High Infection Fatality Rate Among Elderly and Risk Factors Associated With Infection Fatality Rate and Asymptomatic Infections of COVID-19 Cases in Hong Kong

Increasing Levels of Serum Anti-Spike S1-RBD IgG after 120 Days of the Pfizer-BioNTech-mRNA Second Dose Vaccination

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccines, such as Pfizer-BioNTech, have demonstrated high efficacy; however, there is limited data on the duration of immune responses besides their relationships with age, gender, body mass index (BMI), and the presence of previous coronavirus disease-2019 (COVID-19) infection. This study aimed to evaluate SARS-COVID-19 Anti-Spike IgG levels after 30 days (one month) and 120 days (four months) of the 2nd dose of Pfizer-BioNTech vaccine given to medical students at Al-Iraqi University, Baghdad, Iraq. This study was performed after the obtainment of the acceptance and approval of the Medical College of Al-Iraqi University and the Iraqi Ministry of Health. Two groups of students were randomly picked up from the Medical College of Al-Iraqi University. They were completely vaccinated by administering two doses of Pfizer-BioNTech/0.5 ml for each dose. After taking their permission, 5 ml of their blood (one group after one month and the second group after four months of vaccination) was drawn in the Higher Education lab inside the Medical College of Al-Iraqi University. It took approximately four months to collect the samples (from October 2021 until February 2022). Following that, serological analysis was done for measuring the SARS-CoV-2 spike protein IgG by using Elabscience/SARS-CoV-2 spike protein IgG ELISA Kit (USA) (+ve <0.06) that was performed in the Higher Education lab of Medical College of Al-Iraqi University. Demographic data were also collected from participants, including age, gender, BMI, blood group, and the presence of previous COVID-19 infection. For statistical analysis, SPSS (version 26) and STATISTICA (version 12) were used to input, check, and analyze data. Standard approaches of frequencies and percentages were used for qualitative variables, while for quantitative variables, mean±standard deviation was used. A P-value of <0.05 was considered a significant plasma level of the SARS-COVID-19 Anti-Spike IgG. The study results showed that in group 1 (after one month of the 2nd dose), the male-female ratio was 62.2: 37.8, the mean age of the vaccinated students was 28.2000 years old, and the BMI was 25.5454 kg/m2 with 33.3% previously COVID-19 infected individuals. In group 2 (after four months of the 2nd dose), the male-female ratio was 44.4: 55.6, the mean age of the vaccinated students was 25.8444 years old , and the BMI was 24.7584 kg/m2 with 24.4% previously COVID-19 infected individuals. The plasma levels of SARS-COVID-19 Anti-Spike IgG after the 2nd dose of the Pfizer-BioNTech vaccine in group 1 (one month) and group 2 (four months) were statistically non-parametric. Once the independent two samples Mann-Whitney test was used, a significant difference (P<0.05) was observed in SARS-COVID-19 Anti-Spike IgG plasma levels after 30 days of the 2nd dose of the Pfizer-BioNTech vaccine administration, compared to the 120 days of administration. In conclusion, SARS-COVID-19 Anti-Spike IgG levels significantly increased in group 2 (four months after the 2nd dose of the Pfizer-BioNTech vaccine), compared to group 1 (one month after the 2nd dose of the Pfizer-BioNTech vaccine).

Unravelling the dynamics of the COVID-19 pandemic with the effect of vaccination, vertical transmission and hospitalization

The coronavirus disease 2019 (COVID-19) is caused by a newly emerged virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), transmitted through air droplets from an infected person. However, other transmission routes are reported, such as vertical transmission. Here, we propose an epidemic model that considers the combined effect of vertical transmission, vaccination and hospitalization to investigate the dynamics of the virus's dissemination. Rigorous mathematical analysis of the model reveals that two equilibria exist: the disease-free equilibrium, which is locally asymptotically stable when the basic reproduction number ( R 0 ) is less than 1 (unstable otherwise), and an endemic equilibrium, which is globally asymptotically stable when R 0 > 1 under certain conditions, implying the plausibility of the disease to spread and cause large outbreaks in a community. Moreover, we fit the model using the Saudi Arabia cases scenario, which designates the incidence cases from the in-depth surveillance data as well as displays the epidemic trends in Saudi Arabia. Through Caputo fractional-order, simulation results are provided to show dynamics behaviour on the model parameters. Together with the non-integer order variant, the proposed model is considered to explain various dynamics features of the disease. Further numerical simulations are carried out using an efficient numerical technique to offer additional insight into the model's dynamics and investigate the combined effect of vaccination, vertical transmission, and hospitalization. In addition, a sensitivity analysis is conducted on the model parameters against the R 0 and infection attack rate to pinpoint the most crucial parameters that should be emphasized in controlling the pandemic effectively. Finally, the findings suggest that adequate vaccination coupled with basic non-pharmaceutical interventions are crucial in mitigating disease incidences and deaths.

COVID-19 prevalence and mortality in longer-term care facilities

This essay considers the factors that have contributed to very high COVID-19 mortality in longer-term care facilities (LTCFs). We compare the demographic characteristics of LTCF residents with those of community-dwelling older adults, and then we review the evidence regarding prevalence and infection fatality rates (IFRs), including links to frailty and some comorbidities. Finally, we discuss policy measures that could foster the physical and mental health and well-being of LTCF residents in the present context and in potential future pandemics.

Infection fatality rate and infection attack rate of COVID-19 in South American countries

BACKGROUND

The ongoing COVID-19 pandemic hit South America badly with multiple waves. Different COVID-19 variants have been storming across the region, leading to more severe infections and deaths even in places with high vaccination coverage. This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate (IFR), infection attack rate (IAR) and reproduction number ([Formula: see text]) for twelve most affected South American countries.

METHODS

We fit a susceptible-exposed-infectious-recovered (SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities. Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization, Johns Hopkins Coronavirus Resource Center and Our World in Data. We investigate the COVID-19 mortalities in these countries, which could represent the situation  for the overall South American region. We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR, IAR and [Formula: see text] of COVID-19 for the South American countries.

RESULTS

We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR (varies between 0.303% and 0.723%), IAR (varies between 0.03 and 0.784) and [Formula: see text] (varies between 0.7 and 2.5) for the 12 South American countries. We observe that the severity, dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous. Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America.

CONCLUSIONS

This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America. We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths. Thus, strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America.

Infection fatality rate and infection attack rate of COVID-19 in South American countries

BACKGROUND

The ongoing COVID-19 pandemic hit South America badly with multiple waves. Different COVID-19 variants have been storming across the region, leading to more severe infections and deaths even in places with high vaccination coverage. This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate (IFR), infection attack rate (IAR) and reproduction number ([Formula: see text]) for twelve most affected South American countries.

METHODS

We fit a susceptible-exposed-infectious-recovered (SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities. Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization, Johns Hopkins Coronavirus Resource Center and Our World in Data. We investigate the COVID-19 mortalities in these countries, which could represent the situation  for the overall South American region. We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR, IAR and [Formula: see text] of COVID-19 for the South American countries.

RESULTS

We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR (varies between 0.303% and 0.723%), IAR (varies between 0.03 and 0.784) and [Formula: see text] (varies between 0.7 and 2.5) for the 12 South American countries. We observe that the severity, dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous. Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America.

CONCLUSIONS

This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America. We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths. Thus, strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America.

Asymptomatic infection and transmission of COVID-19 among clusters: systematic review and meta-analysis

OBJECTIVES

Countries throughout the world are experiencing COVID-19 viral load in their populations, leading to potential transmission and infectivity of asymptomatic COVID-19 cases. The current systematic review and meta-analysis aims to investigate the role of asymptomatic infection and transmission reported in family clusters, adults, children and health care workers, globally.

STUDY DESIGN

Systematic review and meta-analysis.

METHODS

An online literature search of PubMed, Google Scholar, medRixv and BioRixv was performed using standard Boolean operators and included studies published up to 17 August 2021. For the systematic review, case reports, short communications and retrospective studies were included to ensure sufficient asymptomatic COVID-19 transmission data were reported. For the quantitative synthesis (meta-analysis), participant data from a collection of cohort studies focusing on groups of familial clusters, adults, children and health care workers were included. Inconsistency among studies was assessed using I² statistics. The data synthesis was computed using the STATA 16.0 software.

RESULTS

This study showed asymptomatic transmission among familial clusters, adults, children and health care workers of 15.72%, 29.48%, 24.09% and 0%, respectively. Overall, asymptomatic transmission was 24.51% (95% confidence interval [CI]: 14.38, 36.02) among all studied population groups, with a heterogeneity of I² = 95.30% (P < 0.001). No heterogeneity was seen in the population subgroups of children and health care workers. The risk of bias in all included studies was assessed using the Newcastle Ottawa Scale.

CONCLUSIONS

For minimising the spread of COVID-19 within the community, this study found that following the screening of asymptomatic cases and their close contacts for chest CT scan (for symptomatic patients), even after negative nucleic acid testing, it is essential to perform a rigorous epidemiological history, early isolation, social distancing and an increased quarantine period (a minimum of 14-28 days). This systematic review and meta-analysis supports the notion of asymptomatic COVID-19 infection and person-to-person transmission and suggests that this is dependent on the varying viral incubation period among individuals. Children, especially those of school age (i.e. <18 years), need to be monitored carefully and follow mitigation strategies (e.g. social distancing, hand hygiene, wearing face masks) to prevent asymptomatic community transmission of COVID-19.

Infection fatality ratio and case fatality ratio of COVID-19

The infection fatality ratio (IFR) is the risk of death per infection and is one of the most important epidemiological parameters. Enormous efforts have been undertaken to estimate the IFR for COVID-19. This study examined the pros and cons of several approaches. It is found that the frequently used approaches using serological survey results as the denominator and the number of confirmed deaths as the numerator underestimated the true IFR. The most typical examples are South Africa and Peru (before official correction), where the confirmed deaths are one-third of the excess deaths. We argue that the RT-PCR-based case fatality ratio (CFR) is a reliable indicator of the lethality of COVID-19 in locations where testing is extensive. An accurate IFR is crucial for policymaking and public-risk perception.