Community-Centered Assessment to Inform Pandemic Response in Georgia (US).

The Georgia Community Engagement Alliance (CEAL) Against COVID-19 Disparities Project conducts community-engaged research and outreach to address misinformation and mistrust, to promote inclusion of diverse racial and ethnic populations in clinical trials and increase testing and vaccination uptake. Guided by its Community Coalition Board, The GEORGIA CEAL Survey was administered among Black and Latinx Georgia 18 years and older to learn about community knowledge, perceptions, understandings, and behaviors regarding COVID-19 testing and vaccines. Survey dissemination occurred using survey links generated through Qualtrics and disseminated among board members and other statewide networks. Characteristics of focus counties were (a) highest proportion of 18 years and older Black and Latinx residents; (b) lowest COVID-19 testing rates; and (c) highest SVI values. The final sample included 2082 surveyed respondents. The majority of participants were men (57.1%) and Latinx (62.8%). Approximately half of the sample was aged 18-30 (49.2%); the mean age of the sample was 33.2 years (SD = 9.0), ranging from 18 to 82 years of age. Trusted sources of COVID-19 information that significantly predicted the likelihood of vaccination included their doctor/health care provider (p-value: 0.0054), a clinic (p-value: 0.006), and university hospitals (p-value: 0.0024). Latinx/non-Latinx, Blacks vs. Latinx, Whites were significantly less likely to get tested and/or vaccinated. Non-Latinx, Blacks had higher mean knowledge scores than Latinx, Whites (12.1 vs. 10.9, p < 0.001) and Latinx, Blacks (12.1 vs. 9.6, respectively, p < 0.001). The mean knowledge score was significantly lower in men compared to women (10.3 vs. 11.0, p = 0.001), in those who had been previously tested for COVID-19 compared to those who had never been tested (10.5 vs. 11.5, respectively, p = 0.005), and in those who did not receive any dose of vaccination compared to those who were fully vaccinated (10.0 vs. 11.0, respectively, p < 0.001). These data provide a benchmark for future comparisons of the trajectory of public attitudes and practices related to the COVID-19 pandemic. They also point to the importance of tailoring communication strategies to specific cultural, racial, and ethnic groups to ensure that community-specific barriers to and determinants of health-seeking behaviors are appropriately addressed.

COVID-19 Test Allocation Strategy to Mitigate SARS-CoV-2 Infections across School Districts.

In response to COVID-19, schools across the United States closed in early 2020; many did not fully reopen until late 2021. Although regular testing of asymptomatic students, teachers, and staff can reduce transmission risks, few school systems consistently used proactive testing to safeguard return to classrooms. Socioeconomically diverse public school districts might vary testing levels across campuses to ensure fair, effective use of limited resources. We describe a test allocation approach to reduce overall infections and disparities across school districts. Using a model of SARS-CoV-2 transmission in schools fit to data from a large metropolitan school district in Texas, we reduced incidence between the highest and lowest risk schools from a 5.6-fold difference under proportional test allocation to 1.8-fold difference under our optimized test allocation. This approach provides a roadmap to help school districts deploy proactive testing and mitigate risks of future SARS-CoV-2 variants and other pathogen threats.

Building a Data Bridge: Policies, Structures, and Governance Integrating Primary Care Into the Public Health Response to COVID-19.

PURPOSE: The effective integration of primary care into public health responses to the COVID-19 pandemic, particularly through data sharing, has received some attention in the literature. However, the specific policies and structures that facilitate this integration are understudied. This paper describes the experiences of clinicians and administrators in Alberta, Canada as they built a data bridge between primary care and public health to improve the province's community-based response to the pandemic. METHODS: Fifty-seven semistructured qualitative interviews were conducted with a range of primary care and public health stakeholders working inside the Calgary Health Zone. Interpretive description was used to analyze the interviews. RESULTS: SARS-CoV-2 test results produced by the local public laboratory were, initially, only available to central public health clinicians and not independent primary care physicians. This enabled centrally managed contact tracing but meant primary care physicians were unaware of their patients' COVID-19 status and unable to offer in-community follow-up care. Stakeholders from both central public health and independent primary care were able to leverage a policy commitment to the Patient Medical Home (PMH) care model, and a range of existing organizational structures, and governance arrangements to create a data bridge that would span the gap. CONCLUSIONS: Primary care systems looking to draw lessons from the data bridge's construction may consider ways to: leverage care model commitments to integration and adjust or create organization and governance structures which actively draw together primary care and non-primary care stakeholders to work on common projects. Such policies and structures develop trusting relationships, open the possibility for champions to emerge, and create the spaces in which integrative improvisation can take place.

Simple methods for early warnings of COVID-19 surges: Lessons learned from 21 months of wastewater and clinical data collection in Detroit, Michigan, United States.

Wastewater-based epidemiology (WBE) has drawn great attention since the Coronavirus disease 2019 (COVID-19) pandemic, not only due to its capability to circumvent the limitations of traditional clinical surveillance, but also due to its potential to forewarn fluctuations of disease incidences in communities. One critical application of WBE is to provide "early warnings" for upcoming fluctuations of disease incidences in communities which traditional clinical testing is incapable to achieve. While intricate models have been developed to determine early warnings based on wastewater surveillance data, there is an exigent need for straightforward, rapid, broadly applicable methods for health departments and partner agencies to implement. Our purpose in this study is to develop and evaluate such early-warning methods and clinical-case peak-detection methods based on WBE data to mount an informed public health response. Throughout an extended wastewater surveillance period across Detroit, MI metropolitan area (the entire study period is from September 2020 to May 2022) we designed eight early-warning methods (three real-time and five post-factum). Additionally, we designed three peak-detection methods based on clinical epidemiological data. We demonstrated the utility of these methods for providing early warnings for COVID-19 incidences, with their counterpart accuracies evaluated by hit rates. "Hit rates" were defined as the number of early warning dates (using wastewater surveillance data) that captured defined peaks (using clinical epidemiological data) divided by the total number of early warning dates. Hit rates demonstrated that the accuracy of both real-time and post-factum methods could reach 100 %. Furthermore, the results indicate that the accuracy was influenced by approaches to defining peaks of disease incidence. The proposed methods herein can assist health departments capitalizing on WBE data to assess trends and implement quick public health responses to future epidemics. Besides, this study elucidated critical factors affecting early warnings based on WBE amid the COVID-19 pandemic.

The Epidemiology of COVID-19 by Race/Ethnicity in Oklahoma City-County, Oklahoma (12 March 2020-31 May 2021).

We aimed to better understand the racially-/ethnically-specific COVID-19-related outcomes, with respect to time, to respond more effectively to emerging variants. Surveillance data from Oklahoma City-County (12 March 2020-31 May 2021) were used to summarize COVID-19 cases, hospitalizations, deaths, and COVID-19 vaccination status by racial/ethnic group and ZIP code. We estimated racially-/ethnically-specific daily hospitalization rates, the proportion of cases hospitalized, and disease odds ratios (OR) adjusting for sex, age, and the presence of at least one comorbidity. Hot spot analysis was performed using normalized values of cases, hospitalizations, and deaths generated from incidence rates per 100,000 population. During the study period, there were 103,030 confirmed cases, 3457 COVID-19-related hospitalizations, and 1500 COVID-19-related deaths. The daily 7-day average hospitalization rate for Hispanics peaked earlier than other groups and reached a maximum (3.0/100,000) in July 2020. The proportion of cases hospitalized by race/ethnicity was 6.09% among non-Hispanic Blacks, 5.48% among non-Hispanic Whites, 3.66% among Hispanics, 3.43% among American Indians, and 2.87% among Asian/Pacific Islanders. COVID-19 hot spots were identified in ZIP codes with minority communities. The Hispanic population experienced the first surge in COVID-19 cases and hospitalizations, while non-Hispanic Blacks ultimately bore the highest burden of COVID-19-related hospitalizations and deaths.

Local Public Health System Capabilities and COVID-19 Death Rates.

OBJECTIVES: Efforts to contain the health effects of the COVID-19 pandemic have achieved less success in the United States than in many comparable countries. Previous research documented wide variability in the capabilities of local public health systems to carry out core disease prevention and control activities, but it is unclear how this variability relates to COVID-19 control. Our study explored this relationship by using a nationally representative sample of 725 US communities. METHODS: We used data collected from the National Longitudinal Survey of Public Health Systems to classify each community into 1 of 3 ordinal categories indicating limited, intermediate, or comprehensive public health system capabilities. We used 2-part generalized linear models to estimate the relationship between public health system capabilities and COVID-19 death rates while controlling population and community characteristics associated with COVID-19 risk. RESULTS: Across 3 waves of the pandemic in 2020, we found a significant negative association between COVID-19 mortality and public health system capabilities. Compared with comprehensive public health systems, intermediate public health systems had an average of 4.97 to 19.02 more COVID-19 deaths per 100 000 residents, while limited public health systems had an average of 5.95 to 18.10 more COVID-19 deaths per 100 000 residents. CONCLUSION: Overall, communities with stronger public health capabilities had significantly fewer deaths. Future initiatives to strengthen pandemic preparedness and reduce health disparities in the United States should focus on local public health system capabilities.

"Compared to COVID, HIV Is Nothing": Exploring How Onshore East Asian and Sub-Saharan African International Students in Sydney Navigate COVID-19 versus BBVs/STIs Risk Spectrum.

Background: While a large body of evidence indicates changes in alcohol and other drug use among young people as a result of the COVID-19 pandemic, there is a lack of evidence around changes in sexual practices and how the pandemic may be impacting the potential spread of blood-borne viruses and sexually transmissible infections (BBVs/STIs). Most of what we know about sex during COVID-19 lockdowns is largely based on solitary sexual practices, which may not answer the critical question around how the pandemic may be shaping sexual practices among young people. Against this backdrop, this study explored how the COVID-19 pandemic may be shaping BBVs/STIs risk and protective practices among a sample of onshore African and Asian international students in Sydney, Australia. Methods: This phenomenological qualitative study involved semi-structured telephone and face-to-face interviews with 16 international university students in Sydney, between September 2020-March 2021. Generated data were coded using NVivo and analysis was guided by reflexive thematic analysis. Results: Participants reported elevated mental health distress because of the COVID-19 pandemic. Some participants reported engaging in casual sexual hook-ups as a strategy to mitigate the mental health distress they were experiencing. Some of these sexual hook-ups were condomless partly because COVID-related disruptions impacted condom accessibility. Additionally, the preventive practices of some participants who were sexually active during the lockdowns were focused on preventing COVID-19, while the risk of BBVs/STIs were downplayed. Conclusions: This study indicates a need for a comprehensive public health response to the evolving and near-endemic COVID-19 situation. Such a comprehensive approach should focus on empowering young people to prevent both SARS-CoV-2 and BBVs/STIs.

Time taken by individuals with respiratory symptoms to present to primary care: a descriptive study of assessments at Australian General Practitioner-led respiratory clinics.

Effective control of coronavirus disease 2019 (COVID-19) has been challenging, in part due to significant asymptomatic and pre-symptomatic transmission of disease. Reducing the time between symptom onset and COVID-19 testing and isolation allows enhanced outbreak control. The purpose of this study is to describe the time taken by participants to present to general practitioner-led (GP) respiratory clinics for assessment following the development of symptoms, and to explore associations between demographic and geographic characteristics and the time to presentation. A total of 314,148 participants, who were assessed in GP respiratory clinics between 1 February and 31 August 2021, were included in the analysis. The median age of participants at presentation was 33 years (interquartile range, IQR: 15-49). The median time from development of symptoms to presentation for assessment at GP respiratory clinics was 2 days (IQR: 1-3). Participants were more likely to present within one day of symptom onset if they were aged between 15 and 64 years (43.4%), lived in urban areas (40.9%) or were non-Indigenous (40.2%). Participants in New South Wales and Victoria had twice the odds (OR 2.01; 95% confidence interval (CI): 1.95, 2.08) of presenting at a GP respiratory clinic within one day of symptom onset in August 2021, when there was a COVID-19 outbreak in those states, than they did in March 2021, when there was no COVID-19 outbreak in Australia. The number of days from symptom onset to presentation at a GP respiratory clinic was strongly associated with the presence of a COVID-19 outbreak. Participant age, location of the clinic, and Indigenous status of participants were also associated with the time to presentation. This study highlights the importance of recognising COVID-19 as a potential cause of symptoms, as well as the importance of providing easily accessible, and culturally appropriate, testing facilities for the population.

Investigation into cases of hepatitis of unknown aetiology among young children, Scotland, 1 January 2022 to 12 April 2022.

On 31 March 2022, Public Health Scotland was alerted to five children aged 3-5 years admitted to hospital with severe hepatitis of unknown aetiology. Retrospective investigation identified eight additional cases aged 10 years and younger since 1 January 2022. Two pairs of cases have epidemiological links. Common viral hepatitis causes were excluded in those with available results. Five children were adenovirus PCR-positive. Other childhood viruses, including SARS-CoV-2, have been isolated. Investigations are ongoing, with new cases still presenting.

Using genomic epidemiology of SARS-CoV-2 to support contact tracing and public health surveillance in rural Humboldt County, California.

BACKGROUND: During the COVID-19 pandemic within the United States, much of the responsibility for diagnostic testing and epidemiologic response has relied on the action of county-level departments of public health. Here we describe the integration of genomic surveillance into epidemiologic response within Humboldt County, a rural county in northwest California. METHODS: Through a collaborative effort, 853 whole SARS-CoV-2 genomes were generated, representing ~58% of the 1,449 SARS-CoV-2-positive cases detected in Humboldt County as of March 12, 2021. Phylogenetic analysis of these data was used to develop a comprehensive understanding of SARS-CoV-2 introductions to the county and to support contact tracing and epidemiologic investigations of all large outbreaks in the county. RESULTS: In the case of an outbreak on a commercial farm, viral genomic data were used to validate reported epidemiologic links and link additional cases within the community who did not report a farm exposure to the outbreak. During a separate outbreak within a skilled nursing facility, genomic surveillance data were used to rule out the putative index case, detect the emergence of an independent Spike:N501Y substitution, and verify that the outbreak had been brought under control. CONCLUSIONS: These use cases demonstrate how developing genomic surveillance capacity within local public health departments can support timely and responsive deployment of genomic epidemiology for surveillance and outbreak response based on local needs and priorities.

Chatbot use cases in the Covid-19 public health response.

OBJECTIVE: To identify chatbot use cases deployed for public health response activities during the Covid-19 pandemic. MATERIAL AND METHODS: We searched PubMed/MEDLINE, Web of Knowledge, and Google Scholar in October 2020 and performed a follow-up search in July 2021. We screened articles based on their abstracts and keywords in their text, reviewed potentially relevant articles, and screened their references to (a) assess whether the article met inclusion criteria and (b) identify additional articles. Chatbots, their use cases, and chatbot design characteristics were extracted from the articles and information from other sources and by accessing those chatbots that were publicly accessible. RESULTS: Our search returned 3334 articles, 61 articles met our inclusion criteria, and 61 chatbots deployed in 30 countries were identified. We categorized chatbots based on their public health response use case(s) and design. Six categories of public health response use cases emerged comprising 15 distinct use cases: risk assessment, information dissemination, surveillance, post-Covid eligibility screening, distributed coordination, and vaccine scheduler. Design-wise, chatbots were relatively simple, implemented using decision-tree structures and predetermined response options, and focused on a narrow set of simple tasks, presumably due to need for quick deployment. CONCLUSION: Chatbots' scalability, wide accessibility, ease of use, and fast information dissemination provide complementary functionality that augments public health workers in public health response activities, addressing capacity constraints, social distancing requirements, and misinformation. Additional use cases, more sophisticated chatbot designs, and opportunities for synergies in chatbot development should be explored.

A Study on the Effectiveness of StaySafe PH in Reducing the Spread of COVID-19 in Barangay Bagong Silangan, Quezon City

The growing number of cases of COVID-19 has prompted the government to develop and deploy digital contact tracing applications. [1] The dominant explanation of these measures is mitigating the transmission of the novel coronavirus (COVID-19). [2] Contact tracing is crucial in dealing with a pandemic because it allows rapid detection of cases based on information gathered from affected individuals about other people they may have had recent contact with. Advances in digital technologies have made it possible to use cellular phones in the contact tracing process. The previous study has proved the effectiveness of the contact tracing application in various countries like Singapore and United Kingdom. Having said this, the objective of this study is to determine the efficacy of StaySafe PH in reducing the ballooning cases of COVID-19 in Barangay Bagong Silangan, Quezon City. StaySafe PH is a contact tracing application with medical consultation and allows users to report problems regarding their health conditions easily. The respondents were composed of 55 (fifty-five) residents of Barangay Bagong Silangan, whose ages are within the bracket of 18 to 59 years old. To gather the necessary data needed, the proponents created and administered a questionnaire to the subjects, which focused on the respondents' experience in using the StaySafe PH. The design used by the researcher is correlational, which gathers quantifiable information that can be used for statistical interference through data analysis. In addition, the researchers applied a probability sampling technique in this study. In findings and analysis of the data, most of the respondents are using StaySafe PH, which is thirty-six (36) percent at the same time believed that the application could help in flattening the curve and saving more lives. Furthermore, it is decided that StaySafe PH is effective and safe to use. © 2021 ACM.

Review of COVID-19 epidemiology and public health response in Europe in 2020.

OBJECTIVE: This study focuses on the epidemiology of COVID-19 in Europe and investigates public health response in severely hit countries. METHODS: European Centre for Disease Prevention and Control, Oxford COVID-19 Government Response Tracker and Health System Response Monitor were referred. The relationship between stringency index and COVID-19 cases, and between speed of stringency implementation and growth of cases was examined using linear regression. RESULTS: The case-fatality ratio (CFR) of Europe (2.35%) was higher than the global CFR (2.2%). United Kingdom, Russia, France, Italy, Spain, and Germany together, accounted for 61.15% of cases and 65.62% of deaths in Europe. Significant relationship was observed between growth of COVID-19 cases and late substantive stringency imposed by countries. Population aged 65 and above (r = 0.9037, p < 0.01) and male population (r = 0.8701, p < 0.01) were significantly and positively correlated with COVID-19 deaths. The public health system of even big European countries encountered roadblocks, such as shortages of healthcare resources and deferral of non-COVID-19 treatments while dealing with the unprecedented pandemic. CONCLUSION: Even big and richest European countries delayed the implementation of non-pharmaceutical interventions which led to rapid virus transmission. The pandemic has posed a reminder to make the public health system more resilient, as epidemics and pandemics of this nature will continue to threaten in future as well.

Supplementing SARS-CoV-2 genomic surveillance with PCR-based variant detection for real-time actionable information, the Netherlands, June to July 2021.

We evaluated routine testing with SARS-CoV-2 Delta variant-specific RT-PCR in regional hospital laboratories in addition to centralised national genomic surveillance in the Netherlands during June and July 2021. The increase of the Delta variant detected by RT-PCR correlated well with data from genomic surveillance and was available ca 2 weeks earlier. This rapid identification of the relative abundance and increase of SARS-CoV-2 variants of concern may have important benefits for implementation of local public health measures.

Optimal allocation of PCR tests to minimise disease transmission through contact tracing and quarantine.

PCR testing is a crucial capability for managing disease outbreaks, but it is also a limited resource and must be used carefully to ensure the information gain from testing is valuable. Testing has two broad uses for informing public health policy, namely to track epidemic dynamics and to reduce transmission by identifying and managing cases. In this work we develop a modelling framework to examine the effects of test allocation in an epidemic, with a focus on using testing to minimise transmission. Using the COVID-19 pandemic as an example, we examine how the number of tests conducted per day relates to reduction in disease transmission, in the context of logistical constraints on the testing system. We show that if daily testing is above the routine capacity of a testing system, which can cause delays, then those delays can undermine efforts to reduce transmission through contact tracing and quarantine. This work highlights that the two goals of aiming to reduce transmission and aiming to identify all cases are different, and it is possible that focusing on one may undermine achieving the other. To develop an effective strategy, the goals must be clear and performance metrics must match the goals of the testing strategy. If metrics do not match the objectives of the strategy, then those metrics may incentivise actions that undermine achieving the objectives.

Analyzing disparities in COVID-19 testing trends according to risk for COVID-19 severity across New York City.

BACKGROUND: Given the interplay between race and comorbidities on COVID-19 morbidity and mortality, it is vital that testing be performed in areas of greatest need, where more severe cases are expected. The goal of this analysis is to evaluate COVID-19 testing data in NYC relative to risk factors for COVID-19 disease severity and demographic characteristics of NYC neighborhoods. METHODS: COVID-19 testing and the racial/ethnic composition of NYC Zip Code Tabulation Areas (ZCTA) were obtained from the NYC Coronavirus data repository and the American Community Survey, respectively. The prevalence of neighborhood-level risk factors for COVID-19 severity according to the Centers for Disease Control and Prevention criteria for risk of severe illness and complications from COVID-19 were used to create a ZCTA-level risk index. Poisson regressions were performed to study the ratio of total tests relative to the total ZCTA population and the proportion of positive tests relative to the total tests performed over time. RESULTS: From March 2nd-April 6th, the total tests/population (%) was positively associated with the proportion of white residents (IRRadj: 1.0003, 95% CI: 1.0003-1.0004) and the COVID risk index (IRRadj: 1.038, 95% CI: 1.029-1.046). The risk index (IRRadj: 1.017, 95% CI: 0.939-1.101) was not associated with total tests performed from April 6th-May 12th, and inversely associated from May 12th-July 6th (IRRadj: 0.862, 95% CI: 0.814-0.913). From March 2nd-April 6th the COVID risk index was not statistically associated (IRRadj: 1.010, 95% CI: 0.987-1.034) with positive tests/total tests. From April 6th-May 12th, the COVID risk index was positively associated (IRRadj: 1.031, 95% CI: 1.002-1.060), while from May 12th-July 6th, the risk index was inversely associated (IRRadj: 1.135, 95% CI: 1.042-1.237) with positivity. CONCLUSIONS: Testing in NYC has suffered from the lack of availability in high-risk populations, and was initially limited as a diagnostic tool for those with severe symptoms, which were mostly concentrated in areas where vulnerable residents live. Subsequent time periods of testing were not targeted in areas according to COVID-19 disease risk, as these areas still experience more positive tests.

Enumerating asymptomatic COVID-19 cases and estimating SARS-CoV-2 fecal shedding rates via wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) was utilized to monitor SARS-CoV-2 RNA in sewage collected from manholes specific to individual student dormitories (dorms) at the University of Arizona in the fall semester of 2020, which led to successful identification and reduction of SARS-CoV-2 transmission events. Positive wastewater samples triggered clinical testing of residents within that dorm; thus, SARS-CoV-2 infected individuals were identified regardless of symptom expression. This current study examined clinical testing data to determine the abundance of asymptomatic versus symptomatic cases in these defined communities. Nasal and nasopharyngeal swab samples processed via antigen and PCR tests indicated that 79.2% of SARS-CoV-2 infections were asymptomatic, and only 20.8% of positive cases reported COVID-19 symptoms at the time of testing. Clinical data was paired with corresponding wastewater virus concentrations, which enabled calculation of viral shedding rates in feces per infected person. Mean shedding rates averaged from positive wastewater samples across all dorms were 7.30 ± 0.67 log10 genome copies per gram of feces (gc/g-feces) based on the N1 gene. Quantification of SARS-CoV-2 fecal shedding rates from infected individuals has been the critical missing component necessary for WBE models to measure and predict SARS-CoV-2 infection prevalence in communities. The findings from this study can be utilized to create models that can be used to inform public health prevention and response actions.

Contributions of the EURO 2020 football championship events to a third wave of SARS-CoV-2 in Scotland, 11 June to 7 July 2021.

Public Health Scotland used Scottish national contact tracing data to estimate the European football championship (EURO 2020) contributions to a third wave of SARS-CoV-2 infections. From 11 June to 7 July 2021, 2,632 (4%) of 63,874 SARS-CoV-2 cases self-reported attending a EURO 2020 event; 90% were male, of whom 73% were 20-39-year-olds. Most cases attended unofficial gatherings and averaged more contacts than the general population. Targeted guidance on celebrating safely in closed spaces is key.