Serial Interval Research Articles

Performance of Rapid Antigen Tests to Detect Symptomatic and Asymptomatic SARS-CoV-2 Infection : A Prospective Cohort Study.

The performance of rapid antigen tests (Ag-RDTs) for screening asymptomatic and symptomatic persons for SARS-CoV-2 is not well established. To evaluate the performance of Ag-RDTs for detection of SARS-CoV-2 among symptomatic and asymptomatic participants. This prospective cohort study enrolled participants between October 2021 and January 2022. Participants completed Ag-RDTs and reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 every 48 hours for 15 days. Participants were enrolled digitally throughout the mainland United States. They self-collected anterior nasal swabs for Ag-RDTs and RT-PCR testing. Nasal swabs for RT-PCR were shipped to a central laboratory, whereas Ag-RDTs were done at home. Of 7361 participants in the study, 5353 who were asymptomatic and negative for SARS-CoV-2 on study day 1 were eligible. In total, 154 participants had at least 1 positive RT-PCR result. The sensitivity of Ag-RDTs was measured on the basis of testing once (same-day), twice (after 48 hours), and thrice (after a total of 96 hours). The analysis was repeated for different days past index PCR positivity (DPIPPs) to approximate real-world scenarios where testing initiation may not always coincide with DPIPP 0. Results were stratified by symptom status. Among 154 participants who tested positive for SARS-CoV-2, 97 were asymptomatic and 57 had symptoms at infection onset. Serial testing with Ag-RDTs twice 48 hours apart resulted in an aggregated sensitivity of 93.4% (95% CI, 90.4% to 95.9%) among symptomatic participants on DPIPPs 0 to 6. When singleton positive results were excluded, the aggregated sensitivity on DPIPPs 0 to 6 for 2-time serial testing among asymptomatic participants was lower at 62.7% (CI, 57.0% to 70.5%), but it improved to 79.0% (CI, 70.1% to 87.4%) with testing 3 times at 48-hour intervals. Participants tested every 48 hours; therefore, these data cannot support conclusions about serial testing intervals shorter than 48 hours. The performance of Ag-RDTs was optimized when asymptomatic participants tested 3 times at 48-hour intervals and when symptomatic participants tested 2 times separated by 48 hours. National Institutes of Health RADx Tech program.

Estimates of Serial Interval and Reproduction Number of Sudan Virus, Uganda, August-November 2022.

We estimated the mean serial interval for Sudan virus in Uganda to be 11.7 days (95 CI% 8.2-15.8 days). Estimates for the 2022 outbreak indicate a mean basic reproduction number of 2.4-2.7 (95% CI 1.7-3.5). Estimated net reproduction numbers across districts suggest a marked spatial heterogeneity.

Improved time-varying reproduction numbers using the generation interval for COVID-19.

Estimating key epidemiological parameters, such as incubation period, serial interval (SI), generation interval (GI) and latent period, is essential to quantify the transmissibility and effects of various interventions of COVID-19. These key parameters play a critical role in quantifying the basic reproduction number. With the hard work of epidemiological investigators in South Korea, estimating these key parameters has become possible based on infector-infectee surveillance data of COVID-19 between February 2020 and April 2021. Herein, the mean incubation period was estimated to be 4.9 days (95% CI: 4.2, 5.7) and the mean generation interval was estimated to be 4.3 days (95% CI: 4.2, 4.4). The mean serial interval was estimated to be 4.3, with a standard deviation of 4.2. It is also revealed that the proportion of presymptomatic transmission was ~57%, which indicates the potential risk of transmission before the disease onset. We compared the time-varying reproduction number based on GI and SI and found that the time-varying reproduction number based on GI may result in a larger estimation of , which refers to the COVID-19 transmission potential around the rapid increase of cases. This highlights the importance of considering presymptomatic transmission and generation intervals when estimating the time-varying reproduction number.

Modeling vaccination coverage during the 2022 central Ohio measles outbreak: a cross-sectional study

Of the eight large (>50 cases) US postelimination outbreaks, the first and last occurred in Ohio. Ohio's vaccination registry is incomplete. Community-level immunity gaps threaten more than two decades of measles elimination in the US. We developed a statistical model, VaxEstim, to rapidly estimate the early-phase vaccination coverage and immunity gap in the exposed population during the 2022 Central Ohio outbreak. We used reconstructed daily incidence (from publicly available data) and assumptions about the distribution of the serial interval, or the time between symptom onset in successive measles cases, to estimate the effective reproduction number (i.e., the average number of secondary infections caused by an infected individual in a partially immune population). We estimated early-phase measles vaccination coverage by comparing the effective reproduction number to the basic reproduction number (i.e., the average number of secondary infections caused by an infected individual in a fully susceptible population) while accounting for vaccine effectiveness. Finally, we estimated the early-phase immunity gap as the difference between the estimated critical vaccination threshold and vaccination coverage. VaxEstim estimated the early-phase vaccination coverage as 53% (95% credible interval, 21%-77%), the critical vaccination threshold as 93%, and the immunity gap as 42% (95% credible interval, 18%-74%). This study estimates a significant immunity gap in the exposed population during the early phase of the 2022 Central Ohio measles outbreak, suggesting a robust public health response is needed to identify the susceptible community and develop community-specific strategies to close the immunity gap. This work was supported in part by the National Institute of General Medical Sciences, National Institutes of Health; the UK Medical Research Council (MRC); the Foreign, Commonwealth and Development Office; the National Institute for Health Research (NIHR) Health Protection Research Unit in Modelling Methodology; Imperial College London, and the London School of Hygiene & Tropical Medicine, Community Jameel; the EDCTP2 programme, supported by the EU; and the Sergei Brin Foundation.

Rapid review and meta-analysis of serial intervals for SARS-CoV-2 Delta and Omicron variants

BackgroundThe serial interval is the period of time between symptom onset in the primary case and symptom onset in the secondary case. Understanding the serial interval is important for determining transmission dynamics of infectious diseases like COVID-19, including the reproduction number and secondary attack rates, which could influence control measures. Early meta-analyses of COVID-19 reported serial intervals of 5.2 days (95% CI: 4.9–5.5) for the original wild-type variant and 5.2 days (95% CI: 4.87–5.47) for Alpha variant. The serial interval has been shown to decrease over the course of an epidemic for other respiratory diseases, which may be due to accumulating viral mutations and implementation of more effective nonpharmaceutical interventions. We therefore aggregated the literature to estimate serial intervals for Delta and Omicron variants.MethodsThis study followed Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. A systematic literature search was conducted of PubMed, Scopus, Cochrane Library, ScienceDirect, and preprint server medRxiv for articles published from April 4, 2021, through May 23, 2023. Search terms were: (“serial interval” or “generation time”), (“Omicron” or “Delta”), and (“SARS-CoV-2” or “COVID-19”). Meta-analyses were done for Delta and Omicron variants using a restricted maximum-likelihood estimator model with a random effect for each study. Pooled average estimates and 95% confidence intervals (95% CI) are reported.ResultsThere were 46,648 primary/secondary case pairs included for the meta-analysis of Delta and 18,324 for Omicron. Mean serial interval for included studies ranged from 2.3–5.8 days for Delta and 2.1–4.8 days for Omicron. The pooled mean serial interval for Delta was 3.9 days (95% CI: 3.4–4.3) (20 studies) and Omicron was 3.2 days (95% CI: 2.9–3.5) (20 studies). Mean estimated serial interval for BA.1 was 3.3 days (95% CI: 2.8–3.7) (11 studies), BA.2 was 2.9 days (95% CI: 2.7–3.1) (six studies), and BA.5 was 2.3 days (95% CI: 1.6–3.1) (three studies).ConclusionsSerial interval estimates for Delta and Omicron were shorter than ancestral SARS-CoV-2 variants. More recent Omicron subvariants had even shorter serial intervals suggesting serial intervals may be shortening over time. This suggests more rapid transmission from one generation of cases to the next, consistent with the observed faster growth dynamic of these variants compared to their ancestors. Additional changes to the serial interval may occur as SARS-CoV-2 continues to circulate and evolve. Changes to population immunity (due to infection and/or vaccination) may further modify it.

Inferring the differences in incubation-period and generation-interval distributions of the Delta and Omicron variants of SARS-CoV-2

Estimating the differences in the incubation-period, serial-interval, and generation-interval distributions of SARS-CoV-2 variants is critical to understanding their transmission. However, the impact of epidemic dynamics is often neglected in estimating the timing of infection-for example, when an epidemic is growing exponentially, a cohort of infected individuals who developed symptoms at the same time are more likely to have been infected recently. Here, we reanalyze incubation-period and serial-interval data describing transmissions of the Delta and Omicron variants from the Netherlands at the end of December 2021. Previous analysis of the same dataset reported shorter mean observed incubation period (3.2 d vs. 4.4 d) and serial interval (3.5 d vs. 4.1 d) for the Omicron variant, but the number of infections caused by the Delta variant decreased during this period as the number of Omicron infections increased. When we account for growth-rate differences of two variants during the study period, we estimate similar mean incubation periods (3.8 to 4.5 d) for both variants but a shorter mean generation interval for the Omicron variant (3.0 d; 95% CI: 2.7 to 3.2 d) than for the Delta variant (3.8 d; 95% CI: 3.7 to 4.0 d). The differences in estimated generation intervals may be driven by the "network effect"-higher effective transmissibility of the Omicron variant can cause faster susceptible depletion among contact networks, which in turn prevents late transmission (therefore shortening realized generation intervals). Using up-to-date generation-interval distributions is critical to accurately estimating the reproduction advantage of the Omicron variant.

Risk factors for post-COVID-19 condition (Long Covid) in children: a prospective cohort study

Adults and children can develop post-Covid-19 condition (PCC) (also referred to as Long Covid). However, existing evidence is scarce, partly due to a lack of a standardised case definition, short follow up duration, and heterogenous study designs, resulting in wide variation of reported outcomes. The primary aim of this study was to characterise risk factors for PCC and longitudinal rates of recovery in a cohort of children and young people using a standardised protocol. We performed a prospective "disease-based" cohort study between 01/02/2020 to 31/10/2022 including children aged 0-18 years old, with a previous diagnosis of Covid-19. Children with microbiologically confirmed SARS-CoV-2 infection, were invited for an in-clinic follow-up assessment at a paediatric post-covid clinic in Rome, Italy, at serial intervals (3-, 6-, 12- and 18-months post-onset). PCC was defined as persistence of otherwise unexplained symptoms for at least three months after initial infection. The statistical association between categorical variables was obtained by Chi-squared tests or Fisher's exact tests. Multivariable logistic regressions are presented using odds ratios (OR) and 95% confidence interval (CI). Survival analysis was conducted using the Kaplan-Meier method. 1243 children were included, median age: 7.5 (4-10.3) years old; 575 (46.3%) were females. Of these, 23% (294/1243) were diagnosed with PCC at three months post-onset. Among the study population, 143 patients remained symptomatic at six months, 38at 12 months, and 15at 18 months follow up evaluation. The following risk factors were associated with PCC: >10 years of age (OR 1.23; 95% CI 1.18-1.28), comorbidities (OR 1.68; 95% CI 1.14-2.50), and hospitalisation during the acute phase (OR 4.80; 95%CI 1.91-12.1). Using multivariable logistic regression, compared to the Omicron variant, all other variants were significantly associated with PCC at 3 and 6 months. At least one dose of vaccine was associated with a reduced, but not statistically significant risk of developing PCC. In our study, acute-phase hospitalisation, pre-existing comorbidity, being infected with pre-Omicron variants and older age were associated with a higher risk of developing PCC. Most children recovered over time, but one-in-twenty of those with PCC at three months reported persistent symptoms 18 months post-Sars-CoV-2 infection. Omicron infection was associated with shorter recovery times. We did not find a strong protective effect of vaccination on PCC development. Although our cohort cannot be translated to all Italian children with PCC as more nationwide studies are needed, our findings highlight the need of new strategies to prevent and treat pediatric PCC are needed. This study has been funded by Pfizer non-competitive grant, granted to DB (# 65925795).

Time Scales of Human Mpox Transmission in The Netherlands.

Mpox has spread rapidly to many countries in nonendemic regions. After reviewing detailed exposure histories of 109 pairs of mpox cases in the Netherlands, we identified 34 pairs where transmission was likely and the infectee reported a single potential infector with a mean serial interval of 10.1 days (95% credible interval, 6.6-14.7 days). Further investigation into pairs from 1 regional public health service revealed that presymptomatic transmission may have occurred in 5 of 18 pairs. These findings emphasize that precaution remains key, regardless of the presence of recognizable symptoms of mpox.

Serial Intervals and Incubation Periods of SARS-CoV-2 Omicron and Delta Variants, Singapore.

We compared serial intervals and incubation periods for SARS-CoV-2 Omicron BA.1 and BA.2 subvariants and Delta variants in Singapore. Median incubation period was 3 days for BA.1 versus 4 days for Delta. Serial interval was 2 days for BA.1 and 3 days for BA.2 but 4 days for Delta.

Serial Interval and Incubation Period Estimates of Monkeypox Virus Infection in 12 Jurisdictions, United States, May-August 2022.

Using data from 12 US health departments, we estimated mean serial interval for monkeypox virus infection to be 8.5 (95% credible interval 7.3-9.9) days for symptom onset, based on 57 case pairs. Mean estimated incubation period was 5.6 (95% credible interval 4.3-7.8) days for symptom onset, based on 35 case pairs.

A new method for the joint estimation of instantaneous reproductive number and serial interval during epidemics.

Although some methods for estimating the instantaneous reproductive number during epidemics have been developed, the existing frameworks usually require information on the distribution of the serial interval and/or additional contact tracing data. However, in the case of outbreaks of emerging infectious diseases with an unknown natural history or undetermined characteristics, the serial interval and/or contact tracing data are often not available, resulting in inaccurate estimates for this quantity. In the present study, a new framework was specifically designed for joint estimates of the instantaneous reproductive number and serial interval. Concretely, a likelihood function for the two quantities was first introduced. Then, the instantaneous reproductive number and the serial interval were modeled parametrically as a function of time using the interpolation method and a known traditional distribution, respectively. Using the Bayesian information criterion and the Markov Chain Monte Carlo method, we ultimately obtained their estimates and distribution. The simulation study revealed that our estimates of the two quantities were consistent with the ground truth. Seven data sets of historical epidemics were considered and further verified the robust performance of our method. Therefore, to some extent, even if we know only the daily incidence, our method can accurately estimate the instantaneous reproductive number and serial interval to provide crucial information for policymakers to design appropriate prevention and control interventions during epidemics.

A case report on the prolonged viability of postmortem human testicular sperm

To report a case of postmortem sperm retrieval with prolonged viability and motility. Case report. Hospital and Medical Examiner Department. A 44-year-old African American male patient with a history of recreational marijuana use and occasional alcohol consumption who died from a cardiac arrest because of drug overdose. Multiple testicular biopsies and sperm analyses. Sperm viability and motility of testicular biopsies at serial time intervals. Sperm obtained from the testis in the morgue remained viable and motile even at 106 hours (>4 days) postmortem. Our study found that sperm obtained from the testis remained viable and motile even after being thawed after cryopreservation, even when obtained up to 100 hours postmortem. This may have implications on the timeframe that postmortem sperm retrieval can be performed successfully several days after death.

Spatiotemporal reproduction number with Bayesian model selection for evaluation of emerging infectious disease transmissibility: an application to COVID-19 national surveillance data

BackgroundTo control emerging diseases, governments often have to make decisions based on limited evidence. The effective or temporal reproductive number is used to estimate the expected number of new cases caused by an infectious person in a partially susceptible population. While the temporal dynamic is captured in the temporal reproduction number, the dominant approach is currently based on modeling that implicitly treats people within a population as geographically well mixed.MethodsIn this study we aimed to develop a generic and robust methodology for estimating spatiotemporal dynamic measures that can be instantaneously computed for each location and time within a Bayesian model selection and averaging framework. A simulation study was conducted to demonstrate robustness of the method. A case study was provided of a real-world application to COVID-19 national surveillance data in Thailand.ResultsOverall, the proposed method allowed for estimation of different scenarios of reproduction numbers in the simulation study. The model selection chose the true serial interval when included in our study whereas model averaging yielded the weighted outcome which could be less accurate than model selection. In the case study of COVID-19 in Thailand, the best model based on model selection and averaging criteria had a similar trend to real data and was consistent with previously published findings in the country.ConclusionsThe method yielded robust estimation in several simulated scenarios of force of transmission with computing flexibility and practical benefits. Thus, this development can be suitable and practically useful for surveillance applications especially for newly emerging diseases. As new outbreak waves continue to develop and the risk changes on both local and global scales, our work can facilitate policymaking for timely disease control.

A Small Surge in Incidence of SARS-CoV-2 Omicron Variant in the "Dynamic Zero" Period.

To describe the epidemiological characteristics and transmission dynamics of SARS-CoV-2 Omicron variant during "Dynamic Zero" period, we analyzed data on the 108 laboratory-confirmed SARS-CoV-2 cases during 14 to 30 May 2022 in Beichen district, Tianjin, China. We collected information on demographic characteristics, exposure history, and illness timelines of the 108 cases. We described characteristics of the patients and estimated the key epidemiological parameters, including serial interval and the time-dependent reproduction number of the Omicron variant, Rt. Among the 108 laboratory-confirmed patients, the median age was 38 years old, and 50.9% were females. Obvious symptoms were observed among 67.6% (73/108) of all cases, and major clinical manifestations included fever, sore throat, and cough, which occurred in 31.5%, 26.9%, and 19.4% of the 108 cases, respectively. The mean and standard deviation of the SI were estimated as 2.89 and 0.95 days, the Rt varied from 1.24 to 0.27 for a 7-day timelapse. The low reproduction number and the Omicron outbreak being suppressed within a short time marked the effectiveness of the implemented public health measures, such as nucleic acid screening, social distancing, masking, vaccination, medical treatment of patients, and isolation of close contacts. These measures play an important role in fulfilling the goal of controlling the spread of the disease.

Analysis on infection sources and transmission chains of three outbreaks caused by 2019-nCoV Omicron variant in Beijing, China

Objective: To investigate the infection sources and the transmission chains of three outbreaks caused by 2019-nCoV Omicron variant possibly spread through cross-border logistics in Beijing. Methods: Epidemiological investigation and big data were used to identify the exposure points of the cases. Close contacts were traced from the exposure points, and the cases' and environmental samples were collected for nucleic acid tests. Positive samples were analyzed by gene sequencing. Results: The Omicron variant causing 3 outbreaks in Beijing from January to April, 2022 belonged to BA.1, BA.1.1 and BA.2. The outbreaks lasted for 8, 12 and 8 days respectively, and 6, 42 and 32 cases infected with 2019-nCoV were reported respectively. International mail might be the infection source for 1 outbreak, and imported clothes might be the infection sources for another 2 outbreaks. The interval between the shipment start time of the imported goods and the infection time of the index case was 3-4 days. The mean incubation period (Q1, Q3) was 3 (2,4) days and the mean serial interval (Q1, Q3) was 3 (2,4)days. Conclusions: The 3 outbreaks highlighted the risk of infection by Omicron variant from international logistics-related imported goods at normal temperature. Omicron variant has stronger transmissibility, indicating that rapid epidemiological investigation and strict management are needed.

Comparing the incubation period, serial interval, and infectiousness profile between SARS-CoV-2 Omicron and Delta variants.

In January 2022, the SARS-CoV-2 Omicron variant initiated major outbreaks and dominated the transmissions in Hong Kong, displacing an earlier outbreak seeded by the Delta variants. To provide insight into the transmission potential of the emerging variants, we aimed to compare the epidemiological characteristics of the Omicron and Delta variants. We analysed the line-list clinical and contact tracing data of the SARS-CoV-2 confirmed cases in Hong Kong. Transmission pairs were constructed based on the individual contact history. We fitted bias-controlled models to the data to estimate the serial interval, incubation period and infectiousness profile of the two variants. Viral load data were extracted and fitted to the random effect models to investigate the potential risk modifiers for the clinical viral shedding course. Totally 14401 confirmed cases were reported between January 1 and February 15, 2022. The estimated mean serial interval (4.4 days vs 5.8 days) and incubation period (3.4 days vs 3.8 days) were shorter for the Omicron than the Delta variants. A larger proportion of pre-symptomatic transmission was observed for the Omicron (62%) compared to the Delta variants (48%). The Omicron cases had higher mean viral load over an infection course than the Delta cases, with the elder cases appearing more infectious than the younger cases for both variants. The epidemiological features of Omicron variant were likely an obstacle to contact tracing measures, imposed as a major intervention in settings like Hong Kong. Continuously monitoring the epidemiological feature for any emerging SARS-CoV-2 variants in the future is needed to assist officials in planning measures for COVID-19 control. This article is protected by copyright. All rights reserved.

Effectiveness of BNT162b2 and ChAdOx1 against SARS-CoV-2 household transmission: a prospective cohort study in England

Background: The ability of SARS-CoV-2 vaccines to protect against infection and onward transmission determines whether immunisation can control global circulation. We estimated the effectiveness of Pfizer-BioNTech mRNA vaccine (BNT162b2) and Oxford AstraZeneca adenovirus vector vaccine (ChAdOx1) vaccines against acquisition and transmission of the Alpha and Delta variants in a prospective household study in England. Methods: Households were recruited based on adult purported index cases testing positive after reverse transcription-quantitative (RT-q)PCR testing of oral-nasal swabs. Purported index cases and their household contacts took oral-nasal swabs on days 1, 3 and 7 after enrolment and a subset of the PCR-positive swabs underwent genomic sequencing conducted on a subset. We used Bayesian logistic regression to infer vaccine effectiveness against acquisition and transmission, adjusted for age, vaccination history and variant. Results: Between 2 February 2021 and 10 September 2021, 213 index cases and 312 contacts were followed up. After excluding households lacking genomic proximity (N=2) or with unlikely serial intervals (N=16), 195 households with 278 contacts remained, of whom 113 (41%) became PCR positive. Delta lineages had 1.53 times the risk (95% Credible Interval: 1.04 – 2.20) of transmission than Alpha; contacts older than 18 years old were 1.48 (1.20 – 1.91) and 1.02 (0.93 – 1.16) times more likely to acquire an Alpha or Delta infection than children. Effectiveness of two doses of BNT162b2 against transmission of Delta was 36% (-1%, 66%) and 49% (18%, 73%) for ChAdOx1, similar to their effectiveness for Alpha. Protection against infection with Alpha was higher than for Delta, 69% (9%, 95%) vs. 18% (-11%, 59%), respectively, for BNT162b2 and 24% (-41%, 72%) vs. 9% (-15%, 42%), respectively, for ChAdOx1. Conclusions: BNT162b2 and ChAdOx1 reduce transmission of the Delta variant from breakthrough infections in the household setting, although their protection against infection within this setting is low.

A Prospective Study on the Transmission dynamics of Corona virus disease (2019) (COVID-19) among Household contacts in Delhi, India.

Background: This study was conducted to understand the transmission dynamics of COVID-19 virus among the household contacts of RT-PCR confirmed cases to have an insight on key epidemiological characteristics of the infection. Methods: This was a prospective case-ascertained study conducted among the contacts of laboratory-confirmed COVID-19 cases residing in the same household in the Central and North-East districts of Delhi between 28th December 2020, and 28th June 2021. Data and specimen for reverse transcription polymerase chain reaction (RT-PCR) and serology were collected from the primary case and their contacts on day one of the visit, and follow-up collection of data and specimen was done on day 7, 14 and 28. A daily symptom diary was also maintained for all the primary cases and their contacts till 28 days from enrolment in the study. A total of 109 houses were enrolled in the study. Results: The secondary attack rate (SAR) estimated among the household contacts was 13.86% [95% C.I. 9.71%, 19.39%] and the secondary infection rate was 33.16% [95% C.I. 26.97%, 40.00%]. The serial interval and basic reproduction number (R0) within the household were estimated to be 3.6± 5.73 days and 1.26 [95% C.I. 1.21—1.31], respectively. Significant predictors of the infection were location of household in central district (SAR = 20% [13.75, 28.16]) versus North-East District (SAR = 4.87% [1.83-12.35]) p= 0.002, sharing of utensils (SAR= 42.85% [14.26—77.11], p=0.02), and using the room to sleep where a specific case has been isolated (SAR= 25% [12.97—42.71], p=0.047). Transmission from the symptomatic primary case was observed to be five times higher. Conclusion: Our analysis showed that the secondary infection rate was higher among household contacts. This study suggests a dose-response association between severity of the primary case of SARS CoV-2 and infection among contacts.

Dose–response of benazepril on biomarkers of the classical and alternative pathways of the renin–angiotensin–aldosterone system in dogs

Angiotensin-converting enzyme inhibitors (ACEI) such as benazepril are commonly prescribed in both humans and dogs with heart disease to mitigate the renin–angiotensin–aldosterone system (RAAS); however, the dose-dependent effects of benazepril on comprehensive RAAS components remain unknown. In this study, nine purpose-bred healthy dogs received three different dosages of oral benazepril (0.125 mg/kg, 0.25 mg/kg, or 0.5 mg/kg) in a randomized crossover design following induction of RAAS activation by consuming a low-sodium diet. Blood samples were collected at serial time intervals after benazepril dosing to measure plasma benazeprilat (active metabolite of benazepril) and serum RAAS biomarkers. Blood pressure and echocardiogram were performed at baseline and after each benazepril administration. Time-weighted averages for RAAS biomarkers for 12 h post-dose and hemodynamic variables were compared between dosing groups using Wilcoxon rank-sum testing. Compared to the lowest dosage of benazepril (0.125 mg/kg), the highest dosage (0.5 mg/kg) resulted in lower time-weighted average values of angiotensin (Ang) II (− 38%, P = 0.004), Ang1-5 (− 53%, P = 0.001), ACE-S (surrogate for ACE activity; − 59%, P = 0.0002), and ALT-S (surrogate for alternative RAAS activity; − 22%, P = 0.004), and higher values of AngI (+ 78%, P = 0.014) and PRA-S (surrogate for plasma renin activity; + 58%, P = 0.040). There were no relevant differences between dosing groups for blood pressure or echocardiographic variables. Knowledge of dose-dependent alterations in biomarkers of the classical and alternative RAAS pathways could help inform clinical trials for dosage optimization in both dogs and humans.

A comparative study on epidemiological characteristics, transmissibility, and pathogenicity of three COVID-19 outbreaks caused by different variants

ObjectivesThe Omicron BA.2 variant is probably the main epidemic strain worldwide at present. Comparing the epidemiological characteristics, transmissibility, and influencing factors of SARS-CoV-2, the results obtained in this paper will help to provide theoretical support for disease control. MethodsThis study was a historical information analysis, using the R programming language and SPSS 24.0 for statistical analysis. The Geoda and Arc GIS were used for spatial autocorrelation analysis. ResultsLocal spatial autocorrelations of the incidence rate were observed in Delta and Omicron BA.1 outbreaks, whereas Omicron BA.2 outbreaks showed a random distribution in incidence rate. The time-dependent reproduction number of Delta, Omicron BA.1, and Omicron BA.2 were 3.21, 4.29, and 2.96, respectively, and correspondingly, the mean serial interval were 4.29 days (95% confidence interval [CI]: 0.37-8.21), 3.84 days (95% CI: 0-8.37), and 2.77 days (95% CI: 0-5.83). The asymptomatic infection rate of cases in Delta, Omicron BA.1, and Omicron BA.2 outbreaks were 21.71%, 6.25%, and 4.35%, respectively. ConclusionThe Omicron BA.2 variant had the greatest serial interval, transmissibility, and transmission speed, followed by BA.1, and then Delta. Compared with Delta and Omicron BA.1 variants, the Omicron BA.2 variant may be less pathogenic and more difficult to control than Omicron BA.1 and Delta.