Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study

The interaction between population age structure and policy interventions on the spread of COVID-19

COVID-19 has triggered an unprecedented public health crisis and a global economic shock. As countries and cities have transitioned away from strict pandemic restrictions, the most effective reopening strategies may vary significantly based on their demographic characteristics and social contact patterns. In this study, we employed an extended age-specific compartment model that incorporates population mobility to investigate the interaction between population age structure and various containment interventions in New York, Los Angeles, Daegu, and Nairobi - four cities with distinct age distributions that served as local epicenters of the epidemic from January 2020 to March 2021. Our results demonstrated that individual social distancing or quarantine strategies alone cannot effectively curb the spread of infection over a one-year period. However, a combined strategy, including school closure, 50 % working from home, 50 % reduction in other mobility, 10 % quarantine rate, and city lockdown interventions, can effectively suppress the infection. Furthermore, our findings revealed that social-distancing policies exhibit strong age-specific effects, and age-targeted interventions can yield significant spillover benefits. Specifically, reducing contact rates among the population under 20 can prevent 14 %, 18 %, 56 %, and 99 % of infections across all age groups in New York, Los Angeles, Daegu, and Nairobi, respectively, surpassing the effectiveness of policies exclusively targeting adults over 60 years old. In particular, to protect the elderly, it is essential to reduce contacts between the younger population and people of all age groups, especially those over 60 years old. While an older population structure may escalate fatality risk, it might also decrease infection risk. Moreover, a higher basic reproduction number amplifies the impact of an older population structure on the fatality risk of the elderly. The considerable variations in susceptibility, severity, and mobility across age groups underscore the need for targeted interventions to effectively control the spread of COVID-19 and mitigate risks in future pandemics.

COVID-19 Symptoms Only Minutely Influenced by Genes Among Children in a Nationwide Twin Cohort

BACKGROUND

The World Health Organization classified coronavirus disease (COVID-19) as a pandemic by March 11, 2020. Children had a milder disease than adults, and many were asymptomatic. The pandemic could be seen as a natural experiment with several changes, including time spent at home. The relative influence of genes and environment on the variability of a trait can be studied using twin pairs. We aimed to investigate the occurrence of reported COVID-19 symptoms and to separate the relative influence of genes and environment on these traits by variance decomposition.

METHODS

This was a population-based twin study conducted between November 2020 and March 2023. A survey was sent out to all parents of 9-year-old twins containing questions related to suspected COVID-19, symptoms of cough, fever and rhinorrhea, as well as concerns for their own and others' health. Twin modeling with variance decomposition was used to separate the relative influence of genes and environment.

RESULTS

In total, 3094 individuals from 1547 complete twin pairs were included (618 monozygotic and 929 dizygotic twin pairs). Suspected COVID-19 increased over time and concerns for own and others' health decreased. We found variability to be attributed mainly to shared environment in all traits investigated ranging between 63.0% and 86.2%. The rest of the variance of each trait was attributed to genetic factors (11.6%-33.5%) and nonshared environment (2.1%-9.9%).

CONCLUSIONS

We found results of substantial shared environment in all traits analyzed among 9-year-old twins. Age and timing seem crucial when investigating the possible influence of genes and the environment when a new virus is introduced before herd immunity is reached.

Risk factors of COVID-19 related hospitalization of paediatric patients with rheumatic diseases: a systematic review and meta-analysis

OBJECTIVE

Among adults who develop coronavirus disease 2019 (COVID-19), those with rheumatic diseases (RDs) have similar hospitalization rates compared with those without RDs. Similar comparisons are lacking in children, due to the overall rarity of COVID-19-related hospitalization in this population. We aimed to examine the risk factors for COVID-19-related hospitalization in paediatric patients with RDs.

METHODS

We conducted a systemic literature search in MEDLINE, EMBASE, Web of Science and China National Knowledge Infrastructure from 1 December 2019, through 22 January 2024. We included observational studies based on inclusion and exclusion criteria. Odds ratios (ORs) with 95% CI were calculated.

RESULTS

Eight cohort studies capturing 1501 paediatric RD patients with SARS-CoV-2 and 118 COVID-19-related hospitalization were included. Odds of hospitalization was increased in children with RDs compared with healthy children. While the diagnosis of juvenile idiopathic arthritis (JIA) was associated with reduced odds of hospitalization overall (OR 0.43 [95% CI: 0.27, 0.68]), systemic JIA was associated with increased odds of hospitalization (OR 2.54 [95% CI: 1.01, 6.40]). The use of glucocorticoids (OR 5.36 [95% CI: 2.21, 13.04]), rituximab (OR 4.62 [95% CI: 1.87, 11.40]), mycophenolate mofetil (OR 4.17 [95% CI: 1.08, 16.16]), hydroxychloroquine (OR 2.97 [95% CI: 1.42, 6.21]), and IL-1 inhibitors (OR 2.28 [95% CI: 1.09, 4.78]) was associated with increased odds of hospitalization, while the use of TNFα inhibitors was associated with reduced odds (OR 0.35 [95% CI: 0.20, 0.66]).

CONCLUSION

Children with RDs are at risk of severe COVID-19 outcomes, while children with JIA taking TNFα inhibitors might be at a lower risk.

Estimating Re and overdispersion in secondary cases from the size of identical sequence clusters of SARS-CoV-2

The wealth of genomic data that was generated during the COVID-19 pandemic provides an exceptional opportunity to obtain information on the transmission of SARS-CoV-2. Specifically, there is great interest to better understand how the effective reproduction number [Formula: see text] and the overdispersion of secondary cases, which can be quantified by the negative binomial dispersion parameter k, changed over time and across regions and viral variants. The aim of our study was to develop a Bayesian framework to infer [Formula: see text] and k from viral sequence data. First, we developed a mathematical model for the distribution of the size of identical sequence clusters, in which we integrated viral transmission, the mutation rate of the virus, and incomplete case-detection. Second, we implemented this model within a Bayesian inference framework, allowing the estimation of [Formula: see text] and k from genomic data only. We validated this model in a simulation study. Third, we identified clusters of identical sequences in all SARS-CoV-2 sequences in 2021 from Switzerland, Denmark, and Germany that were available on GISAID. We obtained monthly estimates of the posterior distribution of [Formula: see text] and k, with the resulting [Formula: see text] estimates slightly lower than estimates obtained by other methods, and k comparable with previous results. We found comparatively higher estimates of k in Denmark which suggests less opportunities for superspreading and more controlled transmission compared to the other countries in 2021. Our model included an estimation of the case detection and sampling probability, but the estimates obtained had large uncertainty, reflecting the difficulty of estimating these parameters simultaneously. Our study presents a novel method to infer information on the transmission of infectious diseases and its heterogeneity using genomic data. With increasing availability of sequences of pathogens in the future, we expect that our method has the potential to provide new insights into the transmission and the overdispersion in secondary cases of other pathogens.

Seroprevalence study of the new coronavirus (SARS-CoV-2) in families and cohabitants of confirmed cases in Mashhad, Iran: a cross-sectional study

The seroepidemiological characteristics of the SARS-CoV-2 were investigated along with the secondary infection rate in the household of confirmed patients in a high-risk population in Mashhad, Iran. The current descriptive cross-sectional study includes a total of 154 confirmed cases of SARS-CoV-2 infection in Mashhad, Iran, from March 2021 to December 2021. The participants' families were screened for SARS-CoV-2 secondary infection rate, and a standard checklist containing the research parameters was completed by all participants. The participants' average age was 43.19 ± 9.86 years, of which 80 (51.9%) were female and the rest were male. Of the participants, 147 (95.5%) reported using face masks, and 83 (53.9%) were using masks all the time. IgG and IgM of COVID-19 were positive in 43 (27.9%) and 8 (5.2%) individuals, respectively. The average positive rate in the participants was 0.12 ± 0.24. Wearing masks when contracting with an infected patient (p < 0.001 and r = -0.370), using a separate room (p < 0.001 and r = -0.663), a separate toilet (p < 0.001 and r = -0.663) and the number of family members (p = 0.013 and r = 0.201) were significantly correlated to the positive rate of infection among the participants. Adherence to wearing masks and using separate rooms, and toilets by households in contact with a COVID-19-confirmed patient reduces the secondary transmission rate of the disease among healthy family members. In addition, the probability of COVID-19 transmission is higher in larger families.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13337-024-00903-9.

Impact of disease severity, age, sex, comorbidity, and vaccination on secondary attack rates of SARS-CoV-2: a global systematic review and meta-analysis

BACKGROUND

Understanding the key drivers of SARS-CoV-2 transmission is essential for shaping effective public health strategies. However, transmission risk is subject to substantial heterogeneity related to disease severity, age, sex, comorbidities, and vaccination status in different population settings and regions. We aimed to quantify the impact of these factors on secondary attack rates (SARs) of SARS-CoV-2 across diverse population settings and regions, and identify key determinants of transmission to inform targeted interventions for improving global pandemic response.

METHODS

To retrieve relevant literature covering the duration of the COVID-19 pandemic, we searched Ovid MEDLINE, Ovid Embase, Web of Science, and the Cochrane COVID-19 Study Register between January 1, 2020 and January 18, 2024 to identify studies estimating SARs of SARS-CoV-2, defined as the proportion of close contacts infected. We pooled SAR estimates using a random-effects model with the Freeman-Tukey double arcsine transformation and derived Clopper-Pearson 95% confidence intervals (CIs). Risk of bias was assessed using a modified Newcastle-Ottawa scale. This study was registered with PROSPERO, CRD42024503782.

RESULTS

A total of 159 eligible studies, involving over 19 million close contacts and 6.8 million cases from 41 countries across five continents, were included in the analysis. SARs increased with disease severity in index cases, ranging from 0.10 (95% CI: 0.06-0.14; I2 = 99.65%) in asymptomatic infection to 0.15 (95% CI: 0.09-0.21; I2 = 92.49%) in those with severe or critical conditions. SARs by age were lowest at 0.20 (95% CI: 0.16-0.23; I2 = 99.44%) for close contacts under 18 years and highest at 0.29 (95% CI: 0.24-0.34; I2 = 99.65%) for index cases aged 65 years or older. Among both index cases and close contacts, pooled SAR estimates were highest for Omicron and lowest for Delta, and declined with increasing vaccine doses. Regionally, North America had the highest SAR at 0.27 (95% CI: 0.24-0.30; I2 = 99.31%), significantly surpassing SARs in Europe (0.19; 95% CI: 0.15-0.25; I2 = 99.99%), Southeast Asia (0.18; 95% CI: 0.13-0.24; I2 = 99.24%), and the Western Pacific (0.11; 95% CI: 0.08-0.15; I2 = 99.95%). Among close contacts with comorbidities, chronic lung disease and hypertension were associated with the highest SARs. No significant association was found between SARs and the sex of either index cases or close contacts.

CONCLUSIONS

Secondary attack rates varied substantially by demographic and regional characteristics of the studied populations. Our findings demonstrate the role of booster vaccinations in curbing transmission, underscoring the importance of maintaining population immunity as variants of SARS-CoV-2 continue to emerge. Effective pandemic responses should prioritise tailored interventions that consider population demographics and social dynamics across different regions.

An agent based simulation of COVID-19 history in Catalonia using extensive real datasets

During the COVID-19 pandemic, effective public policy interventions have been crucial in combating virus transmission, sparking extensive debate on crisis management strategies and emphasizing the necessity for reliable models to inform governmental decisions, particularly at the local level. Leveraging disaggregated socio-demographic microdata, including social determinants, age-specific strata, and mobility patterns, we design a comprehensive network model of Catalonia's population and, through numerical simulation, assess its response to the outbreak of COVID-19 over the two-year period 2020-21. Our findings underscore the critical importance of timely implementation of broad non-pharmaceutical measures and effective vaccination campaigns in curbing virus spread; in addition, the identification of high-risk groups and their corresponding maps of connections within the network paves the way for tailored and more impactful interventions.

Three-year seroprevalence of SARS-CoV-2 nucleocapsid protein antibody among children, parental awareness, and contributors of infection: a single-school cohort study in Chiba, Japan

BACKGROUND

Coronavirus disease 2019 (COVID-19) in children is often asymptomatic, posing challenges in detecting infections. Additionally, factors contributing to infection remain poorly understood. This study aimed to investigate trends in anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid antibody seroprevalence, the relationship between seroprevalence and parental perception of child infection, and factors related to COVID-19 in children.

METHODS

In December 2020, 355 children aged 6-12 years in one elementary school were enrolled in the study. The anti-SARS-CoV-2 nucleocapsid antibody seroprevalence was assessed, and questionnaires were administered annually for three years. Parents' perceptions of infection and factors contributing to infection were examined.

RESULTS

The seroprevalence was 0.6%, 2.2%, and 60.9% in the first, second, and third years, respectively. The third-year seroprevalence among children reported as 'infected,' 'not tested but had symptoms,' and 'not infected' by parents was 97.3%, 83.3%, and 35.7%, respectively. Increased odds of seropositivity at the third-year measurement were observed in lower grades (adjusted odds ratio [aOR]=2.79 compared with higher grades) and in children more likely to play with others (aOR=3.97 for 'somewhat' and 2.84 for 'often,' compared with 'rarely'). No significant associations with seropositivity were found for sex, siblings, body mass index, serum 25-OH vitamin D3 concentration, or sleep duration.

CONCLUSION

The Omicron variant outbreak from the end of 2021 led to a sharp increase in seroprevalence among children, with many unaware of their infection. Frequent play with others may facilitate transmission in children. These data provide useful information for developing countermeasures against COVID-19 and other future pandemics.

HealthPass: a contactless check-in and adaptive access control system for lowering cluster infection risk in public health crisis

Introduction

Ensuring effective measures against the spread of the virus is paramount for educational institutions and workplaces as they resume operations amidst the ongoing public health crisis. A touchless and privacy-conscious check-in procedure for visitor assessment is critical to safeguarding venues against potential virus transmission.

Methods

In our study, we developed an interaction-free entry system featuring anonymous visitors who voluntarily provide data. This system introduces an adaptable venue entry management mechanism that accounts for both visitors' potential risk and the venue's capacity, aiming to curb the risk of localized infections. We assess visitors' liability based on their voluntarily provided data through radar map analysis. Additionally, we evaluate the venue's situation by quantifying its risk from multiple dimensions. A queuing model is then employed to control visitor access adaptively based on visitors' liability and the venue's availability.

Results

Since May, our university campus has been the operational site for the implemented system, catering to the needs of visitors across distinct venues. Using real-world implementation, we conduct a series of simulation experiments and case studies to verify the effectiveness of the HealthPass system in lowering infection risks.

Discussion

The system has demonstrated its capacity to reduce infection risks by adapting visitor entry procedures based on individual risk factors and venue conditions. Our results suggest that the integration of a dynamic queuing model and real-time data analysis can effectively manage the flow of visitors while ensuring public health safety.

Temporal contact patterns and the implications for predicting superspreaders and planning of targeted outbreak control

Directly transmitted infectious diseases spread through social contacts that change over time, but outbreak models typically make simplifying assumptions about network structure and dynamics. To assess how common assumptions relate to real-world interactions, we analysed 11 networks from five settings and developed metrics, capturing crucial epidemiological features of these networks. We developed a novel metric, the 'retention index', to characterize the distribution of retained contacts over consecutive time steps relative to fully static and dynamic networks. In workplaces and schools, contacts in the same department formed most of the retained contacts. In contrast, no clear contact type dominated the retained contacts in hospitals, thus reducing overall risk of disease introduction would be more effective than control targeted at departments. We estimated the contacts repetition over multiple days and showed that simple resource planning models overestimate the number of unique contacts by 20%-70%. We distinguished the difference between 'superspreader' and infectious individuals driving 'superspreading events' by measuring how often the individual represents the top 80% of contacts in the time steps over the study duration. We showed an inherent difficulty in identifying 'superspreaders' reliably: less than 20% of the individuals in most settings were highly connected for multiple time steps.

Association Between Dietary Habit Changes and COVID-19 Prophylaxis During the Pandemic Among Japanese Maintenance Hemodialysis Patients

BACKGROUND

Following COVID-19, dietary habits have been altered frequently along with other societal lifestyle modifications. However, changes in the dietary habits of maintenance hemodialysis patients (MHPs) before and during COVID-19 have not been investigated.

METHODS

A total of 132 MHPs were assessed for changes in their dietary habits before and during the pandemic and their association with COVID-19 prevention. Logistic regression models were used to calculate the adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for the risk of COVID-19. A multivariate logistic regression analysis was performed.

RESULTS

Approximately 27% (36 of 132) of the MHPs modified their dietary habits. Following COVID-19, the frequency of eating out decreased, and that of eating in increased significantly for dinner. However, there was no change in dietary habits for breakfast and lunch. Multivariate analysis revealed an inverse correlation between the number of eating takeout and COVID-19; that is, more eating of takeout was associated with a lower risk of contracting COVID-19.

CONCLUSIONS

Comparing before and after the pandemic, there was a shift from eating out to eating in for dinner. However, the frequency of eating takeout played a role in preventing COVID-19, suggesting that the person preparing the meal may be a more important factor than where the meal is eaten when the main route of infection is household transmission.

Quantifying the impact of prevalence-dependent adaptive behavior on COVID-19 transmission: A modeling case study in Maryland

The COVID-19 pandemic highlighted the need for robust epidemic forecasts, projecting health burden over short- and medium-term time horizons. Many COVID-19 forecasting models incorporate information on infection transmission, disease progression, and the effects of interventions, but few combine information on how individuals change their behavior based on altruism, fear, risk perception, or personal economic circumstances. Moreover, early models of COVID-19 produced under- and over-estimates, failing to consider the complexity of human responses to disease threat and prevention measures. In this study, we modeled adaptive behavior during the first year of the COVID-19 pandemic in Maryland, USA. The adapted compartmental model incorporates time-varying transmissibility informed on data of environmental factors (e.g., absolute humidity) and behavioral factors (aggregate mobility and perceived risk). We show that humidity and mobility alone did little to explain transmissibility after the first 100 days. Including adaptive behavior in the form of perceived risk as a function of hospitalizations more effectively explained inferred transmissibility and improved out-of-sample fit, demonstrating the model's potential in real-time forecasting. These results demonstrate the importance of incorporating endogenous behavior in models, particularly during a pandemic, to produce more accurate projections, which could lead to more impactful and efficient decision making and resource allocation.

Pairwise Accelerated Failure Time Regression Models for Infectious Disease Transmission in Close-Contact Groups With External Sources of Infection

Many important questions in infectious disease epidemiology involve associations between covariates (e.g., age or vaccination status) and infectiousness or susceptibility. Because disease transmission produces dependent outcomes, these questions are difficult or impossible to address using standard regression models from biostatistics. Pairwise survival analysis handles dependent outcomes by calculating likelihoods in terms of contact interval distributions in ordered pairs of individuals. The contact interval in the ordered pairi j $$ ij $$ is the time from the onset of infectiousness ini $$ i $$ to infectious contact fromi $$ i $$ toj $$ j $$ , where an infectious contact is sufficient to infectj $$ j $$ if they are susceptible. Here, we introduce a pairwise accelerated failure time regression model for infectious disease transmission that allows the rate parameter of the contact interval distribution to depend on individual-level infectiousness covariates fori $$ i $$ , individual-level susceptibility covariates forj $$ j $$ , and pair-level covariates (e.g., type of relationship). This model can simultaneously handle internal infections (caused by transmission between individuals under observation) and external infections (caused by environmental or community sources of infection). We show that this model produces consistent and asymptotically normal parameter estimates. In a simulation study, we evaluate bias and confidence interval coverage probabilities, explore the role of epidemiologic study design, and investigate the effects of model misspecification. We use this regression model to analyze household data from Los Angeles County during the 2009 influenza A (H1N1) pandemic, where we find that the ability to account for external sources of infection increases the statistical power to estimate the effect of antiviral prophylaxis.

Dynamics of cytokine and antibody responses in community versus hospital SARS-CoV-2 infections

Introduction

Dysregulated host cytokine responses to SARS-CoV-2 infection are a primary cause of progression to severe disease, whereas early neutralizing antibody responses are considered protective. However, there are gaps in understanding the early temporal dynamics of these immune responses, and the profile of productive immune responses generated by non-hospitalized people with mild infections in the community.

Methods

Here we conducted a prospective cohort study of people with suspected infections/exposures in the US state of North Carolina, before vaccine availability. We recruited participants not only in hospitals/clinics, but also in their homes. With serial sampling, we compared virologic and immunologic factors in 258 community cases versus 114 hospital cases of COVID-19 to define factors associated with severity.

Results

We found that high early neutralizing antibodies were associated with lower nasal viral load, but not protection from hospitalization. Cytokine responses were evaluated in 125 cases, with subsets at first versus second week of illness to assess for time-dependent trajectories. The hospital group demonstrated a higher magnitude of serum IL-6, IL-1R antagonist, IP-10, and MIG; prolonged upregulation of IL-17; and lesser downregulation of GROα, IL-1R antagonist, and MCP1, in comparison to the community group suggesting that these factors may contribute to immunopathology. In the second week of illness, 2-fold increases in IL-6, IL-1R antagonist, and IP-10 were associated with 2.2, 1.8, and 10-fold higher odds of hospitalization respectively, whereas a 2-fold increase in IL-10 was associated with 63% reduction in odds of hospitalization (p<0.05). Moreover, antibody responses at 3-6 months post mild SARS-CoV-2 infections in the community revealed long-lasting antiviral IgM and IgA antibodies as well as a stable set point of neutralizing antibodies that were not waning.

Discussion

Our data provide valuable temporal cytokine benchmarks to track the progression of immunopathology in COVID-19 patients and guide improvements in immunotherapies.

A Retrospective Analysis of Jordan's National COVID-19 Call Center: Operations, Effectiveness, and Lessons Learned

Introduction

Contact tracing has been a cornerstone of non-pharmaceutical interventions to control the COVID-19 epidemic, with highly mixed effectiveness internationally. In Jordan, the Ministry of Health (MOH) collaborated with the Jordan Nurses and Midwives Council and the USAID Local Health System Sustainability Project to set up a call center for contact tracing of COVID-19.

Objective

This study described the operation and assessed the effectiveness of Jordan's COVID-19 call center activities in reaching COVID-19 cases and their contacts.

Methods

A retrospective observational design was conducted using data from all calls made by the COVID-19 call center cases between November 2020 and April 2022. Data were collected from initial and follow-up calls to PCR-confirmed COVID-19 cases and their contacts. Data on socio-demographics, symptoms, and contact tracing activities were recorded. The study focused on key outcomes, including call success rates, the number of cases and contacts reached, and the role of different detection modes in identifying cases.

Results

During the study period, the call center attempted to contact 1,027,911 COVID-19 cases, successfully reaching 802,525 cases (78.1%). Follow-up calls were made to 1,126,334 cases, with a success rate of 74%. The call center appeared particularly valuable during the initial period of the pandemic until it was overwhelmed by the significantly more transmissible Omicron variant of the virus. Two weaknesses were identified: gaps in reaching non-Jordanian citizen cases and difficulty in keeping up with case volume during the Omicron wave of February-March 2022, when reported cases peaked at over 20,000 per day. One-third of all reached cases said that they had been referred for testing through contact tracing.

Conclusion

Contact tracing activities led by the MOH were instrumental in identifying new cases, optimizing resource allocation, improving surveillance and data systems, targeting vulnerable population, and supporting mitigation strategies to combat the COVID-19 pandemic in Jordan.

Could Anemia Impact the Severity of Infections? COVID-19 as an Example

Background

The association between anemia and severity of infection as well as mortality rates among patients infected with COVID-19 has scarcely been studied. This is the first study from the UAE aimed to assess the influence of anemia on COVID-19 severity, ICU admission, and mortality rate.

Methods

A retrospective chart review of hospitalized COVID-19 patients was conducted in a large COVID-19 referral hospital in UAE. The study included adult patients with confirmed COVID-19. Clinical and laboratory data, severity of the disease, ICU admissions, and mortality rates were analyzed and correlated to the presence of anemia among the patients.

Results

A total of 3092 patients were included. 362 patients (11.7%) were anemic and most of the cases were between asymptomatic and mild COVID-19 (77.4%, n=2393). Among patients with anemia, 30.1% (n=109) had moderate to severe COVID-19. Statistically, anemia was associated significantly with a higher risk for severe COVID-19 outcome compared to nonanemic patients (AOR:1.59, 95% CI:1.24-2.04, p<0.001). Intensive care unit (ICU) admission was almost 3 times higher among anemic patients compared to nonanemic (AOR:2.83,95% CI:1.89-4.25, p<0.001). In addition, the overall mortality rate of 2.8% (n=87) was 2.5-fold higher in anemic than nonanemic patients (OR:2.56, CI: 1.49-4.06, p<0.001). Moreover, older age (≥48-year-old) and male gender were independent predictors for severe illness (Age: OR=1.26, CI:1.07-1.51, p=0.006; Gender: OR:1.43,CI:1.15-1.78, p<0.001)) and ICU admission (Age: OR:2.08, CI:1.47-2.94, p<0.001; Gender: OR: 1.83, CI:1.12-3.00, p=0.008) whereas only age ≥48 years old contributed to higher mortality rate (OR:1.60, CI:1.04-2.46, p=0.034).

Conclusion

Anemia was a major risk factor for severe COVID-19, ICU admission and mortality among hospitalized COVID-19 patients. Thus, healthcare providers should be aware of monitoring the hematological parameters among hospitalized patients with COVID-19 and anemia to reduce the risk of disease complications and mortality. This association should also be considered in other infectious diseases.

Rapid and extensive SARS-CoV-2 Omicron variant infection wave revealed by wastewater surveillance in Shenzhen following the lifting of a strict COVID-19 strategy

Wastewater-based epidemiology (WBE) has emerged as a promising tool for monitoring the spread of COVID-19, as SARS-CoV-2 can be shed in the faeces of infected individuals, even in the absence of symptoms. This study aimed to optimize a prediction model for estimating COVID-19 infection rates based on SARS-CoV-2 RNA concentrations in wastewater, and reveal the infection trends and variant diversification in Shenzhen, China following the lifting of a strict COVID-19 strategy. Faecal samples (n = 4337) from 1204 SARS-CoV-2 infected individuals hospitalized in a designated hospital were analysed to obtain Omicron variant-specific faecal shedding dynamics. Wastewater samples from 6 wastewater treatment plants (WWTPs) and 9 pump stations, covering 3.55 million people, were monitored for SARS-CoV-2 RNA concentrations and variant abundance. We found that the viral load in wastewater increased rapidly in December 2022 in the two districts, demonstrating a sharp peak in COVID-19 infections in late-December 2022, mainly caused by Omicron subvariants BA.5.2.48 and BF.7.14. The prediction model, based on the mass balance between total viral load in wastewater and individual faecal viral shedding, revealed a surge in the cumulative infection rate from <0.1 % to over 70 % within three weeks after the strict COVID-19 strategy was lifted. Additionally, 39 cryptic SARS-CoV-2 variants were identified in wastewater, in addition to those detected through clinical surveillance. These findings demonstrate the effectiveness of WBE in providing comprehensive and efficient assessments of COVID-19 infection rates and identifying cryptic variants, highlighting its potential for monitoring emerging pathogens with faecal shedding.

Association of iron deficiency anaemia with the hospitalization and mortality rate of patients with COVID‑19

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) illness led to the coronavirus disease 2019 (COVID-19) pandemic, which has caused enormous health and financial losses, as well as challenges to global health. Iron deficiency anaemia (IDA) has been linked to adverse outcomes in patients infected with SARS-COV-2. The present study aimed to assess the association between IDA and the severity of COVID-19 in hospitalized patients. For this purpose, a retrospective data analysis of 100 patients with COVID-19 was conducted. Data of patients hospitalized with SARS-COV-2 infection confirmed by RT-PCR were collected between June, 2021 and March, 2022. The collected data included patient demographics, comorbidities, clinical signs, symptoms and IDA medical laboratory findings, including complete blood count and iron profiles. The results revealed that patients with COVID-19 admitted to the isolation unit represented 61.0% of the study sample, whereas 39.0% were admitted to the intensive care unit (ICU). No patients had stage I IDA, whereas 4 patients (4%) had stage II IDA. Furthermore, 19 patients (19.0%) had stage III IDA. A significantly higher proportion of patients with IDA (69.6%) were admitted to the ICU compared with those without IDA (29.9%, P<0.001). Additionally, patients with IDA had a higher proportion of a history of stroke compared with those without IDA (17.4 vs. 2.6%, respectively, P=0.024). The most common comorbidities identified were hypertension (29%), diabetes (23%) and heart problems (17%). On the whole, the present study demonstrates significant associations between IDA and a longer hospitalization period. A greater incidence of complications was observed in the hospitalized patients who were SARS-COV-2-positive. Although further studies with larger sample sizes are required to confirm these findings, the results presented herein may provide insight for physicians as regards the prevention and treatment of patients with IDA who are infected with coronavirus.

Survival of hospitalised COVID-19 patients in Hawassa, Ethiopia: a cohort study

The COVID-19 pandemic, caused by SARS-CoV-2, led to 622,119,701 reported cases and 6,546,118 deaths. Most studies on COVID-19 patients in hospitals are from high-income countries, lacking data for developing countries such as Ethiopia.This study assesses clinical features, demographics, and risk factors for in-hospital mortality in Hawassa, Ethiopia. The research cohort comprises 804 cases exhibiting clinical diagnoses and/or radiological findings and indicative of symptoms consistent with COVID-19 at Hawassa University Comprehensive Specialized Hospital from September 24, 2020, to November 26, 2021. In-hospital mortality rate was predicted using Cox regression. The median age was 45 years, with males making up 64.1% of the population. 173 (21.5%) fatalities occurred, with 125 (72.3%) among males. Male patients had higher mortality rates than females. Severe and critical cases were 24% and 21%. 49.1% had at least one comorbidity, with 12.6% having multiple. Common comorbidities were diabetes (15.9%) and hypertension (15.2%). The Cox regression in Ethiopian COVID-19 patients found that factors like gender, advanced age group, disease severity, symptoms upon admission, shortness of breath, sore throat, body weakness, hypertension, diabetes, multiple comorbidities, and prior health facility visits increased the risk of COVID-19 death, similar to high-income nations. However, in Ethiopia, COVID-19 patients were young and economically active. Patients with at least one symptom had reduced death risk. As a conclusion, COVID-19 in Ethiopia mainly affected the younger demographic, particularly economically active individuals. Early detection can reduce the risk of mortality. Prompt medical attention is essential, especially for individuals with comorbidities. Further research needed on diabetes and hypertension management to reduce mortality risk. Risk factors identified at admission play a crucial role in guiding clinical decisions for intensive monitoring and treatment. Broader risk indicators help prioritize patients for allocation of hospital resources, especially in regions with limited medical facilities. Government's focus on timely testing and strict adherence to regulations crucial for reducing economic impact.

Susceptibility and infectiousness of SARS-CoV-2 in children versus adults, by variant (wild-type, alpha, delta): A systematic review and meta-analysis of household contact studies

IMPORTANCE

Understanding the susceptibility and infectiousness of children and adolescents in comparison to adults is important to appreciate their role in the COVID-19 pandemic.

OBJECTIVE

To determine SARS-CoV-2 susceptibility and infectiousness of children and adolescents with adults as comparator for three variants (wild-type, alpha, delta) in the household setting. We aimed to identify the effects independent of vaccination or prior infection.

DATA SOURCES

We searched EMBASE, PubMed and medRxiv up to January 2022.

STUDY SELECTION

Two reviewers independently identified studies providing secondary household attack rates (SAR) for SARS-CoV-2 infection in children (0-9 years), adolescents (10-19 years) or both compared with adults (20 years and older).

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently extracted data, assessed risk of bias and performed a random-effects meta-analysis model.

MAIN OUTCOMES AND MEASURES

Odds ratio (OR) for SARS-CoV-2 infection comparing children and adolescents with adults stratified by wild-type (ancestral type), alpha, and delta variant, respectively. Susceptibility was defined as the secondary attack rate (SAR) among susceptible household contacts irrespective of the age of the index case. Infectiousness was defined as the SAR irrespective of the age of household contacts when children/adolescents/adults were the index case.

RESULTS

Susceptibility analysis: We included 27 studies (308,681 contacts), for delta only one (large) study was available. Compared to adults, children and adolescents were less susceptible to the wild-type and delta, but equally susceptible to alpha. Infectiousness analysis: We included 21 studies (201,199 index cases). Compared to adults, children and adolescents were less infectious when infected with the wild-type and delta. Alpha -related infectiousness remained unclear, 0-9 year old children were at least as infectious as adults. Overall SAR among household contacts varied between the variants.

CONCLUSIONS AND RELEVANCE

When considering the potential role of children and adolescents, variant-specific susceptibility, infectiousness, age group and overall transmissibility need to be assessed.

Effectiveness of probabilistic contact tracing in epidemic containment: The role of superspreaders and transmission path reconstruction

The recent COVID-19 pandemic underscores the significance of early stage nonpharmacological intervention strategies. The widespread use of masks and the systematic implementation of contact tracing strategies provide a potentially equally effective and socially less impactful alternative to more conventional approaches, such as large-scale mobility restrictions. However, manual contact tracing faces strong limitations in accessing the network of contacts, and the scalability of currently implemented protocols for smartphone-based digital contact tracing becomes impractical during the rapid expansion phases of the outbreaks, due to the surge in exposure notifications and associated tests. A substantial improvement in digital contact tracing can be obtained through the integration of probabilistic techniques for risk assessment that can more effectively guide the allocation of diagnostic tests. In this study, we first quantitatively analyze the diagnostic and social costs associated with these containment measures based on contact tracing, employing three state-of-the-art models of SARS-CoV-2 spreading. Our results suggest that probabilistic techniques allow for more effective mitigation at a lower cost. Secondly, our findings reveal a remarkable efficacy of probabilistic contact-tracing techniques in performing backward and multistep tracing and capturing superspreading events.

Children with previous COVID-19 infection are more likely to present with recurrent acute otitis media or tube otorrhea

OBJECTIVE

Since December 2021, the number of children with COVID-19 infections has increased. Sequelae in children have not been well-described. Our goal was to determine if children with a history of COVID-19 infection (C19 group) were more likely to present with recurrent acute otitis media (rAOM) or post-ventilation tube otorrhea (VTO) than children who had no history of COVID-19 infection (NoC19 group).

METHODS

Charts of consecutive children presenting at a pediatric otolaryngology clinic from March-May 2022 were reviewed. Demographics, COVID-19 test history, comorbidities, ultimate diagnosis, physical exam findings, and management plan were included. No children had a known COVID-19 infection at the time of visit.

RESULTS

524 children were included, 228 (43.5 %) girls and 296 (56.5 %) boys. Mean age was 5 years (95 % CI 4.6-5.4). 115 (21.9 %) had a history of COVID-19 infection. 104 (19.8 %) had a diagnosis of rAOM or VTO, 26.1 % (30/115) children in C19 and 18.1 % (74/409) children in NoC19 (Fisher's Exact p = .04, OR = 1.6). For children without ventilation tubes in place, 23.5 % (27/115) in C19 had rAOM versus 15.2 % (62/409) in NoC19 (p = .03, OR = 1.7). 18.3 % (21/115) of the C19 group had nasal congestion compared to 6.6 % (27/409) of the NoC19 group (p < .001, OR = 3.2). There was no difference in incidence of otitis media with effusion, tonsil/adenoid hypertrophy, sleep-disordered breathing, or epistaxis between the groups.

CONCLUSION

Infection with COVID-19 may be associated with an increased risk of rAOM and VTO in children. This may affect healthcare utilization by increasing the need for pediatric and otolaryngologic care.

Did we observe changes in obstetric interventions in SARS-CoV-2 infected pregnant women at the beginning of COVID-pandemic in Belgium? Results of a nationwide population-based study

Background

Pregnant women are more vulnerable to the severe effects of COVID-19 compared to their non-pregnant peers. Early in the pandemic, there was a rise in cesarean deliveries and preterm births among infected pregnant women. This study aims to evaluate whether there were any changes in obstetric interventions during the first two waves of the pandemic in Belgium.

Methods

Between March 2020 and February 2021, the Belgian Obstetric Surveillance System (B.OSS) conducted an extensive, nationwide population-based registry study, that included nearly all births to women with a confirmed SARS-CoV-2 infection within six weeks before hospitalization in Belgium. The perinatal outcomes of these women were analyzed and compared with pre-pandemic regional perinatal data.

Results

A total of 923 SARS-CoV-2 infected pregnant women were admitted to the hospital; 9.3 % were hospitalized for severe COVID-19, while the remaining were hospitalized for obstetric reasons. Infected women had a higher median BMI, a higher incidence of diabetes, and a greater proportion were overweight or obese compared to the reference group (p < 0.001). While the majority of women gave birth vaginally, symptomatic women and those with a severe infection had slightly higher rates of cesarean delivery, though not statistically significant after adjusting for confounders. Only severely ill women had an increased risk of preterm delivery (aOR 2.3; 95 %CI [1.2-2.5]; p = 0.02) and of induced labor (OR 1.8; 95 %CI [1.1-2.8]; p = 0.01). The use of general anesthesia for cesarean delivery was more common in the infected group (OR 2.6; 95 %CI [1.6-4.1]; p < 0.001).

Conclusions

Obstetric interventions, such as cesarean delivery and induction, remained at pre-pandemic levels. However, a SARS-CoV-2 infection appears to have increased medically induced preterm delivery and the use of general anesthesia for cesarean delivery.

Trends in SARS-CoV-2 cycle threshold (Ct) values from nucleic acid testing predict the trajectory of COVID-19 waves

Forecasting COVID-19 waves helps with public health planning and resource allocation. Cycle threshold (Ct) values obtained from positive SARS-CoV-2 nucleic acid amplification test (NAAT) results offer limited value for individual patient management, but real-time analysis of temporal trends of aggregated Ct values may provide helpful information to predict the trajectories of COVID-19 waves in the community. Ct value trends on 59,609 SARS-CoV-2 NAAT-positive results from 574,403 tests using a single testing assay system, between September 2021 and January 2023, were examined to monitor the trend of the proportion of positive NAAT with lower Ct values (≤28) in relation to changing COVID-19 case numbers over time. We applied regression with autoregressive integrated moving average errors modelling approach to study the relation between Ct values and case counts. We also developed an insight product to monitor the temporal trends with Ct values obtained from SARS-CoV-2 NAAT-positive results. In this study, the proportion of lower Ct values preceded by a range of 7-32 days the rising population COVID-19 testing rate reflecting onset of a COVID-19 wave. Monitoring population Ct values may assist in predicting increased disease activity.

Estimating the household secondary attack rate and serial interval of COVID-19 using social media

We propose a method to estimate the household secondary attack rate (hSAR) of COVID-19 in the United Kingdom based on activity on the social media platform X, formerly known as Twitter. Conventional methods of hSAR estimation are resource intensive, requiring regular contact tracing of COVID-19 cases. Our proposed framework provides a complementary method that does not rely on conventional contact tracing or laboratory involvement, including the collection, processing, and analysis of biological samples. We use a text classifier to identify reports of people tweeting about themselves and/or members of their household having COVID-19 infections. A probabilistic analysis is then performed to estimate the hSAR based on the number of self or household, and self and household tweets of COVID-19 infection. The analysis includes adjustments for a reluctance of Twitter users to tweet about household members, and the possibility that the secondary infection was not acquired within the household. Experimental results for the UK, both monthly and weekly, are reported for the period from January 2020 to February 2022. Our results agree with previously reported hSAR estimates, varying with the primary variants of concern, e.g. delta and omicron. The serial interval (SI) is based on the time between the two tweets that indicate a primary and secondary infection. Experimental results, though larger than the consensus, are qualitatively similar. The estimation of hSAR and SI using social media data constitutes a new tool that may help in characterizing, forecasting and managing outbreaks and pandemics in a faster, affordable, and more efficient manner.

Estimating time-varying epidemiological parameters and underreporting of Covid-19 cases in Brazil using a mathematical model with fuzzy transitions between epidemic periods

Our study conducts a comprehensive analysis of the Covid-19 pandemic in Brazil, spanning five waves over three years. We employed a novel Susceptible-Infected-Recovered-Dead-Susceptible (SIRDS) model with a fuzzy transition between epidemic periods to estimate time-varying parameters and evaluate case underreporting. The initial basic reproduction number (R0) is identified at 2.44 (95% Confidence Interval (CI): 2.42-2.46), decreasing to 1.00 (95% CI: 0.99-1.01) during the first wave. The model estimates an underreporting factor of 12.9 (95% CI: 12.5-13.2) more infections than officially reported by Brazilian health authorities, with an increasing factor of 5.8 (95% CI: 5.2-6.4), 12.9 (95% CI: 12.5-13.3), and 16.8 (95% CI: 15.8-17.5) in 2020, 2021, and 2022 respectively. Additionally, the Infection Fatality Rate (IFR) is initially 0.88% (95% CI: 0.81%-0.94%) during the initial phase but consistently reduces across subsequent outbreaks, reaching its lowest value of 0.018% (95% CI: 0.011-0.033) in the last outbreak. Regarding the immunity period, the observed uncertainty and low sensitivity indicate that inferring this parameter is particularly challenging. Brazil successfully reduced R0 during the first wave, coinciding with decreased human mobility. Ineffective public health measures during the second wave resulted in the highest mortality rates within the studied period. We attribute lower mortality rates in 2022 to increased vaccination coverage and the lower lethality of the Omicron variant. We demonstrate the model generalization by its application to other countries. Comparative analyses with serological research further validate the accuracy of the model. In forecasting analysis, our model provides reasonable outbreak predictions. In conclusion, our study provides a nuanced understanding of the Covid-19 pandemic in Brazil, employing a novel epidemiological model. The findings contribute to the broader discourse on pandemic dynamics, underreporting, and the effectiveness of health interventions.

Evolution of the Antigenic Landscape in Children and Young Adults with COVID-19 and MIS-C

There is minimal knowledge regarding the durability of neutralization capacity and level of binding antibody generated against the highly transmissible circulating Omicron subvariants following SARS-CoV-2 infection in children with acute COVID-19 and those diagnosed with multisystem inflammatory syndrome in children (MIS-C) in the absence of vaccination. In this study, SARS-CoV-2 neutralization titers against the ancestral strain (WA1) and Omicron sublineages were evaluated in unvaccinated children admitted for COVID-19 (n = 32) and MIS-C (n = 32) at the time of hospitalization (baseline) and at six to eight weeks post-discharge (follow-up) between 1 April 2020, and 1 September 2022. In addition, antibody binding to the spike receptor binding domain (RBD) from WA1, BA.1, BA.2.75, and BA.4/BA.5 was determined using surface plasmon resonance (SPR). At baseline, the children with MIS-C demonstrated two-fold to three-fold higher binding and neutralizing antibodies against ancestral WA1 compared to those with COVID-19. Importantly, in children with COVID-19, the virus neutralization titers against the Omicron subvariants at six to eight weeks post-discharge reached the same level as those with MIS-C had at baseline but were higher than titers at 6-8 weeks post-discharge for MIS-C cases. Cross-neutralization capacity against recently emerged Omicron BQ.1, BQ.1.1, and XBB.1 variants was very low in children with either COVID-19 or MIS-C at all time points. These findings about post-infection immunity in children with either COVID-19 or MIS-C suggest the need for vaccinations in children with prior COVID-19 or MIS-C to provide effective protection from emerging and circulating SARS-CoV-2 variants.

Observational study on the characteristics of COVID-19 transmission dynamics during the first wave of the epidemic in Lusaka, Zambia

Introduction

coronavirus disease 2019 (COVID-19) transmission dynamics in the communities of low- and middle-income countries, particularly sub-Saharan African countries, are still not fully understood. This study aimed to determine the characteristics of COVID-19 secondary transmission during the first wave of the epidemic (March-October 2020) in Lusaka, Zambia.

Methods

we conducted an observational study on COVID-19 secondary transmission among residents in Lusaka City, between March 18 and October 30, 2020. We compared the secondary attack rate (SAR) among different environmental settings of contacts and characteristics of primary cases (e.g, demographics, medical conditions) by logistic regression analysis.

Results

out of 1862 confirmed cases of COVID-19, 272 primary cases generated 422 secondary cases through 216 secondary transmission events. More contacts and secondary transmissions were reported in planned residential areas than in unplanned residential areas. Households were the most common environmental settings of secondary transmission, representing 76.4% (165/216) of secondary transmission events. The SAR in households was higher than the overall events. None of the environmental settings or host factors of primary cases showed a statistically significant relationship with SAR.

Conclusion

of the settings considered, households had the highest incidence of secondary transmission during the first wave in Lusaka, Zambia. The smaller proportion of contacts and secondary transmission in unplanned residential areas might have been due to underreporting of cases, given that those areas are reported to be vulnerable to infectious disease outbreaks. Continuous efforts are warranted to establish measures to suppress COVID-19 transmission in those high-risk environments.

Uncovering COVID-19 transmission tree: identifying traced and untraced infections in an infection network

Introduction

This paper presents a comprehensive analysis of COVID-19 transmission dynamics using an infection network derived from epidemiological data in South Korea, covering the period from January 3, 2020, to July 11, 2021. The network illustrates infector-infectee relationships and provides invaluable insights for managing and mitigating the spread of the disease. However, significant missing data hinder conventional analysis of such networks from epidemiological surveillance.

Methods

To address this challenge, this article suggests a novel approach for categorizing individuals into four distinct groups, based on the classification of their infector or infectee status as either traced or untraced cases among all confirmed cases. The study analyzes the changes in the infection networks among untraced and traced cases across five distinct periods.

Results

The four types of cases emphasize the impact of various factors, such as the implementation of public health strategies and the emergence of novel COVID-19 variants, which contribute to the propagation of COVID-19 transmission. One of the key findings is the identification of notable transmission patterns in specific age groups, particularly in those aged 20-29, 40-69, and 0-9, based on the four type classifications. Furthermore, we develop a novel real-time indicator to assess the potential for infectious disease transmission more effectively. By analyzing the lengths of connected components, this indicator facilitates improved predictions and enables policymakers to proactively respond, thereby helping to mitigate the effects of the pandemic on global communities.

Conclusion

This study offers a novel approach to categorizing COVID-19 cases, provides insights into transmission patterns, and introduces a real-time indicator for better assessment and management of the disease transmission, thereby supporting more effective public health interventions.

Asymptomatic Children as a Missing Link in Preventing COVID-19 Transmission

BACKGROUND

Investigating the prevalence of the coronavirus disease 2019 (COVID-19) infection in asymptomatic children who have been in close contact with symptomatic individuals is instrumental for refining public health approaches, protecting vulnerable populations, and mitigating the broader impact of the pandemic. Accordingly, this study aimed to evaluate the incidence of COVID-19 infection in asymptomatic children who had been in close contact with parents exhibiting COVID-19 symptoms. Study Design: A cross-sectional study.

METHODS

The present cross-sectional study was conducted on 175 asymptomatic children who had been in close contact with COVID-19 confirmed cases in Hamadan County from March 2021 to August 2021. Reverse transcription polymerase chain reaction (RT-PCR) testing was performed on all asymptomatic children who had been in close contact with an individual with COVID-19. Furthermore, multiple logistic regressions were conducted to determine the predictors of COVID-19 transmission from family members to children.

RESULTS

Out of the 175 children in close contact with index cases, 53 (30.29%) tested positive for COVID-19 through PCR. Regarding factors related to the index case, male cases (Adjusted odds ratio [AOR]=2.29; 95% confidence interval [CI]: 1.03-5.09, P=0.041), rural dwellers (AOR=3.22; 95% CI: 1.02-10.16, P=0.046), illiterate cases (AOR=8.45; 95% CI: 1.76-40.65, P=0.008), and cases presenting with nasal congestion symptoms (AOR=9.12; 95% CI: 2.22-37.40, P=0.002) were more prone to transmitting the virus to children who had close contact with them.

CONCLUSION

The findings of the present study suggested that asymptomatic COVID-19 infection in household contacts is significant in children who were in close contact with a COVID-19-positive patient. Therefore, it is crucial to continue to monitor this group closely.

Limited impact of lifting universal masks on SARS-CoV-2 transmission in schools: The crucial role of outcome measurements

Amid the COVID-19 pandemic, education systems globally implemented protective measures, notably mandatory mask wearing. As the pandemic's dynamics changed, many municipalities lifted these mandates, warranting a critical examination of these policy changes' implications. This study examines the effects of lifting mask mandates on COVID-19 transmission within Massachusetts school districts. We first replicated previous research that utilized a difference-in-difference (DID) model for COVID-19 incidence. We then repeated the DID analysis by replacing the outcome measurement with the reproductive number (Rt ), reflecting the transmissibility. Due to the data availability, the Rt we estimated only measures the within school transmission. We found a similar result in the replication using incidence with an average treatment effect on treated (ATT) of 39.1 (95% CI: 20.4 to 57.4) COVID-19 cases per 1,000 students associated with lifting masking mandates. However, when replacing the outcome measurement to Rt , our findings suggest that no significant association between lifting mask mandates and reduced Rt (ATT: 0.04, 95% CI: -0.09 to 0.18), except for the first 2 weeks postintervention. Moreover, we estimated Rt below 1 at 4 weeks before lifting mask mandates across all school types, suggesting nonsustainable transmission before the implementation. Our reanalysis suggested no evidence of lifting mask mandates in schools impacted the COVID-19 transmission in the long term. Our study highlights the importance of examining the transmissibility outcome when evaluating interventions against transmission.

Contact patterns between index patients and their close contacts and assessing risk for COVID-19 transmission during different exposure time windows: a large retrospective observational study of 450 770 close contacts in Shanghai

ABSTRACT

Introduction

To characterise age-mixing patterns among index cases and contacts of COVID-19, and explore when patients are most infectious during the disease process.

Methods

This study examined all initial 90 885 confirmed index cases in Shanghai and their 450 770 close contacts. A generalised additive mixed model was used to analyse the associations of the number of close contacts with different demographic and clinical characteristics. The effect of different exposure time windows on the infection of close contacts was evaluated using a modified mixed-effects Poisson regression.

Results

Analysis of contacts indicated that 82 467 (18.29%; 95% CI 18.17%, 18.42%) were second-generation cases. Our result indicated the q-index was 0.300 (95% CI 0.298, 0.302) for overall contact matrix, and that assortativity was greatest for students (q-index=0.377; 95% CI 0.357, 0.396) and weakest for people working age not in the labour force (q-index=0.246; 95% CI 0.240, 0.252). The number of contacts was 4.96 individuals per index case (95% CI 4.86, 5.06). Contacts had a higher risk if they were exposed from 1 day before to 3 days after the onset of symptoms in the index patient, with a maximum at day 0 (adjusted relative risk (aRR)=1.52; 95% CI 1.30, 1.76). Contacts exposed from 3 days before to 3 days after an asymptomatic index case had a positive reverse transcriptase-PCR (RT-PCR) result had a higher risk, with a maximum on day 0 (aRR=1.48; 95% CI 1.37, 1.59).

Conclusions

The greatest assortativity was for students and weakest for people working age not in the labour force. Contact in the household was a significant contributor to the infection of close contacts. Contact tracing should focus on individuals who had contact soon before or soon after the onset of symptoms (or positive RT-PCR test) in the index case.

COVID-19 contact tracing and quarantine policies in the Indo-Pacific Region: A mixed-methods study of experiences of public health professionals

Contact tracing and quarantine are valuable public health tools to prevent the transmission of SARS-CoV-2 and control the epidemic. Many low-and middle-income countries (LMICs) adopted global contact tracing and quarantine guidelines but were unable to contextualise the guidance into policies and practices that were relevant to their setting. Therefore, we examine contact tracing policies and practices in the Indo-Pacific region and the need to design context-specific policies. We conducted a mixed-methods study, including a cross-sectional online survey followed by key-informant interviews (KIIs). Using convenience snowball sampling, we invited public health professionals primarily involved in COVID-19 pandemic response from the Indo-Pacific region. We undertook descriptive analyses using counts and percentages for survey data and framework analysis for qualitative data. Seventy-seven public health professionals participated in the survey, of whom ten also participated in the KIIs. The study identified significant gaps between policies and the local contexts. Factors that broaden the gaps were limited knowledge of the changing dynamics of COVID-19 transmission, poor leadership, and coordination, little or no formal training on contact tracing, poor understanding of the guideline recommendations, limited resources, community resistance and mistrust, social stigmatisation and fear of being ostracised, and discrimination. This study revealed substantial disparities between policies and local contexts, significantly influencing policy implementation at national, provincial, and district levels across the studied countries. To bridge these gaps, we advocate for national contact tracing and quarantine guidelines explicitly addressing the quarantine needs of specific demographics, including children, pregnant women, prisoners, and individuals affected by social exclusion issues. Furthermore, we propose strengthening contact tracing training programs, urging revised guidelines to account for social, cultural, and infrastructural nuances influencing contact tracing and quarantine implementation. We also recommend engaging local NGOs, faith-based organisations, and local administrations to reinforce community connections and strengthen contact tracing.

COVID-19 testing, incidence, and positivity trends among school age children during the academic years 2020-2022 in the State of Qatar: special focus on using CDC indicators for community transmission to evaluate school attendance policies and public health response

BACKGROUND

There exists a gap in our understanding of the age-dependent epidemiological dynamics of SARS-CoV-2 among school-age children in comparison to adults within the State of Qatar. Additionally, there has been limited assessment of the timely implementation of physical distancing interventions, notably national school closures, and their impact on infection trends.

METHODS

We used the national database to capture all records of polymerase-chain-reaction (PCR) testing, and rapid antigen tests (RAT) conducted at all health care venues in Qatar and administered between August 26, 2020, and August 21, 2022, across all age groups (≥ 5 years old). Study participants under 18 years old were categorized into two age brackets: (5-11) and (12-17), aligning with the Primary and Preparatory/Secondary grade levels in Qatar, respectively. We assessed age group testing rates, incidence rates, and positivity rates in relation to adults. These epidemiological metrics were compared with the CDC's thresholds for COVID-19 community transmission.

RESULTS

Throughout the school years of 2020-2021 and 2021-2022, a total of 5,063,405 and 6,130,531 tests were respectively conducted. In the 2020-2021 school year, 89.6% of the tests were administered to adults, while 13.7% were conducted on children in the following year. The overall test positivity rates for the 2020-2021 and 2021-2022 school years were 5.8% and 8.1%, respectively. Adolescents underwent the fewest tests during the full study period compared to both adults and young children. Using the CDC indicators, we found that children and adolescents can significantly contribute to elevated infection rates, potentially driving community transmission upon relaxation of social restrictions.

CONCLUSION

It is crucial to acknowledge the potential for higher transmission among youth and adolescents when formulating transmission control strategies and making decisions regarding school closures. Employing data-driven indicators and thresholds to monitor COVID-19 community levels is important for informing decision-making. These approaches also enable the prompt implementation of infection control transmission mitigation measures in future pandemics.

Inference under superspreading: Determinants of SARS-CoV-2 transmission in Germany

Superspreading, under-reporting, reporting delay, and confounding complicate statistical inference on determinants of disease transmission. A model that accounts for these factors within a Bayesian framework is estimated using German Covid-19 surveillance data. Compartments based on date of symptom onset, location, and age group allow to identify age-specific changes in transmission, adjusting for weather, reported prevalence, and testing and tracing. Several factors were associated with a reduction in transmission: public awareness rising, information on local prevalence, testing and tracing, high temperature, stay-at-home orders, and restaurant closures. However, substantial uncertainty remains for other interventions including school closures and mandatory face coverings. The challenge of disentangling the effects of different determinants is discussed and examined through a simulation study. On a broader perspective, the study illustrates the potential of surveillance data with demographic information and date of symptom onset to improve inference in the presence of under-reporting and reporting delay.

Substantial transmission of SARS-CoV-2 through casual contact in retail stores: Evidence from matched administrative microdata on card payments and testing

This paper presents quasiexperimental evidence of Covid-19 transmission through casual contact between customers in retail stores. For a large sample of individuals in Denmark, we match card payment data, indicating exactly where and when each individual made purchases, with Covid-19 test data, indicating when each individual was tested and whether the test was positive. The resulting dataset identifies more than 100,000 instances where an infected individual made a purchase in a store and, in each instance, allows us to track the infection dynamics of other individuals who made purchases in the same store around the same time. We estimate transmissions by comparing the infection rate of exposed customers, who made a purchase within 5 min of an infected individual, and nonexposed customers, who made a purchase in the same store 16 to 30 min before. We find that exposure to an infected individual in a store increases the infection rate by around 0.12 percentage points (P < 0.001) between day 3 and day 7 after exposure. The estimates imply that transmissions in stores contributed around 0.04 to the reproduction number for the average infected individual and significantly more in the period where Omicron was the dominant variant.

How robust are estimates of key parameters in standard viral dynamic models?

Mathematical models of viral infection have been developed, fitted to data, and provide insight into disease pathogenesis for multiple agents that cause chronic infection, including HIV, hepatitis C, and B virus. However, for agents that cause acute infections or during the acute stage of agents that cause chronic infections, viral load data are often collected after symptoms develop, usually around or after the peak viral load. Consequently, we frequently lack data in the initial phase of viral growth, i.e., when pre-symptomatic transmission events occur. Missing data may make estimating the time of infection, the infectious period, and parameters in viral dynamic models, such as the cell infection rate, difficult. However, having extra information, such as the average time to peak viral load, may improve the robustness of the estimation. Here, we evaluated the robustness of estimates of key model parameters when viral load data prior to the viral load peak is missing, when we know the values of some parameters and/or the time from infection to peak viral load. Although estimates of the time of infection are sensitive to the quality and amount of available data, particularly pre-peak, other parameters important in understanding disease pathogenesis, such as the loss rate of infected cells, are less sensitive. Viral infectivity and the viral production rate are key parameters affecting the robustness of data fits. Fixing their values to literature values can help estimate the remaining model parameters when pre-peak data is missing or limited. We find a lack of data in the pre-peak growth phase underestimates the time to peak viral load by several days, leading to a shorter predicted growth phase. On the other hand, knowing the time of infection (e.g., from epidemiological data) and fixing it results in good estimates of dynamical parameters even in the absence of early data. While we provide ways to approximate model parameters in the absence of early viral load data, our results also suggest that these data, when available, are needed to estimate model parameters more precisely.

Within-household SARS-CoV-2 transmission and vaccine effectiveness in the first three COVID-19 school outbreaks in northern Viet Nam, September-December 2021

Objective

The risk of transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from schoolchildren to their household and the protective effects of vaccination in these settings remain poorly understood. We assessed the transmission dynamics of schoolchildren with SARS-CoV-2 within their households and the protective effects of coronavirus disease (COVID-19) vaccination among household members in Viet Nam.

Methods

We estimated the attack rate, vaccine effectiveness and adjusted risk ratio (aRR) of factors associated with SARS-CoV-2 transmission to household contacts of children confirmed to have COVID-19 who attended three schools in Ha Nam, Phu Tho and Thanh Hoa provinces between September and December 2021 using multivariable regression with household-level random effects.

Results

This retrospective cohort study included 157 children infected with SARS-CoV-2 and their 540 household contacts. The attack rate among household contacts was 24.6% (133/540). Overall, vaccine effectiveness among household contacts was 39% (95% confidence interval [CI]: -1 to -63), higher among males than females and higher in adults aged > 40 years. COVID-19 transmission was greater among female household contacts compared with males (aRR: 1.35, 95% CI: 0.94 to 1.95), although not statistically significant, and highest among those aged 19-39 years (aRR: 2.51, 95% CI: 1.50 to 4.21). Fully vaccinated household contacts had significantly lower infection risk (aRR: 0.46, 95% CI: 0.26 to 0.84).

Discussion

We found substantial onward transmission of SARS-CoV-2 from schoolchildren to household members, and older people were more likely to be protected by vaccination. We recommend that schoolchildren and all household members living with schoolchildren receive at least two doses of a COVID-19 vaccine. Recognizing the role of schoolchildren in the onward transmission of COVID-19 is an important lesson learned by Viet Nam that can help not only in managing other outbreaks but also in protecting schoolchildren by predicting the progress of the outbreak and preparing for a timely response.

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don't yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.

Differences between the true reproduction number and the apparent reproduction number of an epidemic time series

The time-varying reproduction number R(t) measures the number of new infections per infectious individual and is closely correlated with the time series of infection incidence by definition. The timings of actual infections are rarely known, and analysis of epidemics usually relies on time series data for other outcomes such as symptom onset. A common implicit assumption, when estimating R(t) from an epidemic time series, is that R(t) has the same relationship with these downstream outcomes as it does with the time series of incidence. However, this assumption is unlikely to be valid given that most epidemic time series are not perfect proxies of incidence. Rather they represent convolutions of incidence with uncertain delay distributions. Here we define the apparent time-varying reproduction number, RA(t), the reproduction number calculated from a downstream epidemic time series and demonstrate how differences between RA(t) and R(t) depend on the convolution function. The mean of the convolution function sets a time offset between the two signals, whilst the variance of the convolution function introduces a relative distortion between them. We present the convolution functions of epidemic time series that were available during the SARS-CoV-2 pandemic. Infection prevalence, measured by random sampling studies, presents fewer biases than other epidemic time series. Here we show that additionally the mean and variance of its convolution function were similar to that obtained from traditional surveillance based on mass-testing and could be reduced using more frequent testing, or by using stricter thresholds for positivity. Infection prevalence studies continue to be a versatile tool for tracking the temporal trends of R(t), and with additional refinements to their study protocol, will be of even greater utility during any future epidemics or pandemics.

Detecting changes in generation and serial intervals under varying pathogen biology, contact patterns and outbreak response

The epidemiological characteristics of SARS-CoV-2 transmission have changed over the pandemic due to emergence of new variants. A decrease in the generation or serial intervals would imply a shortened transmission timescale and, hence, outbreak response measures would need to expand at a faster rate. However, there are challenges in measuring these intervals. Alongside epidemiological changes, factors like varying delays in outbreak response, social contact patterns, dependence on the growth phase of an outbreak, and effects of exposure to multiple infectors can also influence measured generation or serial intervals. To guide real-time interpretation of variant data, we simulated concurrent changes in the aforementioned factors and estimated the statistical power to detect a change in the generation and serial interval. We compared our findings to the reported decrease or lack thereof in the generation and serial intervals of different SARS-CoV-2 variants. Our study helps to clarify contradictory outbreak observations and informs the required sample sizes under certain outbreak conditions to ensure that future studies of generation and serial intervals are adequately powered.

The Pandemics of Mass Destruction: A Comparative Analysis of HIV/AIDS and Coronavirus (COVID-19)

Historically, humanity has suffered and endured deadly pandemics of varying mortality rates. Irrefutably, research shows that the outbreak of pandemics is flooded by mythical and fallacious information among the public, hence stifling the prevention, treatment, and management of diseases. This paper focused on comparing selected aspects of the two pandemics, that is, HIV/AIDS and Coronavirus. This comparative analysis is important for drawing informative lessons for effective response and management of pandemics in the future. Through a literature review analysis, the paper established that both pandemics have more similarities than distinctions. The etiology and epidemiology of the diseases assume a similar cascading trajectory; the public health information about the diseases is characterized by myths, conspiracy theories, illusions, and delusions from the public. The myths associated with pandemics prevail around causation, disease transmission, and cure. The pandemics present economic paradoxes, though arguably the negatives outdo the positives. There is a need for the governments and international health custodians to be richly prepared for the pandemics in the future. This implies having special budgetary allocations for possible pandemic outbreaks, investing in vaccine development and disease surveillance, and training and skilling personnel in all social-health-related sectors.

Identification of Phytochemicals from Arabian Peninsula Medicinal Plants as Strong Binders to SARS-CoV-2 Proteases (3CLPro and PLPro) by Molecular Docking and Dynamic Simulation Studies

We provide promising computational (in silico) data on phytochemicals (compounds 1-10) from Arabian Peninsula medicinal plants as strong binders, targeting 3-chymotrypsin-like protease (3CLPro) and papain-like proteases (PLPro) of SARS-CoV-2. Compounds 1-10 followed the Lipinski rules of five (RO5) and ADMET analysis, exhibiting drug-like characters. Non-covalent (reversible) docking of compounds 1-10 demonstrated their binding with the catalytic dyad (CYS145 and HIS41) of 3CLPro and catalytic triad (CYS111, HIS272, and ASP286) of PLPro. Moreover, the implementation of the covalent (irreversible) docking protocol revealed that only compounds 7, 8, and 9 possess covalent warheads, which allowed the formation of the covalent bond with the catalytic dyad (CYS145) in 3CLPro and the catalytic triad (CYS111) in PLPro. Root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), and radius of gyration (Rg) analysis from molecular dynamic (MD) simulations revealed that complexation between ligands (compounds 7, 8, and 9) and 3CLPro and PLPro was stable, and there was less deviation of ligands. Overall, the in silico data on the inherent properties of the above phytochemicals unravel the fact that they can act as reversible inhibitors for 3CLPro and PLPro. Moreover, compounds 7, 8, and 9 also showed their novel properties to inhibit dual targets by irreversible inhibition, indicating their effectiveness for possibly developing future drugs against SARS-CoV-2. Nonetheless, to confirm the theoretical findings here, the effectiveness of the above compounds as inhibitors of 3CLPro and PLPro warrants future investigations using suitable in vitro and in vivo tests.

Evaluating completion rates of COVID-19 contact tracing surveys in New York City

IMPORTANCE

Contact tracing is the process of identifying people who have recently been in contact with someone diagnosed with an infectious disease. During an outbreak, data collected from contact tracing can inform interventions to reduce the spread of infectious diseases. Understanding factors associated with completion rates of contact tracing surveys can help design improved interview protocols for ongoing and future programs.

OBJECTIVE

To identify factors associated with completion rates of COVID-19 contact tracing surveys in New York City (NYC) and evaluate the utility of a predictive model to improve completion rates, we analyze laboratory-confirmed and probable COVID-19 cases and their self-reported contacts in NYC from October 1st 2020 to May 10th 2021.

METHODS

We analyzed 742,807 case investigation calls made during the study period. Using a log-binomial regression model, we examined the impact of age, time of day of phone call, and zip code-level demographic and socioeconomic factors on interview completion rates. We further developed a random forest model to predict the best phone call time and performed a counterfactual analysis to evaluate the change of completion rates if the predicative model were used.

RESULTS

The percentage of contact tracing surveys that were completed was 79.4%, with substantial variations across ZIP code areas. Using a log-binomial regression model, we found that the age of index case (an individual who has tested positive through PCR or antigen testing and is thus subjected to a case investigation) had a significant effect on the completion of case investigation - compared with young adults (the reference group,24 years old < age <  = 65 years old), the completion rate for seniors (age > 65 years old) were lower by 12.1% (95%CI: 11.1% - 13.3%), and the completion rate for youth group (age <  = 24 years old) were lower by 1.6% (95%CI: 0.6% -2.6%). In addition, phone calls made from 6 to 9 pm had a 4.1% (95% CI: 1.8% - 6.3%) higher completion rate compared with the reference group of phone calls attempted from 12 and 3 pm. We further used a random forest algorithm to assess its potential utility for selecting the time of day of phone call. In counterfactual simulations, the overall completion rate in NYC was marginally improved by 1.2%; however, certain ZIP code areas had improvements up to 7.8%.

CONCLUSION

These findings suggest that age and time of day of phone call were associated with completion rates of case investigations. It is possible to develop predictive models to estimate better phone call time for improving completion rates in certain communities.

Phylogenomic early warning signals for SARS-CoV-2 epidemic waves

BACKGROUND

Epidemic waves of coronavirus disease 2019 (COVID-19) infections have often been associated with the emergence of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Rapid detection of growing genomic variants can therefore serve as a predictor of future waves, enabling timely implementation of countermeasures such as non-pharmaceutical interventions (social distancing), additional vaccination (booster campaigns), or healthcare capacity adjustments. The large amount of SARS-CoV-2 genomic sequence data produced during the pandemic has provided a unique opportunity to explore the utility of these data for generating early warning signals (EWS).

METHODS

We developed an analytical pipeline (Transmission Fitness Polymorphism Scanner - designated in an R package mrc-ide/tfpscanner) for systematically exploring all clades within a SARS-CoV-2 virus phylogeny to detect variants showing unusually high growth rates. We investigated the use of these cluster growth rates as the basis for a variety of statistical time series to use as leading indicators for the epidemic waves in the UK during the pandemic between August 2020 and March 2022. We also compared the performance of these phylogeny-derived leading indicators with a range of non-phylogeny-derived leading indicators. Our experiments simulated data generation and real-time analysis.

FINDINGS

Using phylogenomic analysis, we identified leading indicators that would have generated EWS ahead of significant increases in COVID-19 hospitalisations in the UK between August 2020 and March 2022. Our results also show that EWS lead time is sensitive to the threshold set for the number of false positive (FP) EWS. It is often possible to generate longer EWS lead times if more FP EWS are tolerated. On the basis of maximising lead time and minimising the number of FP EWS, the best performing leading indicators that we identified, amongst a set of 1.4 million, were the maximum logistic growth rate (LGR) amongst clusters of the dominant Pango lineage and the mean simple LGR across a broader set of clusters. In the case of the former, the time between the EWS and wave inflection points (a conservative measure of wave start dates) for the seven waves ranged between a 20-day lead time and a 7-day lag, with a mean lead time of 5.4 days. The maximum number of FP EWS generated prior to a true positive (TP) EWS was two and this only occurred for two of the seven waves in the period. The mean simple LGR amongst a broader set of clusters also performed well in terms of lead time but with slightly more FP EWS.

INTERPRETATION

As a result of the significant surveillance effort during the pandemic, early detection of SARS-CoV-2 variants of concern Alpha, Delta, and Omicron provided some of the first examples where timely detection and characterisation of pathogen variants has been used to tailor public health response. The success of our method in generating early warning signals based on phylogenomic analysis for SARS-CoV-2 in the UK may make it a worthwhile addition to existing surveillance strategies. In addition, the method may be translatable to other countries and/or regions, and to other pathogens with large-scale and rapid genomic surveillance.

FUNDING

This research was funded in whole, or in part, by the Wellcome Trust (220885_Z_20_Z). For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. KOD, OB, VBF and EMV acknowledge funding from the MRC Centre for Global Infectious Disease Analysis (reference MR/X020258/1), jointly funded by the UK Medical Research Council (MRC) and the UK Foreign, Commonwealth & Development Office (FCDO), under the MRC/FCDO Concordat agreement and is also part of the EDCTP2 programme supported by the European Union. RMC acknowledges funding from the Wellcome Trust Collaborators Award (206298/Z/17/Z).

Do Children with Previous COVID Infection Have Hyposmia?

OBJECTIVE

Our goal was to see if children with a history of COVID infection had subclinical hyposmia.

METHODS

Consecutive patients at a pediatric otolaryngology clinic aged 5-17 years were recruited. Demographics including gender, race, use of nasal topical medications (NTM), previous nasal surgery including adenoidectomy (NSA), and previous COVID-19 infection were collected. Each child performed a test of their sense of smell using the Pediatric Smell Wheel (PSW, Sensonics Intl, USA) under the direct supervision and scores were compared.

RESULTS

260 children were included; mean age 10.1 years (95% CI 9.7-10.5), 128 (49.2%) female and 132 (50.8%) male. 65 (25%) used steroid nasal sprays, 100 (38.5%) had undergone adenoidectomy, and 36 (13.8%) had other nasal surgery. 120 (46.2%) had a previous COVID-19 infection. The COVID+ and COVID- groups were the same for age, gender, race, use of NTMs, and previous NSA (p > 0.05). Mean PSW score was 7.8 (95% CI 7.6-8.0), median of 8, ranging from 2 to 11. The mean PSW score was 8.0 for the COVID- group and 7.6 for the COVID+ group (p = 0.005). There was no significant difference in total PSW scores based on gender, race, use of NTMs, previous NSA. Linear regression showed previous COVID infection was significantly negatively associated with total PSW score (Beta -0.636, p = 0.006) with age significantly positively associated (Beta 0.122, p < 0.001).

CONCLUSION

Children with a history of COVID infection performed slightly worse when identifying odors than children without a COVID history. More study into the rates of pediatric anosmia related to COVID infection is needed.

LEVEL OF EVIDENCE

3 Laryngoscope, 134:901-906, 2024.

Predictors of mortality among inpatients in COVID-19 treatment centers in the city of Butembo, North Kivu, Democratic Republic of Congo

Determining the risk factors for severe disease and death among hospitalized Covid-19 patients is critical to optimize health outcomes and health services efficiency, especially in resource-constrained and humanitarian settings. This study aimed to identify the predictors of mortality of Covid-19 patients in North Kivu province in the Democratic Republic of Congo.A retrospective cohort study was conducted in 6 Covid-19 treatment centers in the city of Butembo from 1 January to 31 December 2021. The time to event (death), the outcome variable, was visualized by Kaplan-Meier curves and the log-rank test was used to confirm differences in trends. Cox regression was used for all the predictors in the bivariate analysis and multivariate analysis was done using predictors found statistically significant in the bivariate analysis. The following variables were considered for inclusion to the Cox regression model: Age, Sex, Disease length, Treatment site, History of at least one co-morbidity, Body mass index, Stage according to SpO2 and the NEWS-modified score.Among the 303 participants (mean age of 53 years), the fatality rate was 33.8 deaths per 1000 patient-days. Four predictors were independently associated with inpatient death: age category (≥ 60 years) (adjusted HR: 9.90; 95% CI: 2.68-36.27), presence of at least one comorbidity (adjusted HR: 11.39; 95% CI: 3.19-40.71); duration of illness of > 5 days before hospitalization (adjusted HR:1.70, 95% CI: 1.04-2.79) and peripheral capillary oxygen saturation (SpO2) < 90% (adjusted HR = 14.02, 95% CI: 2.23-88.32). In addition to advanced age, comorbidity, and length of disease before hospitalization, ambient air SpO2 measured by healthcare providers using low-tech, affordable and relatively accessible pulse oximetry could inform the care pathways of Covid-19 inpatients in resource-challenged health systems in humanitarian settings.

Association between COVID-19 Vaccination and SARS-CoV-2 Infection among Household Contacts of Infected Individuals: A Prospective Household Study in England

BACKGROUND

We investigated whether COVID-19 vaccination reduced SARS-CoV-2 infection risk among adult household contacts of COVID-19 index cases during the Alpha, Delta, and Omicron waves in England.

METHODS

Between February 2021 and February 2022, SARS-CoV-2 RT-PCR nasal swabs were collected from COVID-19-confirmed index cases aged ≥20 years and their household contacts at enrolment and three and seven days thereafter. Generalized Estimating Equations models were fitted with SARS-CoV-2 positivity as the outcome and household contacts' vaccination status as the main exposure while adjusting for confounders.

RESULTS

SARS-CoV-2 infection was confirmed in 238/472 household contacts (50.4%) aged ≥20 years. The adjusted relative risk (95% confidence interval) of infection in vaccinated versus unvaccinated household contacts was 0.50 (0.35-0.72) and 0.69 (0.53-0.90) for receipt of two doses 8-90 and >90 days ago, respectively, and 0.34 (0.23-0.50) for vaccination with three doses 8-151 days ago. Primary vaccination protected household contacts against infection during the Alpha and Delta waves, but only three doses protected during the Omicron wave. Vaccination with three doses in the index case independently reduced contacts' infection risk: 0.45 (0.23-0.89).

CONCLUSIONS

Vaccination of household contacts reduces their risk of infection under conditions of household exposure though, for Omicron, only after a booster dose.

Overview of COVID-19 Infection, Treatment, and Prevention in Children

Coronavirus disease 2019 (COVID-19), caused by the novel respiratory virus-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-was declared a global pandemic by the World Health Organization on 11 March 2020. Since then, substantial gains have been made in our understanding of COVID-19 epidemiology, disease presentation, and management. While children tend to have less severe disease courses compared to adults, children can still develop severe COVID-19 infections, particularly in those with underlying medical conditions such as obesity, chronic lung disease, or prematurity. In addition, children are at risk of severe complications of COVID-19 infection, such as multisystem inflammatory syndrome in children (MIS-C) or long COVID. The case definitions of MIS-C and long COVID have continued to evolve with the increased understanding of these new entities; however, improved methods of diagnosis and determination of the optimal management are still needed. Furthermore, with the continued circulation of SARS-CoV-2 variants, there remains a need for clinicians to remain up-to-date on the latest treatment and prevention options. The purpose of this review is to provide an evidence-based review of what we have learned about COVID-19 in children since the start of the pandemic and how best to counsel children and their families on the best methods of prevention.

Transmission characteristics and inactivated vaccine effectiveness against transmission of the SARS-CoV-2 Omicron BA.2 variant in Shenzhen, China

We conducted a retrospective cohort study to evaluate the transmission risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BA.2 variant and the effectiveness of inactivated COVID-19 vaccine boosters in Shenzhen during a BA.2 outbreak period from 1 February to 21 April 2022. A total of 1,248 individuals were infected with the BA.2 variant, and 7,855 close contacts were carefully investigated. The risk factors for the high secondary attack rate of SARS-CoV-2 infection were household contacts [adjusted odds ratio (aOR): 1.748; 95% confidence interval (CI): 1.448, 2.110], younger individuals aged 0-17 years (aOR: 2.730; 95% CI: 2.118, 3.518), older persons aged ≥60 years (aOR: 1.342; 95% CI: 1.135, 1.588), women (aOR: 1.442; 95% CI: 1.210, 1.718), and the subjects exposed to the post-onset index cases (aOR: 8.546; 95% CI: 6.610, 11.050), respectively. Compared with the unvaccinated and partially vaccinated individuals, a relatively low risk of secondary attack was found for the individuals who received booster vaccination (aOR: 0.871; 95% CI: 0.761, 0.997). Moreover, a high transmission risk was found for the index cases aged ≥60 years (aOR: 1.359; 95% CI: 1.132, 1.632), whereas a relatively low transmission risk was observed for the index cases who received full vaccination (aOR: 0.642; 95% CI: 0.490, 0.841) and booster vaccination (aOR: 0.676; 95% CI: 0.594, 0.770). Compared with full vaccination, booster vaccination of inactivated COVID-19 vaccine showed an effectiveness of 24.0% (95% CI: 7.0%, 37.9%) against BA.2 transmission for the adults ≥18 years and 93.7% (95% CI: 72.4%, 98.6%) for the adults ≥60 years, whereas the effectiveness was 51.0% (95% CI: 21.9%, 69.3%) for the individuals of 14 days to 179 days after booster vaccination and 51.2% (95% CI: 37.5%, 61.9%) for the non-household contacts. The estimated mean values of the generation interval, serial interval, incubation period, latent period, and viral shedding period were 2.7 days, 3.2 days, 2.4 days, 2.1 days, and 17.9 days, respectively. In summary, our results confirmed that the main transmission route of Omicron BA.2 subvariant was household contact, and booster vaccination of the inactivated vaccines was relatively effective against BA.2 subvariant transmission in older people.