Coronavirus Disease 2019 Surveillance Research Articles

Differential COVID-19 case ascertainment by age and vaccination status in Victoria, Australia: a serosurveillance and record linkage study.

To compare serological evidence of prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with linked coronavirus disease 2019 (COVID-19) case notification data in Victoria, Australia, and to determine in vitro SARS-CoV-2 neutralisation activity based on prior infection and vaccination history. Four cross-sectional serological surveys were conducted between 30 June and 31 October 2022 (a period of Omicron BA.4/BA.5 dominance) using 1,974 residual serum samples obtained from the Victorian Infectious Diseases Reference Laboratory. Serological results were linked to COVID-19 case notification and vaccination data. Surrogate virus neutralisation testing was performed to obtain in vitro inhibition estimates by anti-nucleocapsid serostatus and COVID-19 vaccination history. Adjusted anti-SARS-CoV-2 spike and nucleocapsid seropositivity by sex, age and region of residence; adjusted proportion of cases notified by anti-nucleocapsid serostatus, age and number of COVID-19 vaccination doses received; adjusted percentage in vitro inhibition against wildtype and Omicron BA.4/BA.5 SARS-CoV-2 variants by anti-nucleocapsid serostatus and COVID-19 vaccination history. The prevalence of anti-SARS-CoV-2 nucleocapsid antibodies was inversely proportional to age. In October 2022, prevalence was 84% (95% confidence interval [95% CI]: 75-93%) among 18-29-year-olds, compared to 39% (95% CI: 27-52%) among ≥ 80-year-olds. In most age groups, approximately 40% of COVID-19 cases appear to have been notified via existing surveillance mechanisms. Case notification was highest among individuals older than 80 years and people who had received COVID-19 vaccine booster doses. In vitro neutralisation of Omicron BA.4/BA.5 sub-variants was highest for individuals with evidence of both prior infection and booster vaccination. Under-notification of SARS-CoV-2 infections in the Victorian population is not uniform across age and vaccination strata. Seroprevalence data that give insights into case notification behaviour provide additional context for the interpretation of existing COVID-19 surveillance information.

The immune response of nano carbon-based photic-driving vaccines to severe acute respiratory syndrome coronavirus 2

As the most severe novel infectious disease in this century, coronavirus disease 2019 (COVID-19) faces tremendous challenges due to the hysteresis of drugs and vaccine development. Elucidating the panoramic mechanism of coronavirus-host immune interaction is a strategy for disease surveillance, diagnosis, treatment, prevention, and immunity assessment of COVID-19. A robust carbon nanotube (CNT)-based photic vaccine technology contributes to address the core scientific issues of these challenges. This perspective states the latest prevention and control strategy of CNT-based photic vaccine and its broad-spectrum resistance to high transmissible and pathogenic variants. Furthermore, this perspective covers the potential immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) under the CNT-based photic vaccine intervention and finally evaluates its efficacy and the underlying interactive mechanisms. In the future, findings of the highly efficient and conservative T cell epitopes depending on an intelligent chem-physical modulation would provide a promising basis for the development of next generation vaccines. Ideally, these next generation vaccines are prone to be with the function of dynamic allostery responding to the chem-physical changing and present the allosteric epitopes which are affinity to the viral variation.

Application of Skimmed-Milk Flocculation Method for Wastewater Surveillance of COVID-19 in Kathmandu, Nepal.

Wastewater surveillance (WS) has been used globally as a complementary tool to monitor the spread of coronavirus disease 2019 (COVID-19) throughout the pandemic. However, a concern about the appropriateness of WS in low- and middle-income countries (LMICs) exists due to low sewer coverage and expensive viral concentration methods. In this study, influent wastewater samples (n = 63) collected from two wastewater treatment plants (WWTPs) of the Kathmandu Valley between March 2021 and February 2022 were concentrated using the economical skimmed-milk flocculation method (SMFM). The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was tested by qPCR using assays that target the nucleocapsid (N) and envelope (E) genes. Overall, 84% (53/63) of the total samples were positive for SARS-CoV-2 according to at least one of the tested assays, with concentrations ranging from 3.5 to 8.3 log10 gene copies/L, indicating the effectiveness of the SMFM. No correlation was observed between the total number of COVID-19 cases and SARS-CoV-2 RNA concentrations in wastewater collected from the two WWTPs (p > 0.05). This finding cautions the prediction of future COVID-19 waves and the estimation of the number of COVID-19 cases based on wastewater concentration in settings with low sewer coverage by WWTPs. Future studies on WS in LMICs are recommended to be conducted by downscaling to sewer drainage, targeting a limited number of houses. Overall, this study supports the notion that SMFM can be an excellent economical virus-concentrating method for WS of COVID-19 in LMICs.

Association between work sick-leave absenteeism and SARS-CoV-2 notifications in the Netherlands during the COVID-19 epidemic.

Alternative data sources for surveillance have gained importance in maintaining coronavirus disease 2019 (COVID-19) situational awareness as nationwide testing has drastically decreased. Therefore, we explored whether rates of sick-leave from work are associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) notification trends and at which lag, to indicate the usefulness of sick-leave data for COVID-19 surveillance. We explored trends during the COVID-19 epidemic of weekly sick-leave rates and SARS-CoV-2 notification rates from 1 June 2020 to 10 April 2022. Separate time series were inspected visually. Then, Spearman correlation coefficients were calculated at different lag and lead times of zero to four weeks between sick-leave and SARS-CoV-2 notification rates. We distinguished between four SARS-CoV-2 variant periods, two labour sectors and overall, and all-cause sick-leave versus COVID-19-specific sick-leave. The correlation coefficients between weekly all-cause sick-leave and SARS-CoV-2 notification rate at optimal lags were between 0.58 and 0.93, varying by the variant period and sector (overall: 0.83, lag -1; 95% CI [0.76, 0.88]). COVID-19-specific sick-leave correlations were higher than all-cause sick-leave correlations. Correlations were slightly lower in healthcare and education than overall. The highest correlations were mostly at lag -2 and -1 for all-cause sick-leave, meaning that sick-leave preceded SARS-CoV-2 notifications. Correlations were highest mostly at lag zero for COVID-19-specific sick-leave (coinciding with SARS-CoV-2 notifications). All-cause sick-leave might offer an earlier indication and evolution of trends in SARS-CoV-2 rates, especially when testing is less available. Sick-leave data may complement COVID-19 and other infectious disease surveillance systems as a syndromic data source.

Wastewater surveillance for COVID-19 in shelters: A creative strategy for a complex setting.

People experiencing homelessness experience disproportionate rates of morbidity and mortality from coronavirus disease 2019 (COVID-19) compared to the general population and shelters for people experiencing homelessness are a major contributing factor to these negative outcomes. As a result of their unique structure, population and physical space, these settings pose several challenges to the prevention of COVID-19 infection that are not adequately addressed by conventional non-pharmaceutical public health interventions. Wastewater surveillance for COVID-19 is a viable strategy for health protection in shelters due to its ability to meet these unique challenges. Its passive nature does not depend on individual health-seeking behaviours, and it can provide useful epidemiological information early on in an outbreak setting. In this commentary, the authors examine a recent application of wastewater surveillance of COVID-19 in a men's shelter in Toronto. Further applications of wastewater surveillance for other infectious diseases of concern in shelters are proposed, and the need for the development of ethical frameworks governing the use of this technology is discussed.

Estimates of Direct Medical and Indirect Costs Associated With COVID-19 Among U.S. Active Duty Army Soldiers.

This study estimated the direct medical and indirect costs associated with coronavirus disease 2019 (COVID-19) diagnoses among U.S. active duty (AD) Army service members (SMs). These cost estimates provide the U.S. Military with a better understanding of the financial burden of COVID-19 and provide a foundation for cost-effectiveness estimates. The study was approved as Public Health Practice (#17-605) by the U.S. Army Public Health Center, Public Health Review Board. U.S. AD Army SMs with COVID-19 were identified using an Army COVID-19 testing and surveillance database. Encounters for these SMs were captured from medical record where International Classification of Disease Tenth Revision, Clinical Modification code U07.1 was in the first or second diagnostic position. Analyses were conducted on SMs with COVID-19 who either had no healthcare encounters in the Military Health System (MHS); at least one MHS COVID-19 inpatient hospitalization; or at least one MHS outpatient COVID-19 encounter. Coronavirus disease 2019 (COVID-19) costs captured from the encounters were used to develop direct medical cost estimates. Literature on COVID-19 recovery post-hospitalization, along with the number of COVID-19 hospitalizations and outpatient visits from encounters were used to describe the intensity of COVID-19 care. Estimates of the indirect cost of lost duty were based on SMs salary information, along with recovery time, bed days, or outpatient visit time. The indirect cost of limited duty was estimated using the time associated with the Department of Defense (DoD) COVID-19 pandemic mitigation strategies in place when these SMs were identified as positive for COVID-19. Coronavirus disease 2019 (COVID-19) cost estimates were developed for the Army using data from 19,086 SMs identified as positive for COVID-19 between June 1, 2020, and December 31, 2020. Direct medical costs, or the amount paid by the DoD to facilities for COVID-19 care, averaged $606 per SM with an encounter. Indirect costs for lost duty or the cost for recovery and the time taken to seek care for COVID-19 averaged $319 per SM, while indirect costs for limited duty or isolation associated with COVID-19 averaged $4,111 per SM or $411 per day. Service members (SMs) with an inpatient hospitalization averaged 4.8 bed days (range 1-43) and 266 recovery hours while SMs who sought outpatient care for COVID-19 averaged two outpatient visits (range 1-60 visits). The direct medical costs of a COVID-19 encounter in the MHS ($606) are a small portion of the costs for a SM with COVID-19. Indirect costs of lost and limited duty associated with COVID-19 averaged seven times higher ($4,331) and accounted for the vast majority of costs. Recognition of these costs is important especially given that soldiers in the hospital or in quarters being quarantined are complete losses of manpower to the Army. While the COVID-19 pandemic is ongoing and prevention, treatment, and mitigation efforts continue to evolve, having reliable estimates of direct medical and indirect costs from this study allows the U.S. Army and MHS to better account for the cost of this pandemic for its population.

Surveillance for COVID-19 associated mucormycosis: A coordinated effort in prevention and management of rhino-orbital mucormycosis

Abstract Context: Patients of coronavirus disease 2019 (COVID-19) and factors inducing a diabetogenic state are at increased risk for rhino-orbital mucormycosis (ROM). Efforts to diagnose ROM in its pre-clinical stage would avoid the disease and its consequences. Aim: This study aimed to diagnose ROM in the pre-clinical stage of the disease in high-risk patients and treat patients accordingly. Settings and Design: This is a single-center, prospective study conducted at a tertiary care center in Northern India in collaboration with departments of Otolaryngology, Internal Medicine, and Mycology. Materials and Methods: Fifty-three high-risk patients were enrolled in the study, and all underwent bedside nasal endoscopy with tissue sampling for fungal culture. Patients with suspicious nasal endoscopy findings but negative fungal culture were prescribed oral posaconazole. Those with positive fungal hyphae on nasal endoscopy and culture underwent surgical intervention followed by intravenous amphotericin B, while the remaining patients were kept on follow-up. Statistical Analysis Used: Statistical analysis was performed using the Statistical Package for Social Sciences software. Results: Among the 53 patients, 13 (24.5%) patients had abnormalities on nasal endoscopy, while the remaining 40 (75.5%) patients had normal nasal mucosal cavities. Seven patients (13.2%) underwent surgery and received intravenous liposomal amphotericin B, while another 7 (13.2%) received oral posaconazole. Thirty-five (66.03%) patients were placed under observation, and 4 (7.5%) patients died due to COVID-19-related illness. Conclusions: Nasal endoscopic-guided tissue sampling for fungal culture serves as a valuable surveillance tool for predicting ROM in COVID-19 patients.

Epidemiology of Coronavirus Disease 2019 during the Second and Third Wave in Chennai, India: An Analysis of the Coronavirus Disease 2019 Surveillance System, February 2021-February 2022.

Analysis of the coronavirus disease 2019 (COVID-19) surveillance system in the first wave indicated that the data-driven approach helped in resource allocation and public health interventions. We described the epidemiology of COVID-19 cases in Chennai, Tamil Nadu, India, from February 2021 to February 2022. We analyzed the COVID-19 surveillance data from Chennai City, Tamil Nadu, India's Greater Chennai Corporation. We described the deidentified line list of COVID-19 cases and deaths by months, zones, age, and gender. We estimated the incidence of COVID-19 cases per million population, test positivity rate (TPR), and case fatality ratio (CFR). Of the 434,040 cases reported in Chennai from February 1, 2021, to February 28, 2022, 53% were male. The incidence per million peaked in May 2021 (19,210) and January 2022 (15,881). Age groups more than 60 years reported maximum incidence. Southern region zones reported higher incidence. Overall TPR was 5.8%, peaked in May 2021 (17.5%) and January 2022 (15.1%). Over half of the 4929 reported deaths were in May 2021 (56%). Almost half of the deaths were 61-80 years (52%), followed by 41-60 years (26%). Overall CFR was 1%, which peaked in June 2021 (4%). We conclude that Chennai city experienced a surge in COVID-19 due to delta and omicron variants. Understanding descriptive epidemiology is vital for planning the public health response, resource allocation, vaccination policies, and risk communication to the community.

Association Between Health Insurance Type and Adverse Outcomes for Children and Young Adults With Type 1 Diabetes and Coronavirus Disease 2019.

Health insurance coverage type differs significantly by socioeconomic status and racial group in the United States. The aim of this study was to determine whether publicly insured children and young adults with type 1 diabetes were more likely to experience adverse outcomes compared with privately insured patients with acute coronavirus disease 2019 (COVID-19) infections. Data from 619 patients with previously established type 1 diabetes who were <24 years of age with acute COVID-19 infections were analyzed from the T1D Exchange COVID-19 surveillance registry. Data for the registry was collected from 52 endocrinology clinics across the United States using an online survey tool. Each site completed the survey using electronic health record data between April 2020 and December 2021. Of the 619 patients included in this study, 257 had public insurance and 362 had private insurance. Of the 257 publicly insured patients with COVID-19, 57 reported severe adverse outcomes (22%), defined as diabetic ketoacidosis (DKA) or severe hypoglycemia. In comparison, there were 25 reported adverse outcomes (7%) among the 362 privately insured patients. Our data reveal high rates of hospitalization and DKA among publicly insured racial/ethnic minority children and young adults with type 1 diabetes and COVID-19.

Development of monoclonal antibody-based blocking ELISA for detecting SARS-CoV-2 exposure in animals.

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a significant threat to public health. Besides humans, SARS-CoV-2 can infect several animal species. Highly sensitive and specific diagnostic reagents and assays are urgently needed for rapid detection and implementation of strategies for prevention and control of the infection in animals. In this study, we initially developed a panel of monoclonal antibodies (mAbs) against SARS-CoV-2 nucleocapsid protein. To detect SARS-CoV-2 antibodies in a broad spectrum of animal species, an mAb-based blocking enzyme-linked immunosorbent assay (bELISA) was developed. Test validation using a set of animal serum samples with known infection status obtained an optimal percentage of inhibition cut-off value of 17.6% with diagnostic sensitivity of 97.8% and diagnostic specificity of 98.9%. The assay demonstrates high repeatability as determined by a low coefficient of variation (7.23%, 4.89%, and 3.16%) between-runs, within-run, and within-plate, respectively. Testing of samples collected over time from experimentally infected cats showed that the bELISA was able to detect seroconversion as early as 7 days post-infection. Subsequently, the bELISA was applied for testing pet animals with coronavirus disease 2019 (COVID-19)-like symptoms and specific antibody responses were detected in two dogs. The panel of mAbs generated in this study provides a valuable tool for SARS-CoV-2 diagnostics and research. The mAb-based bELISA provides a serological test in aid of COVID-19 surveillance in animals. IMPORTANCE Antibody tests are commonly used as a diagnostic tool for detecting host immune response following infection. Serology (antibody) tests complement nucleic acid assays by providing a history of virus exposure, no matter symptoms developed from infection or the infection was asymptomatic. Serology tests for COVID-19 are in high demand, especially when the vaccines become available. They are important to determine the prevalence of the viral infection in a population and identify individuals who have been infected or vaccinated. ELISA is a simple and practically reliable serological test, which allows high-throughput implementation in surveillance studies. Several COVID-19 ELISA kits are available. However, they are mostly designed for human samples and species-specific secondary antibody is required for indirect ELISA format. This paper describes the development of an all species applicable monoclonal antibody (mAb)-based blocking ELISA to facilitate the detection and surveillance of COVID-19 in animals.

The Effect of COVID-19 Vaccines on Hospital Admission and Severity of Symptoms Among COVID-19 Patients in Saudi Arabia, 2021.

Introduction Following the World Health Organization (WHO) declaration of coronavirus disease 2019 (COVID-19) as a pandemic, Saudi Arabia took unpreceded precautions to prevent and control the spread of the severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) infection. It is one of the first countries in the world to grant the authorization to use the Pfizer-BioNTech vaccine. This study aimed to assess the effect of one dose of COVID-19 vaccines (Pfizer-BioNTech,Manhattan, New York City, and Oxford-AstraZeneca, Cambridge, United Kingdom) among the Saudi population regarding symptom severity, hospital admission rate, and death. Methods An observational retrospective cohort study was conducted using data from COVID-19 surveillance records at King Abdulaziz Medical City (KAMC), Saudi Arabia, from January to May 2021. All confirmed COVID-19 patients who had positive tests by reverse transcription polymerase chain reaction (RT-PCR) assay of a nasopharyngeal swab were included in the study. Patients diagnosed outside KAMC and cases below 18 years old were excluded from the study. The research was approved by King Abdullah International Medical Research Center (NRJ21J/303/12). Multivariable logistic regression was conducted to estimate the odds of hospitalization among vaccinated and unvaccinated patients. Results A total of 1058 cases were included in the analysis. Two hundred sixty-five (265; 25%) patients were vaccinated with one dose of either Pfizer-BioNTech or Oxford Astra-Zeneca, and 793 (75%) were unvaccinated. The median age was 34 (IQR 25-51), primarily Saudi (94.6%) and male (59.5%). The odds of being vaccinated (CI: 1.284-2.882, P 0.002) were 1.924 times greater for males than females. Young patients below 40 had 1.997 times higher odds (CI: 1.238-3.222, P 0.004) of being vaccinated than patients above 60. The hospital admission rate was low among both groups (12.9%); however, it was significantly lower among the vaccinated group (2.3%) as compared to the unvaccinated (16.5%). The results showed significant differences in symptom severity among the groups. For vaccinated, only one patient (0.4%) died, one patient was admitted to the ICU, and one patient (0.4%) was admitted to the hospital isolation ward. On the contrary, among the unvaccinated group, 19 patients (2.4%) died, 17 patients (2.1%) were admitted to the ICU, and 114 patients (14.4%) were admitted to the hospital isolation ward. Conclusion This study demonstrates that one dose of COVID-19 vaccines, either Pfizer-BioNTech or Oxford-AstraZeneca, reduced the probability of death by 2% and hospital admission by 15% before the spread of the Delta variant (B.1.617). For generalizable results, nationwide studies using national surveillance data are recommended to assess multiple doses efficacy on different variants of the SARS-CoV-2 infection.

Long-term exposure to air pollution and risk of SARS-CoV-2 infection and COVID-19 hospitalisation or death: Danish nationwide cohort study.

Early ecological studies have suggested links between air pollution and risk of coronavirus disease 2019 (COVID-19), but evidence from individual-level cohort studies is still sparse. We examined whether long-term exposure to air pollution is associated with risk of COVID-19 and who is most susceptible. We followed 3 721 810 Danish residents aged ≥30 years on 1 March 2020 in the National COVID-19 Surveillance System until the date of first positive test (incidence), COVID-19 hospitalisation or death until 26 April 2021. We estimated residential annual mean particulate matter with diameter ≤2.5 μm (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone (O3) in 2019 by the Danish DEHM/UBM model, and used Cox proportional hazards regression models to estimate the associations of air pollutants with COVID-19 outcomes, adjusting for age, sex, individual- and area-level socioeconomic status, and population density. 138 742 individuals were infected, 11 270 were hospitalised and 2557 died from COVID-19 during 14 months. We detected associations of PM2.5 (per 0.53 μg·m-3) and NO2 (per 3.59 μg·m-3) with COVID-19 incidence (hazard ratio (HR) 1.10 (95% CI 1.05-1.14) and HR 1.18 (95% CI 1.14-1.23), respectively), hospitalisations (HR 1.09 (95% CI 1.01-1.17) and HR 1.19 (95% CI 1.12-1.27), respectively) and death (HR 1.23 (95% CI 1.04-1.44) and HR 1.18 (95% CI 1.03-1.34), respectively), which were strongest in the lowest socioeconomic groups and among patients with chronic respiratory, cardiometabolic and neurodegenerative diseases. We found positive associations with BC and negative associations with O3. Long-term exposure to air pollution may contribute to increased risk of contracting severe acute respiratory syndrome coronavirus 2 infection as well as developing severe COVID-19 disease requiring hospitalisation or resulting in death.

EPH203 Patients Characteristics, Vaccine Uptake, Healthcare Resource Utilization and Costs Associated with Acute COVID-19 during the Omicron Predominant Period in Brazil: A Nationwide Database Study

The coronavirus disease 2019 (COVID-19) pandemic has imposed significant burden on Brazil’s health system. The present study aims to describe patients’ demographic and clinical characteristics, vaccine uptake and assess healthcare resource utilization (HCRU) and costs associated with acute COVID-19 in Brazil during the Omicron predominant period. A population-based retrospective study was conducted using the National Health Data Network (RNDS), National Vaccination Campaign against COVID-19 data and surveillance data in public setting. Individuals with positive COVID-19 test results between January-April 2022 were identified. Patients’ demographics, comorbidities, vaccination status, HCRU for those who were admitted to hospitals and their associated costs were described by age groups. A total of 8,160,715 COVID-19 cases were identified and 2.7% were aged <5 years, 11.6% were 5-19 years, 76.9% were 20-64 years and 8.7% were ≥ 65 years. The presence of comorbidity was 23.1% with a higher prevalence of comorbidities in the elderly (61.8% for 65-74 years and 71.2% for ≥75 years). Regarding COVID -19 vaccination uptake, among those aged ≤19 years, 20-64 years and ≥65 years, 40.6%, 86.5% and 92.2% had primary series, respectively. Among adults, the booster uptake was 47.3% and 75.8% for those aged 20-64 years and ≥ 65 years, respectively. Among those with confirmed COVID-19, regardless of vaccination status, 87% were being symptomatic and 1.7% were hospitalized (3.8% in aged <5 years, 4.2% in 5-19 years, 34.3% in 20-64 years and 57.6% in ≥ 65 years). Among hospitalized patients, 32,6% were admitted to ICU and 80% required mechanical ventilation support. The average cost per day in normal wards and ICU without ventilation was R$291,89 and R$923,90, respectively. Our results quantify the public health and economic burden of COVID-19 in Brazil, suggesting substantial healthcare resources required to manage the COVID-19 pandemic.

Predictors of ICU Admission in Children with COVID-19: Analysis of a Large Mexican Population Dataset.

Children, although mostly affected mildly or asymptomatically, have also developed severe coronavirus disease 2019 (COVID-19). This study aims to assess potential predictors of intensive care unit (ICU) admission in a large population (n = 21,121) of children aged 0-9 years with laboratory-confirmed disease. We performed a cross-sectional analysis of a publicly available dataset derived from the normative epidemiological surveillance of COVID-19 in Mexico. The primary binary outcome of interest was admission to the ICU due to respiratory failure. Results showed that immunosuppressed children and those with a personal history of cardiovascular disease had a higher likelihood of being admitted to the ICU, while increasing age and the pandemic duration were associated with a lower likelihood of admission. The study's results have the potential to inform clinical decision-making and enhance management and outcomes for children affected by COVID-19 in Mexico.

Accelerated waning of the humoral response to COVID-19 vaccines in obesity

Obesity is associated with an increased risk of severe Coronavirus Disease 2019 (COVID-19) infection and mortality. COVID-19 vaccines reduce the risk of serious COVID-19 outcomes; however, their effectiveness in people with obesity is incompletely understood. We studied the relationship among body mass index (BMI), hospitalization and mortality due to COVID-19 among 3.6 million people in Scotland using the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) surveillance platform. We found that vaccinated individuals with severe obesity (BMI > 40 kg/m2) were 76% more likely to experience hospitalization or death from COVID-19 (adjusted rate ratio of 1.76 (95% confidence interval (CI), 1.60–1.94). We also conducted a prospective longitudinal study of a cohort of 28 individuals with severe obesity compared to 41 control individuals with normal BMI (BMI 18.5–24.9 kg/m2). We found that 55% of individuals with severe obesity had unquantifiable titers of neutralizing antibody against authentic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus compared to 12% of individuals with normal BMI (P = 0.0003) 6 months after their second vaccine dose. Furthermore, we observed that, for individuals with severe obesity, at any given anti-spike and anti-receptor-binding domain (RBD) antibody level, neutralizing capacity was lower than that of individuals with a normal BMI. Neutralizing capacity was restored by a third dose of vaccine but again declined more rapidly in people with severe obesity. We demonstrate that waning of COVID-19 vaccine-induced humoral immunity is accelerated in individuals with severe obesity. As obesity is associated with increased hospitalization and mortality from breakthrough infections, our findings have implications for vaccine prioritization policies.

Standardized Cumulative Metrics of Excess Mortality to Monitor Health System Resilience Throughout COVID-19 and Other Respiratory Virus Resurgences.

Monitoring morbidity and mortality in resurgences of respiratory infections poses significant challenges, as shown by coronavirus disease 2019 (COVID-19). For example, case fatality rates and deaths attributed to specific respiratory pathogens are known to suffer from significant biases undermining their comparability through time and space. As a result, it is difficult to evaluate the protective effect of public health interventions or quantify the impact of a resurgence on the general population through direct recording of COVID-19 related deaths. To overcome these limitations, more robust, less-biased metrics, such as all-cause deaths, have been proposed for monitoring the effect of an epidemic over a population and over time. More specifically, metrics of excess mortality over time, which have been used for influenza surveillance in the past, are increasingly considered important for COVID-19 surveillance. Here, we discuss excess mortality surveillance focusing on standardized single-point and standardized cumulative metrics that allow comparability of excess mortality through space and time. We explain why z score allows for comparison of excess mortality between countries and different periods, while cumulative z score allows assessment of excess mortality over long periods. Our commentary reiterates the importance of standardized statistics of excess mortality for COVID-19 surveillance as we move toward a coexistence with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that will allow drawing conclusions from best practices in different health systems and different periods.

"PHILIPPINE PEDIATRIC COVID-19 LIVING CLINICAL PRACTICE GUIDELINES as of March 2022"

The Coronavirus disease 2019 (COVID-19) pandemic has triggered a global crisis and has affected millions of people worldwide. With the evolution of the different variants of concern, the incidence of COVID-19 in the pediatric population has risen. The Surveillance and Analysis of COVID-19 in Children Nationwide (SALVACION) Registry, developed by the Pediatric Infectious Disease Society of the Philippines (PIDSP) and the Philippine Pediatric Society (PPS), has reported 3,221 cases as of March 31, 2022, with 90.4% requiring hospitalization and 36.2% with moderate to critical disease severity. Given the magnitude of the impact of COVID-19, with most of the clinical recommendations available designed towards adult patients, there was an urgent need for clinicians, public health officials and the government to also prioritize evidence-based clinical practice guidelines for the pediatric population. Hence, the development of the Philippine Pediatric COVID-19 Living Clinical Practice Guidelines was conceptualized. This independent project, funded and supported by the PPS and PIDSP, aimed to formulate up-to-date, evidence-based recommendations on the treatment, diagnosis, infection prevention and control of COVID-19 in children. Following the standard CPG development process outlined in the DOH Manual for CPG Development and the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology, 15 evidence summaries and 24 recommendations were generated by 12 consensus panelists representing their specific health organizations and institutions.

Emerging Technologies of Three-Dimensional Printing and Mobile Health in COVID-19 Immunity and Regenerative Dentistry.

The ongoing coronavirus disease 2019 (COVID-19) pandemic highlights the importance of developing point-of-care (POC) antibody tests for monitoring the COVID-19 immune response upon viral infection or following vaccination, which requires three key aspects to achieve optimal monitoring, including three-dimensional (3D)-printed POC devices, mobile health (mHealth), and noninvasive sampling. As a critical tissue engineering concept, additive manufacturing (AM, also known as 3D printing) enables accurate control over the dimensional and architectural features of the devices. mHealth refers to the use of portable digital devices, such as smartphones, tablet computers, and fitness and medical wearables, to support health, which facilitates contact tracing, and telehealth consultations during the pandemic. Compared with invasive biosample (blood), saliva is of great importance in the spread and surveillance of COVID-19 as a noninvasive diagnostic method for virus detection and immune status monitoring. However, investigations into 3D-printed POC antibody test and mHealth using noninvasive saliva are relatively limited. Further exploration of 3D-printed antibody POC tests and mHealth applications to monitor antibody production for either disease onset or immune response following vaccination is warranted. This review briefly describes the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and immune response after infection and vaccination, then discusses current widely used binding antibody tests using blood samples and enzyme-linked immunosorbent assays on two-dimensional microplates before focusing upon emerging POC technological platforms, such as field-effect transistor biosensors, lateral flow assay, microfluidics, and AM for fabricating immunoassays, and the possibility of their combination with mHealth. This review proposes that noninvasive biofluid sampling combined with 3D POC antibody tests and mHealth technologies is a promising and novel approach for POC detection and surveillance of SARS-CoV-2 immune response. Furthermore, as key concepts in dentistry, the application of 3D printing and mHealth was also included to facilitate the appreciation of cutting edge techniques in regenerative dentistry. This review highlights the potential of 3D printing and mHealth in both COVID-19 immunity monitoring and regenerative dentistry.

A wastewater-based risk index for SARS-CoV-2 infections among three cities on the Canadian Prairie

Wastewater surveillance (WWS) is useful to better understand the spreading of coronavirus disease 2019 (COVID-19) in communities, which can help design and implement suitable mitigation measures. The main objective of this study was to develop the Wastewater Viral Load Risk Index (WWVLRI) for three Saskatchewan cities to offer a simple metric to interpret WWS. The index was developed by considering relationships between reproduction number, clinical data, daily per capita concentrations of virus particles in wastewater, and weekly viral load change rate. Trends of daily per capita concentrations of SARS-CoV-2 in wastewater for Saskatoon, Prince Albert, and North Battleford were similar during the pandemic, suggesting that per capita viral load can be useful to quantitatively compare wastewater signals among cities and develop an effective and comprehensible WWVLRI. The effective reproduction number (Rt) and the daily per capita efficiency adjusted viral load thresholds of 85 × 106 and 200 × 106 N2 gene counts (gc)/population day (pd) were determined. These values with rates of change were used to categorize the potential for COVID-19 outbreaks and subsequent declines. The weekly average was considered ‘low risk’ when the per capita viral load was 85 × 106 N2 gc/pd. A ‘medium risk’ occurs when the per capita copies were between 85 × 106 and 200 × 106 N2 gc/pd. with a rate of change <100 %. The start of an outbreak is indicated by a ‘medium-high’ risk classification when the week-over-week rate of change was >100 %, and the absolute magnitude of concentrations of viral particles was >85 × 106 N2 gc/pd. Lastly, a ‘high risk’ occurs when the viral load exceeds 200 × 106 N2 gc/pd. This methodology provides a valuable resource for decision-makers and health authorities, specifically given the limitation of COVID-19 surveillance based on clinical data.

COVID-19 surveillance in wastewater: An epidemiological tool for the monitoring of SARS-CoV-2.

The coronavirus disease 2019 (COVID-19) pandemic has prompted a lot of questions globally regarding the range of information about the virus's possible routes of transmission, diagnostics, and therapeutic tools. Worldwide studies have pointed out the importance of monitoring and early surveillance techniques based on the identification of viral RNA in wastewater. These studies indicated the presence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in human feces, which is shed via excreta including mucus, feces, saliva, and sputum. Subsequently, they get dumped into wastewater, and their presence in wastewater provides a possibility of using it as a tool to help prevent and eradicate the virus. Its monitoring is still done in many regions worldwide and serves as an early "warning signal"; however, a lot of limitations of wastewater surveillance have also been identified.