondents). The most frequently reported barrier was lack of clarity regarding use of their blood specimen (53% of respondents). For specimen collection type, caregivers consistently preferred finger prick blood collection over both venous blood draw and oral swabs. Conclusion: Serosurvey participation was deemed acceptable to most study participants. The socioecological model revealed barriers and facilitators for participation to guide strategies to improve participation which can be applied to ongoing serosurveys for SARS-CoV-2. Serosurveys should develop an engagement plan to provide information about blood collection ahead of the serosurvey and communicate the objectives of the study through a trusted source such as community health workers.

Virtual Residency Interviews during the COVID-19 Pandemic: The Applicant's Perspective.

OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic has had a profound impact on medical education at all levels, particularly on applicants applying to residency programs. The objective of the study was to gain a comprehensive understanding of applicants' perspectives on virtual interviews in the setting of the COVID-19 pandemic. METHODS: We conducted a quantitative survey and a qualitative study between March and April 2021. The link to an anonymous online survey was emailed to fourth-year medical students from one allopathic medical school. The survey link also was posted on the social media page of one allopathic medical school and one osteopathic medical school. Participants were then invited to participate in a follow-up 15- to 45-minute qualitative virtual interview. RESULTS: A total of 46 participants completed the survey, with a response rate of approximately 29.1%. The most beneficial aspect of the virtual interview was saving money on travel (31, 78.39%). In contrast, the least beneficial aspect of the virtual interview was the inability to personally explore the culture of the program (16, 34.78%), followed by the inability to explore the city and surrounding area (11, 23.91%). Thematic saturation was reached after interviewing 14 participants over Zoom. Four major themes of the virtual residency interview experience were discussed: virtual interviews offered many advantages, virtual interviews posed unique challenges, residency programs need more organizational improvements, and virtual specific preparations are needed. CONCLUSIONS: Despite the challenges associated with the virtual interview process, applicants rated the overall virtual interview experience positively. Given the continued impact of COVID-19 on medical education, the majority of residency programs will elect to continue virtual interviews for the 2022 Electronic Residency Application Services cycle. We hope that our findings may provide insight into the applicant's perspective on the virtual interview experience and help optimize virtual interviews for future cycles.

Playing catch-up in building an open research commons.

As efforts advance around the globe, the US falls behind.

Interprofessional collaboration among first responder students in a simulated disaster exercise.

INTRODUCTION: Interprofessional disaster simulation exercises provide an opportunity for first responder students to learn about disaster response and recovery, to practice their roles and to learn to collaborate with other first responders. With the move to virtual education during the COVID-19 pandemic, a table-top disaster exercise is an alternative format to inperson exercises. To date, most disaster simulation exercises for students have focused on the roles of healthcare providers. As first responders play a critical role in disaster management, there is a need for interprofessional exercises that include students in first responder programs. METHODS: A table-top disaster simulation exercise was held with students from the police (n = 94) and firefighter (n = 30) programs at a large community college in Toronto, Canada, in February 2021. It was held virtually using the Zoom® platform, with college faculty as well as professionals from community partner sites. An evaluation survey that had open- and closed-ended items was administered to students following the event. RESULTS: Thirty-eight percent of the students participated in the survey, and the majority rated the event highly useful and reported that the exercise demonstrated the importance of interprofessional collaboration. Students' responses to the open-ended survey items yielded two themes: understanding roles and performing under duress. DISCUSSION: This evaluation demonstrates the value of using a simulated disaster exercise to teach first responder students about their role in disaster response and recovery, and the importance of interprofessional collaboration.

Associations Between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants and Risk of Coronavirus Disease 2019 (COVID-19) Hospitalization Among Confirmed Cases in Washington State: A Retrospective Cohort Study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is dominated by variant viruses; the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the hospitalization risk following infection with 7 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. METHODS: Our study includes individuals with positive SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) in the Washington Disease Reporting System with available viral genome data, from 1 December 2020 to 14 January 2022. The analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for hospitalization risk following infection with a variant, adjusting for age, sex, calendar week, and vaccination. RESULTS: In total, 58 848 cases were sequenced through sentinel surveillance, of which 1705 (2.9%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.20, 95% confidence interval [CI] 2.40-4.26), Beta (HR 2.85, 95% CI 1.56-5.23), Delta (HR 2.28 95% CI 1.56-3.34), or Alpha (HR 1.64, 95% CI 1.29-2.07) compared to infections with ancestral lineages; Omicron (HR 0.92, 95% CI .56-1.52) showed no significant difference in risk. Following Alpha, Gamma, or Delta infection, unvaccinated patients show higher hospitalization risk, while vaccinated patients show no significant difference in risk, both compared to unvaccinated, ancestral lineage cases. Hospitalization risk following Omicron infection is lower with vaccination. CONCLUSIONS: Infection with Alpha, Gamma, or Delta results in a higher hospitalization risk, with vaccination attenuating that risk. Our findings support hospital preparedness, vaccination, and genomic surveillance.

Suite of TMPRSS2 Assays for Screening Drug Repurposing Candidates as Potential Treatments of COVID-19.

SARS-CoV-2 is the causative viral pathogen driving the COVID-19 pandemic that prompted an immediate global response to the development of vaccines and antiviral therapeutics. For antiviral therapeutics, drug repurposing allows for rapid movement of the existing clinical candidates and therapies into human clinical trials to be tested as COVID-19 therapies. One effective antiviral treatment strategy used early in symptom onset is to prevent viral entry. SARS-CoV-2 enters ACE2-expressing cells when the receptor-binding domain of the spike protein on the surface of SARS-CoV-2 binds to ACE2 followed by cleavage at two cut sites by TMPRSS2. Therefore, a molecule capable of inhibiting the protease activity of TMPRSS2 could be a valuable antiviral therapy. Initially, we used a fluorogenic high-throughput screening assay for the biochemical screening of 6030 compounds in NCATS annotated libraries. Then, we developed an orthogonal biochemical assay that uses mass spectrometry detection of product formation to ensure that hits from the primary screen are not assay artifacts from the fluorescent detection of product formation. Finally, we assessed the hits from the biochemical screening in a cell-based SARS-CoV-2 pseudotyped particle entry assay. Of the six molecules advanced for further studies, two are approved drugs in Japan (camostat and nafamostat), two have entered clinical trials (PCI-27483 and otamixaban), while the other two molecules are peptidomimetic inhibitors of TMPRSS2 taken from the literature that have not advanced into clinical trials (compounds 92 and 114). This work demonstrates a suite of assays for the discovery and development of new inhibitors of TMPRSS2.

Respiratory viruses in rural Zambia before and during the COVID-19 pandemic.

OBJECTIVES: With the emergence of the COVID-19 pandemic, restrictions were implemented globally to control the virus. Data on respiratory pathogens in sub-Saharan Africa during the COVID-19 pandemic are scarce. This analysis was conducted to evaluate patterns of respiratory pathogens in rural Zambia before and during the first year of the pandemic. METHODS: Surveillance was established in December 2018 at Macha Hospital in southern Zambia. Patients with respiratory symptoms in the outpatient and inpatient clinics were recruited. Nasopharyngeal samples were collected and tested for respiratory pathogens. The prevalence of respiratory symptoms and pathogens was evaluated and compared in the first (December 10, 2018-December 9, 2019) and second (December 10, 2019-November 30, 2020) years of surveillance. RESULTS: Outpatient visits and admissions for respiratory illness significantly decreased from the first to second year, especially among children. SARS-CoV-2 was not detected from any participants in Year 2. Among outpatients and inpatients with respiratory symptoms, the prevalence of respiratory syncytial virus and influenza viruses decreased from the first to second year. In contrast, the prevalence of rhinovirus/enterovirus, metapneumovirus and parainfluenza virus increased. CONCLUSIONS: The epidemiology of respiratory viruses in rural Zambia changed during the first year of the COVID-19 pandemic, suggesting that public health interventions may have had an impact on the introduction and circulation of respiratory pathogens in this area.

Rapid Cycle Implementation and Retrospective Evaluation of a SARS-CoV-2 Checklist in Labor and Delivery.

BACKGROUND: Preparedness efforts for a COVID-19 outbreak required redesign and implementation of a perioperative workflow for the management of obstetric patients. In this report we describe factors which influenced rapid cycle implementation of a novel comprehensive checklist for the perioperative care of the COVID-19 parturient. METHODS: Within our labour and delivery unit, implementation of a novel checklist for the COVID-19 parturient requiring perioperative care was accomplished through rapid cycling, debriefing and on-site walkthroughs. Post-implementation, consistent use of the checklist was reported for all obstetric COVID-19 perioperative cases (100% workflow checklist utilization). Retrospective analysis of the factors influencing implementation was performed using a group deliberation approach, mapped against the Consolidated Framework for Implementation Research (CFIR). RESULTS: Analysis of factors influencing implementation using CFIR revealed domains of process implementation and innovation characteristics as overwhelming facilitators for success. Constructs within the outer setting, inner setting, and characteristic of individuals (external pressures, baseline culture, and personal attributes) were perceived to act as early barriers. Constructs such as communication culture and learning climate, shifted in influence over time. CONCLUSION: We describe the influential factors of implementing a novel comprehensive obstetric workflow for care of the COVID-19 perioperative parturient during the first surge of the pandemic using the CFIR framework. Early workflow adoption was facilitated primarily by two domains, namely thoughtful innovation design and careful implementation planning in the setting of a long-standing culture of improvement. Factors initially assessed as barriers such as communication, culture and learning climate, transitioned into facilitators once a perceived benefit was experienced by healthcare teams. These results provide important information for the implementation of rapid change during a time of crisis.